Incidence, predictors, and outcomes of hospital-acquired anemia

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Incidence, predictors, and outcomes of hospital-acquired anemia

Hospital-acquired anemia (HAA) is defined as having a normal hemoglobin value upon admission but developing anemia during the course of hospitalization. The condition is common, with an incidence ranging from approximately 25% when defined by using the hemoglobin value prior to discharge to 74% when using the nadir hemoglobin value during hospitalization.1-5 While there are many potential etiologies for HAA, given that iatrogenic blood loss from phlebotomy may lead to its development,6,7 HAA has been postulated to be a hazard of hospitalization that is potentially preventable.8 However, it is unclear whether the development of HAA portends worse outcomes after hospital discharge.

The limited number of studies on the association between HAA and postdischarge outcomes has been restricted to patients hospitalized for acute myocardial infarction (AMI).3,9,10 Among this subpopulation, HAA is independently associated with greater morbidity and mortality following hospital discharge.3,9,10 In a more broadly representative population of hospitalized adults, Koch et al.2 found that the development of HAA is associated with greater length of stay (LOS), hospital charges, and inpatient mortality. However, given that HAA was defined by the lowest hemoglobin level during hospitalization (and not necessarily the last value prior to discharge), it is unclear if the worse outcomes observed were the cause of the HAA, rather than its effect, since hospital LOS is a robust predictor for the development of HAA, as well as a major driver of hospital costs and a prognostic marker for inpatient mortality.3,9 Furthermore, this study evaluated outcomes only during the index hospitalization, so it is unclear if patients who develop HAA have worse clinical outcomes after discharge.

Therefore, in this study, we used clinically granular electronic health record (EHR) data from a diverse cohort of consecutive medicine inpatients hospitalized for any reason at 1 of 6 hospitals to: 1) describe the epidemiology of HAA; 2) identify predictors of its development; and 3) examine its association with 30-day postdischarge adverse outcomes. We hypothesized that the development of HAA would be independently associated with 30-day readmission and mortality in a dose-dependent fashion, with increasing severity of HAA associated with worse outcomes.

METHODS

Study Design, Population, and Data Sources

We conducted a retrospective observational cohort study using EHR data collected from November 1, 2009 to October 30, 2010 from 6 hospitals in the north Texas region. One site was a university-affiliated safety-net hospital; the remaining 5 community hospitals were a mix of teaching and nonteaching sites. All hospitals used the Epic EHR system (Epic Systems Corporation, Verona, Wisconsin). Details of this cohort have been published.11,12This study included consecutive hospitalizations among adults age 18 years or older who were discharged from a medicine inpatient service with any diagnosis. We excluded hospitalizations by individuals who were anemic within the first 24 hours of admission (hematocrit less than 36% for women and less than 40% for men), were missing a hematocrit value within the first 24 hours of hospitalization or a repeat hematocrit value prior to discharge, had a hospitalization in the preceding 30 days (ie, index hospitalization was considered a readmission), died in the hospital, were transferred to another hospital, or left against medical advice. For individuals with multiple eligible hospitalizations during the study period, we included only the first hospitalization. We also excluded those discharged to hospice, given that this population of individuals may have intentionally desired less aggressive care.

 

 

Definition of Hospital-Acquired Anemia

HAA was defined as having a normal hematocrit value (36% or greater for women and 40% or greater for men) within the first 24 hours of admission and a hematocrit value at the time of hospital discharge lower than the World Health Organization’s sex-specific cut points.13 If there was more than 1 hematocrit value on the same day, we chose the lowest value. Based on prior studies, HAA was further categorized by severity as mild (hematocrit greater than 33% and less than 36% in women; and greater than 33% and less than 40% in men), moderate (hematocrit greater than 27% and 33% or less for all), or severe (hematocrit 27% or less for all).2,14

Characteristics

We extracted information on sociodemographic characteristics, comorbidities, LOS, procedures, blood transfusions, and laboratory values from the EHR. Hospitalizations in the 12 months preceding the index hospitalization were ascertained from the EHR and from an all-payer regional hospitalization database that captures hospitalizations from 75 acute care hospitals within a 100-mile radius of Dallas-Fort Worth. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis codes were categorized according to the Agency for Healthcare Research and Quality (AHRQ) Clinical Classifications Software (CCS).15 We defined a diagnosis for hemorrhage and coagulation, and hemorrhagic disorder as the presence of any ICD-9-CM code (primary or secondary) that mapped to the AHRQ CCS diagnoses 60 and 153, and 62, respectively. Procedures were categorized as minor diagnostic, minor therapeutic, major diagnostic, and major therapeutic using the AHRQ Healthcare Cost and Utilization Procedure Classes tool.16

Outcomes

The primary outcome was a composite of death or readmission within 30 days of hospital discharge. Hospital readmissions were ascertained at the index hospital and at any of 75 acute care hospitals in the region as described earlier. Death was ascertained from each of the hospitals’ EHR and administrative data and the Social Security Death Index. Individuals who had both outcomes (eg, a 30-day readmission and death) were considered to have only 1 occurrence of the composite primary outcome measure. Our secondary outcomes were death and readmission within 30 days of discharge, considered as separate outcomes.

Statistical Analysis

We used logistic regression models to evaluate predictors of HAA and to estimate the association of HAA on subsequent 30-day adverse outcomes after hospital discharge. All models accounted for clustering of patients by hospital. For the outcomes analyses, models were adjusted for potential confounders based on prior literature and our group’s expertise, which included age, sex, race/ethnicity, Charlson comorbidity index, prior hospitalizations, nonelective admission status, creatinine level on admission, blood urea nitrogen (BUN) to creatinine ratio of more than 20:1 on admission, LOS, receipt of a major diagnostic or therapeutic procedure during the index hospitalization, a discharge diagnosis for hemorrhage, and a discharge diagnosis for a coagulation or hemorrhagic disorder. For the mortality analyses, given the limited number of 30-day deaths after hospital discharge in our cohort, we collapsed moderate and severe HAA into a single category. In sensitivity analyses, we repeated the adjusted model, but excluded patients in our cohort who had received at least 1 blood transfusion during the index hospitalization (2.6%) given its potential for harm, and patients with a primary discharge diagnosis for AMI (3.1%).17

The functional forms of continuous variables were assessed using restricted cubic splines and locally weighted scatterplot smoothing techniques. All analyses were performed using STATA statistical software version 12.0 (StataCorp, College Station, Texas). The University of Texas Southwestern Medical Center institutional review board approved this study.

Incidence of Adverse Outcomes by Severity of HAA
Figure

RESULTS

Of 53,995 consecutive medicine hospitalizations among adults age 18 years or older during our study period, 11,309 index hospitalizations were included in our study cohort (Supplemental Figure 1). The majority of patients excluded were because of having documented anemia within the first 24 hours of admission (n=24,950). With increasing severity of HAA, patients were older, more likely to be female, non-Hispanic white, electively admitted, have fewer comorbidities, less likely to be hospitalized in the past year, more likely to have had a major procedure, receive a blood transfusion, have a longer LOS, and have a primary or secondary discharge diagnosis for a hemorrhage or a coagulation or hemorrhagic disorder (Table 1).

Baseline Characteristics of Hospitalized Medicine Patients
Table 1

Epidemiology of HAA

Among this cohort of patients without anemia on admission, the median hematocrit value on admission was 40.6 g/dL and on discharge was 38.9 g/dL. One-third of patients with normal hematocrit value at admission developed HAA, with 21.6% developing mild HAA, 10.1% developing moderate HAA, and 1.4% developing severe HAA. The median discharge hematocrit value was 36 g/dL (interquartile range [IQR]), 35-38 g/dL) for the group of patients who developed mild HAA, 31 g/dL (IQR, 30-32 g/dL) for moderate HAA, and 26 g/dL (IQR, 25-27 g/dL) for severe HAA (Supplemental Figure 2). Among the severe HAA group, 135 of the 159 patients (85%) had a major procedure (n=123, accounting for 219 unique major procedures), a diagnosis for hemorrhage (n=30), and/or a diagnosis for a coagulation or hemorrhagic disorder (n=23) during the index hospitalization. Of the 219 major procedures among patients with severe HAA, most were musculoskeletal (92 procedures), cardiovascular (61 procedures), or digestive system-related (41 procedures). The most common types of procedures were coronary artery bypass graft (36 procedures), hip replacement (25 procedures), knee replacement (17 procedures), and femur fracture reduction (15 procedures). The 10 most common principal discharge diagnoses of the index hospitalization by HAA group are shown in Supplemental Table 1. For the severe HAA group, the most common diagnosis was hip fracture (20.8%).

 

 

Predictors of HAA

Compared to no or mild HAA, female sex, elective admission status, serum creatinine on admission, BUN to creatinine ratio greater than 20 to 1, hospital LOS, and undergoing a major diagnostic or therapeutic procedure were predictors for the development of moderate or severe HAA (Table 2). The model explained 23% of the variance (McFadden’s pseudo R2).

Predictors of Developing Moderate or Severe HAA
Table 2

Incidence of Postdischarge Outcomes by Severity of HAA

The severity of HAA was associated with a dose-dependent increase in the incidence of 30-day adverse outcomes, such that patients with increasing severity of HAA had greater 30-day composite, mortality, and readmission outcomes (P < 0.001; Figure). The 30-day postdischarge composite outcome was primarily driven by hospital readmissions given the low mortality rate in our cohort. Patients who did not develop HAA had an incidence of 9.7% for the composite outcome, whereas patients with severe HAA had an incidence of 16.4%. Among the 24 patients with severe HAA but who had not undergone a major procedure or had a discharge diagnosis for hemorrhage or for a coagulation or hemorrhagic disorder, only 3 (12.5%) had a composite postdischarge adverse outcome (2 readmissions and 1 death). The median time to readmission was similar between groups, but more patients with severe HAA had an early readmission within 7 days of hospital discharge than patients who did not develop HAA (6.9% vs. 2.9%, P = 0.001; Supplemental Table 2).

Association of HAA and Postdischarge Outcomes

In unadjusted analyses, compared to not developing HAA, mild, moderate, and severe HAA were associated with a 29%, 61%, and 81% increase in the odds for a composite outcome, respectively (Table 3). After adjustment for confounders, the effect size for HAA attenuated and was no longer statistically significant for mild and moderate HAA. However, severe HAA was significantly associated with a 39% increase in the odds for the composite outcome and a 41% increase in the odds for 30-day readmission (P = 0.008 and P = 0.02, respectively).

Association of HAA and 30-Day Postdischarge Adverse Outcomes
Table 3

In sensitivity analyses, the exclusion of individuals who received at least 1 blood transfusion during the index hospitalization (n=298) and individuals who had a primary discharge diagnosis for AMI (n=353) did not substantively change the estimates of the association between severe HAA and postdischarge outcomes (Supplemental Tables 3 and 4). However, because of the fewer number of adverse events for each analysis, the confidence intervals were wider and the association of severe HAA and the composite outcome and readmission were no longer statistically significant in these subcohorts.

DISCUSSION

In this large and diverse sample of medical inpatients, we found that HAA occurs in one-third of adults with normal hematocrit value at admission, where 10.1% of the cohort developed moderately severe HAA and 1.4% developed severe HAA by the time of discharge. Length of stay and undergoing a major diagnostic or therapeutic procedure were the 2 strongest potentially modifiable predictors of developing moderate or severe HAA. Severe HAA was independently associated with a 39% increase in the odds of being readmitted or dying within 30 days after hospital discharge compared to not developing HAA. However, the associations between mild or moderate HAA with adverse outcomes were attenuated after adjusting for confounders and were no longer statistically significant.

To our knowledge, this is the first study on the postdischarge adverse outcomes of HAA among a diverse cohort of medical inpatients hospitalized for any reason. In a more restricted population, Salisbury et al.3 found that patients hospitalized for AMI who developed moderate to severe HAA (hemoglobin value at discharge of 11 g/dL or less) had greater 1-year mortality than those without HAA (8.4% vs. 2.6%, P < 0.001), and had an 82% increase in the hazard for mortality (95% confidence interval, hazard ratio 1.11-2.98). Others have similarly shown that HAA is common among patients hospitalized with AMI and is associated with greater mortality.5,9,18 Our study extends upon this prior research by showing that severe HAA increases the risk for adverse outcomes for all adult inpatients, not only those hospitalized for AMI or among those receiving blood transfusions.

Despite the increased harm associated with severe HAA, it is unclear whether HAA is a preventable hazard of hospitalization, as suggested by others.6,8 Most patients in our cohort who developed severe HAA underwent a major procedure, had a discharge diagnosis for hemorrhage, and/or had a discharge diagnosis for a coagulation or hemorrhagic disorder. Thus, blood loss due to phlebotomy, 1 of the more modifiable etiologies of HAA, was unlikely to have been the primary driver for most patients who developed severe HAA. Since it has been estimated to take 15 days of daily phlebotomy of 53 mL of whole blood in females of average body weight (and 20 days for average weight males) with no bone marrow synthesis for severe anemia to develop, it is even less likely that phlebotomy was the principal etiology given an 8-day median LOS among patients with severe HAA.19,20 However, since the etiology of HAA can be multifactorial, limiting blood loss due to phlebotomy by using smaller volume tubes, blood conservation devices, or reducing unnecessary testing may mitigate the development of severe HAA.21,22 Additionally, since more than three-quarters of patients who developed severe HAA underwent a major procedure, more care and attention to minimizing operative blood loss could lessen the severity of HAA and facilitate better recovery. If minimizing blood loss is not feasible, in the absence of symptoms related to anemia or ongoing blood loss, randomized controlled trials overwhelmingly support a restrictive transfusion strategy using a hemoglobin value threshold of 7 mg/dL, even in the postoperative setting.23-25

The implications of mild to moderate HAA are less clear. The odds ratios for mild and moderate HAA, while not statistically significant, suggest a small increase in harm compared to not developing HAA. Furthermore, the upper boundary of the confidence intervals for mild and moderate HAA cannot exclude a possible 30% and 56% increase in the odds for the 30-day composite outcome, respectively. Thus, a better powered study, including more patients and extending the time interval for ascertaining postdischarge adverse events beyond 30 days, may reveal a harmful association. Lastly, our study assessed only the association of HAA with 30-day readmission and mortality. Examining the association between HAA and other patient-centered outcomes such as fatigue, functional impairment, and prolonged posthospitalization recovery time may uncover other important adverse effects of mild and moderate HAA, both of which occur far more frequently than severe HAA.

Our findings should be interpreted in the context of several limitations. First, although we included a diverse group of patients from a multihospital cohort, generalizability to other settings is uncertain. Second, as this was a retrospective study using EHR data, we had limited information to infer the precise mechanism of HAA for each patient. However, procedure codes and discharge diagnoses enabled us to assess which patients underwent a major procedure or had a hemorrhage or hemorrhagic disorder during the hospitalization. Third, given the relatively few number of patients with severe HAA in our cohort, we were unable to assess if the association of severe HAA differed by suspected etiology. Lastly, because we were unable to ascertain the timing of the hematocrit values within the first 24 hours of admission, we excluded both patients with preexisting anemia on admission and those who developed HAA within the first 24 hours of admission, which is not uncommon.26 Thus, we were unable to assess the effect of acute on chronic anemia arising during hospitalization and HAA that develops within the first 24 hours, both of which may also be harmful.18,27,28

In conclusion, severe HAA occurs in 1.4% of all medical hospitalizations and is associated with increased odds of death or readmission within 30 days. Since most patients with severe HAA had undergone a major procedure or had a discharge diagnosis of hemorrhage or a coagulation or hemorrhagic disorder, it is unclear if severe HAA is potentially preventable through preventing blood loss from phlebotomy or by reducing iatrogenic injury during procedures. Future research should assess the potential preventability of severe HAA, and examine other patient-centered outcomes potentially related to anemia, including fatigue, functional impairment, and trajectory of posthospital recovery.

 

 

Acknowledgments

The authors would like to acknowledge Ruben Amarasingham, MD, MBA, President and Chief Executive Officer of the Parkland Center for Clinical Innovation, and Ferdinand Velasco, MD, Chief Health Information Officer at Texas Health Resources, for their assistance in assembling the 6 hospital cohort used in this study. The authors would also like to thank Valy Fontil, MD, MAS, Assistant Professor of Medicine at the University of California San Francisco School of Medicine, and Elizabeth Rogers, MD, MAS, Assistant Professor of Internal Medicine and Pediatrics at the University of Minnesota Medical School, for their constructive feedback on an earlier version of this manuscript.

Disclosures

This work was supported by the Agency for Healthcare Research and Quality-funded UT Southwestern Center for Patient-Centered Outcomes Research (R24 HS022418-01); the Commonwealth Foundation (#20100323); the UT Southwestern KL2 Scholars Program supported by the National Institutes of Health (KL2 TR001103); the National Center for Advancing Translational Sciences at the National Institute of Health (U54 RFA-TR-12-006); and the National Institute on Aging (K23AG052603). The study sponsors had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. The authors have no financial conflicts of interest to disclose.

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References

1. Kurniali PC, Curry S, Brennan KW, et al. A retrospective study investigating the incidence and predisposing factors of hospital-acquired anemia. Anemia. 2014;2014:634582. PubMed
2. Koch CG, Li L, Sun Z, et al. Hospital-acquired anemia: prevalence, outcomes, and healthcare implications. J Hosp Med. 2013;8(9):506-512. PubMed
3. Salisbury AC, Alexander KP, Reid KJ, et al. Incidence, correlates, and outcomes of acute, hospital-acquired anemia in patients with acute myocardial infarction. Circ Cardiovasc Qual Outcomes. 2010;3(4):337-346. PubMed
4. Salisbury AC, Amin AP, Reid KJ, et al. Hospital-acquired anemia and in-hospital mortality in patients with acute myocardial infarction. Am Heart J. 2011;162(2):300-309 e303. PubMed
5. Meroño O, Cladellas M, Recasens L, et al. In-hospital acquired anemia in acute coronary syndrome. Predictors, in-hospital prognosis and one-year mortality. Rev Esp Cardiol (Engl Ed). 2012;65(8):742-748. PubMed
6. Salisbury AC, Reid KJ, Alexander KP, et al. Diagnostic blood loss from phlebotomy and hospital-acquired anemia during acute myocardial infarction. Arch Intern Med. 2011;171(18):1646-1653. PubMed
7. Thavendiranathan P, Bagai A, Ebidia A, Detsky AS, Choudhry NK. Do blood tests cause anemia in hospitalized patients? The effect of diagnostic phlebotomy on hemoglobin and hematocrit levels. J Gen Intern Med. 2005;20(6):520-524. PubMed
8. Rennke S, Fang MC. Hazards of hospitalization: more than just “never events”. Arch Intern Med. 2011;171(18):1653-1654. PubMed
9. Choi JS, Kim YA, Kang YU, et al. Clinical impact of hospital-acquired anemia in association with acute kidney injury and chronic kidney disease in patients with acute myocardial infarction. PLoS One. 2013;8(9):e75583. PubMed
10. Salisbury AC, Kosiborod M, Amin AP, et al. Recovery from hospital-acquired anemia after acute myocardial infarction and effect on outcomes. Am J Cardiol. 2011;108(7):949-954. PubMed
11. Nguyen OK, Makam AN, Clark C, et al. Predicting all-cause readmissions using electronic health record data from the entire hospitalization: Model development and comparison. J Hosp Med. 2016;11(7):473-480. PubMed
12. Amarasingham R, Velasco F, Xie B, et al. Electronic medical record-based multicondition models to predict the risk of 30 day readmission or death among adult medicine patients: validation and comparison to existing models. BMC Med Inform Decis Mak. 2015;15:39. PubMed
13. World Health Organization. Hemoglobin concentrations for the diagnosis of anaemia and assessment of severity. http://www.who.int/vmnis/indicators/haemoglobin.pdf. Accessed March 15, 2016.
14. Martin ND, Scantling D. Hospital-acquired anemia: a contemporary review of etiologies and prevention strategies. J Infus Nurs. 2015;38(5):330-338. PubMed
15. Agency for Healthcare Research and Quality, Rockville, MD. Clinical classification software (CCS) for ICD-9-CM. Healthcare Cost and Utilization Project. 2015 http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Accessed November 18, 2015.
16. Agency for Healthcare Research and Quality, Rockville, MD. Procedure classes2015. Healthcare Cost and Utilization Project. 2015. https://www.hcup-us.ahrq.gov/toolssoftware/procedure/procedure.jsp. Accessed November 18, 2015.
17. Corwin HL, Gettinger A, Pearl RG, et al. The CRIT Study: Anemia and blood transfusion in the critically ill--current clinical practice in the United States. Crit Care Med. 2004;32(1):39-52. PubMed
18. Aronson D, Suleiman M, Agmon Y, et al. Changes in haemoglobin levels during hospital course and long-term outcome after acute myocardial infarction. Eur Heart J. 2007;28(11):1289-1296. PubMed
19. Lyon AW, Chin AC, Slotsve GA, Lyon ME. Simulation of repetitive diagnostic blood loss and onset of iatrogenic anemia in critical care patients with a mathematical model. Comput Biol Med. 2013;43(2):84-90. PubMed
20. van der Bom JG, Cannegieter SC. Hospital-acquired anemia: the contribution of diagnostic blood loss. J Thromb Haemost. 2015;13(6):1157-1159. PubMed
21. Sanchez-Giron F, Alvarez-Mora F. Reduction of blood loss from laboratory testing in hospitalized adult patients using small-volume (pediatric) tubes. Arch Pathol Lab Med. 2008;132(12):1916-1919. PubMed
22. Smoller BR, Kruskall MS. Phlebotomy for diagnostic laboratory tests in adults. Pattern of use and effect on transfusion requirements. N Engl J Med. 1986;314(19):1233-1235. PubMed
23. Carson JL, Carless PA, Hebert PC. Transfusion thresholds and other strategies for guiding allogeneic red blood cell transfusion. Cochrane Database Syst Rev. 2012(4):CD002042. PubMed
24. Carson JL, Carless PA, Hébert PC. Outcomes using lower vs higher hemoglobin thresholds for red blood cell transfusion. JAMA. 2013;309(1):83-84. PubMed
25. Carson JL, Sieber F, Cook DR, et al. Liberal versus restrictive blood transfusion strategy: 3-year survival and cause of death results from the FOCUS randomised controlled trial. Lancet. 2015;385(9974):1183-1189. PubMed
26. Rajkomar A, McCulloch CE, Fang MC. Low diagnostic utility of rechecking hemoglobins within 24 hours in hospitalized patients. Am J Med. 2016;129(11):1194-1197. PubMed
27. Reade MC, Weissfeld L, Angus DC, Kellum JA, Milbrandt EB. The prevalence of anemia and its association with 90-day mortality in hospitalized community-acquired pneumonia. BMC Pulm Med. 2010;10:15. PubMed
28. Halm EA, Wang JJ, Boockvar K, et al. The effect of perioperative anemia on clinical and functional outcomes in patients with hip fracture. J Orthop Trauma. 2004;18(6):369-374. PubMed

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Hospital-acquired anemia (HAA) is defined as having a normal hemoglobin value upon admission but developing anemia during the course of hospitalization. The condition is common, with an incidence ranging from approximately 25% when defined by using the hemoglobin value prior to discharge to 74% when using the nadir hemoglobin value during hospitalization.1-5 While there are many potential etiologies for HAA, given that iatrogenic blood loss from phlebotomy may lead to its development,6,7 HAA has been postulated to be a hazard of hospitalization that is potentially preventable.8 However, it is unclear whether the development of HAA portends worse outcomes after hospital discharge.

The limited number of studies on the association between HAA and postdischarge outcomes has been restricted to patients hospitalized for acute myocardial infarction (AMI).3,9,10 Among this subpopulation, HAA is independently associated with greater morbidity and mortality following hospital discharge.3,9,10 In a more broadly representative population of hospitalized adults, Koch et al.2 found that the development of HAA is associated with greater length of stay (LOS), hospital charges, and inpatient mortality. However, given that HAA was defined by the lowest hemoglobin level during hospitalization (and not necessarily the last value prior to discharge), it is unclear if the worse outcomes observed were the cause of the HAA, rather than its effect, since hospital LOS is a robust predictor for the development of HAA, as well as a major driver of hospital costs and a prognostic marker for inpatient mortality.3,9 Furthermore, this study evaluated outcomes only during the index hospitalization, so it is unclear if patients who develop HAA have worse clinical outcomes after discharge.

Therefore, in this study, we used clinically granular electronic health record (EHR) data from a diverse cohort of consecutive medicine inpatients hospitalized for any reason at 1 of 6 hospitals to: 1) describe the epidemiology of HAA; 2) identify predictors of its development; and 3) examine its association with 30-day postdischarge adverse outcomes. We hypothesized that the development of HAA would be independently associated with 30-day readmission and mortality in a dose-dependent fashion, with increasing severity of HAA associated with worse outcomes.

METHODS

Study Design, Population, and Data Sources

We conducted a retrospective observational cohort study using EHR data collected from November 1, 2009 to October 30, 2010 from 6 hospitals in the north Texas region. One site was a university-affiliated safety-net hospital; the remaining 5 community hospitals were a mix of teaching and nonteaching sites. All hospitals used the Epic EHR system (Epic Systems Corporation, Verona, Wisconsin). Details of this cohort have been published.11,12This study included consecutive hospitalizations among adults age 18 years or older who were discharged from a medicine inpatient service with any diagnosis. We excluded hospitalizations by individuals who were anemic within the first 24 hours of admission (hematocrit less than 36% for women and less than 40% for men), were missing a hematocrit value within the first 24 hours of hospitalization or a repeat hematocrit value prior to discharge, had a hospitalization in the preceding 30 days (ie, index hospitalization was considered a readmission), died in the hospital, were transferred to another hospital, or left against medical advice. For individuals with multiple eligible hospitalizations during the study period, we included only the first hospitalization. We also excluded those discharged to hospice, given that this population of individuals may have intentionally desired less aggressive care.

 

 

Definition of Hospital-Acquired Anemia

HAA was defined as having a normal hematocrit value (36% or greater for women and 40% or greater for men) within the first 24 hours of admission and a hematocrit value at the time of hospital discharge lower than the World Health Organization’s sex-specific cut points.13 If there was more than 1 hematocrit value on the same day, we chose the lowest value. Based on prior studies, HAA was further categorized by severity as mild (hematocrit greater than 33% and less than 36% in women; and greater than 33% and less than 40% in men), moderate (hematocrit greater than 27% and 33% or less for all), or severe (hematocrit 27% or less for all).2,14

Characteristics

We extracted information on sociodemographic characteristics, comorbidities, LOS, procedures, blood transfusions, and laboratory values from the EHR. Hospitalizations in the 12 months preceding the index hospitalization were ascertained from the EHR and from an all-payer regional hospitalization database that captures hospitalizations from 75 acute care hospitals within a 100-mile radius of Dallas-Fort Worth. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis codes were categorized according to the Agency for Healthcare Research and Quality (AHRQ) Clinical Classifications Software (CCS).15 We defined a diagnosis for hemorrhage and coagulation, and hemorrhagic disorder as the presence of any ICD-9-CM code (primary or secondary) that mapped to the AHRQ CCS diagnoses 60 and 153, and 62, respectively. Procedures were categorized as minor diagnostic, minor therapeutic, major diagnostic, and major therapeutic using the AHRQ Healthcare Cost and Utilization Procedure Classes tool.16

Outcomes

The primary outcome was a composite of death or readmission within 30 days of hospital discharge. Hospital readmissions were ascertained at the index hospital and at any of 75 acute care hospitals in the region as described earlier. Death was ascertained from each of the hospitals’ EHR and administrative data and the Social Security Death Index. Individuals who had both outcomes (eg, a 30-day readmission and death) were considered to have only 1 occurrence of the composite primary outcome measure. Our secondary outcomes were death and readmission within 30 days of discharge, considered as separate outcomes.

Statistical Analysis

We used logistic regression models to evaluate predictors of HAA and to estimate the association of HAA on subsequent 30-day adverse outcomes after hospital discharge. All models accounted for clustering of patients by hospital. For the outcomes analyses, models were adjusted for potential confounders based on prior literature and our group’s expertise, which included age, sex, race/ethnicity, Charlson comorbidity index, prior hospitalizations, nonelective admission status, creatinine level on admission, blood urea nitrogen (BUN) to creatinine ratio of more than 20:1 on admission, LOS, receipt of a major diagnostic or therapeutic procedure during the index hospitalization, a discharge diagnosis for hemorrhage, and a discharge diagnosis for a coagulation or hemorrhagic disorder. For the mortality analyses, given the limited number of 30-day deaths after hospital discharge in our cohort, we collapsed moderate and severe HAA into a single category. In sensitivity analyses, we repeated the adjusted model, but excluded patients in our cohort who had received at least 1 blood transfusion during the index hospitalization (2.6%) given its potential for harm, and patients with a primary discharge diagnosis for AMI (3.1%).17

The functional forms of continuous variables were assessed using restricted cubic splines and locally weighted scatterplot smoothing techniques. All analyses were performed using STATA statistical software version 12.0 (StataCorp, College Station, Texas). The University of Texas Southwestern Medical Center institutional review board approved this study.

Incidence of Adverse Outcomes by Severity of HAA
Figure

RESULTS

Of 53,995 consecutive medicine hospitalizations among adults age 18 years or older during our study period, 11,309 index hospitalizations were included in our study cohort (Supplemental Figure 1). The majority of patients excluded were because of having documented anemia within the first 24 hours of admission (n=24,950). With increasing severity of HAA, patients were older, more likely to be female, non-Hispanic white, electively admitted, have fewer comorbidities, less likely to be hospitalized in the past year, more likely to have had a major procedure, receive a blood transfusion, have a longer LOS, and have a primary or secondary discharge diagnosis for a hemorrhage or a coagulation or hemorrhagic disorder (Table 1).

Baseline Characteristics of Hospitalized Medicine Patients
Table 1

Epidemiology of HAA

Among this cohort of patients without anemia on admission, the median hematocrit value on admission was 40.6 g/dL and on discharge was 38.9 g/dL. One-third of patients with normal hematocrit value at admission developed HAA, with 21.6% developing mild HAA, 10.1% developing moderate HAA, and 1.4% developing severe HAA. The median discharge hematocrit value was 36 g/dL (interquartile range [IQR]), 35-38 g/dL) for the group of patients who developed mild HAA, 31 g/dL (IQR, 30-32 g/dL) for moderate HAA, and 26 g/dL (IQR, 25-27 g/dL) for severe HAA (Supplemental Figure 2). Among the severe HAA group, 135 of the 159 patients (85%) had a major procedure (n=123, accounting for 219 unique major procedures), a diagnosis for hemorrhage (n=30), and/or a diagnosis for a coagulation or hemorrhagic disorder (n=23) during the index hospitalization. Of the 219 major procedures among patients with severe HAA, most were musculoskeletal (92 procedures), cardiovascular (61 procedures), or digestive system-related (41 procedures). The most common types of procedures were coronary artery bypass graft (36 procedures), hip replacement (25 procedures), knee replacement (17 procedures), and femur fracture reduction (15 procedures). The 10 most common principal discharge diagnoses of the index hospitalization by HAA group are shown in Supplemental Table 1. For the severe HAA group, the most common diagnosis was hip fracture (20.8%).

 

 

Predictors of HAA

Compared to no or mild HAA, female sex, elective admission status, serum creatinine on admission, BUN to creatinine ratio greater than 20 to 1, hospital LOS, and undergoing a major diagnostic or therapeutic procedure were predictors for the development of moderate or severe HAA (Table 2). The model explained 23% of the variance (McFadden’s pseudo R2).

Predictors of Developing Moderate or Severe HAA
Table 2

Incidence of Postdischarge Outcomes by Severity of HAA

The severity of HAA was associated with a dose-dependent increase in the incidence of 30-day adverse outcomes, such that patients with increasing severity of HAA had greater 30-day composite, mortality, and readmission outcomes (P < 0.001; Figure). The 30-day postdischarge composite outcome was primarily driven by hospital readmissions given the low mortality rate in our cohort. Patients who did not develop HAA had an incidence of 9.7% for the composite outcome, whereas patients with severe HAA had an incidence of 16.4%. Among the 24 patients with severe HAA but who had not undergone a major procedure or had a discharge diagnosis for hemorrhage or for a coagulation or hemorrhagic disorder, only 3 (12.5%) had a composite postdischarge adverse outcome (2 readmissions and 1 death). The median time to readmission was similar between groups, but more patients with severe HAA had an early readmission within 7 days of hospital discharge than patients who did not develop HAA (6.9% vs. 2.9%, P = 0.001; Supplemental Table 2).

Association of HAA and Postdischarge Outcomes

In unadjusted analyses, compared to not developing HAA, mild, moderate, and severe HAA were associated with a 29%, 61%, and 81% increase in the odds for a composite outcome, respectively (Table 3). After adjustment for confounders, the effect size for HAA attenuated and was no longer statistically significant for mild and moderate HAA. However, severe HAA was significantly associated with a 39% increase in the odds for the composite outcome and a 41% increase in the odds for 30-day readmission (P = 0.008 and P = 0.02, respectively).

Association of HAA and 30-Day Postdischarge Adverse Outcomes
Table 3

In sensitivity analyses, the exclusion of individuals who received at least 1 blood transfusion during the index hospitalization (n=298) and individuals who had a primary discharge diagnosis for AMI (n=353) did not substantively change the estimates of the association between severe HAA and postdischarge outcomes (Supplemental Tables 3 and 4). However, because of the fewer number of adverse events for each analysis, the confidence intervals were wider and the association of severe HAA and the composite outcome and readmission were no longer statistically significant in these subcohorts.

DISCUSSION

In this large and diverse sample of medical inpatients, we found that HAA occurs in one-third of adults with normal hematocrit value at admission, where 10.1% of the cohort developed moderately severe HAA and 1.4% developed severe HAA by the time of discharge. Length of stay and undergoing a major diagnostic or therapeutic procedure were the 2 strongest potentially modifiable predictors of developing moderate or severe HAA. Severe HAA was independently associated with a 39% increase in the odds of being readmitted or dying within 30 days after hospital discharge compared to not developing HAA. However, the associations between mild or moderate HAA with adverse outcomes were attenuated after adjusting for confounders and were no longer statistically significant.

To our knowledge, this is the first study on the postdischarge adverse outcomes of HAA among a diverse cohort of medical inpatients hospitalized for any reason. In a more restricted population, Salisbury et al.3 found that patients hospitalized for AMI who developed moderate to severe HAA (hemoglobin value at discharge of 11 g/dL or less) had greater 1-year mortality than those without HAA (8.4% vs. 2.6%, P < 0.001), and had an 82% increase in the hazard for mortality (95% confidence interval, hazard ratio 1.11-2.98). Others have similarly shown that HAA is common among patients hospitalized with AMI and is associated with greater mortality.5,9,18 Our study extends upon this prior research by showing that severe HAA increases the risk for adverse outcomes for all adult inpatients, not only those hospitalized for AMI or among those receiving blood transfusions.

Despite the increased harm associated with severe HAA, it is unclear whether HAA is a preventable hazard of hospitalization, as suggested by others.6,8 Most patients in our cohort who developed severe HAA underwent a major procedure, had a discharge diagnosis for hemorrhage, and/or had a discharge diagnosis for a coagulation or hemorrhagic disorder. Thus, blood loss due to phlebotomy, 1 of the more modifiable etiologies of HAA, was unlikely to have been the primary driver for most patients who developed severe HAA. Since it has been estimated to take 15 days of daily phlebotomy of 53 mL of whole blood in females of average body weight (and 20 days for average weight males) with no bone marrow synthesis for severe anemia to develop, it is even less likely that phlebotomy was the principal etiology given an 8-day median LOS among patients with severe HAA.19,20 However, since the etiology of HAA can be multifactorial, limiting blood loss due to phlebotomy by using smaller volume tubes, blood conservation devices, or reducing unnecessary testing may mitigate the development of severe HAA.21,22 Additionally, since more than three-quarters of patients who developed severe HAA underwent a major procedure, more care and attention to minimizing operative blood loss could lessen the severity of HAA and facilitate better recovery. If minimizing blood loss is not feasible, in the absence of symptoms related to anemia or ongoing blood loss, randomized controlled trials overwhelmingly support a restrictive transfusion strategy using a hemoglobin value threshold of 7 mg/dL, even in the postoperative setting.23-25

The implications of mild to moderate HAA are less clear. The odds ratios for mild and moderate HAA, while not statistically significant, suggest a small increase in harm compared to not developing HAA. Furthermore, the upper boundary of the confidence intervals for mild and moderate HAA cannot exclude a possible 30% and 56% increase in the odds for the 30-day composite outcome, respectively. Thus, a better powered study, including more patients and extending the time interval for ascertaining postdischarge adverse events beyond 30 days, may reveal a harmful association. Lastly, our study assessed only the association of HAA with 30-day readmission and mortality. Examining the association between HAA and other patient-centered outcomes such as fatigue, functional impairment, and prolonged posthospitalization recovery time may uncover other important adverse effects of mild and moderate HAA, both of which occur far more frequently than severe HAA.

Our findings should be interpreted in the context of several limitations. First, although we included a diverse group of patients from a multihospital cohort, generalizability to other settings is uncertain. Second, as this was a retrospective study using EHR data, we had limited information to infer the precise mechanism of HAA for each patient. However, procedure codes and discharge diagnoses enabled us to assess which patients underwent a major procedure or had a hemorrhage or hemorrhagic disorder during the hospitalization. Third, given the relatively few number of patients with severe HAA in our cohort, we were unable to assess if the association of severe HAA differed by suspected etiology. Lastly, because we were unable to ascertain the timing of the hematocrit values within the first 24 hours of admission, we excluded both patients with preexisting anemia on admission and those who developed HAA within the first 24 hours of admission, which is not uncommon.26 Thus, we were unable to assess the effect of acute on chronic anemia arising during hospitalization and HAA that develops within the first 24 hours, both of which may also be harmful.18,27,28

In conclusion, severe HAA occurs in 1.4% of all medical hospitalizations and is associated with increased odds of death or readmission within 30 days. Since most patients with severe HAA had undergone a major procedure or had a discharge diagnosis of hemorrhage or a coagulation or hemorrhagic disorder, it is unclear if severe HAA is potentially preventable through preventing blood loss from phlebotomy or by reducing iatrogenic injury during procedures. Future research should assess the potential preventability of severe HAA, and examine other patient-centered outcomes potentially related to anemia, including fatigue, functional impairment, and trajectory of posthospital recovery.

 

 

Acknowledgments

The authors would like to acknowledge Ruben Amarasingham, MD, MBA, President and Chief Executive Officer of the Parkland Center for Clinical Innovation, and Ferdinand Velasco, MD, Chief Health Information Officer at Texas Health Resources, for their assistance in assembling the 6 hospital cohort used in this study. The authors would also like to thank Valy Fontil, MD, MAS, Assistant Professor of Medicine at the University of California San Francisco School of Medicine, and Elizabeth Rogers, MD, MAS, Assistant Professor of Internal Medicine and Pediatrics at the University of Minnesota Medical School, for their constructive feedback on an earlier version of this manuscript.

Disclosures

This work was supported by the Agency for Healthcare Research and Quality-funded UT Southwestern Center for Patient-Centered Outcomes Research (R24 HS022418-01); the Commonwealth Foundation (#20100323); the UT Southwestern KL2 Scholars Program supported by the National Institutes of Health (KL2 TR001103); the National Center for Advancing Translational Sciences at the National Institute of Health (U54 RFA-TR-12-006); and the National Institute on Aging (K23AG052603). The study sponsors had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. The authors have no financial conflicts of interest to disclose.

Hospital-acquired anemia (HAA) is defined as having a normal hemoglobin value upon admission but developing anemia during the course of hospitalization. The condition is common, with an incidence ranging from approximately 25% when defined by using the hemoglobin value prior to discharge to 74% when using the nadir hemoglobin value during hospitalization.1-5 While there are many potential etiologies for HAA, given that iatrogenic blood loss from phlebotomy may lead to its development,6,7 HAA has been postulated to be a hazard of hospitalization that is potentially preventable.8 However, it is unclear whether the development of HAA portends worse outcomes after hospital discharge.

The limited number of studies on the association between HAA and postdischarge outcomes has been restricted to patients hospitalized for acute myocardial infarction (AMI).3,9,10 Among this subpopulation, HAA is independently associated with greater morbidity and mortality following hospital discharge.3,9,10 In a more broadly representative population of hospitalized adults, Koch et al.2 found that the development of HAA is associated with greater length of stay (LOS), hospital charges, and inpatient mortality. However, given that HAA was defined by the lowest hemoglobin level during hospitalization (and not necessarily the last value prior to discharge), it is unclear if the worse outcomes observed were the cause of the HAA, rather than its effect, since hospital LOS is a robust predictor for the development of HAA, as well as a major driver of hospital costs and a prognostic marker for inpatient mortality.3,9 Furthermore, this study evaluated outcomes only during the index hospitalization, so it is unclear if patients who develop HAA have worse clinical outcomes after discharge.

Therefore, in this study, we used clinically granular electronic health record (EHR) data from a diverse cohort of consecutive medicine inpatients hospitalized for any reason at 1 of 6 hospitals to: 1) describe the epidemiology of HAA; 2) identify predictors of its development; and 3) examine its association with 30-day postdischarge adverse outcomes. We hypothesized that the development of HAA would be independently associated with 30-day readmission and mortality in a dose-dependent fashion, with increasing severity of HAA associated with worse outcomes.

METHODS

Study Design, Population, and Data Sources

We conducted a retrospective observational cohort study using EHR data collected from November 1, 2009 to October 30, 2010 from 6 hospitals in the north Texas region. One site was a university-affiliated safety-net hospital; the remaining 5 community hospitals were a mix of teaching and nonteaching sites. All hospitals used the Epic EHR system (Epic Systems Corporation, Verona, Wisconsin). Details of this cohort have been published.11,12This study included consecutive hospitalizations among adults age 18 years or older who were discharged from a medicine inpatient service with any diagnosis. We excluded hospitalizations by individuals who were anemic within the first 24 hours of admission (hematocrit less than 36% for women and less than 40% for men), were missing a hematocrit value within the first 24 hours of hospitalization or a repeat hematocrit value prior to discharge, had a hospitalization in the preceding 30 days (ie, index hospitalization was considered a readmission), died in the hospital, were transferred to another hospital, or left against medical advice. For individuals with multiple eligible hospitalizations during the study period, we included only the first hospitalization. We also excluded those discharged to hospice, given that this population of individuals may have intentionally desired less aggressive care.

 

 

Definition of Hospital-Acquired Anemia

HAA was defined as having a normal hematocrit value (36% or greater for women and 40% or greater for men) within the first 24 hours of admission and a hematocrit value at the time of hospital discharge lower than the World Health Organization’s sex-specific cut points.13 If there was more than 1 hematocrit value on the same day, we chose the lowest value. Based on prior studies, HAA was further categorized by severity as mild (hematocrit greater than 33% and less than 36% in women; and greater than 33% and less than 40% in men), moderate (hematocrit greater than 27% and 33% or less for all), or severe (hematocrit 27% or less for all).2,14

Characteristics

We extracted information on sociodemographic characteristics, comorbidities, LOS, procedures, blood transfusions, and laboratory values from the EHR. Hospitalizations in the 12 months preceding the index hospitalization were ascertained from the EHR and from an all-payer regional hospitalization database that captures hospitalizations from 75 acute care hospitals within a 100-mile radius of Dallas-Fort Worth. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis codes were categorized according to the Agency for Healthcare Research and Quality (AHRQ) Clinical Classifications Software (CCS).15 We defined a diagnosis for hemorrhage and coagulation, and hemorrhagic disorder as the presence of any ICD-9-CM code (primary or secondary) that mapped to the AHRQ CCS diagnoses 60 and 153, and 62, respectively. Procedures were categorized as minor diagnostic, minor therapeutic, major diagnostic, and major therapeutic using the AHRQ Healthcare Cost and Utilization Procedure Classes tool.16

Outcomes

The primary outcome was a composite of death or readmission within 30 days of hospital discharge. Hospital readmissions were ascertained at the index hospital and at any of 75 acute care hospitals in the region as described earlier. Death was ascertained from each of the hospitals’ EHR and administrative data and the Social Security Death Index. Individuals who had both outcomes (eg, a 30-day readmission and death) were considered to have only 1 occurrence of the composite primary outcome measure. Our secondary outcomes were death and readmission within 30 days of discharge, considered as separate outcomes.

Statistical Analysis

We used logistic regression models to evaluate predictors of HAA and to estimate the association of HAA on subsequent 30-day adverse outcomes after hospital discharge. All models accounted for clustering of patients by hospital. For the outcomes analyses, models were adjusted for potential confounders based on prior literature and our group’s expertise, which included age, sex, race/ethnicity, Charlson comorbidity index, prior hospitalizations, nonelective admission status, creatinine level on admission, blood urea nitrogen (BUN) to creatinine ratio of more than 20:1 on admission, LOS, receipt of a major diagnostic or therapeutic procedure during the index hospitalization, a discharge diagnosis for hemorrhage, and a discharge diagnosis for a coagulation or hemorrhagic disorder. For the mortality analyses, given the limited number of 30-day deaths after hospital discharge in our cohort, we collapsed moderate and severe HAA into a single category. In sensitivity analyses, we repeated the adjusted model, but excluded patients in our cohort who had received at least 1 blood transfusion during the index hospitalization (2.6%) given its potential for harm, and patients with a primary discharge diagnosis for AMI (3.1%).17

The functional forms of continuous variables were assessed using restricted cubic splines and locally weighted scatterplot smoothing techniques. All analyses were performed using STATA statistical software version 12.0 (StataCorp, College Station, Texas). The University of Texas Southwestern Medical Center institutional review board approved this study.

Incidence of Adverse Outcomes by Severity of HAA
Figure

RESULTS

Of 53,995 consecutive medicine hospitalizations among adults age 18 years or older during our study period, 11,309 index hospitalizations were included in our study cohort (Supplemental Figure 1). The majority of patients excluded were because of having documented anemia within the first 24 hours of admission (n=24,950). With increasing severity of HAA, patients were older, more likely to be female, non-Hispanic white, electively admitted, have fewer comorbidities, less likely to be hospitalized in the past year, more likely to have had a major procedure, receive a blood transfusion, have a longer LOS, and have a primary or secondary discharge diagnosis for a hemorrhage or a coagulation or hemorrhagic disorder (Table 1).

Baseline Characteristics of Hospitalized Medicine Patients
Table 1

Epidemiology of HAA

Among this cohort of patients without anemia on admission, the median hematocrit value on admission was 40.6 g/dL and on discharge was 38.9 g/dL. One-third of patients with normal hematocrit value at admission developed HAA, with 21.6% developing mild HAA, 10.1% developing moderate HAA, and 1.4% developing severe HAA. The median discharge hematocrit value was 36 g/dL (interquartile range [IQR]), 35-38 g/dL) for the group of patients who developed mild HAA, 31 g/dL (IQR, 30-32 g/dL) for moderate HAA, and 26 g/dL (IQR, 25-27 g/dL) for severe HAA (Supplemental Figure 2). Among the severe HAA group, 135 of the 159 patients (85%) had a major procedure (n=123, accounting for 219 unique major procedures), a diagnosis for hemorrhage (n=30), and/or a diagnosis for a coagulation or hemorrhagic disorder (n=23) during the index hospitalization. Of the 219 major procedures among patients with severe HAA, most were musculoskeletal (92 procedures), cardiovascular (61 procedures), or digestive system-related (41 procedures). The most common types of procedures were coronary artery bypass graft (36 procedures), hip replacement (25 procedures), knee replacement (17 procedures), and femur fracture reduction (15 procedures). The 10 most common principal discharge diagnoses of the index hospitalization by HAA group are shown in Supplemental Table 1. For the severe HAA group, the most common diagnosis was hip fracture (20.8%).

 

 

Predictors of HAA

Compared to no or mild HAA, female sex, elective admission status, serum creatinine on admission, BUN to creatinine ratio greater than 20 to 1, hospital LOS, and undergoing a major diagnostic or therapeutic procedure were predictors for the development of moderate or severe HAA (Table 2). The model explained 23% of the variance (McFadden’s pseudo R2).

Predictors of Developing Moderate or Severe HAA
Table 2

Incidence of Postdischarge Outcomes by Severity of HAA

The severity of HAA was associated with a dose-dependent increase in the incidence of 30-day adverse outcomes, such that patients with increasing severity of HAA had greater 30-day composite, mortality, and readmission outcomes (P < 0.001; Figure). The 30-day postdischarge composite outcome was primarily driven by hospital readmissions given the low mortality rate in our cohort. Patients who did not develop HAA had an incidence of 9.7% for the composite outcome, whereas patients with severe HAA had an incidence of 16.4%. Among the 24 patients with severe HAA but who had not undergone a major procedure or had a discharge diagnosis for hemorrhage or for a coagulation or hemorrhagic disorder, only 3 (12.5%) had a composite postdischarge adverse outcome (2 readmissions and 1 death). The median time to readmission was similar between groups, but more patients with severe HAA had an early readmission within 7 days of hospital discharge than patients who did not develop HAA (6.9% vs. 2.9%, P = 0.001; Supplemental Table 2).

Association of HAA and Postdischarge Outcomes

In unadjusted analyses, compared to not developing HAA, mild, moderate, and severe HAA were associated with a 29%, 61%, and 81% increase in the odds for a composite outcome, respectively (Table 3). After adjustment for confounders, the effect size for HAA attenuated and was no longer statistically significant for mild and moderate HAA. However, severe HAA was significantly associated with a 39% increase in the odds for the composite outcome and a 41% increase in the odds for 30-day readmission (P = 0.008 and P = 0.02, respectively).

Association of HAA and 30-Day Postdischarge Adverse Outcomes
Table 3

In sensitivity analyses, the exclusion of individuals who received at least 1 blood transfusion during the index hospitalization (n=298) and individuals who had a primary discharge diagnosis for AMI (n=353) did not substantively change the estimates of the association between severe HAA and postdischarge outcomes (Supplemental Tables 3 and 4). However, because of the fewer number of adverse events for each analysis, the confidence intervals were wider and the association of severe HAA and the composite outcome and readmission were no longer statistically significant in these subcohorts.

DISCUSSION

In this large and diverse sample of medical inpatients, we found that HAA occurs in one-third of adults with normal hematocrit value at admission, where 10.1% of the cohort developed moderately severe HAA and 1.4% developed severe HAA by the time of discharge. Length of stay and undergoing a major diagnostic or therapeutic procedure were the 2 strongest potentially modifiable predictors of developing moderate or severe HAA. Severe HAA was independently associated with a 39% increase in the odds of being readmitted or dying within 30 days after hospital discharge compared to not developing HAA. However, the associations between mild or moderate HAA with adverse outcomes were attenuated after adjusting for confounders and were no longer statistically significant.

To our knowledge, this is the first study on the postdischarge adverse outcomes of HAA among a diverse cohort of medical inpatients hospitalized for any reason. In a more restricted population, Salisbury et al.3 found that patients hospitalized for AMI who developed moderate to severe HAA (hemoglobin value at discharge of 11 g/dL or less) had greater 1-year mortality than those without HAA (8.4% vs. 2.6%, P < 0.001), and had an 82% increase in the hazard for mortality (95% confidence interval, hazard ratio 1.11-2.98). Others have similarly shown that HAA is common among patients hospitalized with AMI and is associated with greater mortality.5,9,18 Our study extends upon this prior research by showing that severe HAA increases the risk for adverse outcomes for all adult inpatients, not only those hospitalized for AMI or among those receiving blood transfusions.

Despite the increased harm associated with severe HAA, it is unclear whether HAA is a preventable hazard of hospitalization, as suggested by others.6,8 Most patients in our cohort who developed severe HAA underwent a major procedure, had a discharge diagnosis for hemorrhage, and/or had a discharge diagnosis for a coagulation or hemorrhagic disorder. Thus, blood loss due to phlebotomy, 1 of the more modifiable etiologies of HAA, was unlikely to have been the primary driver for most patients who developed severe HAA. Since it has been estimated to take 15 days of daily phlebotomy of 53 mL of whole blood in females of average body weight (and 20 days for average weight males) with no bone marrow synthesis for severe anemia to develop, it is even less likely that phlebotomy was the principal etiology given an 8-day median LOS among patients with severe HAA.19,20 However, since the etiology of HAA can be multifactorial, limiting blood loss due to phlebotomy by using smaller volume tubes, blood conservation devices, or reducing unnecessary testing may mitigate the development of severe HAA.21,22 Additionally, since more than three-quarters of patients who developed severe HAA underwent a major procedure, more care and attention to minimizing operative blood loss could lessen the severity of HAA and facilitate better recovery. If minimizing blood loss is not feasible, in the absence of symptoms related to anemia or ongoing blood loss, randomized controlled trials overwhelmingly support a restrictive transfusion strategy using a hemoglobin value threshold of 7 mg/dL, even in the postoperative setting.23-25

The implications of mild to moderate HAA are less clear. The odds ratios for mild and moderate HAA, while not statistically significant, suggest a small increase in harm compared to not developing HAA. Furthermore, the upper boundary of the confidence intervals for mild and moderate HAA cannot exclude a possible 30% and 56% increase in the odds for the 30-day composite outcome, respectively. Thus, a better powered study, including more patients and extending the time interval for ascertaining postdischarge adverse events beyond 30 days, may reveal a harmful association. Lastly, our study assessed only the association of HAA with 30-day readmission and mortality. Examining the association between HAA and other patient-centered outcomes such as fatigue, functional impairment, and prolonged posthospitalization recovery time may uncover other important adverse effects of mild and moderate HAA, both of which occur far more frequently than severe HAA.

Our findings should be interpreted in the context of several limitations. First, although we included a diverse group of patients from a multihospital cohort, generalizability to other settings is uncertain. Second, as this was a retrospective study using EHR data, we had limited information to infer the precise mechanism of HAA for each patient. However, procedure codes and discharge diagnoses enabled us to assess which patients underwent a major procedure or had a hemorrhage or hemorrhagic disorder during the hospitalization. Third, given the relatively few number of patients with severe HAA in our cohort, we were unable to assess if the association of severe HAA differed by suspected etiology. Lastly, because we were unable to ascertain the timing of the hematocrit values within the first 24 hours of admission, we excluded both patients with preexisting anemia on admission and those who developed HAA within the first 24 hours of admission, which is not uncommon.26 Thus, we were unable to assess the effect of acute on chronic anemia arising during hospitalization and HAA that develops within the first 24 hours, both of which may also be harmful.18,27,28

In conclusion, severe HAA occurs in 1.4% of all medical hospitalizations and is associated with increased odds of death or readmission within 30 days. Since most patients with severe HAA had undergone a major procedure or had a discharge diagnosis of hemorrhage or a coagulation or hemorrhagic disorder, it is unclear if severe HAA is potentially preventable through preventing blood loss from phlebotomy or by reducing iatrogenic injury during procedures. Future research should assess the potential preventability of severe HAA, and examine other patient-centered outcomes potentially related to anemia, including fatigue, functional impairment, and trajectory of posthospital recovery.

 

 

Acknowledgments

The authors would like to acknowledge Ruben Amarasingham, MD, MBA, President and Chief Executive Officer of the Parkland Center for Clinical Innovation, and Ferdinand Velasco, MD, Chief Health Information Officer at Texas Health Resources, for their assistance in assembling the 6 hospital cohort used in this study. The authors would also like to thank Valy Fontil, MD, MAS, Assistant Professor of Medicine at the University of California San Francisco School of Medicine, and Elizabeth Rogers, MD, MAS, Assistant Professor of Internal Medicine and Pediatrics at the University of Minnesota Medical School, for their constructive feedback on an earlier version of this manuscript.

Disclosures

This work was supported by the Agency for Healthcare Research and Quality-funded UT Southwestern Center for Patient-Centered Outcomes Research (R24 HS022418-01); the Commonwealth Foundation (#20100323); the UT Southwestern KL2 Scholars Program supported by the National Institutes of Health (KL2 TR001103); the National Center for Advancing Translational Sciences at the National Institute of Health (U54 RFA-TR-12-006); and the National Institute on Aging (K23AG052603). The study sponsors had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. The authors have no financial conflicts of interest to disclose.

References

1. Kurniali PC, Curry S, Brennan KW, et al. A retrospective study investigating the incidence and predisposing factors of hospital-acquired anemia. Anemia. 2014;2014:634582. PubMed
2. Koch CG, Li L, Sun Z, et al. Hospital-acquired anemia: prevalence, outcomes, and healthcare implications. J Hosp Med. 2013;8(9):506-512. PubMed
3. Salisbury AC, Alexander KP, Reid KJ, et al. Incidence, correlates, and outcomes of acute, hospital-acquired anemia in patients with acute myocardial infarction. Circ Cardiovasc Qual Outcomes. 2010;3(4):337-346. PubMed
4. Salisbury AC, Amin AP, Reid KJ, et al. Hospital-acquired anemia and in-hospital mortality in patients with acute myocardial infarction. Am Heart J. 2011;162(2):300-309 e303. PubMed
5. Meroño O, Cladellas M, Recasens L, et al. In-hospital acquired anemia in acute coronary syndrome. Predictors, in-hospital prognosis and one-year mortality. Rev Esp Cardiol (Engl Ed). 2012;65(8):742-748. PubMed
6. Salisbury AC, Reid KJ, Alexander KP, et al. Diagnostic blood loss from phlebotomy and hospital-acquired anemia during acute myocardial infarction. Arch Intern Med. 2011;171(18):1646-1653. PubMed
7. Thavendiranathan P, Bagai A, Ebidia A, Detsky AS, Choudhry NK. Do blood tests cause anemia in hospitalized patients? The effect of diagnostic phlebotomy on hemoglobin and hematocrit levels. J Gen Intern Med. 2005;20(6):520-524. PubMed
8. Rennke S, Fang MC. Hazards of hospitalization: more than just “never events”. Arch Intern Med. 2011;171(18):1653-1654. PubMed
9. Choi JS, Kim YA, Kang YU, et al. Clinical impact of hospital-acquired anemia in association with acute kidney injury and chronic kidney disease in patients with acute myocardial infarction. PLoS One. 2013;8(9):e75583. PubMed
10. Salisbury AC, Kosiborod M, Amin AP, et al. Recovery from hospital-acquired anemia after acute myocardial infarction and effect on outcomes. Am J Cardiol. 2011;108(7):949-954. PubMed
11. Nguyen OK, Makam AN, Clark C, et al. Predicting all-cause readmissions using electronic health record data from the entire hospitalization: Model development and comparison. J Hosp Med. 2016;11(7):473-480. PubMed
12. Amarasingham R, Velasco F, Xie B, et al. Electronic medical record-based multicondition models to predict the risk of 30 day readmission or death among adult medicine patients: validation and comparison to existing models. BMC Med Inform Decis Mak. 2015;15:39. PubMed
13. World Health Organization. Hemoglobin concentrations for the diagnosis of anaemia and assessment of severity. http://www.who.int/vmnis/indicators/haemoglobin.pdf. Accessed March 15, 2016.
14. Martin ND, Scantling D. Hospital-acquired anemia: a contemporary review of etiologies and prevention strategies. J Infus Nurs. 2015;38(5):330-338. PubMed
15. Agency for Healthcare Research and Quality, Rockville, MD. Clinical classification software (CCS) for ICD-9-CM. Healthcare Cost and Utilization Project. 2015 http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Accessed November 18, 2015.
16. Agency for Healthcare Research and Quality, Rockville, MD. Procedure classes2015. Healthcare Cost and Utilization Project. 2015. https://www.hcup-us.ahrq.gov/toolssoftware/procedure/procedure.jsp. Accessed November 18, 2015.
17. Corwin HL, Gettinger A, Pearl RG, et al. The CRIT Study: Anemia and blood transfusion in the critically ill--current clinical practice in the United States. Crit Care Med. 2004;32(1):39-52. PubMed
18. Aronson D, Suleiman M, Agmon Y, et al. Changes in haemoglobin levels during hospital course and long-term outcome after acute myocardial infarction. Eur Heart J. 2007;28(11):1289-1296. PubMed
19. Lyon AW, Chin AC, Slotsve GA, Lyon ME. Simulation of repetitive diagnostic blood loss and onset of iatrogenic anemia in critical care patients with a mathematical model. Comput Biol Med. 2013;43(2):84-90. PubMed
20. van der Bom JG, Cannegieter SC. Hospital-acquired anemia: the contribution of diagnostic blood loss. J Thromb Haemost. 2015;13(6):1157-1159. PubMed
21. Sanchez-Giron F, Alvarez-Mora F. Reduction of blood loss from laboratory testing in hospitalized adult patients using small-volume (pediatric) tubes. Arch Pathol Lab Med. 2008;132(12):1916-1919. PubMed
22. Smoller BR, Kruskall MS. Phlebotomy for diagnostic laboratory tests in adults. Pattern of use and effect on transfusion requirements. N Engl J Med. 1986;314(19):1233-1235. PubMed
23. Carson JL, Carless PA, Hebert PC. Transfusion thresholds and other strategies for guiding allogeneic red blood cell transfusion. Cochrane Database Syst Rev. 2012(4):CD002042. PubMed
24. Carson JL, Carless PA, Hébert PC. Outcomes using lower vs higher hemoglobin thresholds for red blood cell transfusion. JAMA. 2013;309(1):83-84. PubMed
25. Carson JL, Sieber F, Cook DR, et al. Liberal versus restrictive blood transfusion strategy: 3-year survival and cause of death results from the FOCUS randomised controlled trial. Lancet. 2015;385(9974):1183-1189. PubMed
26. Rajkomar A, McCulloch CE, Fang MC. Low diagnostic utility of rechecking hemoglobins within 24 hours in hospitalized patients. Am J Med. 2016;129(11):1194-1197. PubMed
27. Reade MC, Weissfeld L, Angus DC, Kellum JA, Milbrandt EB. The prevalence of anemia and its association with 90-day mortality in hospitalized community-acquired pneumonia. BMC Pulm Med. 2010;10:15. PubMed
28. Halm EA, Wang JJ, Boockvar K, et al. The effect of perioperative anemia on clinical and functional outcomes in patients with hip fracture. J Orthop Trauma. 2004;18(6):369-374. PubMed

References

1. Kurniali PC, Curry S, Brennan KW, et al. A retrospective study investigating the incidence and predisposing factors of hospital-acquired anemia. Anemia. 2014;2014:634582. PubMed
2. Koch CG, Li L, Sun Z, et al. Hospital-acquired anemia: prevalence, outcomes, and healthcare implications. J Hosp Med. 2013;8(9):506-512. PubMed
3. Salisbury AC, Alexander KP, Reid KJ, et al. Incidence, correlates, and outcomes of acute, hospital-acquired anemia in patients with acute myocardial infarction. Circ Cardiovasc Qual Outcomes. 2010;3(4):337-346. PubMed
4. Salisbury AC, Amin AP, Reid KJ, et al. Hospital-acquired anemia and in-hospital mortality in patients with acute myocardial infarction. Am Heart J. 2011;162(2):300-309 e303. PubMed
5. Meroño O, Cladellas M, Recasens L, et al. In-hospital acquired anemia in acute coronary syndrome. Predictors, in-hospital prognosis and one-year mortality. Rev Esp Cardiol (Engl Ed). 2012;65(8):742-748. PubMed
6. Salisbury AC, Reid KJ, Alexander KP, et al. Diagnostic blood loss from phlebotomy and hospital-acquired anemia during acute myocardial infarction. Arch Intern Med. 2011;171(18):1646-1653. PubMed
7. Thavendiranathan P, Bagai A, Ebidia A, Detsky AS, Choudhry NK. Do blood tests cause anemia in hospitalized patients? The effect of diagnostic phlebotomy on hemoglobin and hematocrit levels. J Gen Intern Med. 2005;20(6):520-524. PubMed
8. Rennke S, Fang MC. Hazards of hospitalization: more than just “never events”. Arch Intern Med. 2011;171(18):1653-1654. PubMed
9. Choi JS, Kim YA, Kang YU, et al. Clinical impact of hospital-acquired anemia in association with acute kidney injury and chronic kidney disease in patients with acute myocardial infarction. PLoS One. 2013;8(9):e75583. PubMed
10. Salisbury AC, Kosiborod M, Amin AP, et al. Recovery from hospital-acquired anemia after acute myocardial infarction and effect on outcomes. Am J Cardiol. 2011;108(7):949-954. PubMed
11. Nguyen OK, Makam AN, Clark C, et al. Predicting all-cause readmissions using electronic health record data from the entire hospitalization: Model development and comparison. J Hosp Med. 2016;11(7):473-480. PubMed
12. Amarasingham R, Velasco F, Xie B, et al. Electronic medical record-based multicondition models to predict the risk of 30 day readmission or death among adult medicine patients: validation and comparison to existing models. BMC Med Inform Decis Mak. 2015;15:39. PubMed
13. World Health Organization. Hemoglobin concentrations for the diagnosis of anaemia and assessment of severity. http://www.who.int/vmnis/indicators/haemoglobin.pdf. Accessed March 15, 2016.
14. Martin ND, Scantling D. Hospital-acquired anemia: a contemporary review of etiologies and prevention strategies. J Infus Nurs. 2015;38(5):330-338. PubMed
15. Agency for Healthcare Research and Quality, Rockville, MD. Clinical classification software (CCS) for ICD-9-CM. Healthcare Cost and Utilization Project. 2015 http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Accessed November 18, 2015.
16. Agency for Healthcare Research and Quality, Rockville, MD. Procedure classes2015. Healthcare Cost and Utilization Project. 2015. https://www.hcup-us.ahrq.gov/toolssoftware/procedure/procedure.jsp. Accessed November 18, 2015.
17. Corwin HL, Gettinger A, Pearl RG, et al. The CRIT Study: Anemia and blood transfusion in the critically ill--current clinical practice in the United States. Crit Care Med. 2004;32(1):39-52. PubMed
18. Aronson D, Suleiman M, Agmon Y, et al. Changes in haemoglobin levels during hospital course and long-term outcome after acute myocardial infarction. Eur Heart J. 2007;28(11):1289-1296. PubMed
19. Lyon AW, Chin AC, Slotsve GA, Lyon ME. Simulation of repetitive diagnostic blood loss and onset of iatrogenic anemia in critical care patients with a mathematical model. Comput Biol Med. 2013;43(2):84-90. PubMed
20. van der Bom JG, Cannegieter SC. Hospital-acquired anemia: the contribution of diagnostic blood loss. J Thromb Haemost. 2015;13(6):1157-1159. PubMed
21. Sanchez-Giron F, Alvarez-Mora F. Reduction of blood loss from laboratory testing in hospitalized adult patients using small-volume (pediatric) tubes. Arch Pathol Lab Med. 2008;132(12):1916-1919. PubMed
22. Smoller BR, Kruskall MS. Phlebotomy for diagnostic laboratory tests in adults. Pattern of use and effect on transfusion requirements. N Engl J Med. 1986;314(19):1233-1235. PubMed
23. Carson JL, Carless PA, Hebert PC. Transfusion thresholds and other strategies for guiding allogeneic red blood cell transfusion. Cochrane Database Syst Rev. 2012(4):CD002042. PubMed
24. Carson JL, Carless PA, Hébert PC. Outcomes using lower vs higher hemoglobin thresholds for red blood cell transfusion. JAMA. 2013;309(1):83-84. PubMed
25. Carson JL, Sieber F, Cook DR, et al. Liberal versus restrictive blood transfusion strategy: 3-year survival and cause of death results from the FOCUS randomised controlled trial. Lancet. 2015;385(9974):1183-1189. PubMed
26. Rajkomar A, McCulloch CE, Fang MC. Low diagnostic utility of rechecking hemoglobins within 24 hours in hospitalized patients. Am J Med. 2016;129(11):1194-1197. PubMed
27. Reade MC, Weissfeld L, Angus DC, Kellum JA, Milbrandt EB. The prevalence of anemia and its association with 90-day mortality in hospitalized community-acquired pneumonia. BMC Pulm Med. 2010;10:15. PubMed
28. Halm EA, Wang JJ, Boockvar K, et al. The effect of perioperative anemia on clinical and functional outcomes in patients with hip fracture. J Orthop Trauma. 2004;18(6):369-374. PubMed

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Association between radiologic incidental findings and resource utilization in patients admitted with chest pain in an urban medical center

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Association between radiologic incidental findings and resource utilization in patients admitted with chest pain in an urban medical center

Diagnostic imaging is an integral part of patient evaluation in acute care settings. The use of imaging for presenting complaints of chest pain, abdominal pain, and injuries has increased in emergency departments across the United States without an increase in detection of acute pathologic conditions.1,2 An unintended consequence of this increase in diagnostic imaging is the discovery of incidental findings (IFs).

Incidental findings are unexpected findings (eg, nodules) noted on diagnostic imaging that are not related to the presenting complaint.3 The increasing use of diagnostic imaging and increased sensitivity of these tests have led to a higher burden of radiologic IFs.4 In a tertiary level hospital, Lumbreras et al.5 found that the overall incidence of IFs for all radiologic imaging for inpatients and outpatients was 15%, while Orme et al.6 found that the incidence in imaging research was 39.8%. The existing evidence base suggests that the identification of radiologic IFs has financial,5,7 clinical,6 ethical, and legal implications.8 Also, IFs increase workload for healthcare professionals, including that related to follow-up and surveillance.9

In the field of radiology, the burden of radiologic IFs is a well-accepted fact and various white papers have been published by the American College of Radiology on how to address them.4,7 Hospitalized patients are a population that undergoes a substantial number of diagnostic tests. In the era of accountable care organizations10 with an emphasis on population health and high-value care, radiologic IFs pose a particular challenge to healthcare providers.

Chest pain is one of the most common reasons for emergency department visits in the United States.11 In this study, we report on radiologic IFs and factors associated with these among patients hospitalized for chest pain of suspected cardiac origin, and we evaluate the hypothesis that radiologic IFs are associated with an increase in LOS in this population.

METHODS

We conducted a secondary analysis of data from the Chest Pain and Cocaine Study (CPAC). The CPAC study is a cross sectional study of all patients hospitalized with chest pain to our urban academic medical center. Medical records were reviewed to generate a database of all such patients during the study period. The main focus of CPAC was to look at healthcare disparities and resource utilization in patients with or without a concomitant diagnosis of cocaine use.12

Flow chart of patient selection.
Figure

Study Population

The Figure shows the selection of the study sample for this analysis. The CPaC Study identified 1811 consecutive admissions for chest pain/angina pectoris (based on admitting diagnosis ICD-9-CM codes: 411.x; 413.x, 414.x; and 786.5x) over 24 months. Per the CPaC Study protocol, patients older than 65 years were excluded (n=567 admissions). After chart review, all admissions diagnosed with acute myocardial infarction (n=97) or noncardiac chest pain (n=655) were excluded. For this analysis, we excluded 39 additional admissions of patients who had known prior radiologic IFs, leading to a sample size of 453 admissions. Three hundred and seventy six patients had accounted for 453 admissions during the study period, and we included1 of these admissions in the analysis using the following process: If a patient had a radiologic IF on any admission during the study period, that patient was included in the “IF” group for the analysis, and data from the first admission with an IF were used for the analysis. If a patient had no radiologic IFs on any admission during the study period, that patient was included in the “no IF” group, and the data from the first admission in the database were used for analysis.

 

 

Measurements

Data collection was completed retrospectively by medical record review using a standardized CPaC Study protocol. The database was created and maintained using REDCap (Research Electronic Data Capture; Vanderbilt University, Knoxville, Tennessee) electronic data capture tool hosted at Johns Hopkins University.13 All data were manually abstracted into REDCap from electronic medical records. All missing values and inconsistent data were reviewed by multiple physicians to ensure data integrity.

We defined all diagnostic (noninterventional; nonlaboratory) testing done during a patient’s hospitalization as “diagnostic” tests, except cardiac stress testing and echocardiogram. We defined diagnostic tests as “primary” tests if they were done in response to patients’ presenting complaint. We defined diagnostic tests as “secondary” tests if they were done by providers due to IFs. Cardiac computed tomography was included in diagnostic tests. Cardiac testing (echocardiogram, cardiac stress testing, cardiac catheterization and pacemaker placement) was considered separate from the “diagnostic tests” since these were focused cardiac imaging that are interventional in nature with low yield on extra-cardiac radiologic IFs.

Incidental findings were defined as any unexpected findings on diagnostic imaging unrelated to the reason for admission, and were classified based on organ systems and their clinical significance as major, moderate, or minor using a classification previously published by Lumbreras et al.14 All radiologic IFs data underwent sequential dual review by investigators for accuracy of documentation. Individuals with multiple radiologic IFs belonging to more than one category of clinical significance were categorized with the IFs group of highest clinical significance. Ten percent of the patients with no IFs were reviewed again, and no errors found.

Demographic variables at the time of admission included age, sex, race, level of education, employment status, insurance status, body mass index (BMI), and smoking status. Comorbid conditions at the time of admission consisted of the following: hypertension, diabetes mellitus, chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), history of myocardial infarction, cerebrovascular accident (CVA), congestive heart failure (CHF), drug use and malignancy or history of it. Initial laboratory values were extracted from electronic medical records and included hemoglobin, creatinine, blood urea nitrogen (BUN), aspartate transaminase, alanine transaminase, and alkaline phosphatase. We calculated the estimated glomerular filtration rate (eGFR) using the MDRD (Modification of Diet in Renal Disease) equation.15 Admission and discharge information as well as whether the patient had a primary care provider, were obtained from medical records. The length of hospital stay was calculated by subtracting date of admission from date of discharge.

Statistical Analysis

We conducted 2 main analyses: 1) a descriptive analysis of the association between patient characteristics (independent variables) and identification of IFs during admission (primary outcome) and 2) an analysis of the association between identification of incidental findings during admission (independent variable) and LOS (primary outcome).

For the descriptive analysis of radiologic IFs, we compared the characteristics of patients with and without radiologic IFs during admission using a t-test (for normally distributed continuous variables) or Mann-Whitney test (for nonnormally distributed continuous variables) and a chi-square or Fisher exact test for categorical variables based on the number of observations. We included variables significantly associated with the occurrence of radiologic IFs (P < 0.05) in a multiple logistic regression model to identify characteristics independently associated with presence of radiologic IFs.

Length of stay was right-skewed even after natural logarithm transformation and, therefore, we used negative binomial regression for the analysis of the association between the identification of radiologic IFs during admission and LOS. We included potential confounding variables in the multiple negative binomial regression model based on plausibility of confounding and association with both the exposure (identification of radiologic IFs during admission) and outcome (LOS) at a level of P < 0.3. Age, education level, history of drug use, history of CHF, history of CKD, lower eGFR, higher serum creatinine/BUN, hemoglobin, occurrence of cardiac catheterization, stress testing, and multiple admissions during the study period were identified as confounders. For correlated variables (eg, hemoglobin and hematocrit), the variable with the strongest statistical association (lowest P value) was included in the model. In sensitivity analysis, we dropped patients with extreme LOS (longer than 10 days). All analyses were performed using STATA 13 (Stata Statistical Software: Release 13; StataCorp., College Station, Texas).

Table 1

RESULTS

Table 1 shows the characteristics of the 376 patients included in this study. Overall mean age was 50.5 years, 40% were females, 62% were Caucasian, 66% were unemployed, 84% identified a primary care provider upon admission, and 68% were cared for by a hospitalist. Overall median LOS was 2 days (interquartile range [IQR] = 2). Of the 376 patients in the study, 197 (52%) had new radiologic IFs. Comparing the patients with radiologic IFs and no IFs, it was evident that more radiological tests were performed in the IF group (2.2 tests per patient) in comparison with the no IF group (1.26 tests per patient). Looking at patient characteristics, patients with radiologic IFs were older (52 years vs. 48.8 years; P < 0.001), reported a lower education level and lower hemoglobin levels on admission (12.0 gm/dL vs. 13.4 gm/dL; P = 0.029), but were more likely to be unemployed (72% vs. 59%; P = 0.009), have COPD (19% vs. 10%; P = 0.007), and a history of malignancy (7% vs. 2%, P = 0.04). In addition, patients in the radiologic IF group had lower rates of cardiac catheterization (18% vs. 28%; P = 0.02), were more likely to be readmitted more than once during the study period (17% vs. 7%; P = 0.02) and be discharged by hospitalists (75% vs. 60%; P = 0.003; Supplemental Table 1).

 

 

Overall, 658 diagnostic tests were performed in the study population; of these, 268 (40.7%) tests revealed 364 new radiologic IFs (Supplement Table 2). Of these radiologic IFs, 27 (7.4%) were of major clinical significance, 154 (42%) were of moderate clinical significance, and 183 (50%) were of minor clinical significance (Supplement Table 3). Computed tomography (CT) scans yielded more IFs compared to any other imaging modalities. Of the radiologic IFs of major clinical significance, 3 malignant/premalignant lesions were found. While pulmonary nodules were the most common moderate clinically significant findings, atelectasis and spinal degenerative changes were the most common radiologic IFs of minor clinical significance (Supplement Table 4).


Table 2

Results of the logistic regression models testing the association between patient characteristics and radiologic IFs are displayed in Table 2. Only age and repeat admissions remained significantly associated with radiologic IFs in the fully adjusted model (adjusted odds ratio [OR], 1.04; 95% confidence interval [CI], 1.01-1.06 and 2.68; 95% CI, 1.60-4.44, respectively).

Median LOS was 2 days (IQR=1) for patients with no IFs and 2 days (IQR=2) for patient with radiologic IFs (P = 0.08). Unadjusted negative binomial regression analysis revealed that identification of any radiologic IFs during admission (vs. none) was associated with an increased LOS by 24% (unadjusted IRR, 1.24; 95% CI, 1.06-1.45). After adjustment for confounders, identification of any radiologic IFs during admission remained significantly associated with a longer LOS (adjusted IRR, 1.26; 95% CI, 1.07-1.49). Results remained significant on a sensitivity analysis excluding admissions lasting longer than 10 days (adjusted IRR, 1.21; 95% CI, 1.03-1.42; Supplement Table 5).

Multivariate Negative Binomial Regression of LOS by IF Clinical Significance
Table 3


Incidental findings of minor and moderate clinical significance were associated with increase in LOS on multiple negative binomial regression (adjusted IRR, 1.27; 95% CI, 1.03-1.57 and 1.24; 95% CI, 1.02-1.52, respectively; Table 3); however, upon dropping length of hospitalization outliers, only radiologic IFs with major clinical significance were associated with increase in length of hospitalization (adjusted IRR, 1.39; 95% CI, 1.04-1.87; Table 3).

Supplemental chart review revealed that 26 patients accounted for the 27 radiologic IFs of major clinical significance. This group had 54% women, median LOS remained 2 days (IQR 2) and, on average, had about 3 diagnostic tests performed per patient. Cardiac testing was performed less on these patients compared to others (Supplement Table S6). Review also revealed that, of the 26 patients, 2 had abnormal labs, 2 had drug abuse/psychiatric issues, and another 2 had radiologic IFs that warranted further consultations, imaging, and longer LOS.

DISCUSSION

Radiologic IFs in patients admitted with chest pain of suspected cardiac origin are a common occurrence as shown in our study. Similar to prior studies, 41% of all radiologic tests done in our study population revealed IFs.6 The majority of the IFs were of minor to moderate clinical significance and, as reported in the literature, were more common with older age and CT imaging.14,16 In addition, an IF diagnosed during admission for chest pain was associated with a 26% increase in length of hospital stay.

To our knowledge, we present the first study on the impact of identification of radiologic IFs in hospitalized patients on length of hospital stay and specifically in patients hospitalized with chest pain of suspected cardiac origin. Trends over the past decade have shown a decrease in LOS and hospitalizations but with an increase in health resource utilization.17,18 Association of radiologic IFs with increase in LOS is significant as this potentially increases hospital-acquired conditions such as infections and resource utilization leading to increase in costs of hospitalizations.19 This in return is a concern for patient safety.

The positive association between LOS and radiologic IFs, interestingly, continued to exist despite sensitivity analysis. Incidental findings of major clinical significance were associated with longer LOS in the sensitivity analysis. Supplemental chart review of patients with major clinical findings suggested more extra-cardiac workup compared to patients with minor/moderate radiologic IFs. This could indicate that the presence of clinically significant radiologic IFs could have led to further inpatient work-up and consultations. The downstream healthcare expenditure associated with workup of IFs in individual radiologic tests is well established.20 In case of cardiac CT, Goehler et al.21 found that the healthcare expenditure was high following incidentally detected pulmonary nodules with an overall small reduction in lung cancer mortality. Incidental findings also increase the burden of reporting and concern for medico-legal issues for providers.4 These concerns are likely valid for hospitalized patients as well.

The socioeconomic trends in the study population were consistent with data from the Bureau of Labor Statistics in that low education is associated with higher unemployment.22 Although, overall, gender, race and insurance mix were similar in both groups, we did see trends of socioeconomic differences in the patients with radiologic IFs of major clinical significance that might not have been statistically significant owing to the small sample size. Despite the population being relatively of younger age (given our cut off age was 65 years) there was still a positive association with age and presence of radiologic IFs. The higher number of patients with COPD or history of malignancy in the radiologic IF group suggests that an association with IFs could exist for these disease cohorts; however, after adjustment for multiple covariates, such an association did not transpire. Interestingly, patients with no radiologic IFs underwent cardiac catheterization or stress testing more often than patients with discovered IFs. This speaks of 2 possibilities; first, that both tests probably do not yield many extra-cardiac IFs, or, secondly, that these patients did not require further workup. More patients in the IF group had more than 1 admission during the study period, and this was associated with increased odds of detecting radiologic IFs. We hypothesize that this might have occurred because of the diagnostic dilemma in these patients who have multiple admissions for the same reason leading to wider array of diagnostic workup. Indeed, we did not note upon chart review alternative diagnoses in these patients but only more IFs. There are several study limitations to consider. First, the fact that this is a single center study sets limitations to interpretation and generalizability of the data. Second, we cannot exclude the possibility of residual confounding. Third, the small number of patients included in this study precludes definitive identification of more factors potentially associated with IFs. However, this study sheds light on a yet unidentified problem within the realm of inpatient management especially for the internists and hospitalists. We tried to limit bias to the extent possible by including only 1 presenting complaint and age-restricting the population.

 

 

CONCLUSION

Incidental findings are both clinical and financial challenges to the medical field. This study attempted to shed light on impact of radiologic IFs on care and resource utilization in patients admitted with chest pain of suspected cardiac origin. The positive association between radiologic IFs and length of hospital stay implies that the presence of IFs is associated with increase in LOS and indirectly a likely increase in overall healthcare expenditure. Given the high incidence of radiologic IFs, assuming that these will be present on radiologic tests, should be more a norm than an exception. Providers should know that radiologic testing, especially CT, is associated with detection of IFs.16 By avoiding inappropriate ordering of imaging, the issue of IFs could be mitigated.

While radiologists have recommendations about necessary follow-up for some IFs,7 no clear follow-up guidelines exist for most IFs arising in hospitalized patients. Further prospective and cost analysis studies are needed to assess the overall impact of IFs on other hospitalized patient populations and on the healthcare system in general.

Disclosure

The authors report no conflicts of interest.

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References

1. Korley FK, Pham JC, Kirsch TD. Use of advanced radiology during visits to US emergency departments for injury-related conditions, 1998-2007. JAMA. 2010;304(13):1465-1471. PubMed
2. Pines JM. Trends in the rates of radiography use and important diagnoses in emergency department patients with abdominal pain. Med Care. 2009;47(7):782-786. PubMed
3. McGraw-Hill Concise Dictionary of Modern Medicine. Incidentalomas. http://medical-dictionary.thefreedictionary.com/Incidental+findings. Updated 2002. Accessed April 13, 2017.
4. Berland LL, Silverman SG, Gore RM, et al. Managing incidental findings on abdominal CT: White paper of the ACR incidental findings committee. J Am Coll Radiol. 2010;7(10):754-773. PubMed
5. Lumbreras B, González-Alvárez I, Lorente MF, Calbo J, Aranaz J, Hernández-Aguado I. Unexpected findings at imaging: Predicting frequency in various types of studies. Eur J Radiol. 2010;74(1):269-274. PubMed
6. Orme NM, Fletcher JG, Siddiki HA, et al. Incidental findings in imaging research: Evaluating incidence, benefit, and burden. Arch Intern Med. 2010;170(17):1525-1532. PubMed
7. Berland LL. Overview of white papers of the ACR incidental findings committee II on adnexal, vascular, splenic, nodal, gallbladder, and biliary findings. J Am Coll Radiol. 2013;10(9):672-674. PubMed
8. Booth TC, Jackson A, Wardlaw JM, Taylor SA, Waldman AD. Incidental findings found in “healthy” volunteers during imaging performed for research: Current legal and ethical implications. Br J Radiol. 2010;83(990):456-465. PubMed
9. Kelly ME, Heeney A, Redmond CE, et al. Incidental findings detected on emergency abdominal CT scans: A 1-year review. Abdom Imaging. 2015;40(6):1853-1857. PubMed
10. Centers for Medicare and Medicaid Services. Accountable care organizations (ACO). https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ACO/index.html?redirect=/aco. Baltimore, Maryland. Updated 01/06/2015.
11. Weiss AJ (Truven Health Analytics), Wier LM (Truven Health Analytics), Stocks C (AHRQ), Blanchard J (RAND). Overview of Emergency Department Visits in the United States, 2011. HCUP Statistical Brief #174. June 2014. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb174-Emergency-Department-Visits-Overview.pdf.
12. Chibungu A, Gundareddy V, Wright SM, Nwabuo C, Bollampally P, Landis R, Eid SM. Management of cocaine-induced myocardial infarction: 4-year experience at an urban medical center. South Med J. 2016;109(3):185-190. PubMed
13. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377-381. PubMed
14. Lumbreras B, Donat L, Hernández-Aguado I. Incidental findings in imaging diagnostic tests: a systematic review. Br J Radiol. 2010;83(988):276-289. PubMed
15. Fontela PC, Winkelmann ER, Ott JN, Uggeri DP. Estimated glomerular filtration rate in patients with type 2 diabetes mellitus. Rev Assoc Méd Bras (1992). 2014;60(6):531-537. PubMed
16. Samim M, Goss S, Luty S, Weinreb J, Moore C. Incidental findings on CT for suspected renal colic in emergency department patients: prevalence and types in 5,383 consecutive examinations. J Am Coll Radiol. 2015;12(1):63-69. PubMed
17. Avalere Health for the American Health Association. TrendWatch ChartBook 2014; trends affecting hospitals and health systems. 2014. http://www.aha.org/research/reports/tw/chartbook/2014/14chartbook.pdf.
18. Weiss AJ, Elixhauser A. Overview of hospital stays in the United States, 2012. HCUP statistical brief #180. https://www.hcup-us.ahrq.gov/reports/statbriefs/sb180-Hospitalizations-United-States-2012.jsp. Accessed April 13, 2017.
19. Hauck K, Zhao X. How dangerous is a day in hospital?: A model of adverse events and length of stay for medical inpatients. Med Care. 2011;49(12):1068-1075. PubMed
20. Ding A, Eisenberg JD, Pandharipande PV. The economic burden of incidentally detected findings. Radiol Clin North Am. 2011;49(2):257-265. PubMed
21. Goehler A, McMahon PM, Lumish HS, et al. Cost-effectiveness of follow-up of pulmonary nodules incidentally detected on cardiac computed tomographic angiography in patients with suspected coronary artery disease. Circulation. 2014;130(8):668-675. PubMed
22. U.S. Department of Labor. Bureau of Labor Statistics. Employment projections. Earning and unemployment rates by educational attainment, 2015. http://www.bls.gov/emp/ep_chart_001.htm. Updated March 15, 2016. Accessed April 13, 2017

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Diagnostic imaging is an integral part of patient evaluation in acute care settings. The use of imaging for presenting complaints of chest pain, abdominal pain, and injuries has increased in emergency departments across the United States without an increase in detection of acute pathologic conditions.1,2 An unintended consequence of this increase in diagnostic imaging is the discovery of incidental findings (IFs).

Incidental findings are unexpected findings (eg, nodules) noted on diagnostic imaging that are not related to the presenting complaint.3 The increasing use of diagnostic imaging and increased sensitivity of these tests have led to a higher burden of radiologic IFs.4 In a tertiary level hospital, Lumbreras et al.5 found that the overall incidence of IFs for all radiologic imaging for inpatients and outpatients was 15%, while Orme et al.6 found that the incidence in imaging research was 39.8%. The existing evidence base suggests that the identification of radiologic IFs has financial,5,7 clinical,6 ethical, and legal implications.8 Also, IFs increase workload for healthcare professionals, including that related to follow-up and surveillance.9

In the field of radiology, the burden of radiologic IFs is a well-accepted fact and various white papers have been published by the American College of Radiology on how to address them.4,7 Hospitalized patients are a population that undergoes a substantial number of diagnostic tests. In the era of accountable care organizations10 with an emphasis on population health and high-value care, radiologic IFs pose a particular challenge to healthcare providers.

Chest pain is one of the most common reasons for emergency department visits in the United States.11 In this study, we report on radiologic IFs and factors associated with these among patients hospitalized for chest pain of suspected cardiac origin, and we evaluate the hypothesis that radiologic IFs are associated with an increase in LOS in this population.

METHODS

We conducted a secondary analysis of data from the Chest Pain and Cocaine Study (CPAC). The CPAC study is a cross sectional study of all patients hospitalized with chest pain to our urban academic medical center. Medical records were reviewed to generate a database of all such patients during the study period. The main focus of CPAC was to look at healthcare disparities and resource utilization in patients with or without a concomitant diagnosis of cocaine use.12

Flow chart of patient selection.
Figure

Study Population

The Figure shows the selection of the study sample for this analysis. The CPaC Study identified 1811 consecutive admissions for chest pain/angina pectoris (based on admitting diagnosis ICD-9-CM codes: 411.x; 413.x, 414.x; and 786.5x) over 24 months. Per the CPaC Study protocol, patients older than 65 years were excluded (n=567 admissions). After chart review, all admissions diagnosed with acute myocardial infarction (n=97) or noncardiac chest pain (n=655) were excluded. For this analysis, we excluded 39 additional admissions of patients who had known prior radiologic IFs, leading to a sample size of 453 admissions. Three hundred and seventy six patients had accounted for 453 admissions during the study period, and we included1 of these admissions in the analysis using the following process: If a patient had a radiologic IF on any admission during the study period, that patient was included in the “IF” group for the analysis, and data from the first admission with an IF were used for the analysis. If a patient had no radiologic IFs on any admission during the study period, that patient was included in the “no IF” group, and the data from the first admission in the database were used for analysis.

 

 

Measurements

Data collection was completed retrospectively by medical record review using a standardized CPaC Study protocol. The database was created and maintained using REDCap (Research Electronic Data Capture; Vanderbilt University, Knoxville, Tennessee) electronic data capture tool hosted at Johns Hopkins University.13 All data were manually abstracted into REDCap from electronic medical records. All missing values and inconsistent data were reviewed by multiple physicians to ensure data integrity.

We defined all diagnostic (noninterventional; nonlaboratory) testing done during a patient’s hospitalization as “diagnostic” tests, except cardiac stress testing and echocardiogram. We defined diagnostic tests as “primary” tests if they were done in response to patients’ presenting complaint. We defined diagnostic tests as “secondary” tests if they were done by providers due to IFs. Cardiac computed tomography was included in diagnostic tests. Cardiac testing (echocardiogram, cardiac stress testing, cardiac catheterization and pacemaker placement) was considered separate from the “diagnostic tests” since these were focused cardiac imaging that are interventional in nature with low yield on extra-cardiac radiologic IFs.

Incidental findings were defined as any unexpected findings on diagnostic imaging unrelated to the reason for admission, and were classified based on organ systems and their clinical significance as major, moderate, or minor using a classification previously published by Lumbreras et al.14 All radiologic IFs data underwent sequential dual review by investigators for accuracy of documentation. Individuals with multiple radiologic IFs belonging to more than one category of clinical significance were categorized with the IFs group of highest clinical significance. Ten percent of the patients with no IFs were reviewed again, and no errors found.

Demographic variables at the time of admission included age, sex, race, level of education, employment status, insurance status, body mass index (BMI), and smoking status. Comorbid conditions at the time of admission consisted of the following: hypertension, diabetes mellitus, chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), history of myocardial infarction, cerebrovascular accident (CVA), congestive heart failure (CHF), drug use and malignancy or history of it. Initial laboratory values were extracted from electronic medical records and included hemoglobin, creatinine, blood urea nitrogen (BUN), aspartate transaminase, alanine transaminase, and alkaline phosphatase. We calculated the estimated glomerular filtration rate (eGFR) using the MDRD (Modification of Diet in Renal Disease) equation.15 Admission and discharge information as well as whether the patient had a primary care provider, were obtained from medical records. The length of hospital stay was calculated by subtracting date of admission from date of discharge.

Statistical Analysis

We conducted 2 main analyses: 1) a descriptive analysis of the association between patient characteristics (independent variables) and identification of IFs during admission (primary outcome) and 2) an analysis of the association between identification of incidental findings during admission (independent variable) and LOS (primary outcome).

For the descriptive analysis of radiologic IFs, we compared the characteristics of patients with and without radiologic IFs during admission using a t-test (for normally distributed continuous variables) or Mann-Whitney test (for nonnormally distributed continuous variables) and a chi-square or Fisher exact test for categorical variables based on the number of observations. We included variables significantly associated with the occurrence of radiologic IFs (P < 0.05) in a multiple logistic regression model to identify characteristics independently associated with presence of radiologic IFs.

Length of stay was right-skewed even after natural logarithm transformation and, therefore, we used negative binomial regression for the analysis of the association between the identification of radiologic IFs during admission and LOS. We included potential confounding variables in the multiple negative binomial regression model based on plausibility of confounding and association with both the exposure (identification of radiologic IFs during admission) and outcome (LOS) at a level of P < 0.3. Age, education level, history of drug use, history of CHF, history of CKD, lower eGFR, higher serum creatinine/BUN, hemoglobin, occurrence of cardiac catheterization, stress testing, and multiple admissions during the study period were identified as confounders. For correlated variables (eg, hemoglobin and hematocrit), the variable with the strongest statistical association (lowest P value) was included in the model. In sensitivity analysis, we dropped patients with extreme LOS (longer than 10 days). All analyses were performed using STATA 13 (Stata Statistical Software: Release 13; StataCorp., College Station, Texas).

Table 1

RESULTS

Table 1 shows the characteristics of the 376 patients included in this study. Overall mean age was 50.5 years, 40% were females, 62% were Caucasian, 66% were unemployed, 84% identified a primary care provider upon admission, and 68% were cared for by a hospitalist. Overall median LOS was 2 days (interquartile range [IQR] = 2). Of the 376 patients in the study, 197 (52%) had new radiologic IFs. Comparing the patients with radiologic IFs and no IFs, it was evident that more radiological tests were performed in the IF group (2.2 tests per patient) in comparison with the no IF group (1.26 tests per patient). Looking at patient characteristics, patients with radiologic IFs were older (52 years vs. 48.8 years; P < 0.001), reported a lower education level and lower hemoglobin levels on admission (12.0 gm/dL vs. 13.4 gm/dL; P = 0.029), but were more likely to be unemployed (72% vs. 59%; P = 0.009), have COPD (19% vs. 10%; P = 0.007), and a history of malignancy (7% vs. 2%, P = 0.04). In addition, patients in the radiologic IF group had lower rates of cardiac catheterization (18% vs. 28%; P = 0.02), were more likely to be readmitted more than once during the study period (17% vs. 7%; P = 0.02) and be discharged by hospitalists (75% vs. 60%; P = 0.003; Supplemental Table 1).

 

 

Overall, 658 diagnostic tests were performed in the study population; of these, 268 (40.7%) tests revealed 364 new radiologic IFs (Supplement Table 2). Of these radiologic IFs, 27 (7.4%) were of major clinical significance, 154 (42%) were of moderate clinical significance, and 183 (50%) were of minor clinical significance (Supplement Table 3). Computed tomography (CT) scans yielded more IFs compared to any other imaging modalities. Of the radiologic IFs of major clinical significance, 3 malignant/premalignant lesions were found. While pulmonary nodules were the most common moderate clinically significant findings, atelectasis and spinal degenerative changes were the most common radiologic IFs of minor clinical significance (Supplement Table 4).


Table 2

Results of the logistic regression models testing the association between patient characteristics and radiologic IFs are displayed in Table 2. Only age and repeat admissions remained significantly associated with radiologic IFs in the fully adjusted model (adjusted odds ratio [OR], 1.04; 95% confidence interval [CI], 1.01-1.06 and 2.68; 95% CI, 1.60-4.44, respectively).

Median LOS was 2 days (IQR=1) for patients with no IFs and 2 days (IQR=2) for patient with radiologic IFs (P = 0.08). Unadjusted negative binomial regression analysis revealed that identification of any radiologic IFs during admission (vs. none) was associated with an increased LOS by 24% (unadjusted IRR, 1.24; 95% CI, 1.06-1.45). After adjustment for confounders, identification of any radiologic IFs during admission remained significantly associated with a longer LOS (adjusted IRR, 1.26; 95% CI, 1.07-1.49). Results remained significant on a sensitivity analysis excluding admissions lasting longer than 10 days (adjusted IRR, 1.21; 95% CI, 1.03-1.42; Supplement Table 5).

Multivariate Negative Binomial Regression of LOS by IF Clinical Significance
Table 3


Incidental findings of minor and moderate clinical significance were associated with increase in LOS on multiple negative binomial regression (adjusted IRR, 1.27; 95% CI, 1.03-1.57 and 1.24; 95% CI, 1.02-1.52, respectively; Table 3); however, upon dropping length of hospitalization outliers, only radiologic IFs with major clinical significance were associated with increase in length of hospitalization (adjusted IRR, 1.39; 95% CI, 1.04-1.87; Table 3).

Supplemental chart review revealed that 26 patients accounted for the 27 radiologic IFs of major clinical significance. This group had 54% women, median LOS remained 2 days (IQR 2) and, on average, had about 3 diagnostic tests performed per patient. Cardiac testing was performed less on these patients compared to others (Supplement Table S6). Review also revealed that, of the 26 patients, 2 had abnormal labs, 2 had drug abuse/psychiatric issues, and another 2 had radiologic IFs that warranted further consultations, imaging, and longer LOS.

DISCUSSION

Radiologic IFs in patients admitted with chest pain of suspected cardiac origin are a common occurrence as shown in our study. Similar to prior studies, 41% of all radiologic tests done in our study population revealed IFs.6 The majority of the IFs were of minor to moderate clinical significance and, as reported in the literature, were more common with older age and CT imaging.14,16 In addition, an IF diagnosed during admission for chest pain was associated with a 26% increase in length of hospital stay.

To our knowledge, we present the first study on the impact of identification of radiologic IFs in hospitalized patients on length of hospital stay and specifically in patients hospitalized with chest pain of suspected cardiac origin. Trends over the past decade have shown a decrease in LOS and hospitalizations but with an increase in health resource utilization.17,18 Association of radiologic IFs with increase in LOS is significant as this potentially increases hospital-acquired conditions such as infections and resource utilization leading to increase in costs of hospitalizations.19 This in return is a concern for patient safety.

The positive association between LOS and radiologic IFs, interestingly, continued to exist despite sensitivity analysis. Incidental findings of major clinical significance were associated with longer LOS in the sensitivity analysis. Supplemental chart review of patients with major clinical findings suggested more extra-cardiac workup compared to patients with minor/moderate radiologic IFs. This could indicate that the presence of clinically significant radiologic IFs could have led to further inpatient work-up and consultations. The downstream healthcare expenditure associated with workup of IFs in individual radiologic tests is well established.20 In case of cardiac CT, Goehler et al.21 found that the healthcare expenditure was high following incidentally detected pulmonary nodules with an overall small reduction in lung cancer mortality. Incidental findings also increase the burden of reporting and concern for medico-legal issues for providers.4 These concerns are likely valid for hospitalized patients as well.

The socioeconomic trends in the study population were consistent with data from the Bureau of Labor Statistics in that low education is associated with higher unemployment.22 Although, overall, gender, race and insurance mix were similar in both groups, we did see trends of socioeconomic differences in the patients with radiologic IFs of major clinical significance that might not have been statistically significant owing to the small sample size. Despite the population being relatively of younger age (given our cut off age was 65 years) there was still a positive association with age and presence of radiologic IFs. The higher number of patients with COPD or history of malignancy in the radiologic IF group suggests that an association with IFs could exist for these disease cohorts; however, after adjustment for multiple covariates, such an association did not transpire. Interestingly, patients with no radiologic IFs underwent cardiac catheterization or stress testing more often than patients with discovered IFs. This speaks of 2 possibilities; first, that both tests probably do not yield many extra-cardiac IFs, or, secondly, that these patients did not require further workup. More patients in the IF group had more than 1 admission during the study period, and this was associated with increased odds of detecting radiologic IFs. We hypothesize that this might have occurred because of the diagnostic dilemma in these patients who have multiple admissions for the same reason leading to wider array of diagnostic workup. Indeed, we did not note upon chart review alternative diagnoses in these patients but only more IFs. There are several study limitations to consider. First, the fact that this is a single center study sets limitations to interpretation and generalizability of the data. Second, we cannot exclude the possibility of residual confounding. Third, the small number of patients included in this study precludes definitive identification of more factors potentially associated with IFs. However, this study sheds light on a yet unidentified problem within the realm of inpatient management especially for the internists and hospitalists. We tried to limit bias to the extent possible by including only 1 presenting complaint and age-restricting the population.

 

 

CONCLUSION

Incidental findings are both clinical and financial challenges to the medical field. This study attempted to shed light on impact of radiologic IFs on care and resource utilization in patients admitted with chest pain of suspected cardiac origin. The positive association between radiologic IFs and length of hospital stay implies that the presence of IFs is associated with increase in LOS and indirectly a likely increase in overall healthcare expenditure. Given the high incidence of radiologic IFs, assuming that these will be present on radiologic tests, should be more a norm than an exception. Providers should know that radiologic testing, especially CT, is associated with detection of IFs.16 By avoiding inappropriate ordering of imaging, the issue of IFs could be mitigated.

While radiologists have recommendations about necessary follow-up for some IFs,7 no clear follow-up guidelines exist for most IFs arising in hospitalized patients. Further prospective and cost analysis studies are needed to assess the overall impact of IFs on other hospitalized patient populations and on the healthcare system in general.

Disclosure

The authors report no conflicts of interest.

Diagnostic imaging is an integral part of patient evaluation in acute care settings. The use of imaging for presenting complaints of chest pain, abdominal pain, and injuries has increased in emergency departments across the United States without an increase in detection of acute pathologic conditions.1,2 An unintended consequence of this increase in diagnostic imaging is the discovery of incidental findings (IFs).

Incidental findings are unexpected findings (eg, nodules) noted on diagnostic imaging that are not related to the presenting complaint.3 The increasing use of diagnostic imaging and increased sensitivity of these tests have led to a higher burden of radiologic IFs.4 In a tertiary level hospital, Lumbreras et al.5 found that the overall incidence of IFs for all radiologic imaging for inpatients and outpatients was 15%, while Orme et al.6 found that the incidence in imaging research was 39.8%. The existing evidence base suggests that the identification of radiologic IFs has financial,5,7 clinical,6 ethical, and legal implications.8 Also, IFs increase workload for healthcare professionals, including that related to follow-up and surveillance.9

In the field of radiology, the burden of radiologic IFs is a well-accepted fact and various white papers have been published by the American College of Radiology on how to address them.4,7 Hospitalized patients are a population that undergoes a substantial number of diagnostic tests. In the era of accountable care organizations10 with an emphasis on population health and high-value care, radiologic IFs pose a particular challenge to healthcare providers.

Chest pain is one of the most common reasons for emergency department visits in the United States.11 In this study, we report on radiologic IFs and factors associated with these among patients hospitalized for chest pain of suspected cardiac origin, and we evaluate the hypothesis that radiologic IFs are associated with an increase in LOS in this population.

METHODS

We conducted a secondary analysis of data from the Chest Pain and Cocaine Study (CPAC). The CPAC study is a cross sectional study of all patients hospitalized with chest pain to our urban academic medical center. Medical records were reviewed to generate a database of all such patients during the study period. The main focus of CPAC was to look at healthcare disparities and resource utilization in patients with or without a concomitant diagnosis of cocaine use.12

Flow chart of patient selection.
Figure

Study Population

The Figure shows the selection of the study sample for this analysis. The CPaC Study identified 1811 consecutive admissions for chest pain/angina pectoris (based on admitting diagnosis ICD-9-CM codes: 411.x; 413.x, 414.x; and 786.5x) over 24 months. Per the CPaC Study protocol, patients older than 65 years were excluded (n=567 admissions). After chart review, all admissions diagnosed with acute myocardial infarction (n=97) or noncardiac chest pain (n=655) were excluded. For this analysis, we excluded 39 additional admissions of patients who had known prior radiologic IFs, leading to a sample size of 453 admissions. Three hundred and seventy six patients had accounted for 453 admissions during the study period, and we included1 of these admissions in the analysis using the following process: If a patient had a radiologic IF on any admission during the study period, that patient was included in the “IF” group for the analysis, and data from the first admission with an IF were used for the analysis. If a patient had no radiologic IFs on any admission during the study period, that patient was included in the “no IF” group, and the data from the first admission in the database were used for analysis.

 

 

Measurements

Data collection was completed retrospectively by medical record review using a standardized CPaC Study protocol. The database was created and maintained using REDCap (Research Electronic Data Capture; Vanderbilt University, Knoxville, Tennessee) electronic data capture tool hosted at Johns Hopkins University.13 All data were manually abstracted into REDCap from electronic medical records. All missing values and inconsistent data were reviewed by multiple physicians to ensure data integrity.

We defined all diagnostic (noninterventional; nonlaboratory) testing done during a patient’s hospitalization as “diagnostic” tests, except cardiac stress testing and echocardiogram. We defined diagnostic tests as “primary” tests if they were done in response to patients’ presenting complaint. We defined diagnostic tests as “secondary” tests if they were done by providers due to IFs. Cardiac computed tomography was included in diagnostic tests. Cardiac testing (echocardiogram, cardiac stress testing, cardiac catheterization and pacemaker placement) was considered separate from the “diagnostic tests” since these were focused cardiac imaging that are interventional in nature with low yield on extra-cardiac radiologic IFs.

Incidental findings were defined as any unexpected findings on diagnostic imaging unrelated to the reason for admission, and were classified based on organ systems and their clinical significance as major, moderate, or minor using a classification previously published by Lumbreras et al.14 All radiologic IFs data underwent sequential dual review by investigators for accuracy of documentation. Individuals with multiple radiologic IFs belonging to more than one category of clinical significance were categorized with the IFs group of highest clinical significance. Ten percent of the patients with no IFs were reviewed again, and no errors found.

Demographic variables at the time of admission included age, sex, race, level of education, employment status, insurance status, body mass index (BMI), and smoking status. Comorbid conditions at the time of admission consisted of the following: hypertension, diabetes mellitus, chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), history of myocardial infarction, cerebrovascular accident (CVA), congestive heart failure (CHF), drug use and malignancy or history of it. Initial laboratory values were extracted from electronic medical records and included hemoglobin, creatinine, blood urea nitrogen (BUN), aspartate transaminase, alanine transaminase, and alkaline phosphatase. We calculated the estimated glomerular filtration rate (eGFR) using the MDRD (Modification of Diet in Renal Disease) equation.15 Admission and discharge information as well as whether the patient had a primary care provider, were obtained from medical records. The length of hospital stay was calculated by subtracting date of admission from date of discharge.

Statistical Analysis

We conducted 2 main analyses: 1) a descriptive analysis of the association between patient characteristics (independent variables) and identification of IFs during admission (primary outcome) and 2) an analysis of the association between identification of incidental findings during admission (independent variable) and LOS (primary outcome).

For the descriptive analysis of radiologic IFs, we compared the characteristics of patients with and without radiologic IFs during admission using a t-test (for normally distributed continuous variables) or Mann-Whitney test (for nonnormally distributed continuous variables) and a chi-square or Fisher exact test for categorical variables based on the number of observations. We included variables significantly associated with the occurrence of radiologic IFs (P < 0.05) in a multiple logistic regression model to identify characteristics independently associated with presence of radiologic IFs.

Length of stay was right-skewed even after natural logarithm transformation and, therefore, we used negative binomial regression for the analysis of the association between the identification of radiologic IFs during admission and LOS. We included potential confounding variables in the multiple negative binomial regression model based on plausibility of confounding and association with both the exposure (identification of radiologic IFs during admission) and outcome (LOS) at a level of P < 0.3. Age, education level, history of drug use, history of CHF, history of CKD, lower eGFR, higher serum creatinine/BUN, hemoglobin, occurrence of cardiac catheterization, stress testing, and multiple admissions during the study period were identified as confounders. For correlated variables (eg, hemoglobin and hematocrit), the variable with the strongest statistical association (lowest P value) was included in the model. In sensitivity analysis, we dropped patients with extreme LOS (longer than 10 days). All analyses were performed using STATA 13 (Stata Statistical Software: Release 13; StataCorp., College Station, Texas).

Table 1

RESULTS

Table 1 shows the characteristics of the 376 patients included in this study. Overall mean age was 50.5 years, 40% were females, 62% were Caucasian, 66% were unemployed, 84% identified a primary care provider upon admission, and 68% were cared for by a hospitalist. Overall median LOS was 2 days (interquartile range [IQR] = 2). Of the 376 patients in the study, 197 (52%) had new radiologic IFs. Comparing the patients with radiologic IFs and no IFs, it was evident that more radiological tests were performed in the IF group (2.2 tests per patient) in comparison with the no IF group (1.26 tests per patient). Looking at patient characteristics, patients with radiologic IFs were older (52 years vs. 48.8 years; P < 0.001), reported a lower education level and lower hemoglobin levels on admission (12.0 gm/dL vs. 13.4 gm/dL; P = 0.029), but were more likely to be unemployed (72% vs. 59%; P = 0.009), have COPD (19% vs. 10%; P = 0.007), and a history of malignancy (7% vs. 2%, P = 0.04). In addition, patients in the radiologic IF group had lower rates of cardiac catheterization (18% vs. 28%; P = 0.02), were more likely to be readmitted more than once during the study period (17% vs. 7%; P = 0.02) and be discharged by hospitalists (75% vs. 60%; P = 0.003; Supplemental Table 1).

 

 

Overall, 658 diagnostic tests were performed in the study population; of these, 268 (40.7%) tests revealed 364 new radiologic IFs (Supplement Table 2). Of these radiologic IFs, 27 (7.4%) were of major clinical significance, 154 (42%) were of moderate clinical significance, and 183 (50%) were of minor clinical significance (Supplement Table 3). Computed tomography (CT) scans yielded more IFs compared to any other imaging modalities. Of the radiologic IFs of major clinical significance, 3 malignant/premalignant lesions were found. While pulmonary nodules were the most common moderate clinically significant findings, atelectasis and spinal degenerative changes were the most common radiologic IFs of minor clinical significance (Supplement Table 4).


Table 2

Results of the logistic regression models testing the association between patient characteristics and radiologic IFs are displayed in Table 2. Only age and repeat admissions remained significantly associated with radiologic IFs in the fully adjusted model (adjusted odds ratio [OR], 1.04; 95% confidence interval [CI], 1.01-1.06 and 2.68; 95% CI, 1.60-4.44, respectively).

Median LOS was 2 days (IQR=1) for patients with no IFs and 2 days (IQR=2) for patient with radiologic IFs (P = 0.08). Unadjusted negative binomial regression analysis revealed that identification of any radiologic IFs during admission (vs. none) was associated with an increased LOS by 24% (unadjusted IRR, 1.24; 95% CI, 1.06-1.45). After adjustment for confounders, identification of any radiologic IFs during admission remained significantly associated with a longer LOS (adjusted IRR, 1.26; 95% CI, 1.07-1.49). Results remained significant on a sensitivity analysis excluding admissions lasting longer than 10 days (adjusted IRR, 1.21; 95% CI, 1.03-1.42; Supplement Table 5).

Multivariate Negative Binomial Regression of LOS by IF Clinical Significance
Table 3


Incidental findings of minor and moderate clinical significance were associated with increase in LOS on multiple negative binomial regression (adjusted IRR, 1.27; 95% CI, 1.03-1.57 and 1.24; 95% CI, 1.02-1.52, respectively; Table 3); however, upon dropping length of hospitalization outliers, only radiologic IFs with major clinical significance were associated with increase in length of hospitalization (adjusted IRR, 1.39; 95% CI, 1.04-1.87; Table 3).

Supplemental chart review revealed that 26 patients accounted for the 27 radiologic IFs of major clinical significance. This group had 54% women, median LOS remained 2 days (IQR 2) and, on average, had about 3 diagnostic tests performed per patient. Cardiac testing was performed less on these patients compared to others (Supplement Table S6). Review also revealed that, of the 26 patients, 2 had abnormal labs, 2 had drug abuse/psychiatric issues, and another 2 had radiologic IFs that warranted further consultations, imaging, and longer LOS.

DISCUSSION

Radiologic IFs in patients admitted with chest pain of suspected cardiac origin are a common occurrence as shown in our study. Similar to prior studies, 41% of all radiologic tests done in our study population revealed IFs.6 The majority of the IFs were of minor to moderate clinical significance and, as reported in the literature, were more common with older age and CT imaging.14,16 In addition, an IF diagnosed during admission for chest pain was associated with a 26% increase in length of hospital stay.

To our knowledge, we present the first study on the impact of identification of radiologic IFs in hospitalized patients on length of hospital stay and specifically in patients hospitalized with chest pain of suspected cardiac origin. Trends over the past decade have shown a decrease in LOS and hospitalizations but with an increase in health resource utilization.17,18 Association of radiologic IFs with increase in LOS is significant as this potentially increases hospital-acquired conditions such as infections and resource utilization leading to increase in costs of hospitalizations.19 This in return is a concern for patient safety.

The positive association between LOS and radiologic IFs, interestingly, continued to exist despite sensitivity analysis. Incidental findings of major clinical significance were associated with longer LOS in the sensitivity analysis. Supplemental chart review of patients with major clinical findings suggested more extra-cardiac workup compared to patients with minor/moderate radiologic IFs. This could indicate that the presence of clinically significant radiologic IFs could have led to further inpatient work-up and consultations. The downstream healthcare expenditure associated with workup of IFs in individual radiologic tests is well established.20 In case of cardiac CT, Goehler et al.21 found that the healthcare expenditure was high following incidentally detected pulmonary nodules with an overall small reduction in lung cancer mortality. Incidental findings also increase the burden of reporting and concern for medico-legal issues for providers.4 These concerns are likely valid for hospitalized patients as well.

The socioeconomic trends in the study population were consistent with data from the Bureau of Labor Statistics in that low education is associated with higher unemployment.22 Although, overall, gender, race and insurance mix were similar in both groups, we did see trends of socioeconomic differences in the patients with radiologic IFs of major clinical significance that might not have been statistically significant owing to the small sample size. Despite the population being relatively of younger age (given our cut off age was 65 years) there was still a positive association with age and presence of radiologic IFs. The higher number of patients with COPD or history of malignancy in the radiologic IF group suggests that an association with IFs could exist for these disease cohorts; however, after adjustment for multiple covariates, such an association did not transpire. Interestingly, patients with no radiologic IFs underwent cardiac catheterization or stress testing more often than patients with discovered IFs. This speaks of 2 possibilities; first, that both tests probably do not yield many extra-cardiac IFs, or, secondly, that these patients did not require further workup. More patients in the IF group had more than 1 admission during the study period, and this was associated with increased odds of detecting radiologic IFs. We hypothesize that this might have occurred because of the diagnostic dilemma in these patients who have multiple admissions for the same reason leading to wider array of diagnostic workup. Indeed, we did not note upon chart review alternative diagnoses in these patients but only more IFs. There are several study limitations to consider. First, the fact that this is a single center study sets limitations to interpretation and generalizability of the data. Second, we cannot exclude the possibility of residual confounding. Third, the small number of patients included in this study precludes definitive identification of more factors potentially associated with IFs. However, this study sheds light on a yet unidentified problem within the realm of inpatient management especially for the internists and hospitalists. We tried to limit bias to the extent possible by including only 1 presenting complaint and age-restricting the population.

 

 

CONCLUSION

Incidental findings are both clinical and financial challenges to the medical field. This study attempted to shed light on impact of radiologic IFs on care and resource utilization in patients admitted with chest pain of suspected cardiac origin. The positive association between radiologic IFs and length of hospital stay implies that the presence of IFs is associated with increase in LOS and indirectly a likely increase in overall healthcare expenditure. Given the high incidence of radiologic IFs, assuming that these will be present on radiologic tests, should be more a norm than an exception. Providers should know that radiologic testing, especially CT, is associated with detection of IFs.16 By avoiding inappropriate ordering of imaging, the issue of IFs could be mitigated.

While radiologists have recommendations about necessary follow-up for some IFs,7 no clear follow-up guidelines exist for most IFs arising in hospitalized patients. Further prospective and cost analysis studies are needed to assess the overall impact of IFs on other hospitalized patient populations and on the healthcare system in general.

Disclosure

The authors report no conflicts of interest.

References

1. Korley FK, Pham JC, Kirsch TD. Use of advanced radiology during visits to US emergency departments for injury-related conditions, 1998-2007. JAMA. 2010;304(13):1465-1471. PubMed
2. Pines JM. Trends in the rates of radiography use and important diagnoses in emergency department patients with abdominal pain. Med Care. 2009;47(7):782-786. PubMed
3. McGraw-Hill Concise Dictionary of Modern Medicine. Incidentalomas. http://medical-dictionary.thefreedictionary.com/Incidental+findings. Updated 2002. Accessed April 13, 2017.
4. Berland LL, Silverman SG, Gore RM, et al. Managing incidental findings on abdominal CT: White paper of the ACR incidental findings committee. J Am Coll Radiol. 2010;7(10):754-773. PubMed
5. Lumbreras B, González-Alvárez I, Lorente MF, Calbo J, Aranaz J, Hernández-Aguado I. Unexpected findings at imaging: Predicting frequency in various types of studies. Eur J Radiol. 2010;74(1):269-274. PubMed
6. Orme NM, Fletcher JG, Siddiki HA, et al. Incidental findings in imaging research: Evaluating incidence, benefit, and burden. Arch Intern Med. 2010;170(17):1525-1532. PubMed
7. Berland LL. Overview of white papers of the ACR incidental findings committee II on adnexal, vascular, splenic, nodal, gallbladder, and biliary findings. J Am Coll Radiol. 2013;10(9):672-674. PubMed
8. Booth TC, Jackson A, Wardlaw JM, Taylor SA, Waldman AD. Incidental findings found in “healthy” volunteers during imaging performed for research: Current legal and ethical implications. Br J Radiol. 2010;83(990):456-465. PubMed
9. Kelly ME, Heeney A, Redmond CE, et al. Incidental findings detected on emergency abdominal CT scans: A 1-year review. Abdom Imaging. 2015;40(6):1853-1857. PubMed
10. Centers for Medicare and Medicaid Services. Accountable care organizations (ACO). https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ACO/index.html?redirect=/aco. Baltimore, Maryland. Updated 01/06/2015.
11. Weiss AJ (Truven Health Analytics), Wier LM (Truven Health Analytics), Stocks C (AHRQ), Blanchard J (RAND). Overview of Emergency Department Visits in the United States, 2011. HCUP Statistical Brief #174. June 2014. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb174-Emergency-Department-Visits-Overview.pdf.
12. Chibungu A, Gundareddy V, Wright SM, Nwabuo C, Bollampally P, Landis R, Eid SM. Management of cocaine-induced myocardial infarction: 4-year experience at an urban medical center. South Med J. 2016;109(3):185-190. PubMed
13. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377-381. PubMed
14. Lumbreras B, Donat L, Hernández-Aguado I. Incidental findings in imaging diagnostic tests: a systematic review. Br J Radiol. 2010;83(988):276-289. PubMed
15. Fontela PC, Winkelmann ER, Ott JN, Uggeri DP. Estimated glomerular filtration rate in patients with type 2 diabetes mellitus. Rev Assoc Méd Bras (1992). 2014;60(6):531-537. PubMed
16. Samim M, Goss S, Luty S, Weinreb J, Moore C. Incidental findings on CT for suspected renal colic in emergency department patients: prevalence and types in 5,383 consecutive examinations. J Am Coll Radiol. 2015;12(1):63-69. PubMed
17. Avalere Health for the American Health Association. TrendWatch ChartBook 2014; trends affecting hospitals and health systems. 2014. http://www.aha.org/research/reports/tw/chartbook/2014/14chartbook.pdf.
18. Weiss AJ, Elixhauser A. Overview of hospital stays in the United States, 2012. HCUP statistical brief #180. https://www.hcup-us.ahrq.gov/reports/statbriefs/sb180-Hospitalizations-United-States-2012.jsp. Accessed April 13, 2017.
19. Hauck K, Zhao X. How dangerous is a day in hospital?: A model of adverse events and length of stay for medical inpatients. Med Care. 2011;49(12):1068-1075. PubMed
20. Ding A, Eisenberg JD, Pandharipande PV. The economic burden of incidentally detected findings. Radiol Clin North Am. 2011;49(2):257-265. PubMed
21. Goehler A, McMahon PM, Lumish HS, et al. Cost-effectiveness of follow-up of pulmonary nodules incidentally detected on cardiac computed tomographic angiography in patients with suspected coronary artery disease. Circulation. 2014;130(8):668-675. PubMed
22. U.S. Department of Labor. Bureau of Labor Statistics. Employment projections. Earning and unemployment rates by educational attainment, 2015. http://www.bls.gov/emp/ep_chart_001.htm. Updated March 15, 2016. Accessed April 13, 2017

References

1. Korley FK, Pham JC, Kirsch TD. Use of advanced radiology during visits to US emergency departments for injury-related conditions, 1998-2007. JAMA. 2010;304(13):1465-1471. PubMed
2. Pines JM. Trends in the rates of radiography use and important diagnoses in emergency department patients with abdominal pain. Med Care. 2009;47(7):782-786. PubMed
3. McGraw-Hill Concise Dictionary of Modern Medicine. Incidentalomas. http://medical-dictionary.thefreedictionary.com/Incidental+findings. Updated 2002. Accessed April 13, 2017.
4. Berland LL, Silverman SG, Gore RM, et al. Managing incidental findings on abdominal CT: White paper of the ACR incidental findings committee. J Am Coll Radiol. 2010;7(10):754-773. PubMed
5. Lumbreras B, González-Alvárez I, Lorente MF, Calbo J, Aranaz J, Hernández-Aguado I. Unexpected findings at imaging: Predicting frequency in various types of studies. Eur J Radiol. 2010;74(1):269-274. PubMed
6. Orme NM, Fletcher JG, Siddiki HA, et al. Incidental findings in imaging research: Evaluating incidence, benefit, and burden. Arch Intern Med. 2010;170(17):1525-1532. PubMed
7. Berland LL. Overview of white papers of the ACR incidental findings committee II on adnexal, vascular, splenic, nodal, gallbladder, and biliary findings. J Am Coll Radiol. 2013;10(9):672-674. PubMed
8. Booth TC, Jackson A, Wardlaw JM, Taylor SA, Waldman AD. Incidental findings found in “healthy” volunteers during imaging performed for research: Current legal and ethical implications. Br J Radiol. 2010;83(990):456-465. PubMed
9. Kelly ME, Heeney A, Redmond CE, et al. Incidental findings detected on emergency abdominal CT scans: A 1-year review. Abdom Imaging. 2015;40(6):1853-1857. PubMed
10. Centers for Medicare and Medicaid Services. Accountable care organizations (ACO). https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ACO/index.html?redirect=/aco. Baltimore, Maryland. Updated 01/06/2015.
11. Weiss AJ (Truven Health Analytics), Wier LM (Truven Health Analytics), Stocks C (AHRQ), Blanchard J (RAND). Overview of Emergency Department Visits in the United States, 2011. HCUP Statistical Brief #174. June 2014. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb174-Emergency-Department-Visits-Overview.pdf.
12. Chibungu A, Gundareddy V, Wright SM, Nwabuo C, Bollampally P, Landis R, Eid SM. Management of cocaine-induced myocardial infarction: 4-year experience at an urban medical center. South Med J. 2016;109(3):185-190. PubMed
13. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377-381. PubMed
14. Lumbreras B, Donat L, Hernández-Aguado I. Incidental findings in imaging diagnostic tests: a systematic review. Br J Radiol. 2010;83(988):276-289. PubMed
15. Fontela PC, Winkelmann ER, Ott JN, Uggeri DP. Estimated glomerular filtration rate in patients with type 2 diabetes mellitus. Rev Assoc Méd Bras (1992). 2014;60(6):531-537. PubMed
16. Samim M, Goss S, Luty S, Weinreb J, Moore C. Incidental findings on CT for suspected renal colic in emergency department patients: prevalence and types in 5,383 consecutive examinations. J Am Coll Radiol. 2015;12(1):63-69. PubMed
17. Avalere Health for the American Health Association. TrendWatch ChartBook 2014; trends affecting hospitals and health systems. 2014. http://www.aha.org/research/reports/tw/chartbook/2014/14chartbook.pdf.
18. Weiss AJ, Elixhauser A. Overview of hospital stays in the United States, 2012. HCUP statistical brief #180. https://www.hcup-us.ahrq.gov/reports/statbriefs/sb180-Hospitalizations-United-States-2012.jsp. Accessed April 13, 2017.
19. Hauck K, Zhao X. How dangerous is a day in hospital?: A model of adverse events and length of stay for medical inpatients. Med Care. 2011;49(12):1068-1075. PubMed
20. Ding A, Eisenberg JD, Pandharipande PV. The economic burden of incidentally detected findings. Radiol Clin North Am. 2011;49(2):257-265. PubMed
21. Goehler A, McMahon PM, Lumish HS, et al. Cost-effectiveness of follow-up of pulmonary nodules incidentally detected on cardiac computed tomographic angiography in patients with suspected coronary artery disease. Circulation. 2014;130(8):668-675. PubMed
22. U.S. Department of Labor. Bureau of Labor Statistics. Employment projections. Earning and unemployment rates by educational attainment, 2015. http://www.bls.gov/emp/ep_chart_001.htm. Updated March 15, 2016. Accessed April 13, 2017

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Association between radiologic incidental findings and resource utilization in patients admitted with chest pain in an urban medical center
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Address for correspondence and reprint requests: Venkat Pradeep Gundareddy, MD, MPH; Johns Hopkins University School of Medicine; Division of Hospital Medicine, Johns Hopkins Bayview Medical Center, 5200 Eastern Ave, MFL West 6th Floor, Baltimore, MD 21224; Telephone: 410-550-5018; Fax: 410-550-2972; E-mail: [email protected]
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Overuse of troponin? A comprehensive evaluation of testing in a large hospital system

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Overuse of troponin? A comprehensive evaluation of testing in a large hospital system

The ability of serum troponin measurement in the diagnosis of acute myocardial infarction (AMI) was validated in patients with at least a moderate pretest probability for the disease.1 The diagnostic yield of troponin testing in clinical trials has been between 20% and 50%, excluded patients thought unlikely to have AMI. In practice, physicians often encounter low-risk patients and patients in whom the diagnosis on initial presentation is unclear. Several noncardiac diagnoses, such as pneumonia and respiratory failure, are associated with an elevated troponin level in the absence of AMI, but patients can present with symptoms similar or identical to those of patients who present with AMI.2-4 Elevated troponin level in sepsis has been associated with worsened prognosis, though there is no evidence that this finding alters management. An American College of Cardiology Foundation opinion published in 2012 expressly recommends against troponin testing in patients with sepsis.4

The only guideline-based indication for troponin testing is the diagnosis or exclusion of AMI.5 We conducted a comprehensive review of troponin testing in our healthcare system to see whether testing might be used in clinical settings in which AMI was unlikely.

METHODS

We retrospectively obtained data on all visits to 14 hospitals in an integrated healthcare system in Texas between June 2013 and June 2014. We analyzed data for all hospital encounters during which a troponin assay was ordered and a troponin level reported—including qualitative point-of-care assays and quantitative laboratory troponin I measurements. We identified 93,436 visits. Quantitative measurements were divided into negative (<0.05 ng/mL), indeterminate (0.05-0.09 ng/mL), and elevated (>0.09 ng/mL), based on the reference ranges reported to physicians. We associated troponin levels with ICD-9 (International Classification of Diseases, Ninth Revision) primary and secondary diagnoses, grouping ICD-9 codes 410 (AMI), 411 (other acute or subacute forms of ischemic heart disease [IHD]), 412 (old myocardial infarction), 413 (angina pectoris), and 414 (other forms of chronic IHD) as representing IHD diagnoses.

To further evaluate troponin testing, we constructed 2 contingency matrices (Table).6 We included visits for which both primary and secondary diagnoses were available for review and for which quantitative troponin I measurements were available; 92,445 encounters met criteria for inclusion in matrix calculations. In the first matrix (part A of Table), a primary diagnosis of any AMI (ICD-9 code 410) was used as “positive” and all others “negative.” In the second matrix (part B of Table), “positive” includes any primary or secondary diagnosis of AMI.

Contingency Matrices Evaluating Elevated Troponin Levels and AMI Diagnoses
Table

RESULTS

We identified a total of 93,436 hospital visits associated with troponin testing; 179,239 troponin measurements were associated with these visits (an average of 1.81 per encounter). Of these visits, 59,897 (64.1%) were associated with a single measurement. Of the 179,239 measurements, 147,051 (82.1%) were negative, 21,881 (12.1%) indeterminate, and 10,307 (5.8%) positive. Primary diagnoses of hypertension, dizziness, abdominal pain, anxiety, dehydration, and headache associated with troponin testing comprised 6127 encounters and had no associated elevated troponin levels. Several non-cardiac primary diagnoses were associated with significant numbers of elevated troponin values including septicemia (27%), acute respiratory failure (28%), and cerebrovascular accident (10%). Seventy-six percent of encounters associated with troponin testing had no primary or secondary IHD diagnosis. Only 2% of 16,941 visits with a primary diagnosis of chest pain were associated with abnormal troponin levels (Figure).

Notable non-AMI primary diagnoses associated with elevated troponin I values.
Figure

 

 

Analysis of contingency matrices revealed AMI prevalence of 2.6% when primary AMI diagnoses were considered and 3.5% when any AMI diagnoses were considered. Sensitivity and specificity were high (>90%), and negative predictive value extremely high (>99%) in each circumstance. However, positive predictive values were low (21.7% and 28.8%, respectively), indicating the majority of patients with elevated troponin levels were not reported to have AMI by attending physicians.

DISCUSSION

We were surprised to find that troponin level was measured only once during 64% of the hospital encounters. Although there are clinical scenarios in which a single measurement might be indicated, detecting a rise or fall in troponin level is integral to the diagnosis of AMI, which is why guidelines recommend serial measurement.4 We were also surprised to find a low rate of either primary or secondary AMI in patients tested. As others have found,2,3 elevated troponin levels were associated with noncardiac primary diagnoses, such as sepsis, respiratory failure, and stroke. Of interest, the majority (72%) of patients with elevated troponin levels did not receive a primary or secondary diagnosis of AMI.

Determining the appropriate level of use for a diagnostic laboratory test can be difficult. Primary diagnostic codes, including codes for headache and dizziness, accounted for thousands of tested patients but were associated with no elevated troponin levels. On the other hand, sepsis, pneumonia, and stroke were associated with high rates of elevated troponin levels. Elevated troponin levels likely precipitate cardiology consultation and testing, which increase cost of care perhaps without improving either quality or value of care. However, evidence for the potential prognostic value of testing has led to ongoing research at our institution to evaluate whether troponin measurement might guide better management of such patients.

Appropriate use criteria have been developed for many diagnostic studies, including echocardiography, stress testing, and cardiac catheterization, but not for laboratory testing. Our data suggest possible overuse of troponin testing in our healthcare system. The low AMI incidence we found (2.6%-3.5%) indicates that many patients without AMI are being tested.

Although it is impossible to accurately estimate sensitivity and specificity of testing post hoc, it is reassuring to see that measured sensitivity, specificity, and negative predictive values were all high and consistent with published values from prospective clinical trials.7,8

As potential roles for troponin testing develop for patients without primary cardiac disease, it becomes even more important to develop guidelines for testing and to avoid universal testing of all hospitalized patients. The high negative predictive value of troponin testing (99%) is attractive to physicians who want to avoid missing AMI. Electronic order sets allow troponin testing to be included alongside “standard” testing, such as complete blood cell counts and comprehensive metabolic panels, and may contribute to overuse.

The troponin assays used in our healthcare system in 2014 likely will be replaced with high-sensitivity assays currently being used in Europe.9,10 These high-sensitivity assays can improve sensitivity but cannot be expected to increase positive predictive value or reduce false detection rates. When performed as single measurements, hs troponin has the potential to increase the number of elevated troponins detected that are not associated with AMI.

On the basis of our data, we have initiated a system-wide program to improve performance of troponin testing in our healthcare system. We are working with hospitalists and critical care and emergency department physicians to ensure that serial measurements are being performed and that the correct patients are being tested. Future data collection will help determine the success or failure of these efforts.

Disclosure

Nothing to report.

 

References

1. Thygesen K, Alpert JS, Jaffe AS, et al. Third universal definition of myocardial infarction. Circulation. 2012;126(16):2020-2035. PubMed
2. Hamm CW, Giannitsis E, Katus HA. Cardiac troponin elevations in patients without acute coronary syndrome. Circulation. 2002;106(23):2871-2872. PubMed
3. Roongsritong C, Warraich I, Bradley C. Common causes of troponin elevations in the absence of acute myocardial infarction: incidence and clinical significance. Chest. 2004;125(5):1877-1884. PubMed
4. Newby LK, Jesse RL, Babb JD, et al. ACCF 2012 expert consensus document on practical clinical considerations in the interpretation of troponin elevations: a report of the American College of Cardiology Foundation Task Force on Clinical Consensus Documents. J Am Coll Cardiol. 2012;60(23):2427-2463. PubMed
5. Amsterdam EA, Wenger NK, Brindis RG, et al; American College of Cardiology; American Heart Association Task Force on Practice Guidelines; Society for Cardiovascular Angiography and Interventions; Society of Thoracic Surgeons; American Association for Clinical Chemistry. 2014 AHA/ACC Guideline for the Management of Patients With Non-ST-Elevation Acute Coronary Syndromes: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014;64(24):e139-e228.
6. Pearson K. On the Theory of Contingency and Its Relationship to Association and Normal Correlation. Mathematical Contributions to the Theory of Evolution. London, England: Dulau & Co; 1904.
7. Katus HA, Remppis A, Neumann FJ, et al. Diagnostic efficiency of troponin T measurements in acute myocardial infarction. Circulation. 1991;83(3):902-912. PubMed
8. Olatidoye AG, Wu AH, Feng YJ, Waters D. Prognostic role of troponin T versus troponin I in unstable angina pectoris for cardiac events with meta-analysis comparing published studies. Am J Cardiol. 1998;81(12):1405-1410. PubMed
9. Reichlin T, Hochholzer W, Bassetti S, et al. Early diagnosis of myocardial infarction with sensitive cardiac troponin assays. N Engl J Med. 2009;361(9):858-867. PubMed
10. Keller T, Zeller T, Peetz D, et al. Sensitive troponin I assay in early diagnosis of acute myocardial infarction. N Engl J Med. 2009;361(9):868-877. PubMed

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The ability of serum troponin measurement in the diagnosis of acute myocardial infarction (AMI) was validated in patients with at least a moderate pretest probability for the disease.1 The diagnostic yield of troponin testing in clinical trials has been between 20% and 50%, excluded patients thought unlikely to have AMI. In practice, physicians often encounter low-risk patients and patients in whom the diagnosis on initial presentation is unclear. Several noncardiac diagnoses, such as pneumonia and respiratory failure, are associated with an elevated troponin level in the absence of AMI, but patients can present with symptoms similar or identical to those of patients who present with AMI.2-4 Elevated troponin level in sepsis has been associated with worsened prognosis, though there is no evidence that this finding alters management. An American College of Cardiology Foundation opinion published in 2012 expressly recommends against troponin testing in patients with sepsis.4

The only guideline-based indication for troponin testing is the diagnosis or exclusion of AMI.5 We conducted a comprehensive review of troponin testing in our healthcare system to see whether testing might be used in clinical settings in which AMI was unlikely.

METHODS

We retrospectively obtained data on all visits to 14 hospitals in an integrated healthcare system in Texas between June 2013 and June 2014. We analyzed data for all hospital encounters during which a troponin assay was ordered and a troponin level reported—including qualitative point-of-care assays and quantitative laboratory troponin I measurements. We identified 93,436 visits. Quantitative measurements were divided into negative (<0.05 ng/mL), indeterminate (0.05-0.09 ng/mL), and elevated (>0.09 ng/mL), based on the reference ranges reported to physicians. We associated troponin levels with ICD-9 (International Classification of Diseases, Ninth Revision) primary and secondary diagnoses, grouping ICD-9 codes 410 (AMI), 411 (other acute or subacute forms of ischemic heart disease [IHD]), 412 (old myocardial infarction), 413 (angina pectoris), and 414 (other forms of chronic IHD) as representing IHD diagnoses.

To further evaluate troponin testing, we constructed 2 contingency matrices (Table).6 We included visits for which both primary and secondary diagnoses were available for review and for which quantitative troponin I measurements were available; 92,445 encounters met criteria for inclusion in matrix calculations. In the first matrix (part A of Table), a primary diagnosis of any AMI (ICD-9 code 410) was used as “positive” and all others “negative.” In the second matrix (part B of Table), “positive” includes any primary or secondary diagnosis of AMI.

Contingency Matrices Evaluating Elevated Troponin Levels and AMI Diagnoses
Table

RESULTS

We identified a total of 93,436 hospital visits associated with troponin testing; 179,239 troponin measurements were associated with these visits (an average of 1.81 per encounter). Of these visits, 59,897 (64.1%) were associated with a single measurement. Of the 179,239 measurements, 147,051 (82.1%) were negative, 21,881 (12.1%) indeterminate, and 10,307 (5.8%) positive. Primary diagnoses of hypertension, dizziness, abdominal pain, anxiety, dehydration, and headache associated with troponin testing comprised 6127 encounters and had no associated elevated troponin levels. Several non-cardiac primary diagnoses were associated with significant numbers of elevated troponin values including septicemia (27%), acute respiratory failure (28%), and cerebrovascular accident (10%). Seventy-six percent of encounters associated with troponin testing had no primary or secondary IHD diagnosis. Only 2% of 16,941 visits with a primary diagnosis of chest pain were associated with abnormal troponin levels (Figure).

Notable non-AMI primary diagnoses associated with elevated troponin I values.
Figure

 

 

Analysis of contingency matrices revealed AMI prevalence of 2.6% when primary AMI diagnoses were considered and 3.5% when any AMI diagnoses were considered. Sensitivity and specificity were high (>90%), and negative predictive value extremely high (>99%) in each circumstance. However, positive predictive values were low (21.7% and 28.8%, respectively), indicating the majority of patients with elevated troponin levels were not reported to have AMI by attending physicians.

DISCUSSION

We were surprised to find that troponin level was measured only once during 64% of the hospital encounters. Although there are clinical scenarios in which a single measurement might be indicated, detecting a rise or fall in troponin level is integral to the diagnosis of AMI, which is why guidelines recommend serial measurement.4 We were also surprised to find a low rate of either primary or secondary AMI in patients tested. As others have found,2,3 elevated troponin levels were associated with noncardiac primary diagnoses, such as sepsis, respiratory failure, and stroke. Of interest, the majority (72%) of patients with elevated troponin levels did not receive a primary or secondary diagnosis of AMI.

Determining the appropriate level of use for a diagnostic laboratory test can be difficult. Primary diagnostic codes, including codes for headache and dizziness, accounted for thousands of tested patients but were associated with no elevated troponin levels. On the other hand, sepsis, pneumonia, and stroke were associated with high rates of elevated troponin levels. Elevated troponin levels likely precipitate cardiology consultation and testing, which increase cost of care perhaps without improving either quality or value of care. However, evidence for the potential prognostic value of testing has led to ongoing research at our institution to evaluate whether troponin measurement might guide better management of such patients.

Appropriate use criteria have been developed for many diagnostic studies, including echocardiography, stress testing, and cardiac catheterization, but not for laboratory testing. Our data suggest possible overuse of troponin testing in our healthcare system. The low AMI incidence we found (2.6%-3.5%) indicates that many patients without AMI are being tested.

Although it is impossible to accurately estimate sensitivity and specificity of testing post hoc, it is reassuring to see that measured sensitivity, specificity, and negative predictive values were all high and consistent with published values from prospective clinical trials.7,8

As potential roles for troponin testing develop for patients without primary cardiac disease, it becomes even more important to develop guidelines for testing and to avoid universal testing of all hospitalized patients. The high negative predictive value of troponin testing (99%) is attractive to physicians who want to avoid missing AMI. Electronic order sets allow troponin testing to be included alongside “standard” testing, such as complete blood cell counts and comprehensive metabolic panels, and may contribute to overuse.

The troponin assays used in our healthcare system in 2014 likely will be replaced with high-sensitivity assays currently being used in Europe.9,10 These high-sensitivity assays can improve sensitivity but cannot be expected to increase positive predictive value or reduce false detection rates. When performed as single measurements, hs troponin has the potential to increase the number of elevated troponins detected that are not associated with AMI.

On the basis of our data, we have initiated a system-wide program to improve performance of troponin testing in our healthcare system. We are working with hospitalists and critical care and emergency department physicians to ensure that serial measurements are being performed and that the correct patients are being tested. Future data collection will help determine the success or failure of these efforts.

Disclosure

Nothing to report.

 

The ability of serum troponin measurement in the diagnosis of acute myocardial infarction (AMI) was validated in patients with at least a moderate pretest probability for the disease.1 The diagnostic yield of troponin testing in clinical trials has been between 20% and 50%, excluded patients thought unlikely to have AMI. In practice, physicians often encounter low-risk patients and patients in whom the diagnosis on initial presentation is unclear. Several noncardiac diagnoses, such as pneumonia and respiratory failure, are associated with an elevated troponin level in the absence of AMI, but patients can present with symptoms similar or identical to those of patients who present with AMI.2-4 Elevated troponin level in sepsis has been associated with worsened prognosis, though there is no evidence that this finding alters management. An American College of Cardiology Foundation opinion published in 2012 expressly recommends against troponin testing in patients with sepsis.4

The only guideline-based indication for troponin testing is the diagnosis or exclusion of AMI.5 We conducted a comprehensive review of troponin testing in our healthcare system to see whether testing might be used in clinical settings in which AMI was unlikely.

METHODS

We retrospectively obtained data on all visits to 14 hospitals in an integrated healthcare system in Texas between June 2013 and June 2014. We analyzed data for all hospital encounters during which a troponin assay was ordered and a troponin level reported—including qualitative point-of-care assays and quantitative laboratory troponin I measurements. We identified 93,436 visits. Quantitative measurements were divided into negative (<0.05 ng/mL), indeterminate (0.05-0.09 ng/mL), and elevated (>0.09 ng/mL), based on the reference ranges reported to physicians. We associated troponin levels with ICD-9 (International Classification of Diseases, Ninth Revision) primary and secondary diagnoses, grouping ICD-9 codes 410 (AMI), 411 (other acute or subacute forms of ischemic heart disease [IHD]), 412 (old myocardial infarction), 413 (angina pectoris), and 414 (other forms of chronic IHD) as representing IHD diagnoses.

To further evaluate troponin testing, we constructed 2 contingency matrices (Table).6 We included visits for which both primary and secondary diagnoses were available for review and for which quantitative troponin I measurements were available; 92,445 encounters met criteria for inclusion in matrix calculations. In the first matrix (part A of Table), a primary diagnosis of any AMI (ICD-9 code 410) was used as “positive” and all others “negative.” In the second matrix (part B of Table), “positive” includes any primary or secondary diagnosis of AMI.

Contingency Matrices Evaluating Elevated Troponin Levels and AMI Diagnoses
Table

RESULTS

We identified a total of 93,436 hospital visits associated with troponin testing; 179,239 troponin measurements were associated with these visits (an average of 1.81 per encounter). Of these visits, 59,897 (64.1%) were associated with a single measurement. Of the 179,239 measurements, 147,051 (82.1%) were negative, 21,881 (12.1%) indeterminate, and 10,307 (5.8%) positive. Primary diagnoses of hypertension, dizziness, abdominal pain, anxiety, dehydration, and headache associated with troponin testing comprised 6127 encounters and had no associated elevated troponin levels. Several non-cardiac primary diagnoses were associated with significant numbers of elevated troponin values including septicemia (27%), acute respiratory failure (28%), and cerebrovascular accident (10%). Seventy-six percent of encounters associated with troponin testing had no primary or secondary IHD diagnosis. Only 2% of 16,941 visits with a primary diagnosis of chest pain were associated with abnormal troponin levels (Figure).

Notable non-AMI primary diagnoses associated with elevated troponin I values.
Figure

 

 

Analysis of contingency matrices revealed AMI prevalence of 2.6% when primary AMI diagnoses were considered and 3.5% when any AMI diagnoses were considered. Sensitivity and specificity were high (>90%), and negative predictive value extremely high (>99%) in each circumstance. However, positive predictive values were low (21.7% and 28.8%, respectively), indicating the majority of patients with elevated troponin levels were not reported to have AMI by attending physicians.

DISCUSSION

We were surprised to find that troponin level was measured only once during 64% of the hospital encounters. Although there are clinical scenarios in which a single measurement might be indicated, detecting a rise or fall in troponin level is integral to the diagnosis of AMI, which is why guidelines recommend serial measurement.4 We were also surprised to find a low rate of either primary or secondary AMI in patients tested. As others have found,2,3 elevated troponin levels were associated with noncardiac primary diagnoses, such as sepsis, respiratory failure, and stroke. Of interest, the majority (72%) of patients with elevated troponin levels did not receive a primary or secondary diagnosis of AMI.

Determining the appropriate level of use for a diagnostic laboratory test can be difficult. Primary diagnostic codes, including codes for headache and dizziness, accounted for thousands of tested patients but were associated with no elevated troponin levels. On the other hand, sepsis, pneumonia, and stroke were associated with high rates of elevated troponin levels. Elevated troponin levels likely precipitate cardiology consultation and testing, which increase cost of care perhaps without improving either quality or value of care. However, evidence for the potential prognostic value of testing has led to ongoing research at our institution to evaluate whether troponin measurement might guide better management of such patients.

Appropriate use criteria have been developed for many diagnostic studies, including echocardiography, stress testing, and cardiac catheterization, but not for laboratory testing. Our data suggest possible overuse of troponin testing in our healthcare system. The low AMI incidence we found (2.6%-3.5%) indicates that many patients without AMI are being tested.

Although it is impossible to accurately estimate sensitivity and specificity of testing post hoc, it is reassuring to see that measured sensitivity, specificity, and negative predictive values were all high and consistent with published values from prospective clinical trials.7,8

As potential roles for troponin testing develop for patients without primary cardiac disease, it becomes even more important to develop guidelines for testing and to avoid universal testing of all hospitalized patients. The high negative predictive value of troponin testing (99%) is attractive to physicians who want to avoid missing AMI. Electronic order sets allow troponin testing to be included alongside “standard” testing, such as complete blood cell counts and comprehensive metabolic panels, and may contribute to overuse.

The troponin assays used in our healthcare system in 2014 likely will be replaced with high-sensitivity assays currently being used in Europe.9,10 These high-sensitivity assays can improve sensitivity but cannot be expected to increase positive predictive value or reduce false detection rates. When performed as single measurements, hs troponin has the potential to increase the number of elevated troponins detected that are not associated with AMI.

On the basis of our data, we have initiated a system-wide program to improve performance of troponin testing in our healthcare system. We are working with hospitalists and critical care and emergency department physicians to ensure that serial measurements are being performed and that the correct patients are being tested. Future data collection will help determine the success or failure of these efforts.

Disclosure

Nothing to report.

 

References

1. Thygesen K, Alpert JS, Jaffe AS, et al. Third universal definition of myocardial infarction. Circulation. 2012;126(16):2020-2035. PubMed
2. Hamm CW, Giannitsis E, Katus HA. Cardiac troponin elevations in patients without acute coronary syndrome. Circulation. 2002;106(23):2871-2872. PubMed
3. Roongsritong C, Warraich I, Bradley C. Common causes of troponin elevations in the absence of acute myocardial infarction: incidence and clinical significance. Chest. 2004;125(5):1877-1884. PubMed
4. Newby LK, Jesse RL, Babb JD, et al. ACCF 2012 expert consensus document on practical clinical considerations in the interpretation of troponin elevations: a report of the American College of Cardiology Foundation Task Force on Clinical Consensus Documents. J Am Coll Cardiol. 2012;60(23):2427-2463. PubMed
5. Amsterdam EA, Wenger NK, Brindis RG, et al; American College of Cardiology; American Heart Association Task Force on Practice Guidelines; Society for Cardiovascular Angiography and Interventions; Society of Thoracic Surgeons; American Association for Clinical Chemistry. 2014 AHA/ACC Guideline for the Management of Patients With Non-ST-Elevation Acute Coronary Syndromes: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014;64(24):e139-e228.
6. Pearson K. On the Theory of Contingency and Its Relationship to Association and Normal Correlation. Mathematical Contributions to the Theory of Evolution. London, England: Dulau & Co; 1904.
7. Katus HA, Remppis A, Neumann FJ, et al. Diagnostic efficiency of troponin T measurements in acute myocardial infarction. Circulation. 1991;83(3):902-912. PubMed
8. Olatidoye AG, Wu AH, Feng YJ, Waters D. Prognostic role of troponin T versus troponin I in unstable angina pectoris for cardiac events with meta-analysis comparing published studies. Am J Cardiol. 1998;81(12):1405-1410. PubMed
9. Reichlin T, Hochholzer W, Bassetti S, et al. Early diagnosis of myocardial infarction with sensitive cardiac troponin assays. N Engl J Med. 2009;361(9):858-867. PubMed
10. Keller T, Zeller T, Peetz D, et al. Sensitive troponin I assay in early diagnosis of acute myocardial infarction. N Engl J Med. 2009;361(9):868-877. PubMed

References

1. Thygesen K, Alpert JS, Jaffe AS, et al. Third universal definition of myocardial infarction. Circulation. 2012;126(16):2020-2035. PubMed
2. Hamm CW, Giannitsis E, Katus HA. Cardiac troponin elevations in patients without acute coronary syndrome. Circulation. 2002;106(23):2871-2872. PubMed
3. Roongsritong C, Warraich I, Bradley C. Common causes of troponin elevations in the absence of acute myocardial infarction: incidence and clinical significance. Chest. 2004;125(5):1877-1884. PubMed
4. Newby LK, Jesse RL, Babb JD, et al. ACCF 2012 expert consensus document on practical clinical considerations in the interpretation of troponin elevations: a report of the American College of Cardiology Foundation Task Force on Clinical Consensus Documents. J Am Coll Cardiol. 2012;60(23):2427-2463. PubMed
5. Amsterdam EA, Wenger NK, Brindis RG, et al; American College of Cardiology; American Heart Association Task Force on Practice Guidelines; Society for Cardiovascular Angiography and Interventions; Society of Thoracic Surgeons; American Association for Clinical Chemistry. 2014 AHA/ACC Guideline for the Management of Patients With Non-ST-Elevation Acute Coronary Syndromes: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014;64(24):e139-e228.
6. Pearson K. On the Theory of Contingency and Its Relationship to Association and Normal Correlation. Mathematical Contributions to the Theory of Evolution. London, England: Dulau & Co; 1904.
7. Katus HA, Remppis A, Neumann FJ, et al. Diagnostic efficiency of troponin T measurements in acute myocardial infarction. Circulation. 1991;83(3):902-912. PubMed
8. Olatidoye AG, Wu AH, Feng YJ, Waters D. Prognostic role of troponin T versus troponin I in unstable angina pectoris for cardiac events with meta-analysis comparing published studies. Am J Cardiol. 1998;81(12):1405-1410. PubMed
9. Reichlin T, Hochholzer W, Bassetti S, et al. Early diagnosis of myocardial infarction with sensitive cardiac troponin assays. N Engl J Med. 2009;361(9):858-867. PubMed
10. Keller T, Zeller T, Peetz D, et al. Sensitive troponin I assay in early diagnosis of acute myocardial infarction. N Engl J Med. 2009;361(9):868-877. PubMed

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Overuse of troponin? A comprehensive evaluation of testing in a large hospital system
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Address for correspondence and reprint requests: Jeffrey Michel, MD, FACC, Department of Cardiology, Scott and White Memorial Hospital, 2410 S 31st St, MS-33-ST156, Temple, TX 76508; Telephone: 512-568-2494; Fax: 254-724-9854; E-mail: [email protected]

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It all just clicks: Development of an inpatient e-consult program

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It all just clicks: Development of an inpatient e-consult program

Electronic consultation (e-consult) in the outpatient setting allows subspecialists to provide assessment and recommendations for patients without in-person visits.1 An e-consult is an asynchronous communication that uses the electronic medical record (EMR) and typically involves an electronic order from a requesting provider and an electronic note from a consulting provider. The initial motivation for developing this consultation modality was to improve access to subspecialty care for patients in the primary care setting, and findings of studies at several sites support this claim.1-4 In addition, e-consult may also reduce cost because converting unnecessary face-to-face encounters into e-consults reduces patients’ travel costs and healthcare organizations’ expensive subspecialty clinic time.3,5 Moreover, instead of addressing less complex clinical questions in informal, undocumented face-to-face or telephone “curbside” consultations with specialists, providers can instead ask for e-consults and thereby ensure thorough chart review and proper documentation.6

Use of e-consults in the inpatient setting is relatively novel.7 In addition to having the advantages already mentioned, e-consults are faster than in-person bedside consultations and may be beneficial in the fast-moving inpatient care setting. Finally, healthcare systems with multiple hospital sites may not have the capacity to physically locate subspecialists at each site, which makes e-consults attractive for avoiding unnecessary travel time.

In this article, we describe how we developed an inpatient e-consult protocol for a new, remote hospital within our healthcare system and explore data on safety and physician attitudes after e-consult implementation.

METHODS

The Institutional Review Board of the University of California San Francisco (UCSF) approved this study.

Setting

In February 2015, UCSF opened a new hospital in the Mission Bay neighborhood of San Francisco, 4 miles from the existing hospital. The new hospital is home to several adult inpatient services: urology, otolaryngology, colorectal surgery, obstetrics, and gynecologic surgery. A hospitalist is on-site 24 hours a day to provide consultation for these services around issues that relate to internal medicine. A hospitalist who requires subspecialty expertise to answer a clinical question can request a consultation by in-person visit, video telemedicine, or e-consult, each of which is available 24/7. Almost all of the medicine subspecialists work on the existing campus, not in Mission Bay.

Protocol Development and Implementation

The protocol for the e-consult program was developed over several months by an interdisciplinary group that included 3 hospitalists, 1 obstetrician, 1 project manager, and 1 informaticist. The group outlined the process for requesting and completing an e-consult (Figure), designed a note template for consultants to use for EMR documentation, conducted outreach with subspecialty groups to discuss the protocol, and developed an EMR report to track e-consult use and content over time. As our medical center does not bill payers for inpatient e-consults, e-consult note tracking is used to provide reimbursement internally, from the medical center to the respective departments of the consultants. Reimbursement is made at a set rate per e-consult note, with the rate set to approximate the reimbursement of a low-acuity in-person consult on the main campus.

Process for requesting and completing an e-consult. Order not mandatory.
Figure

The workflow of an e-consult is as follows: (1) When a primary team requires a consultation on an issue that falls within the purview of internal medicine, it pages the on-site hospitalist. (2) The hospitalist accepts the consultation by phone, reviews the chart, and examines the patient. (3) If the hospitalist requires subspecialty assistance to answer a clinical question, he or she contacts the appropriate subspecialty service by pager. (4) The subspecialist speaks with the hospitalist about the consultation question, and together they decide if an e-consult is appropriate, based on the complexity of the clinical scenario. (5) The subspecialist reviews the patient’s chart and documents their care plan recommendations in an e-consult note. Consultants can use e-consult for both initial and follow-up assessment, and there is no strict requirement that they also contact the hospitalist or the primary team by phone in addition to consultation note. Given their novelty, almost all e-consults are performed by subspecialist attendings, not residents or fellows.

 

 

Evaluation

Each month, we tracked e-consult use using an EMR report built as part of the implementation of the program. For the first four months of implementation, every patient who received an e-consult also had a manual chart review of the period around the e-consult, performed by a hospitalist, in order to audit for any potential safety issues. These issues included, for example, an e-consult performed for a patient whose complexity or severity of illness was felt to be too great to defer an in-person visit, or a patient who received e-consult recommendations that were significantly retracted in a follow-up in-person note.

Eight months after the program started, we assessed experience by electronically surveying the 9 hospitalists and 11 consultants who had requested or performed at least 2 e-consults.8 Survey items were measured on a 5-point Likert scale: strongly disagree to strongly agree. The items, which related to ease of calling for a consultation, quality of e-consults, impact on clinical care, safety concerns, and satisfaction, were inspired by themes identified in a systematic review of the literature on e-consults in the outpatient setting.2 We sent 2 reminders to responders. Data were summarized using descriptive statistics. Analysis was performed in SPSS version 22.0 (IBM).

RESULTS

There were 143 initial subspecialty consultations by e-consult between program launch in February 2015 and manuscript preparation in February 2016, an average of 11 e-consults per month. There were 313 total e-consult notes (these included both initial and follow-up e-consult notes). By comparison, 240 initial in-person consultations occurred during the same period, and there were 435 total in-person consultation notes (46% new or initial notes, 54% follow-up notes). The top 5 subspecialties by volume of e-consults were infectious disease (35%), hematology (20%), endocrinology (14%), nephrology (13%), and cardiology (8%). For reference, e-consults are also available from psychiatry, neurology, oncology, gastroenterology, pulmonology, and rheumatology. Percentage of consultations performed during daytime hours (defined as 8 a.m. to 5 p.m.) was 92% for e-consults and 96% for in-person consultations.

There were no e-consult–related patient safety issues reported through the medical center’s incident reporting system during the study period. There were also no patient safety issues identified in the manual audits of 80 charts during the first 4 months of the program.

Seven (78%) of 9 hospitalists and 7 (64%) of 11 consultants completed the survey. Both groups agreed that e-consults were easy to use and efficient (Table). All hospitalists were satisfied with the quality of e-consult recommendations, but only 3 (43%) of the 7 consultants agreed they could provide high-quality consultation by e-consult. In their comments, 2 consultants expressed concerns. One concern was about missing crucial information by performing only a chart review, and the other was about being tempted to perform an e-consult simply because it is expedient.

Results of E-Consult Survey Given to Hospitalists and Consultants
Table

DISCUSSION

Although use of e-consults in the outpatient setting is relatively commonplace, our program represents a novel use of e-consults in safely and efficiently providing subspecialty consultation to inpatients at a remote hospital.

For hospitalists, an e-consult system offers numerous benefits. Clinical questions beyond an internists’ scope of practice come up often, and simple questions might traditionally result in an informal curbside consult. While a curbside consult provides answers faster than an in-person visit, it creates risks for the requesting hospitalists: the consultants only know what they are told, whether the information is incomplete or erroneous; their opinions are given without documentation or compensation, which reduces a sense of accountability; and the lack of documentation does not allow their advice to persist in the chart as a reference for future providers.9 Our e-consult program solves these problems by requiring that consultants perform chart review and provide documentation as well as obligating the medical center to pay a small compensation to consultants for their time. We hope this lowers the bar to requesting consultation for remote sites, where the alternative would be burdensome travel time to do an in-person visit.

In our study, hospitalists were universally pleased with the quality of e-consult recommendations, but only 43% of consultants agreed. These findings correlate with the literature on e-consults in the outpatient setting.2 Unfortunately, our survey comments did not shed further light on this sentiment. In the outpatient literature, consultants were most concerned with having a clear clinical question, facing the liability of providing recommendations without performing an examination, and receiving appropriate compensation for answering e-consults.

The generalizability of our program findings is limited most significantly by the particular arrangement of our clinical services: Our remote site is home to a select group of adult inpatient services, a hospitalist is available on-site for these services 24 hours a day, and the distance to the remote site can be overcome with modest effort should a patient require an in-person visit in the initial or follow-up period. The generalizability of our safety findings is limited by the use of a single reviewer for chart auditing.

Given the rise of accountable care organizations and the prevalence of hospital mergers in the healthcare landscape, we believe that healthcare systems that operate remote sites under constrained budgets could look to e-consults to more cost-effectively extend subspecialty expertise across the inpatient enterprise. With improvements in health information exchange, it may also become feasible for consultants to offer e-consults to hospitals outside a medical center’s network. Our study showed that inpatient e-consult programs can be developed and implemented, that they appear not to pose any significant safety issues, and that they can facilitate delivery of timely clinical care.

 

 

Acknowledgment

The authors thank Raphaela Levy-Moore for creating and implementing the e-consult note template for our electronic medical record.

Disclosure

Nothing to report.

 

References

1. Chen AH, Murphy EJ, Yee HF Jr. eReferral—a new model for integrated care. N Engl J Med. 2013;368(26):2450-2453. PubMed
2. Vimalananda VG, Gupte G, Seraj SM, et al. Electronic consultations (e-consults) to improve access to specialty care: a systematic review and narrative synthesis. J Telemed Telecare. 2015;21(6):323-330. PubMed
3. Kirsh S, Carey E, Aron DC, et al. Impact of a national specialty e-consultation implementation project on access. Am J Manag Care. 2015;21(12):e648-e654. PubMed
4. Bergman J, Neuhausen K, Chamie K, et al. Building a medical neighborhood in the safety net: an innovative technology improves hematuria workups. Urology. 2013;82(6):1277-1282. PubMed
5. Wasfy JH, Rao SK, Chittle MD, Gallen KM, Isselbacher EM, Ferris TG. Initial results of a cardiac e-consult pilot program. J Am Coll Cardiol. 2014;64(24):2706-2707. PubMed
6. Perley CM. Physician use of the curbside consultation to address information needs: report on a collective case study. J Med Libr Assoc. 2006;94(2):137-144. PubMed
7. Gupte G, Vimalananda V, Simon SR, DeVito K, Clark J, Orlander JD. Disruptive innovation: implementation of electronic consultations in a Veterans Affairs health care system. JMIR Med Inform. 2016;4(1):e6. PubMed
8. REDCap. Vanderbilt University website. http://www.project-redcap.org. 2015. Accessed March 3, 2016.
9. Burden M, Sarcone E, Keniston A, et al. Prospective comparison of curbside versus formal consultations. J Hosp Med. 2013;8(1):31-35. PubMed

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Journal of Hospital Medicine 12(5)
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332-334
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Electronic consultation (e-consult) in the outpatient setting allows subspecialists to provide assessment and recommendations for patients without in-person visits.1 An e-consult is an asynchronous communication that uses the electronic medical record (EMR) and typically involves an electronic order from a requesting provider and an electronic note from a consulting provider. The initial motivation for developing this consultation modality was to improve access to subspecialty care for patients in the primary care setting, and findings of studies at several sites support this claim.1-4 In addition, e-consult may also reduce cost because converting unnecessary face-to-face encounters into e-consults reduces patients’ travel costs and healthcare organizations’ expensive subspecialty clinic time.3,5 Moreover, instead of addressing less complex clinical questions in informal, undocumented face-to-face or telephone “curbside” consultations with specialists, providers can instead ask for e-consults and thereby ensure thorough chart review and proper documentation.6

Use of e-consults in the inpatient setting is relatively novel.7 In addition to having the advantages already mentioned, e-consults are faster than in-person bedside consultations and may be beneficial in the fast-moving inpatient care setting. Finally, healthcare systems with multiple hospital sites may not have the capacity to physically locate subspecialists at each site, which makes e-consults attractive for avoiding unnecessary travel time.

In this article, we describe how we developed an inpatient e-consult protocol for a new, remote hospital within our healthcare system and explore data on safety and physician attitudes after e-consult implementation.

METHODS

The Institutional Review Board of the University of California San Francisco (UCSF) approved this study.

Setting

In February 2015, UCSF opened a new hospital in the Mission Bay neighborhood of San Francisco, 4 miles from the existing hospital. The new hospital is home to several adult inpatient services: urology, otolaryngology, colorectal surgery, obstetrics, and gynecologic surgery. A hospitalist is on-site 24 hours a day to provide consultation for these services around issues that relate to internal medicine. A hospitalist who requires subspecialty expertise to answer a clinical question can request a consultation by in-person visit, video telemedicine, or e-consult, each of which is available 24/7. Almost all of the medicine subspecialists work on the existing campus, not in Mission Bay.

Protocol Development and Implementation

The protocol for the e-consult program was developed over several months by an interdisciplinary group that included 3 hospitalists, 1 obstetrician, 1 project manager, and 1 informaticist. The group outlined the process for requesting and completing an e-consult (Figure), designed a note template for consultants to use for EMR documentation, conducted outreach with subspecialty groups to discuss the protocol, and developed an EMR report to track e-consult use and content over time. As our medical center does not bill payers for inpatient e-consults, e-consult note tracking is used to provide reimbursement internally, from the medical center to the respective departments of the consultants. Reimbursement is made at a set rate per e-consult note, with the rate set to approximate the reimbursement of a low-acuity in-person consult on the main campus.

Process for requesting and completing an e-consult. Order not mandatory.
Figure

The workflow of an e-consult is as follows: (1) When a primary team requires a consultation on an issue that falls within the purview of internal medicine, it pages the on-site hospitalist. (2) The hospitalist accepts the consultation by phone, reviews the chart, and examines the patient. (3) If the hospitalist requires subspecialty assistance to answer a clinical question, he or she contacts the appropriate subspecialty service by pager. (4) The subspecialist speaks with the hospitalist about the consultation question, and together they decide if an e-consult is appropriate, based on the complexity of the clinical scenario. (5) The subspecialist reviews the patient’s chart and documents their care plan recommendations in an e-consult note. Consultants can use e-consult for both initial and follow-up assessment, and there is no strict requirement that they also contact the hospitalist or the primary team by phone in addition to consultation note. Given their novelty, almost all e-consults are performed by subspecialist attendings, not residents or fellows.

 

 

Evaluation

Each month, we tracked e-consult use using an EMR report built as part of the implementation of the program. For the first four months of implementation, every patient who received an e-consult also had a manual chart review of the period around the e-consult, performed by a hospitalist, in order to audit for any potential safety issues. These issues included, for example, an e-consult performed for a patient whose complexity or severity of illness was felt to be too great to defer an in-person visit, or a patient who received e-consult recommendations that were significantly retracted in a follow-up in-person note.

Eight months after the program started, we assessed experience by electronically surveying the 9 hospitalists and 11 consultants who had requested or performed at least 2 e-consults.8 Survey items were measured on a 5-point Likert scale: strongly disagree to strongly agree. The items, which related to ease of calling for a consultation, quality of e-consults, impact on clinical care, safety concerns, and satisfaction, were inspired by themes identified in a systematic review of the literature on e-consults in the outpatient setting.2 We sent 2 reminders to responders. Data were summarized using descriptive statistics. Analysis was performed in SPSS version 22.0 (IBM).

RESULTS

There were 143 initial subspecialty consultations by e-consult between program launch in February 2015 and manuscript preparation in February 2016, an average of 11 e-consults per month. There were 313 total e-consult notes (these included both initial and follow-up e-consult notes). By comparison, 240 initial in-person consultations occurred during the same period, and there were 435 total in-person consultation notes (46% new or initial notes, 54% follow-up notes). The top 5 subspecialties by volume of e-consults were infectious disease (35%), hematology (20%), endocrinology (14%), nephrology (13%), and cardiology (8%). For reference, e-consults are also available from psychiatry, neurology, oncology, gastroenterology, pulmonology, and rheumatology. Percentage of consultations performed during daytime hours (defined as 8 a.m. to 5 p.m.) was 92% for e-consults and 96% for in-person consultations.

There were no e-consult–related patient safety issues reported through the medical center’s incident reporting system during the study period. There were also no patient safety issues identified in the manual audits of 80 charts during the first 4 months of the program.

Seven (78%) of 9 hospitalists and 7 (64%) of 11 consultants completed the survey. Both groups agreed that e-consults were easy to use and efficient (Table). All hospitalists were satisfied with the quality of e-consult recommendations, but only 3 (43%) of the 7 consultants agreed they could provide high-quality consultation by e-consult. In their comments, 2 consultants expressed concerns. One concern was about missing crucial information by performing only a chart review, and the other was about being tempted to perform an e-consult simply because it is expedient.

Results of E-Consult Survey Given to Hospitalists and Consultants
Table

DISCUSSION

Although use of e-consults in the outpatient setting is relatively commonplace, our program represents a novel use of e-consults in safely and efficiently providing subspecialty consultation to inpatients at a remote hospital.

For hospitalists, an e-consult system offers numerous benefits. Clinical questions beyond an internists’ scope of practice come up often, and simple questions might traditionally result in an informal curbside consult. While a curbside consult provides answers faster than an in-person visit, it creates risks for the requesting hospitalists: the consultants only know what they are told, whether the information is incomplete or erroneous; their opinions are given without documentation or compensation, which reduces a sense of accountability; and the lack of documentation does not allow their advice to persist in the chart as a reference for future providers.9 Our e-consult program solves these problems by requiring that consultants perform chart review and provide documentation as well as obligating the medical center to pay a small compensation to consultants for their time. We hope this lowers the bar to requesting consultation for remote sites, where the alternative would be burdensome travel time to do an in-person visit.

In our study, hospitalists were universally pleased with the quality of e-consult recommendations, but only 43% of consultants agreed. These findings correlate with the literature on e-consults in the outpatient setting.2 Unfortunately, our survey comments did not shed further light on this sentiment. In the outpatient literature, consultants were most concerned with having a clear clinical question, facing the liability of providing recommendations without performing an examination, and receiving appropriate compensation for answering e-consults.

The generalizability of our program findings is limited most significantly by the particular arrangement of our clinical services: Our remote site is home to a select group of adult inpatient services, a hospitalist is available on-site for these services 24 hours a day, and the distance to the remote site can be overcome with modest effort should a patient require an in-person visit in the initial or follow-up period. The generalizability of our safety findings is limited by the use of a single reviewer for chart auditing.

Given the rise of accountable care organizations and the prevalence of hospital mergers in the healthcare landscape, we believe that healthcare systems that operate remote sites under constrained budgets could look to e-consults to more cost-effectively extend subspecialty expertise across the inpatient enterprise. With improvements in health information exchange, it may also become feasible for consultants to offer e-consults to hospitals outside a medical center’s network. Our study showed that inpatient e-consult programs can be developed and implemented, that they appear not to pose any significant safety issues, and that they can facilitate delivery of timely clinical care.

 

 

Acknowledgment

The authors thank Raphaela Levy-Moore for creating and implementing the e-consult note template for our electronic medical record.

Disclosure

Nothing to report.

 

Electronic consultation (e-consult) in the outpatient setting allows subspecialists to provide assessment and recommendations for patients without in-person visits.1 An e-consult is an asynchronous communication that uses the electronic medical record (EMR) and typically involves an electronic order from a requesting provider and an electronic note from a consulting provider. The initial motivation for developing this consultation modality was to improve access to subspecialty care for patients in the primary care setting, and findings of studies at several sites support this claim.1-4 In addition, e-consult may also reduce cost because converting unnecessary face-to-face encounters into e-consults reduces patients’ travel costs and healthcare organizations’ expensive subspecialty clinic time.3,5 Moreover, instead of addressing less complex clinical questions in informal, undocumented face-to-face or telephone “curbside” consultations with specialists, providers can instead ask for e-consults and thereby ensure thorough chart review and proper documentation.6

Use of e-consults in the inpatient setting is relatively novel.7 In addition to having the advantages already mentioned, e-consults are faster than in-person bedside consultations and may be beneficial in the fast-moving inpatient care setting. Finally, healthcare systems with multiple hospital sites may not have the capacity to physically locate subspecialists at each site, which makes e-consults attractive for avoiding unnecessary travel time.

In this article, we describe how we developed an inpatient e-consult protocol for a new, remote hospital within our healthcare system and explore data on safety and physician attitudes after e-consult implementation.

METHODS

The Institutional Review Board of the University of California San Francisco (UCSF) approved this study.

Setting

In February 2015, UCSF opened a new hospital in the Mission Bay neighborhood of San Francisco, 4 miles from the existing hospital. The new hospital is home to several adult inpatient services: urology, otolaryngology, colorectal surgery, obstetrics, and gynecologic surgery. A hospitalist is on-site 24 hours a day to provide consultation for these services around issues that relate to internal medicine. A hospitalist who requires subspecialty expertise to answer a clinical question can request a consultation by in-person visit, video telemedicine, or e-consult, each of which is available 24/7. Almost all of the medicine subspecialists work on the existing campus, not in Mission Bay.

Protocol Development and Implementation

The protocol for the e-consult program was developed over several months by an interdisciplinary group that included 3 hospitalists, 1 obstetrician, 1 project manager, and 1 informaticist. The group outlined the process for requesting and completing an e-consult (Figure), designed a note template for consultants to use for EMR documentation, conducted outreach with subspecialty groups to discuss the protocol, and developed an EMR report to track e-consult use and content over time. As our medical center does not bill payers for inpatient e-consults, e-consult note tracking is used to provide reimbursement internally, from the medical center to the respective departments of the consultants. Reimbursement is made at a set rate per e-consult note, with the rate set to approximate the reimbursement of a low-acuity in-person consult on the main campus.

Process for requesting and completing an e-consult. Order not mandatory.
Figure

The workflow of an e-consult is as follows: (1) When a primary team requires a consultation on an issue that falls within the purview of internal medicine, it pages the on-site hospitalist. (2) The hospitalist accepts the consultation by phone, reviews the chart, and examines the patient. (3) If the hospitalist requires subspecialty assistance to answer a clinical question, he or she contacts the appropriate subspecialty service by pager. (4) The subspecialist speaks with the hospitalist about the consultation question, and together they decide if an e-consult is appropriate, based on the complexity of the clinical scenario. (5) The subspecialist reviews the patient’s chart and documents their care plan recommendations in an e-consult note. Consultants can use e-consult for both initial and follow-up assessment, and there is no strict requirement that they also contact the hospitalist or the primary team by phone in addition to consultation note. Given their novelty, almost all e-consults are performed by subspecialist attendings, not residents or fellows.

 

 

Evaluation

Each month, we tracked e-consult use using an EMR report built as part of the implementation of the program. For the first four months of implementation, every patient who received an e-consult also had a manual chart review of the period around the e-consult, performed by a hospitalist, in order to audit for any potential safety issues. These issues included, for example, an e-consult performed for a patient whose complexity or severity of illness was felt to be too great to defer an in-person visit, or a patient who received e-consult recommendations that were significantly retracted in a follow-up in-person note.

Eight months after the program started, we assessed experience by electronically surveying the 9 hospitalists and 11 consultants who had requested or performed at least 2 e-consults.8 Survey items were measured on a 5-point Likert scale: strongly disagree to strongly agree. The items, which related to ease of calling for a consultation, quality of e-consults, impact on clinical care, safety concerns, and satisfaction, were inspired by themes identified in a systematic review of the literature on e-consults in the outpatient setting.2 We sent 2 reminders to responders. Data were summarized using descriptive statistics. Analysis was performed in SPSS version 22.0 (IBM).

RESULTS

There were 143 initial subspecialty consultations by e-consult between program launch in February 2015 and manuscript preparation in February 2016, an average of 11 e-consults per month. There were 313 total e-consult notes (these included both initial and follow-up e-consult notes). By comparison, 240 initial in-person consultations occurred during the same period, and there were 435 total in-person consultation notes (46% new or initial notes, 54% follow-up notes). The top 5 subspecialties by volume of e-consults were infectious disease (35%), hematology (20%), endocrinology (14%), nephrology (13%), and cardiology (8%). For reference, e-consults are also available from psychiatry, neurology, oncology, gastroenterology, pulmonology, and rheumatology. Percentage of consultations performed during daytime hours (defined as 8 a.m. to 5 p.m.) was 92% for e-consults and 96% for in-person consultations.

There were no e-consult–related patient safety issues reported through the medical center’s incident reporting system during the study period. There were also no patient safety issues identified in the manual audits of 80 charts during the first 4 months of the program.

Seven (78%) of 9 hospitalists and 7 (64%) of 11 consultants completed the survey. Both groups agreed that e-consults were easy to use and efficient (Table). All hospitalists were satisfied with the quality of e-consult recommendations, but only 3 (43%) of the 7 consultants agreed they could provide high-quality consultation by e-consult. In their comments, 2 consultants expressed concerns. One concern was about missing crucial information by performing only a chart review, and the other was about being tempted to perform an e-consult simply because it is expedient.

Results of E-Consult Survey Given to Hospitalists and Consultants
Table

DISCUSSION

Although use of e-consults in the outpatient setting is relatively commonplace, our program represents a novel use of e-consults in safely and efficiently providing subspecialty consultation to inpatients at a remote hospital.

For hospitalists, an e-consult system offers numerous benefits. Clinical questions beyond an internists’ scope of practice come up often, and simple questions might traditionally result in an informal curbside consult. While a curbside consult provides answers faster than an in-person visit, it creates risks for the requesting hospitalists: the consultants only know what they are told, whether the information is incomplete or erroneous; their opinions are given without documentation or compensation, which reduces a sense of accountability; and the lack of documentation does not allow their advice to persist in the chart as a reference for future providers.9 Our e-consult program solves these problems by requiring that consultants perform chart review and provide documentation as well as obligating the medical center to pay a small compensation to consultants for their time. We hope this lowers the bar to requesting consultation for remote sites, where the alternative would be burdensome travel time to do an in-person visit.

In our study, hospitalists were universally pleased with the quality of e-consult recommendations, but only 43% of consultants agreed. These findings correlate with the literature on e-consults in the outpatient setting.2 Unfortunately, our survey comments did not shed further light on this sentiment. In the outpatient literature, consultants were most concerned with having a clear clinical question, facing the liability of providing recommendations without performing an examination, and receiving appropriate compensation for answering e-consults.

The generalizability of our program findings is limited most significantly by the particular arrangement of our clinical services: Our remote site is home to a select group of adult inpatient services, a hospitalist is available on-site for these services 24 hours a day, and the distance to the remote site can be overcome with modest effort should a patient require an in-person visit in the initial or follow-up period. The generalizability of our safety findings is limited by the use of a single reviewer for chart auditing.

Given the rise of accountable care organizations and the prevalence of hospital mergers in the healthcare landscape, we believe that healthcare systems that operate remote sites under constrained budgets could look to e-consults to more cost-effectively extend subspecialty expertise across the inpatient enterprise. With improvements in health information exchange, it may also become feasible for consultants to offer e-consults to hospitals outside a medical center’s network. Our study showed that inpatient e-consult programs can be developed and implemented, that they appear not to pose any significant safety issues, and that they can facilitate delivery of timely clinical care.

 

 

Acknowledgment

The authors thank Raphaela Levy-Moore for creating and implementing the e-consult note template for our electronic medical record.

Disclosure

Nothing to report.

 

References

1. Chen AH, Murphy EJ, Yee HF Jr. eReferral—a new model for integrated care. N Engl J Med. 2013;368(26):2450-2453. PubMed
2. Vimalananda VG, Gupte G, Seraj SM, et al. Electronic consultations (e-consults) to improve access to specialty care: a systematic review and narrative synthesis. J Telemed Telecare. 2015;21(6):323-330. PubMed
3. Kirsh S, Carey E, Aron DC, et al. Impact of a national specialty e-consultation implementation project on access. Am J Manag Care. 2015;21(12):e648-e654. PubMed
4. Bergman J, Neuhausen K, Chamie K, et al. Building a medical neighborhood in the safety net: an innovative technology improves hematuria workups. Urology. 2013;82(6):1277-1282. PubMed
5. Wasfy JH, Rao SK, Chittle MD, Gallen KM, Isselbacher EM, Ferris TG. Initial results of a cardiac e-consult pilot program. J Am Coll Cardiol. 2014;64(24):2706-2707. PubMed
6. Perley CM. Physician use of the curbside consultation to address information needs: report on a collective case study. J Med Libr Assoc. 2006;94(2):137-144. PubMed
7. Gupte G, Vimalananda V, Simon SR, DeVito K, Clark J, Orlander JD. Disruptive innovation: implementation of electronic consultations in a Veterans Affairs health care system. JMIR Med Inform. 2016;4(1):e6. PubMed
8. REDCap. Vanderbilt University website. http://www.project-redcap.org. 2015. Accessed March 3, 2016.
9. Burden M, Sarcone E, Keniston A, et al. Prospective comparison of curbside versus formal consultations. J Hosp Med. 2013;8(1):31-35. PubMed

References

1. Chen AH, Murphy EJ, Yee HF Jr. eReferral—a new model for integrated care. N Engl J Med. 2013;368(26):2450-2453. PubMed
2. Vimalananda VG, Gupte G, Seraj SM, et al. Electronic consultations (e-consults) to improve access to specialty care: a systematic review and narrative synthesis. J Telemed Telecare. 2015;21(6):323-330. PubMed
3. Kirsh S, Carey E, Aron DC, et al. Impact of a national specialty e-consultation implementation project on access. Am J Manag Care. 2015;21(12):e648-e654. PubMed
4. Bergman J, Neuhausen K, Chamie K, et al. Building a medical neighborhood in the safety net: an innovative technology improves hematuria workups. Urology. 2013;82(6):1277-1282. PubMed
5. Wasfy JH, Rao SK, Chittle MD, Gallen KM, Isselbacher EM, Ferris TG. Initial results of a cardiac e-consult pilot program. J Am Coll Cardiol. 2014;64(24):2706-2707. PubMed
6. Perley CM. Physician use of the curbside consultation to address information needs: report on a collective case study. J Med Libr Assoc. 2006;94(2):137-144. PubMed
7. Gupte G, Vimalananda V, Simon SR, DeVito K, Clark J, Orlander JD. Disruptive innovation: implementation of electronic consultations in a Veterans Affairs health care system. JMIR Med Inform. 2016;4(1):e6. PubMed
8. REDCap. Vanderbilt University website. http://www.project-redcap.org. 2015. Accessed March 3, 2016.
9. Burden M, Sarcone E, Keniston A, et al. Prospective comparison of curbside versus formal consultations. J Hosp Med. 2013;8(1):31-35. PubMed

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Address for correspondence and reprint requests: Nader Najafi, MD, Division of Hospital Medicine, University of California San Francisco, 505 Parnassus Ave, M1283, San Francisco, CA 94143-0131; Telephone: 415-476-2223; Fax: 415-502-1963; E-mail: [email protected]

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Clinical utility of routine CBC testing in patients with community-acquired pneumonia

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Clinical utility of routine CBC testing in patients with community-acquired pneumonia

Avoiding repeated complete blood count (CBC) tests in the face of clinical and lab stability is a focus of the Choosing Wisely® initiatives launched by the American Board of Internal Medicine Foundation1 and endorsed by the Society of Hospital Medicine.2 However, specific scenarios in which daily morning labs can be safely avoided have not been identified. The goal of this study was to identify situations in which routine CBC testing can be avoided in patients with community-acquired pneumonia (CAP), one of the most common reasons for hospital admission.3

METHODS

This was a retrospective study of 50 patients with CAP discharged from our hospital between February 1, 2015 and May 1, 2015. We performed chart abstractions collecting daily vital signs, lab results, provider notes including assessments and plans (A&Ps), and order entry logs, as well as documentation indicating whether a lab result or clinical finding appeared to affect clinical management (eg, a new order or documentation of changing plans). Both escalations and de-escalations were included as management changes. For example, if the note stated “Persistent leukocytosis, add vancomycin,” then the clinical action of expanded antibiotic coverage would be attributed to the CBC.

We defined clinical stability based on Definition B of the Pneumonia Patient Outcomes Research Team (PORT) study criteria.4 We used descriptive statistics and likelihood ratios to characterize the utility of CBC testing in terms of producing clinical management changes. Likelihood ratios were calculated with the “test” representing a CBC being ordered or not ordered and the outcome being any change in management independent of whether it was due to the CBC.

RESULTS

Of 50 patients, 33 (66%) were female, the mean age was 75 years, the mean length of stay was 2.8 days, and the median CURB-65 score,5 an estimate of mortality in CAP used for decision-making about inpatient versus outpatient treatment, was 1 (25th to 75th interquartile range: 1, 2); no patients had a CURB score greater than 3 (Table 1). Forty-one (82%) patients met PORT clinical stability criteria prior to discharge, and 30 (75% of stable patients) had CBCs obtained.

Patient Characteristics
Table 1

On days after admission, 94 subsequent CBCs were obtained. Of these CBCs, 6 (6.4%) were associated with management changes indicated in documentation or orders (Table 2). In 2 of the 6 patients, management changes were likely relevant to pneumonia. In the first case, the patient had a white blood cell count (WBC) of 15.4 on the planned day of discharge but no accompanying clinical changes. Her discharge was potentially delayed pending a repeat CBC which again showed a WBC 14.7; the patient was then discharged without any additional changes in plan. In the second case, the patient experienced new-onset altered mental status on hospital day 3 and increasing O2 requirement with a rising WBC noted on hospital day 4. Repeat chest x-ray, repeat blood cultures, and an ultrasound for parapneumonic effusion were obtained, and the patient’s symptoms and signs resolved over a period of days without changes in treatment. In the 4 other cases, available documentation suggested the hemoglobin abnormalities found represented chronic or incidental illnesses, specifically iron deficiency anemia, iatrogenic anemia due to fluid resuscitation and hemodilution, previously known chronic lymphocytic leukemia, and thrombocytopenia due to acute infection. In all 6 instances, CBC values improved without treatment intervention.

Complete Blood Counts and Changes in Management
Table 2

Among all patients, the positive likelihood ratio of CBCs obtained after admission in terms of being followed by a change in clinical management was very poor (1.12, 95% confidence interval [CI], 0.86-1.44). For clinically unstable patients, there were 64 CBCs ordered, and the likelihood ratio was similar at 0.98 (95% CI, 0.75-1.29). The positive likelihood ratio among clinically stable patients, who had 30 CBCs ordered, was still quite weak, though confidence intervals were wider (1.23, 95% CI, 0.66-2.29).

 

 

DISCUSSION

Though small, our initial study suggests the potential opportunity for savings if Choosing Wisely® recommendations for CBC testing were implemented in patients with community-acquired pneumonia.

Our study has several limitations. Note-writing practices and ordering patterns likely varied between providers, and documentation bias may play a role in our results. However, we defined whether a CBC was associated with changes in clinical decision-making or management by incorporating a number of mutually reinforcing elements of the medical record. We recognize, however, that our approach may not capture undocumented clinical issues or other cognitive (eg, reassurance of clinical resolution) reasons why CBCs were obtained.

Even with these limitations, the likelihood of a CBC value meaningfully changing clinical management among patients with CAP appears to be quite low as evidenced by the case descriptions, particularly when obtained in stable patients by PORT criteria and on the day of discharge. Whether clinical stability as measured by PORT score can be used to target patients in whom CBC testing is unnecessary is difficult to discern from our data, as the overall utility of CBCs obtained after admission was quite low and the rate of changes in management was also low. However, even if CBCs are not particularly costly, unnecessary testing may produce harm in the form of prolonged length of stay, making even one unnecessary CBC potentially extremely expensive. More research involving larger-scale studies are needed to determine the “number needed to screen” for the daily CBC in CAP to determine if the cost savings from overtesting and treatment outweigh the potential benefit of a single CBC that changes management.

Disclosure

Nothing to report.

 

References

1. Choosing Wisely. Promoting conversations between providers and patients. Choosing Wisely. http://www.choosingwisely.org/. Accessed March 28, 2016.
2. Beresford L. The Society of Hospital Medicine’s “Choosing Wisely” Recommendations for Hospitalists. 2013. http://www.the-hospitalist.org/article/the-society-of-hospital-medicines-choosing-wisely-recommendations-for-hospitalists/. Accessed March 28, 2016.
3. File TM Jr, Marrie TJ. Burden of community-acquired pneumonia in North American adults. Postgrad Med. 2010;122(2):130-141. PubMed
4. Halm EA, Fine MJ, Marrie TJ, et al. Time to clinical stability in patients hospitalized with community-acquired pneumonia: Implications for practice guidelines. JAMA. 1998;279(18):1452-1457. PubMed
5. Lim W, van der Eerden MM, Laing R, et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003;58(5):377-382. PubMed

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Avoiding repeated complete blood count (CBC) tests in the face of clinical and lab stability is a focus of the Choosing Wisely® initiatives launched by the American Board of Internal Medicine Foundation1 and endorsed by the Society of Hospital Medicine.2 However, specific scenarios in which daily morning labs can be safely avoided have not been identified. The goal of this study was to identify situations in which routine CBC testing can be avoided in patients with community-acquired pneumonia (CAP), one of the most common reasons for hospital admission.3

METHODS

This was a retrospective study of 50 patients with CAP discharged from our hospital between February 1, 2015 and May 1, 2015. We performed chart abstractions collecting daily vital signs, lab results, provider notes including assessments and plans (A&Ps), and order entry logs, as well as documentation indicating whether a lab result or clinical finding appeared to affect clinical management (eg, a new order or documentation of changing plans). Both escalations and de-escalations were included as management changes. For example, if the note stated “Persistent leukocytosis, add vancomycin,” then the clinical action of expanded antibiotic coverage would be attributed to the CBC.

We defined clinical stability based on Definition B of the Pneumonia Patient Outcomes Research Team (PORT) study criteria.4 We used descriptive statistics and likelihood ratios to characterize the utility of CBC testing in terms of producing clinical management changes. Likelihood ratios were calculated with the “test” representing a CBC being ordered or not ordered and the outcome being any change in management independent of whether it was due to the CBC.

RESULTS

Of 50 patients, 33 (66%) were female, the mean age was 75 years, the mean length of stay was 2.8 days, and the median CURB-65 score,5 an estimate of mortality in CAP used for decision-making about inpatient versus outpatient treatment, was 1 (25th to 75th interquartile range: 1, 2); no patients had a CURB score greater than 3 (Table 1). Forty-one (82%) patients met PORT clinical stability criteria prior to discharge, and 30 (75% of stable patients) had CBCs obtained.

Patient Characteristics
Table 1

On days after admission, 94 subsequent CBCs were obtained. Of these CBCs, 6 (6.4%) were associated with management changes indicated in documentation or orders (Table 2). In 2 of the 6 patients, management changes were likely relevant to pneumonia. In the first case, the patient had a white blood cell count (WBC) of 15.4 on the planned day of discharge but no accompanying clinical changes. Her discharge was potentially delayed pending a repeat CBC which again showed a WBC 14.7; the patient was then discharged without any additional changes in plan. In the second case, the patient experienced new-onset altered mental status on hospital day 3 and increasing O2 requirement with a rising WBC noted on hospital day 4. Repeat chest x-ray, repeat blood cultures, and an ultrasound for parapneumonic effusion were obtained, and the patient’s symptoms and signs resolved over a period of days without changes in treatment. In the 4 other cases, available documentation suggested the hemoglobin abnormalities found represented chronic or incidental illnesses, specifically iron deficiency anemia, iatrogenic anemia due to fluid resuscitation and hemodilution, previously known chronic lymphocytic leukemia, and thrombocytopenia due to acute infection. In all 6 instances, CBC values improved without treatment intervention.

Complete Blood Counts and Changes in Management
Table 2

Among all patients, the positive likelihood ratio of CBCs obtained after admission in terms of being followed by a change in clinical management was very poor (1.12, 95% confidence interval [CI], 0.86-1.44). For clinically unstable patients, there were 64 CBCs ordered, and the likelihood ratio was similar at 0.98 (95% CI, 0.75-1.29). The positive likelihood ratio among clinically stable patients, who had 30 CBCs ordered, was still quite weak, though confidence intervals were wider (1.23, 95% CI, 0.66-2.29).

 

 

DISCUSSION

Though small, our initial study suggests the potential opportunity for savings if Choosing Wisely® recommendations for CBC testing were implemented in patients with community-acquired pneumonia.

Our study has several limitations. Note-writing practices and ordering patterns likely varied between providers, and documentation bias may play a role in our results. However, we defined whether a CBC was associated with changes in clinical decision-making or management by incorporating a number of mutually reinforcing elements of the medical record. We recognize, however, that our approach may not capture undocumented clinical issues or other cognitive (eg, reassurance of clinical resolution) reasons why CBCs were obtained.

Even with these limitations, the likelihood of a CBC value meaningfully changing clinical management among patients with CAP appears to be quite low as evidenced by the case descriptions, particularly when obtained in stable patients by PORT criteria and on the day of discharge. Whether clinical stability as measured by PORT score can be used to target patients in whom CBC testing is unnecessary is difficult to discern from our data, as the overall utility of CBCs obtained after admission was quite low and the rate of changes in management was also low. However, even if CBCs are not particularly costly, unnecessary testing may produce harm in the form of prolonged length of stay, making even one unnecessary CBC potentially extremely expensive. More research involving larger-scale studies are needed to determine the “number needed to screen” for the daily CBC in CAP to determine if the cost savings from overtesting and treatment outweigh the potential benefit of a single CBC that changes management.

Disclosure

Nothing to report.

 

Avoiding repeated complete blood count (CBC) tests in the face of clinical and lab stability is a focus of the Choosing Wisely® initiatives launched by the American Board of Internal Medicine Foundation1 and endorsed by the Society of Hospital Medicine.2 However, specific scenarios in which daily morning labs can be safely avoided have not been identified. The goal of this study was to identify situations in which routine CBC testing can be avoided in patients with community-acquired pneumonia (CAP), one of the most common reasons for hospital admission.3

METHODS

This was a retrospective study of 50 patients with CAP discharged from our hospital between February 1, 2015 and May 1, 2015. We performed chart abstractions collecting daily vital signs, lab results, provider notes including assessments and plans (A&Ps), and order entry logs, as well as documentation indicating whether a lab result or clinical finding appeared to affect clinical management (eg, a new order or documentation of changing plans). Both escalations and de-escalations were included as management changes. For example, if the note stated “Persistent leukocytosis, add vancomycin,” then the clinical action of expanded antibiotic coverage would be attributed to the CBC.

We defined clinical stability based on Definition B of the Pneumonia Patient Outcomes Research Team (PORT) study criteria.4 We used descriptive statistics and likelihood ratios to characterize the utility of CBC testing in terms of producing clinical management changes. Likelihood ratios were calculated with the “test” representing a CBC being ordered or not ordered and the outcome being any change in management independent of whether it was due to the CBC.

RESULTS

Of 50 patients, 33 (66%) were female, the mean age was 75 years, the mean length of stay was 2.8 days, and the median CURB-65 score,5 an estimate of mortality in CAP used for decision-making about inpatient versus outpatient treatment, was 1 (25th to 75th interquartile range: 1, 2); no patients had a CURB score greater than 3 (Table 1). Forty-one (82%) patients met PORT clinical stability criteria prior to discharge, and 30 (75% of stable patients) had CBCs obtained.

Patient Characteristics
Table 1

On days after admission, 94 subsequent CBCs were obtained. Of these CBCs, 6 (6.4%) were associated with management changes indicated in documentation or orders (Table 2). In 2 of the 6 patients, management changes were likely relevant to pneumonia. In the first case, the patient had a white blood cell count (WBC) of 15.4 on the planned day of discharge but no accompanying clinical changes. Her discharge was potentially delayed pending a repeat CBC which again showed a WBC 14.7; the patient was then discharged without any additional changes in plan. In the second case, the patient experienced new-onset altered mental status on hospital day 3 and increasing O2 requirement with a rising WBC noted on hospital day 4. Repeat chest x-ray, repeat blood cultures, and an ultrasound for parapneumonic effusion were obtained, and the patient’s symptoms and signs resolved over a period of days without changes in treatment. In the 4 other cases, available documentation suggested the hemoglobin abnormalities found represented chronic or incidental illnesses, specifically iron deficiency anemia, iatrogenic anemia due to fluid resuscitation and hemodilution, previously known chronic lymphocytic leukemia, and thrombocytopenia due to acute infection. In all 6 instances, CBC values improved without treatment intervention.

Complete Blood Counts and Changes in Management
Table 2

Among all patients, the positive likelihood ratio of CBCs obtained after admission in terms of being followed by a change in clinical management was very poor (1.12, 95% confidence interval [CI], 0.86-1.44). For clinically unstable patients, there were 64 CBCs ordered, and the likelihood ratio was similar at 0.98 (95% CI, 0.75-1.29). The positive likelihood ratio among clinically stable patients, who had 30 CBCs ordered, was still quite weak, though confidence intervals were wider (1.23, 95% CI, 0.66-2.29).

 

 

DISCUSSION

Though small, our initial study suggests the potential opportunity for savings if Choosing Wisely® recommendations for CBC testing were implemented in patients with community-acquired pneumonia.

Our study has several limitations. Note-writing practices and ordering patterns likely varied between providers, and documentation bias may play a role in our results. However, we defined whether a CBC was associated with changes in clinical decision-making or management by incorporating a number of mutually reinforcing elements of the medical record. We recognize, however, that our approach may not capture undocumented clinical issues or other cognitive (eg, reassurance of clinical resolution) reasons why CBCs were obtained.

Even with these limitations, the likelihood of a CBC value meaningfully changing clinical management among patients with CAP appears to be quite low as evidenced by the case descriptions, particularly when obtained in stable patients by PORT criteria and on the day of discharge. Whether clinical stability as measured by PORT score can be used to target patients in whom CBC testing is unnecessary is difficult to discern from our data, as the overall utility of CBCs obtained after admission was quite low and the rate of changes in management was also low. However, even if CBCs are not particularly costly, unnecessary testing may produce harm in the form of prolonged length of stay, making even one unnecessary CBC potentially extremely expensive. More research involving larger-scale studies are needed to determine the “number needed to screen” for the daily CBC in CAP to determine if the cost savings from overtesting and treatment outweigh the potential benefit of a single CBC that changes management.

Disclosure

Nothing to report.

 

References

1. Choosing Wisely. Promoting conversations between providers and patients. Choosing Wisely. http://www.choosingwisely.org/. Accessed March 28, 2016.
2. Beresford L. The Society of Hospital Medicine’s “Choosing Wisely” Recommendations for Hospitalists. 2013. http://www.the-hospitalist.org/article/the-society-of-hospital-medicines-choosing-wisely-recommendations-for-hospitalists/. Accessed March 28, 2016.
3. File TM Jr, Marrie TJ. Burden of community-acquired pneumonia in North American adults. Postgrad Med. 2010;122(2):130-141. PubMed
4. Halm EA, Fine MJ, Marrie TJ, et al. Time to clinical stability in patients hospitalized with community-acquired pneumonia: Implications for practice guidelines. JAMA. 1998;279(18):1452-1457. PubMed
5. Lim W, van der Eerden MM, Laing R, et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003;58(5):377-382. PubMed

References

1. Choosing Wisely. Promoting conversations between providers and patients. Choosing Wisely. http://www.choosingwisely.org/. Accessed March 28, 2016.
2. Beresford L. The Society of Hospital Medicine’s “Choosing Wisely” Recommendations for Hospitalists. 2013. http://www.the-hospitalist.org/article/the-society-of-hospital-medicines-choosing-wisely-recommendations-for-hospitalists/. Accessed March 28, 2016.
3. File TM Jr, Marrie TJ. Burden of community-acquired pneumonia in North American adults. Postgrad Med. 2010;122(2):130-141. PubMed
4. Halm EA, Fine MJ, Marrie TJ, et al. Time to clinical stability in patients hospitalized with community-acquired pneumonia: Implications for practice guidelines. JAMA. 1998;279(18):1452-1457. PubMed
5. Lim W, van der Eerden MM, Laing R, et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003;58(5):377-382. PubMed

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Planning and designing the Improving Addiction Care Team (IMPACT) for hospitalized adults with substance use disorder

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Planning and designing the Improving Addiction Care Team (IMPACT) for hospitalized adults with substance use disorder

Addiction is a national epidemic that represents both a pressing need and a significant burden to the healthcare system.1 Hospitals are increasingly filled with people admitted for medical complications of substance use disorders (SUD).2People with SUD have longer lengths of stay (LOS) and high readmission rates.3 Hospitalization often does not address the root cause—the SUD. For example, many hospitals replace heart valves and deliver prolonged courses of intravenous (IV) antibiotics for endocarditis from injection drug use but do not offer addiction medicine consultation, medication for addiction treatment (MAT), or linkage to posthospital SUD treatment.4,5

Hospitalization can provide reachable moments for initiating addiction care.6 Medications for opioid7 and alcohol use disorders8 can be started during hospitalization, promoting engagement in outpatient SUD care7 and increased uptake of MAT,7-9 and reducing readmissions.8,10 Yet, medications for SUD are underprescribed,11,12 and most hospitals lack inpatient addiction medicine services and pathways to timely SUD care after discharge. Furthermore, traditional SUD treatment programs are often not equipped to manage medically complex patients or they have long waitlists.13 Most behavioral-physical health integration occurs in ambulatory settings. This fails to engage patients who do not access primary care. There is an urgent need for models that can improve care for hospitalized patients with SUD.

Here, we describe our experience using patient needs assessment to engage stakeholders and drive local systems change. We also describe the resulting care model, the Improving Addiction Care Team (IMPACT). Our experience provides a potentially useful example to other hospitals and communities seeking to address the national SUD epidemic.

METHODS

Setting

In 2012, Oregon transformed its Medicaid system by establishing 16 regional “coordinated care organizations” (CCOs) to improve outcomes and slow healthcare spending.14 In a CCO environment, hospitals assume increased financial risk, yet reforms have focused on the outpatient setting. Therefore, executive leadership at Oregon Health & Science University (OHSU), an urban academic medical center, asked clinician-leaders to design point-of-care improvements for Medicaid-funded adults and build on existing models to improve care for socioeconomically vulnerable adults.15,16 One priority that emerged was to make improvements for hospitalized adults with SUD. Of the adult inpatients at OHSU, 30% have Medicaid and 15% have SUD by administrative data alone. Before we started our work, OHSU lacked inpatient addiction medicine services.

Local Needs Assessment

To understand local needs and opportunities, we surveyed hospitalized adults with SUD. We used the electronic health record to generate a list of inpatients flagged by nurses for risky alcohol or drug use. A research assistant screened consecutive adults (≥18 years old) and invited those who screened positive for alcohol use (Alcohol Use Disorders Identification Test–Consumption [AUDIT-C])17 or drug use (single-item screener)18 to participate. We excluded non-English speakers, incarcerated adults, people using only marijuana or tobacco, psychiatry inpatients, and people unable to consent. Surveys assessed social and demographic factors, healthcare utilization, substance use severity, and treatment experience. Participants who reported high-risk illicit drug or alcohol use19 were asked to indicate their readiness to change on a 3-point scale developed for this study. Response range included: no interest, interest in cutting back, or interest in quitting. A subset of participants completed in-depth qualitative interviews exploring patient perceptions of substance use treatment needs.20 We obtained hospital administrative data from hospital financial services.

 

 

Partner Engagement

We identified community partners with which we had an individual or organizational relationship and a common interest and potential for collaboration. All invited partners agreed to attend initial meetings. We convened leadership and frontline staff across partners. OHSU staff included hospital nursing and social work leaders; infectious disease, hospitalist, and addiction physicians; and health services researchers. Community organizations included Central City Concern (CCC), a community organization serving people facing homelessness and addiction; CODA, Inc., a nonprofit SUD treatment agency; and Coram/CVS infusion pharmacy.

Collectively, we reviewed needs assessment findings and examples from the literature7-9 to develop strategies to address patient and system needs. We used patient narratives to foster alignment and prioritized areas in which integration could improve quality and costs. We assumed we would petition OHSU and/or Medicaid CCOs to finance efforts and saved potentially challenging budget discussions for later, when partnerships would be more developed. Our task force attended more than 3 large-group meetings and numerous small-group meetings to develop IMPACT.

RESULTS

Needs Assessment

Between September 2014 and April 2015, a research assistant approached 326 patients. Of these, 235 (72%) met study inclusion criteria, and 185 (78%) agreed to participate (Table 1). Of people who reported any substance use within the preceding 3 months, 58% of alcohol users and 67% of drug users said they were interested in cutting back or quitting. Fifty-four percent of participants with moderate- to high-risk opioid use and 16% with moderate- to high-risk alcohol use reported strong interest in MAT. In qualitative interviews, participants described inadequately treated withdrawal, the importance of trust and choice, and long wait times as a barriers to entering treatment after hospital discharge.20

Needs Assessment Participant Characteristics
Table 1

Administrative data revealed high rates of hospital readmissions and longer than expected LOS (Figure). Mean LOS was 10.26 days—4 days more than medicine patients’. Mean LOS was high among participants who required long-term IV antibiotics, particularly those with endocarditis or osteomyelitis (21.75 days; range, 1.00-51.00 days). We excluded one outlier with a 116-day hospitalization.

Intervention Design

Mapping needs to intervention components. We mapped needs assessment findings to 3 main IMPACT components: inpatient addiction medicine consultation service, pathways to posthospital SUD treatment, and medically enhanced residential treatment (MERT) (Table 2).

Hospital LOS among needs assessment patients.
Figure

Inpatient addiction medicine consultation service. We developed this service to address patients’ report of high readiness to change and interest in starting MAT in the hospital. Community partners highlighted the need for peers to increase engagement and trust. Therefore, we included a physician, a social worker, and two peers on our team. The inpatient service engages patients, advises on withdrawal and pain, performs SUD assessments, initiates MAT, and provides counseling and treatment.

 Key IMPACT Element, Including Year 1 Enrollment Targets, Staff Descriptions and Roles, and Allocated Resources
Table 2

Pathways to posthospital SUD treatment. As pathways from hospital to community SUD treatment were lacking, and long administrative wait times limited access to community treatment, we employed “in-reach” liaisons—community SUD treatment staff who perform in-hospital assessments to triage and coordinate care across systems. Given that patients value having treatment choices, we linked pathways to an array of MAT and abstinence-based treatments, including office-based, intensive outpatient and residential levels of care. For patients who live outside the Portland area, we developed relationships with rural stakeholders and engaged the help of the Oregon State Opioid Authority in introducing our program to SUD treatment providers around the state.

Medically Enhanced Residential Treatment (MERT). In many cases where patients required prolonged courses of IV antibiotics, hospital stays were longer for two reasons: At-home central-line self-administration of antibiotics was deemed unsafe, and patients were denied admission to a skilled nursing facility due to history of substance use. These long LOS create an opportunity to initiate and engage patients in treatment, and to render savings by shifting care to a residential addiction treatment setting that can accommodate IV antibiotic administration and MAT. We increased residential staffing and collaborated with a home infusion pharmacy to administer daily infusions on site.

Funding the Intervention

We used administrative data to estimate potential savings and tailored a business case to CCO and hospital payers. The CCO business case centered on hospitalization as an opportunity to engage out-of-treatment adults and potentially reduce high-cost readmissions by managing physical and behavioral health needs. Working within budgeting time lines, we used data from the first 165 participants. These participants had 137 readmissions over a mean observation period of 4.5 months. Mean charge per readmission was $31,157 (range, $699-$206,596) and was highest for people with endocarditis (mean, $55,493; range, $23,204-$145,066) and osteomyelitis (mean, $68,774; range, $29,359-$124,481). We estimated that a 10% reduction in 6-month readmissions could avoid $674,863 in charges.

 

 

For the hospital, the primary financial incentive was reduced LOS. Given the possibility of shortening hospitalization through MERT, we estimated a 20% mean LOS reduction; for budgeting, we estimated a conservative 10% reduction. A 10% mean LOS reduction would free 205 bed-days (10% × 10.26 days mean LOS × 200 patients) and create space for another 32 inpatient admissions in year 1, assuming no change from medical patients’ 6.26 days mean LOS. The future of bundled payments further bolstered our business case, as did the potential to improve care quality, reduce nonproductive staff time, and increase institutional learning about SUD. Overall program costs approximated projected savings, and the hospital and a local CCO agreed to equally share the costs of the intervention (Table 2).

DISCUSSION

We have described an innovative approach to developing an SUD intervention for hospitalized adults. Using a process of broad stakeholder engagement, data-driven understanding of population needs, and analysis of financial incentives, we built consensus and secured funding for a multicomponent intervention across hospital and post–acute care settings. Other studies have demonstrated the feasibility and efficacy of starting a single medication for a specific indication7-9 (eg, methadone for opioid use disorder), yet strategies for expanding SUD services in hospitals and facilitating posthospital treatment linkages remain scarce.21 Our model addresses a widespread need and could be adapted to other hospitals, SUD treatment organizations, and Medicaid payers.

Our experience has several limitations. First, it took place at a single academic medical center in Oregon, a Medicaid expansion state. Second, our needs assessment involved a convenience sample of limited racial/ethnic diversity. Third, almost all patients had insurance, which could limit generalizability. Fourth, to secure funding, it was essential we had a clinical champion who was persuasive with hospital and CCO leadership; though increasing disease burden and skyrocketing costs2 may drive administrators’ increased demand for ways to address SUD in hospitalized adults.

Our experience has several key implications. First, diverse partners were vital at all stages of program design, suggesting hospitals should look beyond traditional healthcare partners to address the SUD epidemic. Second, an interprofessional team that includes physicians, social workers, and peers may better engage patients and address complex system needs. Finally, a planned IMPACT evaluation will assess effects on substance use, healthcare use, and costs.

The United States faces a burgeoning SUD epidemic. Our experience describes an innovative care model and supports the idea that hospitals may play a leading role in convening partners, providing treatment, and driving population health improvements for adults with SUD.

Acknowledgment

The authors would like to acknowledge Peter Rapp and Thomas Yackel for leadership support; Tara Williams for administrative data support; Sarann Bielavitz and Naomi Wright for project management support, and Lynn Smith-Stott and Maria Michalczyk for help with model design. This work was presented at the American Society of Addiction Medicine national conference in Baltimore, MD in April 2016.

Disclosure

This work was funded by Oregon Health & Science University and CareOregon. The authors have no conflicts of interest to disclose.

 

References

1. Volkow N, Frieden TR, Hyde PS, Cha SS. Medication-assisted therapies—Tackling the opioid-overdose epidemic. N Engl J Med. 2014; 370:2063-2066. PubMed
2. Ronan MV, Herzig SJ. Hospitalizations related to opioid abuse/dependence and associated serious infections increased sharply, 2002-12. Health Aff (Millwood). 2016;35(5):832-837. PubMed
3. Walley AY, Paasche-Orlow M, Lee EC, et al. Acute care hospital utilization among medical inpatients discharged with a substance use disorder diagnosis. J Addict Med. 2012;6(1):50-56. PubMed
4. Rosenthal ES, Karchmer AW, Thiesen-Toupal J, Castillo RA, Rowley CF. Suboptimal addiction interventions for patients hospitalized with injection drug use-associated infective endocarditis. Am J Med. 2016;129(5):481-485. PubMed
5. Fanucchi L, Lofwall MR. Putting parity into practice—integrating opioid-use disorder treatment into the hospital setting. N Engl J Med. 2016;379(9):811-813. PubMed
6. Pollini RA, O’Toole TP, Ford D, Bigelow G. Does this patient really want treatment? Factors associated with baseline and evolving readiness for change among hospitalized substance using adults interested in treatment. Addict Behav. 2006;31(10):1904-1918. PubMed
7. Liebschutz JM, Crooks D, Herman D, et al. Buprenorphine treatment for hospitalized, opioid-dependent patients: a randomized clinical trial. JAMA Intern Med. 2014;174(8):1369-1376. PubMed
8. Wei J, Defries T, Lozada M, Young N, Huen W, Tulsky J. An inpatient treatment and discharge planning protocol for alcohol and dependence: efficacy in reducing 30-day readmissions and emergency department visits. J Gen Intern Med. 2015;30(3):365-370. PubMed
9. Shanahan CW, Beers D, Alford DP, Brigandi E, Samet JH. A transitional opioid program to engage hospitalized drug users. J Gen Intern Med. 2010;25(8):803-808. PubMed
10. Pecoraro A, Horton T, Ewen E, et al. Early data from Project Engage: a program to identify and transition medically hospitalized patients into addictions treatment. Addict Sci Clin Pract. 2012;7:20. PubMed
11. National Center on Addiction and Substance Abuse; Addiction Medicine: Closing the Gap between Science and Practice. June 2012. http://www.centeronaddiction.org/addiction-research/reports/addiction-medicine-closing-gap-between-science-and-practice. Accessed May 2, 2016.
12. Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration, US Department of Health and Human Services. Results From the 2010 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration, US Dept of Health and Human Services; 2011. NSDUH series H-41, HHS publication SMA 11-4658. https://www.samhsa.gov/data/sites/default/files/NSDUHNationalFindingsResults2010-web/2k10ResultsRev/NSDUHresultsRev2010.pdf. Published September 2011. Accessed March 31, 2017.
13. Vestal C. Few doctors are willing, able to prescribe powerful anti-addiction drugs. http://www.pewtrusts.org/en/research-and-analysis/blogs/stateline/2016/01/15/few-doctors-are-willing-able-to-prescribe-powerful-anti-addiction-drugs. Published January 15, 2016. Accessed May 2, 2016.
14. McConnell KJ. Oregon’s Medicaid coordinated care organizations. JAMA. 2016;315(9):869-870. PubMed
15. Englander H, Kansagara D. Planning and designing the Care Transitions Innovation (C-TraIn) for uninsured and Medicaid patients. J Hosp Med. 2012;7(7):524-529. PubMed
16. Englander H, Michaels L, Chan B, Kansagara D. The Care Transitions Innovation (C-TraIn) for socioeconomically disadvantaged adults: results of a cluster randomized controlled trial. J Gen Intern Med. 2014;29(11):1460-1467. PubMed
17. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med. 1998;158(16):1789-1795. PubMed
18. Smith PC, Schmidt SM, Allensworth-Davies D, Saitz R. A single-question screening test for drug use in primary care. Arch Intern Med. 2010;170(13):1155-1160. PubMed
19. Humeniuk R, Ali R, Babor TF, et al. Validation of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Addiction. 2008;103(6):1039-1047. PubMed
20. Velez CM, Nicolaidis C, Korthuis PT, Englander H. “It’s been an experience, a life learning experience”: a qualitative study of hospitalized patients with substance use disorders. J Gen Intern Med. 2017;32(3):296-303. PubMed
21. Gryczynski J, Schwartz RP, O’Grady KE, Restivo L, Mitchell SG, Jaffe JH. Understanding patterns of high-cost health care use across different substance user groups. Health Aff (Millwood). 2016.;35(1):12-19. PubMed

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Journal of Hospital Medicine 12(5)
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Addiction is a national epidemic that represents both a pressing need and a significant burden to the healthcare system.1 Hospitals are increasingly filled with people admitted for medical complications of substance use disorders (SUD).2People with SUD have longer lengths of stay (LOS) and high readmission rates.3 Hospitalization often does not address the root cause—the SUD. For example, many hospitals replace heart valves and deliver prolonged courses of intravenous (IV) antibiotics for endocarditis from injection drug use but do not offer addiction medicine consultation, medication for addiction treatment (MAT), or linkage to posthospital SUD treatment.4,5

Hospitalization can provide reachable moments for initiating addiction care.6 Medications for opioid7 and alcohol use disorders8 can be started during hospitalization, promoting engagement in outpatient SUD care7 and increased uptake of MAT,7-9 and reducing readmissions.8,10 Yet, medications for SUD are underprescribed,11,12 and most hospitals lack inpatient addiction medicine services and pathways to timely SUD care after discharge. Furthermore, traditional SUD treatment programs are often not equipped to manage medically complex patients or they have long waitlists.13 Most behavioral-physical health integration occurs in ambulatory settings. This fails to engage patients who do not access primary care. There is an urgent need for models that can improve care for hospitalized patients with SUD.

Here, we describe our experience using patient needs assessment to engage stakeholders and drive local systems change. We also describe the resulting care model, the Improving Addiction Care Team (IMPACT). Our experience provides a potentially useful example to other hospitals and communities seeking to address the national SUD epidemic.

METHODS

Setting

In 2012, Oregon transformed its Medicaid system by establishing 16 regional “coordinated care organizations” (CCOs) to improve outcomes and slow healthcare spending.14 In a CCO environment, hospitals assume increased financial risk, yet reforms have focused on the outpatient setting. Therefore, executive leadership at Oregon Health & Science University (OHSU), an urban academic medical center, asked clinician-leaders to design point-of-care improvements for Medicaid-funded adults and build on existing models to improve care for socioeconomically vulnerable adults.15,16 One priority that emerged was to make improvements for hospitalized adults with SUD. Of the adult inpatients at OHSU, 30% have Medicaid and 15% have SUD by administrative data alone. Before we started our work, OHSU lacked inpatient addiction medicine services.

Local Needs Assessment

To understand local needs and opportunities, we surveyed hospitalized adults with SUD. We used the electronic health record to generate a list of inpatients flagged by nurses for risky alcohol or drug use. A research assistant screened consecutive adults (≥18 years old) and invited those who screened positive for alcohol use (Alcohol Use Disorders Identification Test–Consumption [AUDIT-C])17 or drug use (single-item screener)18 to participate. We excluded non-English speakers, incarcerated adults, people using only marijuana or tobacco, psychiatry inpatients, and people unable to consent. Surveys assessed social and demographic factors, healthcare utilization, substance use severity, and treatment experience. Participants who reported high-risk illicit drug or alcohol use19 were asked to indicate their readiness to change on a 3-point scale developed for this study. Response range included: no interest, interest in cutting back, or interest in quitting. A subset of participants completed in-depth qualitative interviews exploring patient perceptions of substance use treatment needs.20 We obtained hospital administrative data from hospital financial services.

 

 

Partner Engagement

We identified community partners with which we had an individual or organizational relationship and a common interest and potential for collaboration. All invited partners agreed to attend initial meetings. We convened leadership and frontline staff across partners. OHSU staff included hospital nursing and social work leaders; infectious disease, hospitalist, and addiction physicians; and health services researchers. Community organizations included Central City Concern (CCC), a community organization serving people facing homelessness and addiction; CODA, Inc., a nonprofit SUD treatment agency; and Coram/CVS infusion pharmacy.

Collectively, we reviewed needs assessment findings and examples from the literature7-9 to develop strategies to address patient and system needs. We used patient narratives to foster alignment and prioritized areas in which integration could improve quality and costs. We assumed we would petition OHSU and/or Medicaid CCOs to finance efforts and saved potentially challenging budget discussions for later, when partnerships would be more developed. Our task force attended more than 3 large-group meetings and numerous small-group meetings to develop IMPACT.

RESULTS

Needs Assessment

Between September 2014 and April 2015, a research assistant approached 326 patients. Of these, 235 (72%) met study inclusion criteria, and 185 (78%) agreed to participate (Table 1). Of people who reported any substance use within the preceding 3 months, 58% of alcohol users and 67% of drug users said they were interested in cutting back or quitting. Fifty-four percent of participants with moderate- to high-risk opioid use and 16% with moderate- to high-risk alcohol use reported strong interest in MAT. In qualitative interviews, participants described inadequately treated withdrawal, the importance of trust and choice, and long wait times as a barriers to entering treatment after hospital discharge.20

Needs Assessment Participant Characteristics
Table 1

Administrative data revealed high rates of hospital readmissions and longer than expected LOS (Figure). Mean LOS was 10.26 days—4 days more than medicine patients’. Mean LOS was high among participants who required long-term IV antibiotics, particularly those with endocarditis or osteomyelitis (21.75 days; range, 1.00-51.00 days). We excluded one outlier with a 116-day hospitalization.

Intervention Design

Mapping needs to intervention components. We mapped needs assessment findings to 3 main IMPACT components: inpatient addiction medicine consultation service, pathways to posthospital SUD treatment, and medically enhanced residential treatment (MERT) (Table 2).

Hospital LOS among needs assessment patients.
Figure

Inpatient addiction medicine consultation service. We developed this service to address patients’ report of high readiness to change and interest in starting MAT in the hospital. Community partners highlighted the need for peers to increase engagement and trust. Therefore, we included a physician, a social worker, and two peers on our team. The inpatient service engages patients, advises on withdrawal and pain, performs SUD assessments, initiates MAT, and provides counseling and treatment.

 Key IMPACT Element, Including Year 1 Enrollment Targets, Staff Descriptions and Roles, and Allocated Resources
Table 2

Pathways to posthospital SUD treatment. As pathways from hospital to community SUD treatment were lacking, and long administrative wait times limited access to community treatment, we employed “in-reach” liaisons—community SUD treatment staff who perform in-hospital assessments to triage and coordinate care across systems. Given that patients value having treatment choices, we linked pathways to an array of MAT and abstinence-based treatments, including office-based, intensive outpatient and residential levels of care. For patients who live outside the Portland area, we developed relationships with rural stakeholders and engaged the help of the Oregon State Opioid Authority in introducing our program to SUD treatment providers around the state.

Medically Enhanced Residential Treatment (MERT). In many cases where patients required prolonged courses of IV antibiotics, hospital stays were longer for two reasons: At-home central-line self-administration of antibiotics was deemed unsafe, and patients were denied admission to a skilled nursing facility due to history of substance use. These long LOS create an opportunity to initiate and engage patients in treatment, and to render savings by shifting care to a residential addiction treatment setting that can accommodate IV antibiotic administration and MAT. We increased residential staffing and collaborated with a home infusion pharmacy to administer daily infusions on site.

Funding the Intervention

We used administrative data to estimate potential savings and tailored a business case to CCO and hospital payers. The CCO business case centered on hospitalization as an opportunity to engage out-of-treatment adults and potentially reduce high-cost readmissions by managing physical and behavioral health needs. Working within budgeting time lines, we used data from the first 165 participants. These participants had 137 readmissions over a mean observation period of 4.5 months. Mean charge per readmission was $31,157 (range, $699-$206,596) and was highest for people with endocarditis (mean, $55,493; range, $23,204-$145,066) and osteomyelitis (mean, $68,774; range, $29,359-$124,481). We estimated that a 10% reduction in 6-month readmissions could avoid $674,863 in charges.

 

 

For the hospital, the primary financial incentive was reduced LOS. Given the possibility of shortening hospitalization through MERT, we estimated a 20% mean LOS reduction; for budgeting, we estimated a conservative 10% reduction. A 10% mean LOS reduction would free 205 bed-days (10% × 10.26 days mean LOS × 200 patients) and create space for another 32 inpatient admissions in year 1, assuming no change from medical patients’ 6.26 days mean LOS. The future of bundled payments further bolstered our business case, as did the potential to improve care quality, reduce nonproductive staff time, and increase institutional learning about SUD. Overall program costs approximated projected savings, and the hospital and a local CCO agreed to equally share the costs of the intervention (Table 2).

DISCUSSION

We have described an innovative approach to developing an SUD intervention for hospitalized adults. Using a process of broad stakeholder engagement, data-driven understanding of population needs, and analysis of financial incentives, we built consensus and secured funding for a multicomponent intervention across hospital and post–acute care settings. Other studies have demonstrated the feasibility and efficacy of starting a single medication for a specific indication7-9 (eg, methadone for opioid use disorder), yet strategies for expanding SUD services in hospitals and facilitating posthospital treatment linkages remain scarce.21 Our model addresses a widespread need and could be adapted to other hospitals, SUD treatment organizations, and Medicaid payers.

Our experience has several limitations. First, it took place at a single academic medical center in Oregon, a Medicaid expansion state. Second, our needs assessment involved a convenience sample of limited racial/ethnic diversity. Third, almost all patients had insurance, which could limit generalizability. Fourth, to secure funding, it was essential we had a clinical champion who was persuasive with hospital and CCO leadership; though increasing disease burden and skyrocketing costs2 may drive administrators’ increased demand for ways to address SUD in hospitalized adults.

Our experience has several key implications. First, diverse partners were vital at all stages of program design, suggesting hospitals should look beyond traditional healthcare partners to address the SUD epidemic. Second, an interprofessional team that includes physicians, social workers, and peers may better engage patients and address complex system needs. Finally, a planned IMPACT evaluation will assess effects on substance use, healthcare use, and costs.

The United States faces a burgeoning SUD epidemic. Our experience describes an innovative care model and supports the idea that hospitals may play a leading role in convening partners, providing treatment, and driving population health improvements for adults with SUD.

Acknowledgment

The authors would like to acknowledge Peter Rapp and Thomas Yackel for leadership support; Tara Williams for administrative data support; Sarann Bielavitz and Naomi Wright for project management support, and Lynn Smith-Stott and Maria Michalczyk for help with model design. This work was presented at the American Society of Addiction Medicine national conference in Baltimore, MD in April 2016.

Disclosure

This work was funded by Oregon Health & Science University and CareOregon. The authors have no conflicts of interest to disclose.

 

Addiction is a national epidemic that represents both a pressing need and a significant burden to the healthcare system.1 Hospitals are increasingly filled with people admitted for medical complications of substance use disorders (SUD).2People with SUD have longer lengths of stay (LOS) and high readmission rates.3 Hospitalization often does not address the root cause—the SUD. For example, many hospitals replace heart valves and deliver prolonged courses of intravenous (IV) antibiotics for endocarditis from injection drug use but do not offer addiction medicine consultation, medication for addiction treatment (MAT), or linkage to posthospital SUD treatment.4,5

Hospitalization can provide reachable moments for initiating addiction care.6 Medications for opioid7 and alcohol use disorders8 can be started during hospitalization, promoting engagement in outpatient SUD care7 and increased uptake of MAT,7-9 and reducing readmissions.8,10 Yet, medications for SUD are underprescribed,11,12 and most hospitals lack inpatient addiction medicine services and pathways to timely SUD care after discharge. Furthermore, traditional SUD treatment programs are often not equipped to manage medically complex patients or they have long waitlists.13 Most behavioral-physical health integration occurs in ambulatory settings. This fails to engage patients who do not access primary care. There is an urgent need for models that can improve care for hospitalized patients with SUD.

Here, we describe our experience using patient needs assessment to engage stakeholders and drive local systems change. We also describe the resulting care model, the Improving Addiction Care Team (IMPACT). Our experience provides a potentially useful example to other hospitals and communities seeking to address the national SUD epidemic.

METHODS

Setting

In 2012, Oregon transformed its Medicaid system by establishing 16 regional “coordinated care organizations” (CCOs) to improve outcomes and slow healthcare spending.14 In a CCO environment, hospitals assume increased financial risk, yet reforms have focused on the outpatient setting. Therefore, executive leadership at Oregon Health & Science University (OHSU), an urban academic medical center, asked clinician-leaders to design point-of-care improvements for Medicaid-funded adults and build on existing models to improve care for socioeconomically vulnerable adults.15,16 One priority that emerged was to make improvements for hospitalized adults with SUD. Of the adult inpatients at OHSU, 30% have Medicaid and 15% have SUD by administrative data alone. Before we started our work, OHSU lacked inpatient addiction medicine services.

Local Needs Assessment

To understand local needs and opportunities, we surveyed hospitalized adults with SUD. We used the electronic health record to generate a list of inpatients flagged by nurses for risky alcohol or drug use. A research assistant screened consecutive adults (≥18 years old) and invited those who screened positive for alcohol use (Alcohol Use Disorders Identification Test–Consumption [AUDIT-C])17 or drug use (single-item screener)18 to participate. We excluded non-English speakers, incarcerated adults, people using only marijuana or tobacco, psychiatry inpatients, and people unable to consent. Surveys assessed social and demographic factors, healthcare utilization, substance use severity, and treatment experience. Participants who reported high-risk illicit drug or alcohol use19 were asked to indicate their readiness to change on a 3-point scale developed for this study. Response range included: no interest, interest in cutting back, or interest in quitting. A subset of participants completed in-depth qualitative interviews exploring patient perceptions of substance use treatment needs.20 We obtained hospital administrative data from hospital financial services.

 

 

Partner Engagement

We identified community partners with which we had an individual or organizational relationship and a common interest and potential for collaboration. All invited partners agreed to attend initial meetings. We convened leadership and frontline staff across partners. OHSU staff included hospital nursing and social work leaders; infectious disease, hospitalist, and addiction physicians; and health services researchers. Community organizations included Central City Concern (CCC), a community organization serving people facing homelessness and addiction; CODA, Inc., a nonprofit SUD treatment agency; and Coram/CVS infusion pharmacy.

Collectively, we reviewed needs assessment findings and examples from the literature7-9 to develop strategies to address patient and system needs. We used patient narratives to foster alignment and prioritized areas in which integration could improve quality and costs. We assumed we would petition OHSU and/or Medicaid CCOs to finance efforts and saved potentially challenging budget discussions for later, when partnerships would be more developed. Our task force attended more than 3 large-group meetings and numerous small-group meetings to develop IMPACT.

RESULTS

Needs Assessment

Between September 2014 and April 2015, a research assistant approached 326 patients. Of these, 235 (72%) met study inclusion criteria, and 185 (78%) agreed to participate (Table 1). Of people who reported any substance use within the preceding 3 months, 58% of alcohol users and 67% of drug users said they were interested in cutting back or quitting. Fifty-four percent of participants with moderate- to high-risk opioid use and 16% with moderate- to high-risk alcohol use reported strong interest in MAT. In qualitative interviews, participants described inadequately treated withdrawal, the importance of trust and choice, and long wait times as a barriers to entering treatment after hospital discharge.20

Needs Assessment Participant Characteristics
Table 1

Administrative data revealed high rates of hospital readmissions and longer than expected LOS (Figure). Mean LOS was 10.26 days—4 days more than medicine patients’. Mean LOS was high among participants who required long-term IV antibiotics, particularly those with endocarditis or osteomyelitis (21.75 days; range, 1.00-51.00 days). We excluded one outlier with a 116-day hospitalization.

Intervention Design

Mapping needs to intervention components. We mapped needs assessment findings to 3 main IMPACT components: inpatient addiction medicine consultation service, pathways to posthospital SUD treatment, and medically enhanced residential treatment (MERT) (Table 2).

Hospital LOS among needs assessment patients.
Figure

Inpatient addiction medicine consultation service. We developed this service to address patients’ report of high readiness to change and interest in starting MAT in the hospital. Community partners highlighted the need for peers to increase engagement and trust. Therefore, we included a physician, a social worker, and two peers on our team. The inpatient service engages patients, advises on withdrawal and pain, performs SUD assessments, initiates MAT, and provides counseling and treatment.

 Key IMPACT Element, Including Year 1 Enrollment Targets, Staff Descriptions and Roles, and Allocated Resources
Table 2

Pathways to posthospital SUD treatment. As pathways from hospital to community SUD treatment were lacking, and long administrative wait times limited access to community treatment, we employed “in-reach” liaisons—community SUD treatment staff who perform in-hospital assessments to triage and coordinate care across systems. Given that patients value having treatment choices, we linked pathways to an array of MAT and abstinence-based treatments, including office-based, intensive outpatient and residential levels of care. For patients who live outside the Portland area, we developed relationships with rural stakeholders and engaged the help of the Oregon State Opioid Authority in introducing our program to SUD treatment providers around the state.

Medically Enhanced Residential Treatment (MERT). In many cases where patients required prolonged courses of IV antibiotics, hospital stays were longer for two reasons: At-home central-line self-administration of antibiotics was deemed unsafe, and patients were denied admission to a skilled nursing facility due to history of substance use. These long LOS create an opportunity to initiate and engage patients in treatment, and to render savings by shifting care to a residential addiction treatment setting that can accommodate IV antibiotic administration and MAT. We increased residential staffing and collaborated with a home infusion pharmacy to administer daily infusions on site.

Funding the Intervention

We used administrative data to estimate potential savings and tailored a business case to CCO and hospital payers. The CCO business case centered on hospitalization as an opportunity to engage out-of-treatment adults and potentially reduce high-cost readmissions by managing physical and behavioral health needs. Working within budgeting time lines, we used data from the first 165 participants. These participants had 137 readmissions over a mean observation period of 4.5 months. Mean charge per readmission was $31,157 (range, $699-$206,596) and was highest for people with endocarditis (mean, $55,493; range, $23,204-$145,066) and osteomyelitis (mean, $68,774; range, $29,359-$124,481). We estimated that a 10% reduction in 6-month readmissions could avoid $674,863 in charges.

 

 

For the hospital, the primary financial incentive was reduced LOS. Given the possibility of shortening hospitalization through MERT, we estimated a 20% mean LOS reduction; for budgeting, we estimated a conservative 10% reduction. A 10% mean LOS reduction would free 205 bed-days (10% × 10.26 days mean LOS × 200 patients) and create space for another 32 inpatient admissions in year 1, assuming no change from medical patients’ 6.26 days mean LOS. The future of bundled payments further bolstered our business case, as did the potential to improve care quality, reduce nonproductive staff time, and increase institutional learning about SUD. Overall program costs approximated projected savings, and the hospital and a local CCO agreed to equally share the costs of the intervention (Table 2).

DISCUSSION

We have described an innovative approach to developing an SUD intervention for hospitalized adults. Using a process of broad stakeholder engagement, data-driven understanding of population needs, and analysis of financial incentives, we built consensus and secured funding for a multicomponent intervention across hospital and post–acute care settings. Other studies have demonstrated the feasibility and efficacy of starting a single medication for a specific indication7-9 (eg, methadone for opioid use disorder), yet strategies for expanding SUD services in hospitals and facilitating posthospital treatment linkages remain scarce.21 Our model addresses a widespread need and could be adapted to other hospitals, SUD treatment organizations, and Medicaid payers.

Our experience has several limitations. First, it took place at a single academic medical center in Oregon, a Medicaid expansion state. Second, our needs assessment involved a convenience sample of limited racial/ethnic diversity. Third, almost all patients had insurance, which could limit generalizability. Fourth, to secure funding, it was essential we had a clinical champion who was persuasive with hospital and CCO leadership; though increasing disease burden and skyrocketing costs2 may drive administrators’ increased demand for ways to address SUD in hospitalized adults.

Our experience has several key implications. First, diverse partners were vital at all stages of program design, suggesting hospitals should look beyond traditional healthcare partners to address the SUD epidemic. Second, an interprofessional team that includes physicians, social workers, and peers may better engage patients and address complex system needs. Finally, a planned IMPACT evaluation will assess effects on substance use, healthcare use, and costs.

The United States faces a burgeoning SUD epidemic. Our experience describes an innovative care model and supports the idea that hospitals may play a leading role in convening partners, providing treatment, and driving population health improvements for adults with SUD.

Acknowledgment

The authors would like to acknowledge Peter Rapp and Thomas Yackel for leadership support; Tara Williams for administrative data support; Sarann Bielavitz and Naomi Wright for project management support, and Lynn Smith-Stott and Maria Michalczyk for help with model design. This work was presented at the American Society of Addiction Medicine national conference in Baltimore, MD in April 2016.

Disclosure

This work was funded by Oregon Health & Science University and CareOregon. The authors have no conflicts of interest to disclose.

 

References

1. Volkow N, Frieden TR, Hyde PS, Cha SS. Medication-assisted therapies—Tackling the opioid-overdose epidemic. N Engl J Med. 2014; 370:2063-2066. PubMed
2. Ronan MV, Herzig SJ. Hospitalizations related to opioid abuse/dependence and associated serious infections increased sharply, 2002-12. Health Aff (Millwood). 2016;35(5):832-837. PubMed
3. Walley AY, Paasche-Orlow M, Lee EC, et al. Acute care hospital utilization among medical inpatients discharged with a substance use disorder diagnosis. J Addict Med. 2012;6(1):50-56. PubMed
4. Rosenthal ES, Karchmer AW, Thiesen-Toupal J, Castillo RA, Rowley CF. Suboptimal addiction interventions for patients hospitalized with injection drug use-associated infective endocarditis. Am J Med. 2016;129(5):481-485. PubMed
5. Fanucchi L, Lofwall MR. Putting parity into practice—integrating opioid-use disorder treatment into the hospital setting. N Engl J Med. 2016;379(9):811-813. PubMed
6. Pollini RA, O’Toole TP, Ford D, Bigelow G. Does this patient really want treatment? Factors associated with baseline and evolving readiness for change among hospitalized substance using adults interested in treatment. Addict Behav. 2006;31(10):1904-1918. PubMed
7. Liebschutz JM, Crooks D, Herman D, et al. Buprenorphine treatment for hospitalized, opioid-dependent patients: a randomized clinical trial. JAMA Intern Med. 2014;174(8):1369-1376. PubMed
8. Wei J, Defries T, Lozada M, Young N, Huen W, Tulsky J. An inpatient treatment and discharge planning protocol for alcohol and dependence: efficacy in reducing 30-day readmissions and emergency department visits. J Gen Intern Med. 2015;30(3):365-370. PubMed
9. Shanahan CW, Beers D, Alford DP, Brigandi E, Samet JH. A transitional opioid program to engage hospitalized drug users. J Gen Intern Med. 2010;25(8):803-808. PubMed
10. Pecoraro A, Horton T, Ewen E, et al. Early data from Project Engage: a program to identify and transition medically hospitalized patients into addictions treatment. Addict Sci Clin Pract. 2012;7:20. PubMed
11. National Center on Addiction and Substance Abuse; Addiction Medicine: Closing the Gap between Science and Practice. June 2012. http://www.centeronaddiction.org/addiction-research/reports/addiction-medicine-closing-gap-between-science-and-practice. Accessed May 2, 2016.
12. Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration, US Department of Health and Human Services. Results From the 2010 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration, US Dept of Health and Human Services; 2011. NSDUH series H-41, HHS publication SMA 11-4658. https://www.samhsa.gov/data/sites/default/files/NSDUHNationalFindingsResults2010-web/2k10ResultsRev/NSDUHresultsRev2010.pdf. Published September 2011. Accessed March 31, 2017.
13. Vestal C. Few doctors are willing, able to prescribe powerful anti-addiction drugs. http://www.pewtrusts.org/en/research-and-analysis/blogs/stateline/2016/01/15/few-doctors-are-willing-able-to-prescribe-powerful-anti-addiction-drugs. Published January 15, 2016. Accessed May 2, 2016.
14. McConnell KJ. Oregon’s Medicaid coordinated care organizations. JAMA. 2016;315(9):869-870. PubMed
15. Englander H, Kansagara D. Planning and designing the Care Transitions Innovation (C-TraIn) for uninsured and Medicaid patients. J Hosp Med. 2012;7(7):524-529. PubMed
16. Englander H, Michaels L, Chan B, Kansagara D. The Care Transitions Innovation (C-TraIn) for socioeconomically disadvantaged adults: results of a cluster randomized controlled trial. J Gen Intern Med. 2014;29(11):1460-1467. PubMed
17. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med. 1998;158(16):1789-1795. PubMed
18. Smith PC, Schmidt SM, Allensworth-Davies D, Saitz R. A single-question screening test for drug use in primary care. Arch Intern Med. 2010;170(13):1155-1160. PubMed
19. Humeniuk R, Ali R, Babor TF, et al. Validation of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Addiction. 2008;103(6):1039-1047. PubMed
20. Velez CM, Nicolaidis C, Korthuis PT, Englander H. “It’s been an experience, a life learning experience”: a qualitative study of hospitalized patients with substance use disorders. J Gen Intern Med. 2017;32(3):296-303. PubMed
21. Gryczynski J, Schwartz RP, O’Grady KE, Restivo L, Mitchell SG, Jaffe JH. Understanding patterns of high-cost health care use across different substance user groups. Health Aff (Millwood). 2016.;35(1):12-19. PubMed

References

1. Volkow N, Frieden TR, Hyde PS, Cha SS. Medication-assisted therapies—Tackling the opioid-overdose epidemic. N Engl J Med. 2014; 370:2063-2066. PubMed
2. Ronan MV, Herzig SJ. Hospitalizations related to opioid abuse/dependence and associated serious infections increased sharply, 2002-12. Health Aff (Millwood). 2016;35(5):832-837. PubMed
3. Walley AY, Paasche-Orlow M, Lee EC, et al. Acute care hospital utilization among medical inpatients discharged with a substance use disorder diagnosis. J Addict Med. 2012;6(1):50-56. PubMed
4. Rosenthal ES, Karchmer AW, Thiesen-Toupal J, Castillo RA, Rowley CF. Suboptimal addiction interventions for patients hospitalized with injection drug use-associated infective endocarditis. Am J Med. 2016;129(5):481-485. PubMed
5. Fanucchi L, Lofwall MR. Putting parity into practice—integrating opioid-use disorder treatment into the hospital setting. N Engl J Med. 2016;379(9):811-813. PubMed
6. Pollini RA, O’Toole TP, Ford D, Bigelow G. Does this patient really want treatment? Factors associated with baseline and evolving readiness for change among hospitalized substance using adults interested in treatment. Addict Behav. 2006;31(10):1904-1918. PubMed
7. Liebschutz JM, Crooks D, Herman D, et al. Buprenorphine treatment for hospitalized, opioid-dependent patients: a randomized clinical trial. JAMA Intern Med. 2014;174(8):1369-1376. PubMed
8. Wei J, Defries T, Lozada M, Young N, Huen W, Tulsky J. An inpatient treatment and discharge planning protocol for alcohol and dependence: efficacy in reducing 30-day readmissions and emergency department visits. J Gen Intern Med. 2015;30(3):365-370. PubMed
9. Shanahan CW, Beers D, Alford DP, Brigandi E, Samet JH. A transitional opioid program to engage hospitalized drug users. J Gen Intern Med. 2010;25(8):803-808. PubMed
10. Pecoraro A, Horton T, Ewen E, et al. Early data from Project Engage: a program to identify and transition medically hospitalized patients into addictions treatment. Addict Sci Clin Pract. 2012;7:20. PubMed
11. National Center on Addiction and Substance Abuse; Addiction Medicine: Closing the Gap between Science and Practice. June 2012. http://www.centeronaddiction.org/addiction-research/reports/addiction-medicine-closing-gap-between-science-and-practice. Accessed May 2, 2016.
12. Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration, US Department of Health and Human Services. Results From the 2010 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration, US Dept of Health and Human Services; 2011. NSDUH series H-41, HHS publication SMA 11-4658. https://www.samhsa.gov/data/sites/default/files/NSDUHNationalFindingsResults2010-web/2k10ResultsRev/NSDUHresultsRev2010.pdf. Published September 2011. Accessed March 31, 2017.
13. Vestal C. Few doctors are willing, able to prescribe powerful anti-addiction drugs. http://www.pewtrusts.org/en/research-and-analysis/blogs/stateline/2016/01/15/few-doctors-are-willing-able-to-prescribe-powerful-anti-addiction-drugs. Published January 15, 2016. Accessed May 2, 2016.
14. McConnell KJ. Oregon’s Medicaid coordinated care organizations. JAMA. 2016;315(9):869-870. PubMed
15. Englander H, Kansagara D. Planning and designing the Care Transitions Innovation (C-TraIn) for uninsured and Medicaid patients. J Hosp Med. 2012;7(7):524-529. PubMed
16. Englander H, Michaels L, Chan B, Kansagara D. The Care Transitions Innovation (C-TraIn) for socioeconomically disadvantaged adults: results of a cluster randomized controlled trial. J Gen Intern Med. 2014;29(11):1460-1467. PubMed
17. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med. 1998;158(16):1789-1795. PubMed
18. Smith PC, Schmidt SM, Allensworth-Davies D, Saitz R. A single-question screening test for drug use in primary care. Arch Intern Med. 2010;170(13):1155-1160. PubMed
19. Humeniuk R, Ali R, Babor TF, et al. Validation of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Addiction. 2008;103(6):1039-1047. PubMed
20. Velez CM, Nicolaidis C, Korthuis PT, Englander H. “It’s been an experience, a life learning experience”: a qualitative study of hospitalized patients with substance use disorders. J Gen Intern Med. 2017;32(3):296-303. PubMed
21. Gryczynski J, Schwartz RP, O’Grady KE, Restivo L, Mitchell SG, Jaffe JH. Understanding patterns of high-cost health care use across different substance user groups. Health Aff (Millwood). 2016.;35(1):12-19. PubMed

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Urine eosinophils for acute interstitial nephritis

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The “Things We Do for No Reason” series reviews practices which have become common parts of hospital care but which may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent “black and white” conclusions or clinical practice standards, but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion. https://www.choosingwisely.org/



Acute interstitial nephritis (AIN) is an important cause of acute kidney injury (AKI) in the hospital setting. However, the diagnosis of AIN is challenging because of its nonspecific clinical manifestations and the invasiveness of kidney biopsy, the gold standard for diagnosis. Urine eosinophils (UEs) emerged several decades ago as a noninvasive alternative for diagnosing AIN. Initial studies found UEs had a significant diagnostic value, but these studies had small sample sizes, and the diagnosis of AIN was made on clinical grounds only, without biopsy confirmation. In this article, we review the literature on the diagnostic value of UEs in the diagnosis of AIN.

CASE REPORT

A 62-year-old woman with type 2 diabetes mellitus, systemic hypertension, coronary artery disease, and obesity is admitted for AKI found on routine laboratory testing. She has been taking amoxicillin and doxycycline for left leg cellulitis the past 5 days, but improvement has been minimal. On admission, blood pressure is 120/74 mm Hg, and heart rate is 89 beats per minute. Serum creatinine level is increased, from 0.7 mg/dL at baseline to 3.6 mg/dL on admission. Complete urinalysis reveals 1+ protein and presence of white blood cells and isormorphic red blood cells. No casts or crystals are seen. Given the possibility of AIN, UE testing is ordered. UEs are positive at 25%. Does this result significantly increase the patient’s posttest probability of having AIN?

WHY YOU MIGHT THINK ORDERING URINE EOSINOPHILS IN THE EVALUATION OF AIN IS HELPFUL

AKI occurs in more than 1 in 5 hospitalizations and is associated with a more than 4-fold increased likelihood of in-hospital mortality at 21 days.1 AIN is an important cause of AKI and has been found in 6% to 30% of AKI patients who had biopsies performed.2-4 AIN is characterized by infiltration of inflammatory cells in the kidney interstitium and is more commonly caused by drugs, especially beta-lactam antibiotics, and less commonly by autoimmune or systemic diseases and infections. As the signs and symptoms of AIN are nonspecific, and the gold-standard test is renal biopsy, diagnosticians have sought a noninvasive test, such as UEs.

In 1978, Galpin et al.5 found that UEs comprised 10% to 60% of urine white blood cells in 9 of 9 patients with methicillin-induced interstitial nephritis; 6 of the 9 had biopsy-proven AIN. In 1980, Linton et al.6 found UEs in 6 of 9 patients with drug-induced AIN; 8 of the 9 had biopsy-proven AIN. In 1986, Nolan et al.7 reported that, compared with Wright stain, Hansel stain was more sensitive in visualizing UEs; they did not use biopsy for confirmation. Wright-stain detection of UEs is limited by the variable staining characteristics of “eosinophilic” granules in body fluids other than blood. With Hansel stain, UEs are readily identified by their brilliant red-pink granules. These 3 small studies helped make UEs the go-to noninvasive test for assessing for AIN.8

WHY THERE IS LITTLE REASON TO ORDER URINE EOSINOPHILS IN PATIENTS WITH SUSPICION FOR AIN

While initial studies indicated UEs might be diagnostically helpful, subsequent studies did not. In 1985, Corwin et al.9 used Wright stain and found UEs in 65 of 470 adults with AKI. Only 9 (14%) of the 65 had a diagnosis of AIN, which was made mostly on clinical grounds. These findings showed that UEs were produced by other renal or urinary tract abnormalities, such as urinary tract infections, acute tubular necrosis, and glomerulonephritis. In a second study, Corwin et al.10 found that Hansel stain (vs Wright stain) improved the sensitivity of UEs for AIN diagnosis, from 25% to 62.5%. Sensitivity was improved at the expense of specificity, as Hansel stain was positive in other diagnoses as well. The AIN diagnosis was not confirmed by kidney biopsy in the large majority of patients in this study. Lack of confirmation by biopsy, the gold-standard diagnostic test, was a methodologic flaw of this study and others.

 

 

Sutton11 reviewed data from 10 studies and found AIN could not be reliably excluded in the absence of UEs (only 19 of 32 biopsy-confirmed AIN cases had UEs present). In addition, Ruffing et al.12 used Hansel stain and concluded that the positive predictive value of UEs was inadequate in diagnosing AIN. Only 6 of their 15 patients with AIN had positive UEs. Urine eosinophils were also present in patients with other diagnoses (glomerulonephritis, chronic kidney disease, acute pyelonephritis, prerenal azotemia). Like many other investigators, Ruffing et al. made the AIN diagnosis on clinical grounds in the large majority of cases.

Muriithi et al.13 reported similarly negative results in their retrospective AKI study involving 566 Mayo Clinic patients and spanning almost 2 decades. The study included patients who underwent both Hansel-stain UE testing and kidney biopsy within a week of each other. Only 28 (30%) of 91 biopsy-proven AIN cases were positive for UEs. Using the 1% cutoff for a positive UE test yielded only 30.8% sensitivity and 68.2% specificity. Using the 5% cutoff increased specificity to 91.2%, at the expense of sensitivity (19.2%); positive predictive value improved to only 30%, and negative predictive value remained relatively unchanged, at 85.6%. In short, Muriithi et al. found that UE testing had no utility in AIN diagnosis.

In summary, initial studies, such as those by Corwin et al,9,10 supported the conclusion that UEs are useful in AIN diagnosis but had questionable validity owing to methodologic issues, including small sample size and lack of biopsy confirmation of AIN. On the other hand, more recent studies, such as the one conducted by Muriithi et al.,13 had larger sample sizes and biopsy-proven diagnoses and confirmed the poor diagnostic value of UEs in AIN.

The poor sensitivity and specificity of UE tests can have important consequences. A false positive test may cause the clinician to incorrectly diagnose the patient with AIN and prompt the clinician to remove medications that may be vitally important. The clinician may also consider treating the patient with steroids empirically. A false negative test may inappropriately reassure the clinician that the patient does not have AIN and does not need cessation of the culprit drug. This may also lead the clinician to forego a necessary kidney biopsy.

WHAT YOU SHOULD DO INSTEAD

A history of recent exposure to a classic offending drug (eg, beta-lactam, proton pump inhibitor, nonsteroidal anti-inflammatory drug) in combination with the classic triad of fever, rash, and peripheral eosinophilia suggests an AIN diagnosis. However, less than 5% to 10% of patients present with this triad.14,15 Regardless of the triad’s presence, if other causes of AKI have been excluded, stopping a potential offending agent and monitoring for improvement are recommended. If a culprit drug cannot be safely discontinued, renal biopsy may be necessary for confirmation of the diagnosis. Moreover, if kidney function continues to deteriorate, a nephrology consultation may be warranted for guidance on the risks and benefits of performing a kidney biopsy to confirm the diagnosis and/or the use of corticosteroids.

RECOMMENDATIONS

  • Urine eosinophils should not be used in the diagnosis of AIN.
  • The clinical diagnosis of drug-associated AIN should be based on excluding other possible likely etiologies of AKI and confirming the history of drug exposure. This is reinforced when kidney function improves upon discontinuation of offending agent.
  • Kidney biopsy is the gold standard for AIN and should be performed if the clinical picture is unclear or the renal function is not improving upon discontinuation of offending agent.

Urine Eosinophils in the Diagnosis of Acute Interstitial Nephritis
Table

CONCLUSION

Since the mid-1980s, studies have found that UEs are too insensitive and nonspecific to confirm or exclude the diagnosis of AIN in patients with AKI (Table). UEs are seen in other AKI etiologies, such as pyelonephritis, acute tubular necrosis, atheroembolic renal disease, and glomerulonephritis. Current evidence-based medicine does not support use of UEs as a biomarker for AIN. False-positive and false-negative results confuse the overall picture and result either in discontinuation of important medications and unnecessary steroid treatment or in delayed removal of a culprit medication.16

Our case’s positive UE test does not affect the posttest probability that our patient has AIN. Presence of a culprit drug and absence of clinical data suggesting an alternative diagnosis would lead most clinicians to change antibiotic therapy and observe for improvement in renal function.

Disclosure

Nothing to report.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason?” Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and Liking It on Facebook. We invite you to propose ideas for other “Things We Do for No Reason” topics by emailing [email protected].

 

 

 

References

1. Wang HE, Muntner P, Chertow GM, Warnock DG. Acute kidney injury and mortality in hospitalized patients. Am J Nephrol. 2012;35(4):349-355.
2. Farrington K, Levison DA, Greenwood RN, Cattell WR, Baker LR. Renal biopsy in patients with unexplained renal impairment and normal kidney size. Q J Med. 1989;70(263):221-233.
3. Michel DM, Kelly CJ. Acute interstitial nephritis. J Am Soc Nephrol. 1998;9(3):506-515.
4. Neilson EG. Pathogenesis and therapy of interstitial nephritis. Kidney Int. 1989;35(5):1257-1270.
5. Galpin JE, Shinaberger JH, Stanley TM, et al. Acute interstitial nephritis due to methicillin. Am J Med. 1978;65(5):756-765.
6. Linton AL, Clark WF, Driedger AA, Turnbull DI, Lindsay RM. Acute interstitial nephritis due to drugs: review of the literature with a report of nine cases. Ann Intern Med. 1980;93(5):735-741.
7. Nolan CR 3rd, Anger MS, Kelleher SP. Eosinophiluria—a new method of detection and definition of the clinical spectrum. N Engl J Med. 1986;315(24):1516-1519.
8. Perazella MA, Bomback AS. Urinary eosinophils in AIN: farewell to an old biomarker? Clin J Am Soc Nephrol. 2013;8(11):1841-1843.
9. Corwin HL, Korbet SM, Schwartz MM. Clinical correlates of eosinophiluria. Arch Intern Med. 1985;145(6):1097-1099.
10. Corwin HL, Bray RA, Haber MH. The detection and interpretation of urinary eosinophils. Arch Pathol Lab Med. 1989;113(11):1256-1258.
11. Sutton JM. Urinary eosinophils. Arch Intern Med. 1986;146(11):2243-2244.
12. Ruffing KA, Hoppes P, Blend D, Cugino A, Jarjoura D, Whittier FC. Eosinophils in urine revisited. Clin Nephrol. 1994;41(3):163-166.
13. Muriithi AK, Nasr SH, Leung N. Utility of urine eosinophils in the diagnosis of acute interstitial nephritis. Clin J Am Soc Nephrol. 2013;8(11):1857-1862.
14. Clarkson MR, Giblin L, O’Connell FP, et al. Acute interstitial nephritis: clinical features and response to corticosteroid therapy. Nephrol Dial Transplant. 2004;19(11):2778-2783.
15. Rossert J. Drug-induced acute interstitial nephritis. Kidney Int. 2001;60(2):804-817.
16. Fletcher A. Eosinophiluria and acute interstitial nephritis. N Engl J Med. 2008;358(16):1760-1761.

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The “Things We Do for No Reason” series reviews practices which have become common parts of hospital care but which may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent “black and white” conclusions or clinical practice standards, but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion. https://www.choosingwisely.org/



Acute interstitial nephritis (AIN) is an important cause of acute kidney injury (AKI) in the hospital setting. However, the diagnosis of AIN is challenging because of its nonspecific clinical manifestations and the invasiveness of kidney biopsy, the gold standard for diagnosis. Urine eosinophils (UEs) emerged several decades ago as a noninvasive alternative for diagnosing AIN. Initial studies found UEs had a significant diagnostic value, but these studies had small sample sizes, and the diagnosis of AIN was made on clinical grounds only, without biopsy confirmation. In this article, we review the literature on the diagnostic value of UEs in the diagnosis of AIN.

CASE REPORT

A 62-year-old woman with type 2 diabetes mellitus, systemic hypertension, coronary artery disease, and obesity is admitted for AKI found on routine laboratory testing. She has been taking amoxicillin and doxycycline for left leg cellulitis the past 5 days, but improvement has been minimal. On admission, blood pressure is 120/74 mm Hg, and heart rate is 89 beats per minute. Serum creatinine level is increased, from 0.7 mg/dL at baseline to 3.6 mg/dL on admission. Complete urinalysis reveals 1+ protein and presence of white blood cells and isormorphic red blood cells. No casts or crystals are seen. Given the possibility of AIN, UE testing is ordered. UEs are positive at 25%. Does this result significantly increase the patient’s posttest probability of having AIN?

WHY YOU MIGHT THINK ORDERING URINE EOSINOPHILS IN THE EVALUATION OF AIN IS HELPFUL

AKI occurs in more than 1 in 5 hospitalizations and is associated with a more than 4-fold increased likelihood of in-hospital mortality at 21 days.1 AIN is an important cause of AKI and has been found in 6% to 30% of AKI patients who had biopsies performed.2-4 AIN is characterized by infiltration of inflammatory cells in the kidney interstitium and is more commonly caused by drugs, especially beta-lactam antibiotics, and less commonly by autoimmune or systemic diseases and infections. As the signs and symptoms of AIN are nonspecific, and the gold-standard test is renal biopsy, diagnosticians have sought a noninvasive test, such as UEs.

In 1978, Galpin et al.5 found that UEs comprised 10% to 60% of urine white blood cells in 9 of 9 patients with methicillin-induced interstitial nephritis; 6 of the 9 had biopsy-proven AIN. In 1980, Linton et al.6 found UEs in 6 of 9 patients with drug-induced AIN; 8 of the 9 had biopsy-proven AIN. In 1986, Nolan et al.7 reported that, compared with Wright stain, Hansel stain was more sensitive in visualizing UEs; they did not use biopsy for confirmation. Wright-stain detection of UEs is limited by the variable staining characteristics of “eosinophilic” granules in body fluids other than blood. With Hansel stain, UEs are readily identified by their brilliant red-pink granules. These 3 small studies helped make UEs the go-to noninvasive test for assessing for AIN.8

WHY THERE IS LITTLE REASON TO ORDER URINE EOSINOPHILS IN PATIENTS WITH SUSPICION FOR AIN

While initial studies indicated UEs might be diagnostically helpful, subsequent studies did not. In 1985, Corwin et al.9 used Wright stain and found UEs in 65 of 470 adults with AKI. Only 9 (14%) of the 65 had a diagnosis of AIN, which was made mostly on clinical grounds. These findings showed that UEs were produced by other renal or urinary tract abnormalities, such as urinary tract infections, acute tubular necrosis, and glomerulonephritis. In a second study, Corwin et al.10 found that Hansel stain (vs Wright stain) improved the sensitivity of UEs for AIN diagnosis, from 25% to 62.5%. Sensitivity was improved at the expense of specificity, as Hansel stain was positive in other diagnoses as well. The AIN diagnosis was not confirmed by kidney biopsy in the large majority of patients in this study. Lack of confirmation by biopsy, the gold-standard diagnostic test, was a methodologic flaw of this study and others.

 

 

Sutton11 reviewed data from 10 studies and found AIN could not be reliably excluded in the absence of UEs (only 19 of 32 biopsy-confirmed AIN cases had UEs present). In addition, Ruffing et al.12 used Hansel stain and concluded that the positive predictive value of UEs was inadequate in diagnosing AIN. Only 6 of their 15 patients with AIN had positive UEs. Urine eosinophils were also present in patients with other diagnoses (glomerulonephritis, chronic kidney disease, acute pyelonephritis, prerenal azotemia). Like many other investigators, Ruffing et al. made the AIN diagnosis on clinical grounds in the large majority of cases.

Muriithi et al.13 reported similarly negative results in their retrospective AKI study involving 566 Mayo Clinic patients and spanning almost 2 decades. The study included patients who underwent both Hansel-stain UE testing and kidney biopsy within a week of each other. Only 28 (30%) of 91 biopsy-proven AIN cases were positive for UEs. Using the 1% cutoff for a positive UE test yielded only 30.8% sensitivity and 68.2% specificity. Using the 5% cutoff increased specificity to 91.2%, at the expense of sensitivity (19.2%); positive predictive value improved to only 30%, and negative predictive value remained relatively unchanged, at 85.6%. In short, Muriithi et al. found that UE testing had no utility in AIN diagnosis.

In summary, initial studies, such as those by Corwin et al,9,10 supported the conclusion that UEs are useful in AIN diagnosis but had questionable validity owing to methodologic issues, including small sample size and lack of biopsy confirmation of AIN. On the other hand, more recent studies, such as the one conducted by Muriithi et al.,13 had larger sample sizes and biopsy-proven diagnoses and confirmed the poor diagnostic value of UEs in AIN.

The poor sensitivity and specificity of UE tests can have important consequences. A false positive test may cause the clinician to incorrectly diagnose the patient with AIN and prompt the clinician to remove medications that may be vitally important. The clinician may also consider treating the patient with steroids empirically. A false negative test may inappropriately reassure the clinician that the patient does not have AIN and does not need cessation of the culprit drug. This may also lead the clinician to forego a necessary kidney biopsy.

WHAT YOU SHOULD DO INSTEAD

A history of recent exposure to a classic offending drug (eg, beta-lactam, proton pump inhibitor, nonsteroidal anti-inflammatory drug) in combination with the classic triad of fever, rash, and peripheral eosinophilia suggests an AIN diagnosis. However, less than 5% to 10% of patients present with this triad.14,15 Regardless of the triad’s presence, if other causes of AKI have been excluded, stopping a potential offending agent and monitoring for improvement are recommended. If a culprit drug cannot be safely discontinued, renal biopsy may be necessary for confirmation of the diagnosis. Moreover, if kidney function continues to deteriorate, a nephrology consultation may be warranted for guidance on the risks and benefits of performing a kidney biopsy to confirm the diagnosis and/or the use of corticosteroids.

RECOMMENDATIONS

  • Urine eosinophils should not be used in the diagnosis of AIN.
  • The clinical diagnosis of drug-associated AIN should be based on excluding other possible likely etiologies of AKI and confirming the history of drug exposure. This is reinforced when kidney function improves upon discontinuation of offending agent.
  • Kidney biopsy is the gold standard for AIN and should be performed if the clinical picture is unclear or the renal function is not improving upon discontinuation of offending agent.

Urine Eosinophils in the Diagnosis of Acute Interstitial Nephritis
Table

CONCLUSION

Since the mid-1980s, studies have found that UEs are too insensitive and nonspecific to confirm or exclude the diagnosis of AIN in patients with AKI (Table). UEs are seen in other AKI etiologies, such as pyelonephritis, acute tubular necrosis, atheroembolic renal disease, and glomerulonephritis. Current evidence-based medicine does not support use of UEs as a biomarker for AIN. False-positive and false-negative results confuse the overall picture and result either in discontinuation of important medications and unnecessary steroid treatment or in delayed removal of a culprit medication.16

Our case’s positive UE test does not affect the posttest probability that our patient has AIN. Presence of a culprit drug and absence of clinical data suggesting an alternative diagnosis would lead most clinicians to change antibiotic therapy and observe for improvement in renal function.

Disclosure

Nothing to report.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason?” Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and Liking It on Facebook. We invite you to propose ideas for other “Things We Do for No Reason” topics by emailing [email protected].

 

 

 

The “Things We Do for No Reason” series reviews practices which have become common parts of hospital care but which may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent “black and white” conclusions or clinical practice standards, but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion. https://www.choosingwisely.org/



Acute interstitial nephritis (AIN) is an important cause of acute kidney injury (AKI) in the hospital setting. However, the diagnosis of AIN is challenging because of its nonspecific clinical manifestations and the invasiveness of kidney biopsy, the gold standard for diagnosis. Urine eosinophils (UEs) emerged several decades ago as a noninvasive alternative for diagnosing AIN. Initial studies found UEs had a significant diagnostic value, but these studies had small sample sizes, and the diagnosis of AIN was made on clinical grounds only, without biopsy confirmation. In this article, we review the literature on the diagnostic value of UEs in the diagnosis of AIN.

CASE REPORT

A 62-year-old woman with type 2 diabetes mellitus, systemic hypertension, coronary artery disease, and obesity is admitted for AKI found on routine laboratory testing. She has been taking amoxicillin and doxycycline for left leg cellulitis the past 5 days, but improvement has been minimal. On admission, blood pressure is 120/74 mm Hg, and heart rate is 89 beats per minute. Serum creatinine level is increased, from 0.7 mg/dL at baseline to 3.6 mg/dL on admission. Complete urinalysis reveals 1+ protein and presence of white blood cells and isormorphic red blood cells. No casts or crystals are seen. Given the possibility of AIN, UE testing is ordered. UEs are positive at 25%. Does this result significantly increase the patient’s posttest probability of having AIN?

WHY YOU MIGHT THINK ORDERING URINE EOSINOPHILS IN THE EVALUATION OF AIN IS HELPFUL

AKI occurs in more than 1 in 5 hospitalizations and is associated with a more than 4-fold increased likelihood of in-hospital mortality at 21 days.1 AIN is an important cause of AKI and has been found in 6% to 30% of AKI patients who had biopsies performed.2-4 AIN is characterized by infiltration of inflammatory cells in the kidney interstitium and is more commonly caused by drugs, especially beta-lactam antibiotics, and less commonly by autoimmune or systemic diseases and infections. As the signs and symptoms of AIN are nonspecific, and the gold-standard test is renal biopsy, diagnosticians have sought a noninvasive test, such as UEs.

In 1978, Galpin et al.5 found that UEs comprised 10% to 60% of urine white blood cells in 9 of 9 patients with methicillin-induced interstitial nephritis; 6 of the 9 had biopsy-proven AIN. In 1980, Linton et al.6 found UEs in 6 of 9 patients with drug-induced AIN; 8 of the 9 had biopsy-proven AIN. In 1986, Nolan et al.7 reported that, compared with Wright stain, Hansel stain was more sensitive in visualizing UEs; they did not use biopsy for confirmation. Wright-stain detection of UEs is limited by the variable staining characteristics of “eosinophilic” granules in body fluids other than blood. With Hansel stain, UEs are readily identified by their brilliant red-pink granules. These 3 small studies helped make UEs the go-to noninvasive test for assessing for AIN.8

WHY THERE IS LITTLE REASON TO ORDER URINE EOSINOPHILS IN PATIENTS WITH SUSPICION FOR AIN

While initial studies indicated UEs might be diagnostically helpful, subsequent studies did not. In 1985, Corwin et al.9 used Wright stain and found UEs in 65 of 470 adults with AKI. Only 9 (14%) of the 65 had a diagnosis of AIN, which was made mostly on clinical grounds. These findings showed that UEs were produced by other renal or urinary tract abnormalities, such as urinary tract infections, acute tubular necrosis, and glomerulonephritis. In a second study, Corwin et al.10 found that Hansel stain (vs Wright stain) improved the sensitivity of UEs for AIN diagnosis, from 25% to 62.5%. Sensitivity was improved at the expense of specificity, as Hansel stain was positive in other diagnoses as well. The AIN diagnosis was not confirmed by kidney biopsy in the large majority of patients in this study. Lack of confirmation by biopsy, the gold-standard diagnostic test, was a methodologic flaw of this study and others.

 

 

Sutton11 reviewed data from 10 studies and found AIN could not be reliably excluded in the absence of UEs (only 19 of 32 biopsy-confirmed AIN cases had UEs present). In addition, Ruffing et al.12 used Hansel stain and concluded that the positive predictive value of UEs was inadequate in diagnosing AIN. Only 6 of their 15 patients with AIN had positive UEs. Urine eosinophils were also present in patients with other diagnoses (glomerulonephritis, chronic kidney disease, acute pyelonephritis, prerenal azotemia). Like many other investigators, Ruffing et al. made the AIN diagnosis on clinical grounds in the large majority of cases.

Muriithi et al.13 reported similarly negative results in their retrospective AKI study involving 566 Mayo Clinic patients and spanning almost 2 decades. The study included patients who underwent both Hansel-stain UE testing and kidney biopsy within a week of each other. Only 28 (30%) of 91 biopsy-proven AIN cases were positive for UEs. Using the 1% cutoff for a positive UE test yielded only 30.8% sensitivity and 68.2% specificity. Using the 5% cutoff increased specificity to 91.2%, at the expense of sensitivity (19.2%); positive predictive value improved to only 30%, and negative predictive value remained relatively unchanged, at 85.6%. In short, Muriithi et al. found that UE testing had no utility in AIN diagnosis.

In summary, initial studies, such as those by Corwin et al,9,10 supported the conclusion that UEs are useful in AIN diagnosis but had questionable validity owing to methodologic issues, including small sample size and lack of biopsy confirmation of AIN. On the other hand, more recent studies, such as the one conducted by Muriithi et al.,13 had larger sample sizes and biopsy-proven diagnoses and confirmed the poor diagnostic value of UEs in AIN.

The poor sensitivity and specificity of UE tests can have important consequences. A false positive test may cause the clinician to incorrectly diagnose the patient with AIN and prompt the clinician to remove medications that may be vitally important. The clinician may also consider treating the patient with steroids empirically. A false negative test may inappropriately reassure the clinician that the patient does not have AIN and does not need cessation of the culprit drug. This may also lead the clinician to forego a necessary kidney biopsy.

WHAT YOU SHOULD DO INSTEAD

A history of recent exposure to a classic offending drug (eg, beta-lactam, proton pump inhibitor, nonsteroidal anti-inflammatory drug) in combination with the classic triad of fever, rash, and peripheral eosinophilia suggests an AIN diagnosis. However, less than 5% to 10% of patients present with this triad.14,15 Regardless of the triad’s presence, if other causes of AKI have been excluded, stopping a potential offending agent and monitoring for improvement are recommended. If a culprit drug cannot be safely discontinued, renal biopsy may be necessary for confirmation of the diagnosis. Moreover, if kidney function continues to deteriorate, a nephrology consultation may be warranted for guidance on the risks and benefits of performing a kidney biopsy to confirm the diagnosis and/or the use of corticosteroids.

RECOMMENDATIONS

  • Urine eosinophils should not be used in the diagnosis of AIN.
  • The clinical diagnosis of drug-associated AIN should be based on excluding other possible likely etiologies of AKI and confirming the history of drug exposure. This is reinforced when kidney function improves upon discontinuation of offending agent.
  • Kidney biopsy is the gold standard for AIN and should be performed if the clinical picture is unclear or the renal function is not improving upon discontinuation of offending agent.

Urine Eosinophils in the Diagnosis of Acute Interstitial Nephritis
Table

CONCLUSION

Since the mid-1980s, studies have found that UEs are too insensitive and nonspecific to confirm or exclude the diagnosis of AIN in patients with AKI (Table). UEs are seen in other AKI etiologies, such as pyelonephritis, acute tubular necrosis, atheroembolic renal disease, and glomerulonephritis. Current evidence-based medicine does not support use of UEs as a biomarker for AIN. False-positive and false-negative results confuse the overall picture and result either in discontinuation of important medications and unnecessary steroid treatment or in delayed removal of a culprit medication.16

Our case’s positive UE test does not affect the posttest probability that our patient has AIN. Presence of a culprit drug and absence of clinical data suggesting an alternative diagnosis would lead most clinicians to change antibiotic therapy and observe for improvement in renal function.

Disclosure

Nothing to report.

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References

1. Wang HE, Muntner P, Chertow GM, Warnock DG. Acute kidney injury and mortality in hospitalized patients. Am J Nephrol. 2012;35(4):349-355.
2. Farrington K, Levison DA, Greenwood RN, Cattell WR, Baker LR. Renal biopsy in patients with unexplained renal impairment and normal kidney size. Q J Med. 1989;70(263):221-233.
3. Michel DM, Kelly CJ. Acute interstitial nephritis. J Am Soc Nephrol. 1998;9(3):506-515.
4. Neilson EG. Pathogenesis and therapy of interstitial nephritis. Kidney Int. 1989;35(5):1257-1270.
5. Galpin JE, Shinaberger JH, Stanley TM, et al. Acute interstitial nephritis due to methicillin. Am J Med. 1978;65(5):756-765.
6. Linton AL, Clark WF, Driedger AA, Turnbull DI, Lindsay RM. Acute interstitial nephritis due to drugs: review of the literature with a report of nine cases. Ann Intern Med. 1980;93(5):735-741.
7. Nolan CR 3rd, Anger MS, Kelleher SP. Eosinophiluria—a new method of detection and definition of the clinical spectrum. N Engl J Med. 1986;315(24):1516-1519.
8. Perazella MA, Bomback AS. Urinary eosinophils in AIN: farewell to an old biomarker? Clin J Am Soc Nephrol. 2013;8(11):1841-1843.
9. Corwin HL, Korbet SM, Schwartz MM. Clinical correlates of eosinophiluria. Arch Intern Med. 1985;145(6):1097-1099.
10. Corwin HL, Bray RA, Haber MH. The detection and interpretation of urinary eosinophils. Arch Pathol Lab Med. 1989;113(11):1256-1258.
11. Sutton JM. Urinary eosinophils. Arch Intern Med. 1986;146(11):2243-2244.
12. Ruffing KA, Hoppes P, Blend D, Cugino A, Jarjoura D, Whittier FC. Eosinophils in urine revisited. Clin Nephrol. 1994;41(3):163-166.
13. Muriithi AK, Nasr SH, Leung N. Utility of urine eosinophils in the diagnosis of acute interstitial nephritis. Clin J Am Soc Nephrol. 2013;8(11):1857-1862.
14. Clarkson MR, Giblin L, O’Connell FP, et al. Acute interstitial nephritis: clinical features and response to corticosteroid therapy. Nephrol Dial Transplant. 2004;19(11):2778-2783.
15. Rossert J. Drug-induced acute interstitial nephritis. Kidney Int. 2001;60(2):804-817.
16. Fletcher A. Eosinophiluria and acute interstitial nephritis. N Engl J Med. 2008;358(16):1760-1761.

References

1. Wang HE, Muntner P, Chertow GM, Warnock DG. Acute kidney injury and mortality in hospitalized patients. Am J Nephrol. 2012;35(4):349-355.
2. Farrington K, Levison DA, Greenwood RN, Cattell WR, Baker LR. Renal biopsy in patients with unexplained renal impairment and normal kidney size. Q J Med. 1989;70(263):221-233.
3. Michel DM, Kelly CJ. Acute interstitial nephritis. J Am Soc Nephrol. 1998;9(3):506-515.
4. Neilson EG. Pathogenesis and therapy of interstitial nephritis. Kidney Int. 1989;35(5):1257-1270.
5. Galpin JE, Shinaberger JH, Stanley TM, et al. Acute interstitial nephritis due to methicillin. Am J Med. 1978;65(5):756-765.
6. Linton AL, Clark WF, Driedger AA, Turnbull DI, Lindsay RM. Acute interstitial nephritis due to drugs: review of the literature with a report of nine cases. Ann Intern Med. 1980;93(5):735-741.
7. Nolan CR 3rd, Anger MS, Kelleher SP. Eosinophiluria—a new method of detection and definition of the clinical spectrum. N Engl J Med. 1986;315(24):1516-1519.
8. Perazella MA, Bomback AS. Urinary eosinophils in AIN: farewell to an old biomarker? Clin J Am Soc Nephrol. 2013;8(11):1841-1843.
9. Corwin HL, Korbet SM, Schwartz MM. Clinical correlates of eosinophiluria. Arch Intern Med. 1985;145(6):1097-1099.
10. Corwin HL, Bray RA, Haber MH. The detection and interpretation of urinary eosinophils. Arch Pathol Lab Med. 1989;113(11):1256-1258.
11. Sutton JM. Urinary eosinophils. Arch Intern Med. 1986;146(11):2243-2244.
12. Ruffing KA, Hoppes P, Blend D, Cugino A, Jarjoura D, Whittier FC. Eosinophils in urine revisited. Clin Nephrol. 1994;41(3):163-166.
13. Muriithi AK, Nasr SH, Leung N. Utility of urine eosinophils in the diagnosis of acute interstitial nephritis. Clin J Am Soc Nephrol. 2013;8(11):1857-1862.
14. Clarkson MR, Giblin L, O’Connell FP, et al. Acute interstitial nephritis: clinical features and response to corticosteroid therapy. Nephrol Dial Transplant. 2004;19(11):2778-2783.
15. Rossert J. Drug-induced acute interstitial nephritis. Kidney Int. 2001;60(2):804-817.
16. Fletcher A. Eosinophiluria and acute interstitial nephritis. N Engl J Med. 2008;358(16):1760-1761.

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Address for correspondence and reprint requests: Helbert Rondon-Berrios, MD, Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, A915 Scaife Hall, 3550 Terrace St, Pittsburgh, PA 15213; Telephone: 412-647-3120; Fax: 412-647-6222; E-mail: [email protected]
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The approach to clinical conundrums by an expert clinician is revealed through the presentation of an actual patient’s case in an approach typical of a morning report. Similarly to patient care, sequential pieces of information are provided to the clinician, who is unfamiliar with the case. The focus is on the thought processes of both the clinical team caring for the patient and the discussant. The bolded text represents the patient’s case. Each paragraph that follows represents the discussant’s thoughts.

A 63-year-old man at an inpatient rehabilitation center was transferred to an academic tertiary care center for evaluation of slurred speech and episodic confusion. He was accompanied by his wife, who provided the history. Three weeks earlier, the patient had fallen, sustaining a right femur fracture. He underwent surgery and was discharged to rehabilitation on postoperative day 3. During the second week of rehabilitation, he developed a cough and low-grade fevers, which prompted treatment with cefpodoxime for 5 days for presumed pneumonia. The day after completing antimicrobial therapy, he became confused and began to slur his words.

Confusion is a nonspecific symptom that typically has a diffuse or multifocal localization within the cerebral hemispheres and is unlikely to be caused by a single lesion. Slurred speech may accompany global metabolic dysfunction. However, slurred speech typically localizes to the brainstem, the cerebellum in the posterior fossa, the nuclei, or the course of cranial nerves VII, X, or XII, including where these nerves pass through the subarachnoid space.

It seems this patient’s new neurologic symptoms have some relationship to his fall. Long-bone fractures and altered mental status (AMS) lead to consideration of fat emboli, but this syndrome typically presents in the acute period after the fracture. The patient is at risk for a number of complications, related to recent surgery and hospitalization, that could affect the central nervous system (CNS), including systemic infection (possibly with associated meningeal involvement) and venous thromboembolism with concomitant stroke by paradoxical emboli. The episodic nature of the confusion leads to consideration of seizures from structural lesions in the brain. Finally, the circumstances of the fall itself should be explored to determine whether an underlying neurologic dysfunction led to imbalance and gait difficulty.

Over the next 3 days at the inpatient rehabilitation center, the patient’s slurred speech became unintelligible, and he experienced intermittent disorientation to person, place, and time. There was no concomitant fever, dizziness, headache, neck pain, weakness, dyspnea, diarrhea, dysuria, or change in hearing or vision.

Progressive dysarthria argues for an expanding lesion in the posterior fossa, worsening metabolic disturbance, or a problem affecting the cranial nerves (eg, Guillain-Barré syndrome) or neuromuscular junctions (eg, myasthenia gravis). Lack of headache makes a CNS localization less likely, though disorientation must localize to the brain itself. The transient nature of the AMS could signal an ictal phenomenon or a fluctuating toxic or metabolic condition, such as hyperammonemia, drug reaction, or healthcare–acquired delirium.

His past medical history included end-stage liver disease secondary to nonalcoholic steatohepatitis status post transjugular intrahepatic portosystemic shunt (TIPS) procedure three years prior, hepatic encephalopathy, diabetes mellitus type 2, hypertension, previous melanoma excision on his back, and recurrent Clostridium difficile colitis. Two years prior to admission he had been started on an indefinite course of metronidazole 500 mg twice daily without any recurrence. The patient’s other medications were aspirin, furosemide, insulin, lactulose, mirtazapine, pantoprazole, propranolol, spironolactone, and zinc. At the rehabilitation center, he was prescribed oral oxycodone 5 mg as needed every 4 hours for pain. He denied use of tobacco, alcohol, and recreational drugs. He previously worked as a funeral home director and embalmer.

Hyperammonemia and hepatic encephalopathy can present with a fluctuating mental state that often correlates to dietary protein intake or the frequency of bowel movements; the previous TIPS history places the patient at further risk. Use of oxycodone or another narcotic commonly leads to confusion, , especially in patients who are older, have preexisting cognitive decline, or have concomitant medical comorbidities. Mirtazapine and propranolol have been associated more rarely with encephalopathy, and therefore a careful history of adherence, drug interactions, and appropriate dosing should be obtained. Metronidazole is most often associated neurologically with a peripheral neuropathy; however, it is increasingly recognized that some patients can develop a CNS syndrome that features an AMS, which can be severe and accompanied by ataxia, dysarthria, and characteristic brain magnetic resonance imaging (MRI) findings, including hyperintensity surrounding the fourth ventricle on T2-weighted images.

 

 

Embalming fluid has a high concentration of formaldehyde, and a recent epidemiologic study suggested a link between formaldehyde exposure and increased risk for amyotrophic lateral sclerosis (ALS). ALS uncommonly presents with isolated dysarthria, but its bulbar form can, usually over a much longer course than is demonstrated here. Finally, the patient’s history of melanoma places him at risk for stroke from hypercoagulability as well as potential brain metastases or carcinomatous meningitis.

Evaluation was initiated at the rehabilitation facility at the onset of the patient’s slurred speech and confusion. Physical examination were negative for focal neurologic deficits, asterixis, and jaundice. Ammonia level was 41 µmol/L (reference range, 11-35 µmol/L). Noncontrast computed tomography (CT) of the head showed no signs of acute infarct or hemorrhage. Symptoms were attributed to hepatic encephalopathy; lactulose was up-titrated to ensure 2 or 3 bowel movements per day, and rifaximin was started.

Hyperammonemia is a cause of non-inflammatory relapsing encephalopathy, but an elevated level is neither a sensitive nor specific indicator of hepatic encephalopathy. Levels of ammonia can fluctuate widely during the day based on the frequency of bowel movements as well as dietary protein intake. In addition, proper handling of samples with prompt delivery to the laboratory is essential to minimize errors.

The ammonia level of 41 µmol/L discovered here is only modestly elevated, but given the patient’s history of TIPS as well as the clinical picture, it is reasonable to aggressively treat hepatic encephalopathy with lactulose to reduce ammonia levels. If he does not improve, an MRI of the brain to exclude a structural lesion and spinal fluid examination looking for inflammatory or infectious conditions would be important next steps. Although CT excludes a large hemorrhage or mass, this screening examination does not visualize many of the findings of the metabolic etiology and the other etiologies under consideration here.

Despite 3 days of therapy for presumed hepatic encephalopathy, the patient’s slurred speech worsened, and he was transferred to an academic tertiary care center for further evaluation. On admission, his temperature was 36.9°C, heart rate was 80 beats per minute, blood pressure was 139/67 mm Hg, respiratory rate was 10 breaths per minute, and oxygen saturation was 99% on room air. He was alert, awake, and oriented to person, place, and time. He was not jaundiced. He exhibited a moderate dysarthria characterized by monotone speech, decreased volume, decreased breath support, and a hoarse vocal quality with intact language function. Motor control of the lips, tongue, and mandible were normal. Motor strength was 5/5 bilaterally in the upper and lower extremities with the exception of right hip flexion, which was 4/5. The patient exhibited mild bilateral dysmetria on finger-to-nose examination, consistent with appendicular ataxia of the upper extremities. Reflexes were depressed throughout, and there was no asterixis. He had 2+ pulses in all extremities and 1+ pitting edema of the right lower extremity to the mid leg. Pulmonary examination revealed inspiratory crackles at the left base. The rest of the examination findings were normal.


The patient’s altered mental state appears to have resolved, and the neurological examination is now mainly characterized by signs that point to the cerebellum. The description of monotone speech typically refers to loss of prosody, the variable stress or intonation of speech, which is characteristic of a cerebellar speech pattern. The hoarseness should be explored to determine if it is a feature of the patient’s speech or is a separate process. Hoarseness may involve the vocal cord and therefore, potentially, cranial nerve X or its nuclei in the brainstem. The appendicular ataxia of the limbs points definitively to the cerebellar hemispheres or their pathways through the brainstem.

Unilateral lower extremity edema, especially in the context of a recent fracture, raises the possibility of deep vein thrombosis. If this patient has a right-to-left intracardiac or intrapulmonary shunt, embolization could lead to an ischemic stroke of the brainstem or cerebellum, potentially causing dysarthria.

Laboratory evaluation revealed hemoglobin level of 10.9 g/dL, white blood cell count of 5.3 × 10 9 /L, platelet count of 169 × 10 9 /L, glucose level of 177 mg/dL, corrected calcium level of 9.0 mg/dL, sodium level of 135 mmol/L, bicarbonate level of 30 mmol/L, creatinine level of 0.9 mg/dL, total bilirubin level of 1.3 mg/dL, direct bilirubin level of 0.4 mg/dL, alkaline phosphatase level of 503 U/L, alanine aminotransferase level of 12 U/L, aspartate aminotransferase level of 33 U/L, ammonia level of 49 µmol/L (range, 0-30 µ mol/L), international normalized ratio of 1.2, and troponin level of <0.01 ng/mL. Electrocardiogram showed normal sinus rhythm.

 

 

Some patients with bacterial meningitis do not have a leukocytosis, but patients with meningitis caused by seeding from a systemic infection nearly always do. In this patient’s case, lack of a leukocytosis makes bacterial meningitis very unlikely. The elevated alkaline phosphatase level is expected, as this level peaks about 3 weeks after a long-bone fracture and returns to normal over a few months.

Non-contrast CT scan of the head performed on admission demonstrated no large vessel cortical-based infarct, intracranial hemorrhage, hydrocephalus, mass effect, midline shift, or extra-axial fluid. There was mild cortical atrophy as well as very mild periventricular white matter hypodensity.

The atrophy and mild white-matter hypodensities seen on repeat noncontrast CT are nonspecific for any particular entity in this patient’s age group. MRI is more effective in evaluating toxic encephalopathies, including metronidazole toxicity or Wernicke encephalopathy, and in characterizing small infarcts or inflammatory conditions of the brainstem and cerebellum, which are poorly evaluated by CT due to the bone surrounded space of the posterior fossa. An urgent lumbar puncture is not necessary due to the slow pace of illness, lack of fever, nuchal rigidity, or serum elevated white blood cell count. Rather, performing MRI should be prioritized. If MRI is nondiagnostic, then spinal fluid should be evaluated for evidence of an infectious, autoimmune, paraneoplastic, or neoplastic process.

MRI was subsequently performed. It showed symmetric abnormal T2 hyperintensities involving dentate nuclei (Figure 1), left inferior olivary nuclei (Figure 2), restiform bodies, pontine tegmentum, superior cerebellar peduncles, oculomotor nuclei, and subthalamic nuclei. The most prominent hyperintensity was in the dentate nuclei.

Magnetic resonance imaging shows T2 hyperintensity of dentate nuclei bilaterally.
Figure 1
Magnetic resonance imaging shows T2 hyperintensity of left inferior olivary nuclei.
Figure 2

The clinical and radiographic features confirm a diagnosis of metronidazole-associated CNS neurotoxicity. The reason for the predilection for edema in these specific areas of the brainstem and midline cerebellum is unclear but likely is related to selective neuronal vulnerability in these structures. The treatment is to stop metronidazole. In addition, the fluctuating mental status should be evaluated with electroencephalogram to ensure concomitant seizures are not occurring.

These MRI findings were consistent with metronidazole toxicity. Metronidazole was discontinued, and 2 days later the patient’s speech improved. Two weeks after medication discontinuation, his speech was normal. There were no more episodes of confusion.

DISCUSSION

Metronidazole was originally developed in France during the 1950s as an anti-parasitic medication to treat trichomonas infections. In 1962, its antibacterial properties were discovered after a patient with bacterial gingivitis improved while taking metronidazole for treatment of Trichomonas vaginalis.1 Since that time metronidazole has become a first-line treatment for anaerobic bacteria and is now recommended by the Infectious Diseases Society of America2 and the American College of Gastroenterology3 as a first-line therapy for mild and moderate C difficile infections.

Common side effects of metronidazole are nausea, vomiting, decreased appetite, diarrhea, headaches, peripheral neuropathy, and metallic taste; less common is CNS toxicity. Although the incidence of CNS toxicity is unknown, a systematic review of the literature found 64 cases reported between 1965 and 2011.4 CNS toxicity most often occurs between the fifth and sixth decades of life, and about two thirds of the people affected are men.4 CNS adverse effects characteristically fall into 4 categories: cerebellar dysfunction (eg, ataxia, dysarthria, dysmetria, nystagmus; 75%), AMS (33%), seizures (13%), and a combination of the first 3 categories.4

The exact mechanism of metronidazole CNS toxicity is unknown, but vasogenic or cytotoxic edema may be involved.5,6 Other potential etiologies are neural protein inhibition, reversible mitochondrial dysfunction, and modifications of the inhibitory neurotransmitter gamma-aminobutyric acid receptor in the cerebellum.7,8 There is no known genetic predisposition. Although the risk for CNS toxicity traditionally is thought to correlate with therapy duration and cumulative dose,7,9 in 2011 a systemic review found no significant correlation.4 In fact, 26% of patients with CNS toxicity were treated with metronidazole for less than 1 week at time of diagnosis.4

Brain CT is typically normal. On brain MRI, lesions most commonly appear as bilateral symmetric T2 hyperintensities, most often in the cerebellar dentate nuclei (85%) and less often in the midbrain (55%), the splenium of the corpus callosum (50%), the pons (35%), and the medulla (30%).4,10 Radiographic changes have been noted as early as 3 days after symptom onset. Based on damage severity and area affected (white or gray matter), vasogenic edema and cytotoxic edema may in combination be contributing to MRI abnormalities.6,10 Hyperintensities of the bilateral dentate nuclei can help in distinguishing metronidazole-induced encephalopathy from other potential disease processes, such as Wernicke encephalopathy.10

The prognosis for patients with metronidazole-induced neurotoxicity is favorable if metronidazole is discontinued. Approximately two-thirds of patients will have complete resolution of symptoms, which is more commonly observed when patients present with seizures or altered mental status. Approximately one-third will show partial improvement, particularly if the symptoms are due to cerebellar dysfunction. It is rare to experience permanent damage or death.4 Neurologic recovery usually begins within a week after medication discontinuation but may take months for complete recovery to occur.6,8,9,11 Follow-up imaging typically shows reversal of the original lesions, but this does not always correlate with symptom improvement.4,10

Despite its frequent use and long history, metronidazole can have potentially severe toxicity. When patients who are taking this medication present with new signs and symptoms of CNS dysfunction, hospitalists should include metronidazole CNS toxicity in the differential diagnosis and, if they suspect toxicity, have a brain MRI performed. Hospitalists often prescribe metronidazole because of the increasing number of patients being discharged from acute-care hospitals with a diagnosis of C difficile colitis.12 Brain MRI remains the imaging modality of choice for diagnosis. Discontinuation of metronidazole is usually salutary in reversing symptoms. Being keenly aware of this toxicity will help clinicians avoid being rendered speechless by a patient rendered speechless.

 

 

TEACHING POINTS

  • CNS toxicity is a rare but potentially devastating side effect of metronidazole exposure.

  • Metronidazole CNS adverse effects characteristically fall under 4 categories:

○ Cerebellar dysfunction, such as ataxia, dysarthria, dysmetria, or nystagmus (75%).

○ AMS (33%).

○ Seizures (13%).

○ A combination of the first 3 categories.

  • Typically lesions indicating metronidazole toxicity on brain MRI are bilateral symmetric hyperintensities on T2-weighted imaging in the cerebellar dentate nuclei, corpus callosum, midbrain, pons, or medulla.
  • Treatment of CNS toxicity is metronidazole discontinuation, which results in a high rate of symptom resolution.

Disclosure

Nothing to report.

 

References

1. Samuelson J. Why metronidazole is active against both bacteria and parasites. Antimicrob Agents Chemother. 1999;43(7):1533-1541. PubMed
2. Cohen SH, Gerding DN, Johnson S, et al; Society for Healthcare Epidemiology of America; Infectious Diseases Society of America. Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by the Society for Healthcare Epidemiology of America (SHEA) and the Infectious Diseases Society of America (IDSA). Infect Control Hosp Epidemiol. 2010;31(5):431-455. PubMed
3. Surawicz CM, Brandt LJ, Binion DG, et al. Guidelines for diagnosis, treatment, and prevention of Clostridium difficile infections. Am J Gastroenterol. 2013;108(4):478-498. PubMed
4. Kuriyama A, Jackson JL, Doi A, Kamiya T. Metronidazole-induced central nervous system toxicity: a systemic review. Clin Neuropharmacol. 2011;34(6):241-247. PubMed
5. Graves TD, Condon M, Loucaidou M, Perry RJ. Reversible metronidazole-induced cerebellar toxicity in a multiple transplant recipient. J Neurol Sci. 2009;285(1-2):238-240. PubMed
6. Kim DW, Park JM, Yoon BW, Baek MJ, Kim JE, Kim S. Metronidazole-induced encephalopathy. J Neurol Sci. 2004;224(1-2):107-111. PubMed
7. Park KI, Chung JM, Kim JY. Metronidazole neurotoxicity: sequential neuroaxis involvement. Neurol India. 2011;59(1):104-107. PubMed
8. Patel K, Green-Hopkins I, Lu S, Tunkel AR. Cerebellar ataxia following prolonged use of metronidazole: case report and literature review. Int J Infect Dis. 2008;12(6):e111-e114. PubMed
9. Chandak S, Agarwal A, Shukla A, Joon P. A case report of metronidazole induced neurotoxicity in liver abscess patient and the usefulness of MRI for its diagnosis. J Clin Diagn Res. 2016;10(1):TD06-TD07. PubMed
10. Kim E, Na DG, Kim EY, Kim JH, Son KR, Chang KH. MR imaging of metronidazole-induced encephalopathy: lesion distribution and diffusion-weighted imaging findings. AJNR Am J Neuroradiol. 2007;28(9):1652-1658. PubMed
11. Chacko J, Pramod K, Sinha S, et al. Clinical, neuroimaging and pathological features of 5-nitroimidazole-induced encephalo-neuropathy in two patients: insights into possible pathogenesis. Neurol India. 2011;59(5):743-747. PubMed
12. Peery AF, Dellon ES, Lund J, et al. Burden of gastrointestinal disease in the United States: 2012 update. Gastroenterology. 2012;143(5):1179-1187.e1-e3. PubMed

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Journal of Hospital Medicine 12(5)
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The approach to clinical conundrums by an expert clinician is revealed through the presentation of an actual patient’s case in an approach typical of a morning report. Similarly to patient care, sequential pieces of information are provided to the clinician, who is unfamiliar with the case. The focus is on the thought processes of both the clinical team caring for the patient and the discussant. The bolded text represents the patient’s case. Each paragraph that follows represents the discussant’s thoughts.

A 63-year-old man at an inpatient rehabilitation center was transferred to an academic tertiary care center for evaluation of slurred speech and episodic confusion. He was accompanied by his wife, who provided the history. Three weeks earlier, the patient had fallen, sustaining a right femur fracture. He underwent surgery and was discharged to rehabilitation on postoperative day 3. During the second week of rehabilitation, he developed a cough and low-grade fevers, which prompted treatment with cefpodoxime for 5 days for presumed pneumonia. The day after completing antimicrobial therapy, he became confused and began to slur his words.

Confusion is a nonspecific symptom that typically has a diffuse or multifocal localization within the cerebral hemispheres and is unlikely to be caused by a single lesion. Slurred speech may accompany global metabolic dysfunction. However, slurred speech typically localizes to the brainstem, the cerebellum in the posterior fossa, the nuclei, or the course of cranial nerves VII, X, or XII, including where these nerves pass through the subarachnoid space.

It seems this patient’s new neurologic symptoms have some relationship to his fall. Long-bone fractures and altered mental status (AMS) lead to consideration of fat emboli, but this syndrome typically presents in the acute period after the fracture. The patient is at risk for a number of complications, related to recent surgery and hospitalization, that could affect the central nervous system (CNS), including systemic infection (possibly with associated meningeal involvement) and venous thromboembolism with concomitant stroke by paradoxical emboli. The episodic nature of the confusion leads to consideration of seizures from structural lesions in the brain. Finally, the circumstances of the fall itself should be explored to determine whether an underlying neurologic dysfunction led to imbalance and gait difficulty.

Over the next 3 days at the inpatient rehabilitation center, the patient’s slurred speech became unintelligible, and he experienced intermittent disorientation to person, place, and time. There was no concomitant fever, dizziness, headache, neck pain, weakness, dyspnea, diarrhea, dysuria, or change in hearing or vision.

Progressive dysarthria argues for an expanding lesion in the posterior fossa, worsening metabolic disturbance, or a problem affecting the cranial nerves (eg, Guillain-Barré syndrome) or neuromuscular junctions (eg, myasthenia gravis). Lack of headache makes a CNS localization less likely, though disorientation must localize to the brain itself. The transient nature of the AMS could signal an ictal phenomenon or a fluctuating toxic or metabolic condition, such as hyperammonemia, drug reaction, or healthcare–acquired delirium.

His past medical history included end-stage liver disease secondary to nonalcoholic steatohepatitis status post transjugular intrahepatic portosystemic shunt (TIPS) procedure three years prior, hepatic encephalopathy, diabetes mellitus type 2, hypertension, previous melanoma excision on his back, and recurrent Clostridium difficile colitis. Two years prior to admission he had been started on an indefinite course of metronidazole 500 mg twice daily without any recurrence. The patient’s other medications were aspirin, furosemide, insulin, lactulose, mirtazapine, pantoprazole, propranolol, spironolactone, and zinc. At the rehabilitation center, he was prescribed oral oxycodone 5 mg as needed every 4 hours for pain. He denied use of tobacco, alcohol, and recreational drugs. He previously worked as a funeral home director and embalmer.

Hyperammonemia and hepatic encephalopathy can present with a fluctuating mental state that often correlates to dietary protein intake or the frequency of bowel movements; the previous TIPS history places the patient at further risk. Use of oxycodone or another narcotic commonly leads to confusion, , especially in patients who are older, have preexisting cognitive decline, or have concomitant medical comorbidities. Mirtazapine and propranolol have been associated more rarely with encephalopathy, and therefore a careful history of adherence, drug interactions, and appropriate dosing should be obtained. Metronidazole is most often associated neurologically with a peripheral neuropathy; however, it is increasingly recognized that some patients can develop a CNS syndrome that features an AMS, which can be severe and accompanied by ataxia, dysarthria, and characteristic brain magnetic resonance imaging (MRI) findings, including hyperintensity surrounding the fourth ventricle on T2-weighted images.

 

 

Embalming fluid has a high concentration of formaldehyde, and a recent epidemiologic study suggested a link between formaldehyde exposure and increased risk for amyotrophic lateral sclerosis (ALS). ALS uncommonly presents with isolated dysarthria, but its bulbar form can, usually over a much longer course than is demonstrated here. Finally, the patient’s history of melanoma places him at risk for stroke from hypercoagulability as well as potential brain metastases or carcinomatous meningitis.

Evaluation was initiated at the rehabilitation facility at the onset of the patient’s slurred speech and confusion. Physical examination were negative for focal neurologic deficits, asterixis, and jaundice. Ammonia level was 41 µmol/L (reference range, 11-35 µmol/L). Noncontrast computed tomography (CT) of the head showed no signs of acute infarct or hemorrhage. Symptoms were attributed to hepatic encephalopathy; lactulose was up-titrated to ensure 2 or 3 bowel movements per day, and rifaximin was started.

Hyperammonemia is a cause of non-inflammatory relapsing encephalopathy, but an elevated level is neither a sensitive nor specific indicator of hepatic encephalopathy. Levels of ammonia can fluctuate widely during the day based on the frequency of bowel movements as well as dietary protein intake. In addition, proper handling of samples with prompt delivery to the laboratory is essential to minimize errors.

The ammonia level of 41 µmol/L discovered here is only modestly elevated, but given the patient’s history of TIPS as well as the clinical picture, it is reasonable to aggressively treat hepatic encephalopathy with lactulose to reduce ammonia levels. If he does not improve, an MRI of the brain to exclude a structural lesion and spinal fluid examination looking for inflammatory or infectious conditions would be important next steps. Although CT excludes a large hemorrhage or mass, this screening examination does not visualize many of the findings of the metabolic etiology and the other etiologies under consideration here.

Despite 3 days of therapy for presumed hepatic encephalopathy, the patient’s slurred speech worsened, and he was transferred to an academic tertiary care center for further evaluation. On admission, his temperature was 36.9°C, heart rate was 80 beats per minute, blood pressure was 139/67 mm Hg, respiratory rate was 10 breaths per minute, and oxygen saturation was 99% on room air. He was alert, awake, and oriented to person, place, and time. He was not jaundiced. He exhibited a moderate dysarthria characterized by monotone speech, decreased volume, decreased breath support, and a hoarse vocal quality with intact language function. Motor control of the lips, tongue, and mandible were normal. Motor strength was 5/5 bilaterally in the upper and lower extremities with the exception of right hip flexion, which was 4/5. The patient exhibited mild bilateral dysmetria on finger-to-nose examination, consistent with appendicular ataxia of the upper extremities. Reflexes were depressed throughout, and there was no asterixis. He had 2+ pulses in all extremities and 1+ pitting edema of the right lower extremity to the mid leg. Pulmonary examination revealed inspiratory crackles at the left base. The rest of the examination findings were normal.


The patient’s altered mental state appears to have resolved, and the neurological examination is now mainly characterized by signs that point to the cerebellum. The description of monotone speech typically refers to loss of prosody, the variable stress or intonation of speech, which is characteristic of a cerebellar speech pattern. The hoarseness should be explored to determine if it is a feature of the patient’s speech or is a separate process. Hoarseness may involve the vocal cord and therefore, potentially, cranial nerve X or its nuclei in the brainstem. The appendicular ataxia of the limbs points definitively to the cerebellar hemispheres or their pathways through the brainstem.

Unilateral lower extremity edema, especially in the context of a recent fracture, raises the possibility of deep vein thrombosis. If this patient has a right-to-left intracardiac or intrapulmonary shunt, embolization could lead to an ischemic stroke of the brainstem or cerebellum, potentially causing dysarthria.

Laboratory evaluation revealed hemoglobin level of 10.9 g/dL, white blood cell count of 5.3 × 10 9 /L, platelet count of 169 × 10 9 /L, glucose level of 177 mg/dL, corrected calcium level of 9.0 mg/dL, sodium level of 135 mmol/L, bicarbonate level of 30 mmol/L, creatinine level of 0.9 mg/dL, total bilirubin level of 1.3 mg/dL, direct bilirubin level of 0.4 mg/dL, alkaline phosphatase level of 503 U/L, alanine aminotransferase level of 12 U/L, aspartate aminotransferase level of 33 U/L, ammonia level of 49 µmol/L (range, 0-30 µ mol/L), international normalized ratio of 1.2, and troponin level of <0.01 ng/mL. Electrocardiogram showed normal sinus rhythm.

 

 

Some patients with bacterial meningitis do not have a leukocytosis, but patients with meningitis caused by seeding from a systemic infection nearly always do. In this patient’s case, lack of a leukocytosis makes bacterial meningitis very unlikely. The elevated alkaline phosphatase level is expected, as this level peaks about 3 weeks after a long-bone fracture and returns to normal over a few months.

Non-contrast CT scan of the head performed on admission demonstrated no large vessel cortical-based infarct, intracranial hemorrhage, hydrocephalus, mass effect, midline shift, or extra-axial fluid. There was mild cortical atrophy as well as very mild periventricular white matter hypodensity.

The atrophy and mild white-matter hypodensities seen on repeat noncontrast CT are nonspecific for any particular entity in this patient’s age group. MRI is more effective in evaluating toxic encephalopathies, including metronidazole toxicity or Wernicke encephalopathy, and in characterizing small infarcts or inflammatory conditions of the brainstem and cerebellum, which are poorly evaluated by CT due to the bone surrounded space of the posterior fossa. An urgent lumbar puncture is not necessary due to the slow pace of illness, lack of fever, nuchal rigidity, or serum elevated white blood cell count. Rather, performing MRI should be prioritized. If MRI is nondiagnostic, then spinal fluid should be evaluated for evidence of an infectious, autoimmune, paraneoplastic, or neoplastic process.

MRI was subsequently performed. It showed symmetric abnormal T2 hyperintensities involving dentate nuclei (Figure 1), left inferior olivary nuclei (Figure 2), restiform bodies, pontine tegmentum, superior cerebellar peduncles, oculomotor nuclei, and subthalamic nuclei. The most prominent hyperintensity was in the dentate nuclei.

Magnetic resonance imaging shows T2 hyperintensity of dentate nuclei bilaterally.
Figure 1
Magnetic resonance imaging shows T2 hyperintensity of left inferior olivary nuclei.
Figure 2

The clinical and radiographic features confirm a diagnosis of metronidazole-associated CNS neurotoxicity. The reason for the predilection for edema in these specific areas of the brainstem and midline cerebellum is unclear but likely is related to selective neuronal vulnerability in these structures. The treatment is to stop metronidazole. In addition, the fluctuating mental status should be evaluated with electroencephalogram to ensure concomitant seizures are not occurring.

These MRI findings were consistent with metronidazole toxicity. Metronidazole was discontinued, and 2 days later the patient’s speech improved. Two weeks after medication discontinuation, his speech was normal. There were no more episodes of confusion.

DISCUSSION

Metronidazole was originally developed in France during the 1950s as an anti-parasitic medication to treat trichomonas infections. In 1962, its antibacterial properties were discovered after a patient with bacterial gingivitis improved while taking metronidazole for treatment of Trichomonas vaginalis.1 Since that time metronidazole has become a first-line treatment for anaerobic bacteria and is now recommended by the Infectious Diseases Society of America2 and the American College of Gastroenterology3 as a first-line therapy for mild and moderate C difficile infections.

Common side effects of metronidazole are nausea, vomiting, decreased appetite, diarrhea, headaches, peripheral neuropathy, and metallic taste; less common is CNS toxicity. Although the incidence of CNS toxicity is unknown, a systematic review of the literature found 64 cases reported between 1965 and 2011.4 CNS toxicity most often occurs between the fifth and sixth decades of life, and about two thirds of the people affected are men.4 CNS adverse effects characteristically fall into 4 categories: cerebellar dysfunction (eg, ataxia, dysarthria, dysmetria, nystagmus; 75%), AMS (33%), seizures (13%), and a combination of the first 3 categories.4

The exact mechanism of metronidazole CNS toxicity is unknown, but vasogenic or cytotoxic edema may be involved.5,6 Other potential etiologies are neural protein inhibition, reversible mitochondrial dysfunction, and modifications of the inhibitory neurotransmitter gamma-aminobutyric acid receptor in the cerebellum.7,8 There is no known genetic predisposition. Although the risk for CNS toxicity traditionally is thought to correlate with therapy duration and cumulative dose,7,9 in 2011 a systemic review found no significant correlation.4 In fact, 26% of patients with CNS toxicity were treated with metronidazole for less than 1 week at time of diagnosis.4

Brain CT is typically normal. On brain MRI, lesions most commonly appear as bilateral symmetric T2 hyperintensities, most often in the cerebellar dentate nuclei (85%) and less often in the midbrain (55%), the splenium of the corpus callosum (50%), the pons (35%), and the medulla (30%).4,10 Radiographic changes have been noted as early as 3 days after symptom onset. Based on damage severity and area affected (white or gray matter), vasogenic edema and cytotoxic edema may in combination be contributing to MRI abnormalities.6,10 Hyperintensities of the bilateral dentate nuclei can help in distinguishing metronidazole-induced encephalopathy from other potential disease processes, such as Wernicke encephalopathy.10

The prognosis for patients with metronidazole-induced neurotoxicity is favorable if metronidazole is discontinued. Approximately two-thirds of patients will have complete resolution of symptoms, which is more commonly observed when patients present with seizures or altered mental status. Approximately one-third will show partial improvement, particularly if the symptoms are due to cerebellar dysfunction. It is rare to experience permanent damage or death.4 Neurologic recovery usually begins within a week after medication discontinuation but may take months for complete recovery to occur.6,8,9,11 Follow-up imaging typically shows reversal of the original lesions, but this does not always correlate with symptom improvement.4,10

Despite its frequent use and long history, metronidazole can have potentially severe toxicity. When patients who are taking this medication present with new signs and symptoms of CNS dysfunction, hospitalists should include metronidazole CNS toxicity in the differential diagnosis and, if they suspect toxicity, have a brain MRI performed. Hospitalists often prescribe metronidazole because of the increasing number of patients being discharged from acute-care hospitals with a diagnosis of C difficile colitis.12 Brain MRI remains the imaging modality of choice for diagnosis. Discontinuation of metronidazole is usually salutary in reversing symptoms. Being keenly aware of this toxicity will help clinicians avoid being rendered speechless by a patient rendered speechless.

 

 

TEACHING POINTS

  • CNS toxicity is a rare but potentially devastating side effect of metronidazole exposure.

  • Metronidazole CNS adverse effects characteristically fall under 4 categories:

○ Cerebellar dysfunction, such as ataxia, dysarthria, dysmetria, or nystagmus (75%).

○ AMS (33%).

○ Seizures (13%).

○ A combination of the first 3 categories.

  • Typically lesions indicating metronidazole toxicity on brain MRI are bilateral symmetric hyperintensities on T2-weighted imaging in the cerebellar dentate nuclei, corpus callosum, midbrain, pons, or medulla.
  • Treatment of CNS toxicity is metronidazole discontinuation, which results in a high rate of symptom resolution.

Disclosure

Nothing to report.

 

The approach to clinical conundrums by an expert clinician is revealed through the presentation of an actual patient’s case in an approach typical of a morning report. Similarly to patient care, sequential pieces of information are provided to the clinician, who is unfamiliar with the case. The focus is on the thought processes of both the clinical team caring for the patient and the discussant. The bolded text represents the patient’s case. Each paragraph that follows represents the discussant’s thoughts.

A 63-year-old man at an inpatient rehabilitation center was transferred to an academic tertiary care center for evaluation of slurred speech and episodic confusion. He was accompanied by his wife, who provided the history. Three weeks earlier, the patient had fallen, sustaining a right femur fracture. He underwent surgery and was discharged to rehabilitation on postoperative day 3. During the second week of rehabilitation, he developed a cough and low-grade fevers, which prompted treatment with cefpodoxime for 5 days for presumed pneumonia. The day after completing antimicrobial therapy, he became confused and began to slur his words.

Confusion is a nonspecific symptom that typically has a diffuse or multifocal localization within the cerebral hemispheres and is unlikely to be caused by a single lesion. Slurred speech may accompany global metabolic dysfunction. However, slurred speech typically localizes to the brainstem, the cerebellum in the posterior fossa, the nuclei, or the course of cranial nerves VII, X, or XII, including where these nerves pass through the subarachnoid space.

It seems this patient’s new neurologic symptoms have some relationship to his fall. Long-bone fractures and altered mental status (AMS) lead to consideration of fat emboli, but this syndrome typically presents in the acute period after the fracture. The patient is at risk for a number of complications, related to recent surgery and hospitalization, that could affect the central nervous system (CNS), including systemic infection (possibly with associated meningeal involvement) and venous thromboembolism with concomitant stroke by paradoxical emboli. The episodic nature of the confusion leads to consideration of seizures from structural lesions in the brain. Finally, the circumstances of the fall itself should be explored to determine whether an underlying neurologic dysfunction led to imbalance and gait difficulty.

Over the next 3 days at the inpatient rehabilitation center, the patient’s slurred speech became unintelligible, and he experienced intermittent disorientation to person, place, and time. There was no concomitant fever, dizziness, headache, neck pain, weakness, dyspnea, diarrhea, dysuria, or change in hearing or vision.

Progressive dysarthria argues for an expanding lesion in the posterior fossa, worsening metabolic disturbance, or a problem affecting the cranial nerves (eg, Guillain-Barré syndrome) or neuromuscular junctions (eg, myasthenia gravis). Lack of headache makes a CNS localization less likely, though disorientation must localize to the brain itself. The transient nature of the AMS could signal an ictal phenomenon or a fluctuating toxic or metabolic condition, such as hyperammonemia, drug reaction, or healthcare–acquired delirium.

His past medical history included end-stage liver disease secondary to nonalcoholic steatohepatitis status post transjugular intrahepatic portosystemic shunt (TIPS) procedure three years prior, hepatic encephalopathy, diabetes mellitus type 2, hypertension, previous melanoma excision on his back, and recurrent Clostridium difficile colitis. Two years prior to admission he had been started on an indefinite course of metronidazole 500 mg twice daily without any recurrence. The patient’s other medications were aspirin, furosemide, insulin, lactulose, mirtazapine, pantoprazole, propranolol, spironolactone, and zinc. At the rehabilitation center, he was prescribed oral oxycodone 5 mg as needed every 4 hours for pain. He denied use of tobacco, alcohol, and recreational drugs. He previously worked as a funeral home director and embalmer.

Hyperammonemia and hepatic encephalopathy can present with a fluctuating mental state that often correlates to dietary protein intake or the frequency of bowel movements; the previous TIPS history places the patient at further risk. Use of oxycodone or another narcotic commonly leads to confusion, , especially in patients who are older, have preexisting cognitive decline, or have concomitant medical comorbidities. Mirtazapine and propranolol have been associated more rarely with encephalopathy, and therefore a careful history of adherence, drug interactions, and appropriate dosing should be obtained. Metronidazole is most often associated neurologically with a peripheral neuropathy; however, it is increasingly recognized that some patients can develop a CNS syndrome that features an AMS, which can be severe and accompanied by ataxia, dysarthria, and characteristic brain magnetic resonance imaging (MRI) findings, including hyperintensity surrounding the fourth ventricle on T2-weighted images.

 

 

Embalming fluid has a high concentration of formaldehyde, and a recent epidemiologic study suggested a link between formaldehyde exposure and increased risk for amyotrophic lateral sclerosis (ALS). ALS uncommonly presents with isolated dysarthria, but its bulbar form can, usually over a much longer course than is demonstrated here. Finally, the patient’s history of melanoma places him at risk for stroke from hypercoagulability as well as potential brain metastases or carcinomatous meningitis.

Evaluation was initiated at the rehabilitation facility at the onset of the patient’s slurred speech and confusion. Physical examination were negative for focal neurologic deficits, asterixis, and jaundice. Ammonia level was 41 µmol/L (reference range, 11-35 µmol/L). Noncontrast computed tomography (CT) of the head showed no signs of acute infarct or hemorrhage. Symptoms were attributed to hepatic encephalopathy; lactulose was up-titrated to ensure 2 or 3 bowel movements per day, and rifaximin was started.

Hyperammonemia is a cause of non-inflammatory relapsing encephalopathy, but an elevated level is neither a sensitive nor specific indicator of hepatic encephalopathy. Levels of ammonia can fluctuate widely during the day based on the frequency of bowel movements as well as dietary protein intake. In addition, proper handling of samples with prompt delivery to the laboratory is essential to minimize errors.

The ammonia level of 41 µmol/L discovered here is only modestly elevated, but given the patient’s history of TIPS as well as the clinical picture, it is reasonable to aggressively treat hepatic encephalopathy with lactulose to reduce ammonia levels. If he does not improve, an MRI of the brain to exclude a structural lesion and spinal fluid examination looking for inflammatory or infectious conditions would be important next steps. Although CT excludes a large hemorrhage or mass, this screening examination does not visualize many of the findings of the metabolic etiology and the other etiologies under consideration here.

Despite 3 days of therapy for presumed hepatic encephalopathy, the patient’s slurred speech worsened, and he was transferred to an academic tertiary care center for further evaluation. On admission, his temperature was 36.9°C, heart rate was 80 beats per minute, blood pressure was 139/67 mm Hg, respiratory rate was 10 breaths per minute, and oxygen saturation was 99% on room air. He was alert, awake, and oriented to person, place, and time. He was not jaundiced. He exhibited a moderate dysarthria characterized by monotone speech, decreased volume, decreased breath support, and a hoarse vocal quality with intact language function. Motor control of the lips, tongue, and mandible were normal. Motor strength was 5/5 bilaterally in the upper and lower extremities with the exception of right hip flexion, which was 4/5. The patient exhibited mild bilateral dysmetria on finger-to-nose examination, consistent with appendicular ataxia of the upper extremities. Reflexes were depressed throughout, and there was no asterixis. He had 2+ pulses in all extremities and 1+ pitting edema of the right lower extremity to the mid leg. Pulmonary examination revealed inspiratory crackles at the left base. The rest of the examination findings were normal.


The patient’s altered mental state appears to have resolved, and the neurological examination is now mainly characterized by signs that point to the cerebellum. The description of monotone speech typically refers to loss of prosody, the variable stress or intonation of speech, which is characteristic of a cerebellar speech pattern. The hoarseness should be explored to determine if it is a feature of the patient’s speech or is a separate process. Hoarseness may involve the vocal cord and therefore, potentially, cranial nerve X or its nuclei in the brainstem. The appendicular ataxia of the limbs points definitively to the cerebellar hemispheres or their pathways through the brainstem.

Unilateral lower extremity edema, especially in the context of a recent fracture, raises the possibility of deep vein thrombosis. If this patient has a right-to-left intracardiac or intrapulmonary shunt, embolization could lead to an ischemic stroke of the brainstem or cerebellum, potentially causing dysarthria.

Laboratory evaluation revealed hemoglobin level of 10.9 g/dL, white blood cell count of 5.3 × 10 9 /L, platelet count of 169 × 10 9 /L, glucose level of 177 mg/dL, corrected calcium level of 9.0 mg/dL, sodium level of 135 mmol/L, bicarbonate level of 30 mmol/L, creatinine level of 0.9 mg/dL, total bilirubin level of 1.3 mg/dL, direct bilirubin level of 0.4 mg/dL, alkaline phosphatase level of 503 U/L, alanine aminotransferase level of 12 U/L, aspartate aminotransferase level of 33 U/L, ammonia level of 49 µmol/L (range, 0-30 µ mol/L), international normalized ratio of 1.2, and troponin level of <0.01 ng/mL. Electrocardiogram showed normal sinus rhythm.

 

 

Some patients with bacterial meningitis do not have a leukocytosis, but patients with meningitis caused by seeding from a systemic infection nearly always do. In this patient’s case, lack of a leukocytosis makes bacterial meningitis very unlikely. The elevated alkaline phosphatase level is expected, as this level peaks about 3 weeks after a long-bone fracture and returns to normal over a few months.

Non-contrast CT scan of the head performed on admission demonstrated no large vessel cortical-based infarct, intracranial hemorrhage, hydrocephalus, mass effect, midline shift, or extra-axial fluid. There was mild cortical atrophy as well as very mild periventricular white matter hypodensity.

The atrophy and mild white-matter hypodensities seen on repeat noncontrast CT are nonspecific for any particular entity in this patient’s age group. MRI is more effective in evaluating toxic encephalopathies, including metronidazole toxicity or Wernicke encephalopathy, and in characterizing small infarcts or inflammatory conditions of the brainstem and cerebellum, which are poorly evaluated by CT due to the bone surrounded space of the posterior fossa. An urgent lumbar puncture is not necessary due to the slow pace of illness, lack of fever, nuchal rigidity, or serum elevated white blood cell count. Rather, performing MRI should be prioritized. If MRI is nondiagnostic, then spinal fluid should be evaluated for evidence of an infectious, autoimmune, paraneoplastic, or neoplastic process.

MRI was subsequently performed. It showed symmetric abnormal T2 hyperintensities involving dentate nuclei (Figure 1), left inferior olivary nuclei (Figure 2), restiform bodies, pontine tegmentum, superior cerebellar peduncles, oculomotor nuclei, and subthalamic nuclei. The most prominent hyperintensity was in the dentate nuclei.

Magnetic resonance imaging shows T2 hyperintensity of dentate nuclei bilaterally.
Figure 1
Magnetic resonance imaging shows T2 hyperintensity of left inferior olivary nuclei.
Figure 2

The clinical and radiographic features confirm a diagnosis of metronidazole-associated CNS neurotoxicity. The reason for the predilection for edema in these specific areas of the brainstem and midline cerebellum is unclear but likely is related to selective neuronal vulnerability in these structures. The treatment is to stop metronidazole. In addition, the fluctuating mental status should be evaluated with electroencephalogram to ensure concomitant seizures are not occurring.

These MRI findings were consistent with metronidazole toxicity. Metronidazole was discontinued, and 2 days later the patient’s speech improved. Two weeks after medication discontinuation, his speech was normal. There were no more episodes of confusion.

DISCUSSION

Metronidazole was originally developed in France during the 1950s as an anti-parasitic medication to treat trichomonas infections. In 1962, its antibacterial properties were discovered after a patient with bacterial gingivitis improved while taking metronidazole for treatment of Trichomonas vaginalis.1 Since that time metronidazole has become a first-line treatment for anaerobic bacteria and is now recommended by the Infectious Diseases Society of America2 and the American College of Gastroenterology3 as a first-line therapy for mild and moderate C difficile infections.

Common side effects of metronidazole are nausea, vomiting, decreased appetite, diarrhea, headaches, peripheral neuropathy, and metallic taste; less common is CNS toxicity. Although the incidence of CNS toxicity is unknown, a systematic review of the literature found 64 cases reported between 1965 and 2011.4 CNS toxicity most often occurs between the fifth and sixth decades of life, and about two thirds of the people affected are men.4 CNS adverse effects characteristically fall into 4 categories: cerebellar dysfunction (eg, ataxia, dysarthria, dysmetria, nystagmus; 75%), AMS (33%), seizures (13%), and a combination of the first 3 categories.4

The exact mechanism of metronidazole CNS toxicity is unknown, but vasogenic or cytotoxic edema may be involved.5,6 Other potential etiologies are neural protein inhibition, reversible mitochondrial dysfunction, and modifications of the inhibitory neurotransmitter gamma-aminobutyric acid receptor in the cerebellum.7,8 There is no known genetic predisposition. Although the risk for CNS toxicity traditionally is thought to correlate with therapy duration and cumulative dose,7,9 in 2011 a systemic review found no significant correlation.4 In fact, 26% of patients with CNS toxicity were treated with metronidazole for less than 1 week at time of diagnosis.4

Brain CT is typically normal. On brain MRI, lesions most commonly appear as bilateral symmetric T2 hyperintensities, most often in the cerebellar dentate nuclei (85%) and less often in the midbrain (55%), the splenium of the corpus callosum (50%), the pons (35%), and the medulla (30%).4,10 Radiographic changes have been noted as early as 3 days after symptom onset. Based on damage severity and area affected (white or gray matter), vasogenic edema and cytotoxic edema may in combination be contributing to MRI abnormalities.6,10 Hyperintensities of the bilateral dentate nuclei can help in distinguishing metronidazole-induced encephalopathy from other potential disease processes, such as Wernicke encephalopathy.10

The prognosis for patients with metronidazole-induced neurotoxicity is favorable if metronidazole is discontinued. Approximately two-thirds of patients will have complete resolution of symptoms, which is more commonly observed when patients present with seizures or altered mental status. Approximately one-third will show partial improvement, particularly if the symptoms are due to cerebellar dysfunction. It is rare to experience permanent damage or death.4 Neurologic recovery usually begins within a week after medication discontinuation but may take months for complete recovery to occur.6,8,9,11 Follow-up imaging typically shows reversal of the original lesions, but this does not always correlate with symptom improvement.4,10

Despite its frequent use and long history, metronidazole can have potentially severe toxicity. When patients who are taking this medication present with new signs and symptoms of CNS dysfunction, hospitalists should include metronidazole CNS toxicity in the differential diagnosis and, if they suspect toxicity, have a brain MRI performed. Hospitalists often prescribe metronidazole because of the increasing number of patients being discharged from acute-care hospitals with a diagnosis of C difficile colitis.12 Brain MRI remains the imaging modality of choice for diagnosis. Discontinuation of metronidazole is usually salutary in reversing symptoms. Being keenly aware of this toxicity will help clinicians avoid being rendered speechless by a patient rendered speechless.

 

 

TEACHING POINTS

  • CNS toxicity is a rare but potentially devastating side effect of metronidazole exposure.

  • Metronidazole CNS adverse effects characteristically fall under 4 categories:

○ Cerebellar dysfunction, such as ataxia, dysarthria, dysmetria, or nystagmus (75%).

○ AMS (33%).

○ Seizures (13%).

○ A combination of the first 3 categories.

  • Typically lesions indicating metronidazole toxicity on brain MRI are bilateral symmetric hyperintensities on T2-weighted imaging in the cerebellar dentate nuclei, corpus callosum, midbrain, pons, or medulla.
  • Treatment of CNS toxicity is metronidazole discontinuation, which results in a high rate of symptom resolution.

Disclosure

Nothing to report.

 

References

1. Samuelson J. Why metronidazole is active against both bacteria and parasites. Antimicrob Agents Chemother. 1999;43(7):1533-1541. PubMed
2. Cohen SH, Gerding DN, Johnson S, et al; Society for Healthcare Epidemiology of America; Infectious Diseases Society of America. Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by the Society for Healthcare Epidemiology of America (SHEA) and the Infectious Diseases Society of America (IDSA). Infect Control Hosp Epidemiol. 2010;31(5):431-455. PubMed
3. Surawicz CM, Brandt LJ, Binion DG, et al. Guidelines for diagnosis, treatment, and prevention of Clostridium difficile infections. Am J Gastroenterol. 2013;108(4):478-498. PubMed
4. Kuriyama A, Jackson JL, Doi A, Kamiya T. Metronidazole-induced central nervous system toxicity: a systemic review. Clin Neuropharmacol. 2011;34(6):241-247. PubMed
5. Graves TD, Condon M, Loucaidou M, Perry RJ. Reversible metronidazole-induced cerebellar toxicity in a multiple transplant recipient. J Neurol Sci. 2009;285(1-2):238-240. PubMed
6. Kim DW, Park JM, Yoon BW, Baek MJ, Kim JE, Kim S. Metronidazole-induced encephalopathy. J Neurol Sci. 2004;224(1-2):107-111. PubMed
7. Park KI, Chung JM, Kim JY. Metronidazole neurotoxicity: sequential neuroaxis involvement. Neurol India. 2011;59(1):104-107. PubMed
8. Patel K, Green-Hopkins I, Lu S, Tunkel AR. Cerebellar ataxia following prolonged use of metronidazole: case report and literature review. Int J Infect Dis. 2008;12(6):e111-e114. PubMed
9. Chandak S, Agarwal A, Shukla A, Joon P. A case report of metronidazole induced neurotoxicity in liver abscess patient and the usefulness of MRI for its diagnosis. J Clin Diagn Res. 2016;10(1):TD06-TD07. PubMed
10. Kim E, Na DG, Kim EY, Kim JH, Son KR, Chang KH. MR imaging of metronidazole-induced encephalopathy: lesion distribution and diffusion-weighted imaging findings. AJNR Am J Neuroradiol. 2007;28(9):1652-1658. PubMed
11. Chacko J, Pramod K, Sinha S, et al. Clinical, neuroimaging and pathological features of 5-nitroimidazole-induced encephalo-neuropathy in two patients: insights into possible pathogenesis. Neurol India. 2011;59(5):743-747. PubMed
12. Peery AF, Dellon ES, Lund J, et al. Burden of gastrointestinal disease in the United States: 2012 update. Gastroenterology. 2012;143(5):1179-1187.e1-e3. PubMed

References

1. Samuelson J. Why metronidazole is active against both bacteria and parasites. Antimicrob Agents Chemother. 1999;43(7):1533-1541. PubMed
2. Cohen SH, Gerding DN, Johnson S, et al; Society for Healthcare Epidemiology of America; Infectious Diseases Society of America. Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by the Society for Healthcare Epidemiology of America (SHEA) and the Infectious Diseases Society of America (IDSA). Infect Control Hosp Epidemiol. 2010;31(5):431-455. PubMed
3. Surawicz CM, Brandt LJ, Binion DG, et al. Guidelines for diagnosis, treatment, and prevention of Clostridium difficile infections. Am J Gastroenterol. 2013;108(4):478-498. PubMed
4. Kuriyama A, Jackson JL, Doi A, Kamiya T. Metronidazole-induced central nervous system toxicity: a systemic review. Clin Neuropharmacol. 2011;34(6):241-247. PubMed
5. Graves TD, Condon M, Loucaidou M, Perry RJ. Reversible metronidazole-induced cerebellar toxicity in a multiple transplant recipient. J Neurol Sci. 2009;285(1-2):238-240. PubMed
6. Kim DW, Park JM, Yoon BW, Baek MJ, Kim JE, Kim S. Metronidazole-induced encephalopathy. J Neurol Sci. 2004;224(1-2):107-111. PubMed
7. Park KI, Chung JM, Kim JY. Metronidazole neurotoxicity: sequential neuroaxis involvement. Neurol India. 2011;59(1):104-107. PubMed
8. Patel K, Green-Hopkins I, Lu S, Tunkel AR. Cerebellar ataxia following prolonged use of metronidazole: case report and literature review. Int J Infect Dis. 2008;12(6):e111-e114. PubMed
9. Chandak S, Agarwal A, Shukla A, Joon P. A case report of metronidazole induced neurotoxicity in liver abscess patient and the usefulness of MRI for its diagnosis. J Clin Diagn Res. 2016;10(1):TD06-TD07. PubMed
10. Kim E, Na DG, Kim EY, Kim JH, Son KR, Chang KH. MR imaging of metronidazole-induced encephalopathy: lesion distribution and diffusion-weighted imaging findings. AJNR Am J Neuroradiol. 2007;28(9):1652-1658. PubMed
11. Chacko J, Pramod K, Sinha S, et al. Clinical, neuroimaging and pathological features of 5-nitroimidazole-induced encephalo-neuropathy in two patients: insights into possible pathogenesis. Neurol India. 2011;59(5):743-747. PubMed
12. Peery AF, Dellon ES, Lund J, et al. Burden of gastrointestinal disease in the United States: 2012 update. Gastroenterology. 2012;143(5):1179-1187.e1-e3. PubMed

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Address for correspondence and reprint requests: Keri Holmes-Maybank, MD, Division of Hospital Medicine, General Internal Medicine and Geriatrics, Medical University of South Carolina, 135 Rutledge Ave, Charleston, SC 29425; Telephone: 843-792-2900; Fax: 843-792-6355; E-mail: [email protected]
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Systematic review of interventions to reduce urinary tract infection in nursing home residents

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Systematic review of interventions to reduce urinary tract infection in nursing home residents

Given the limited number of geriatricians in the U.S., hospitalists commonly manage nursing home residents admitted for post-acute care.1-4 Urinary tract infection (UTI) is one of the most common infections in nursing homes, often leading to sepsis and readmission to acute care.5 Inappropriate use of antibiotics to treat asymptomatic bacteriuria is both common and hazardous to nursing home residents.6 Up to 10% of nursing home residents will have an indwelling urinary catheter at some point during their stay.7-9 Residents with indwelling urinary catheters are at increased risk for catheter-associated urinary tract infection (CAUTI) and bacteriuria, with an estimated 50% of catheterized residents developing symptomatic CAUTI.5 While urinary catheter prevalence is lower in nursing homes than in the acute care setting, duration of use is often prolonged.7,10 In a setting where utilization is low, but use is prolonged, interventions designed to reduce UTI in acutely ill patients11 may not be as helpful for preventing infection in nursing home residents.

Our objective was to review the available evidence to prevent UTIs in nursing home residents to inform both bedside care and research efforts. Two types of literature review and summary were performed. First, we conducted a systematic review of individual studies reporting outcomes of UTI, CAUTI, bacteriuria, or urinary catheter use after interventions for reducing catheter use, improving insertion and maintenance of catheters, and/or general infection prevention strategies (eg, improving hand hygiene, infection surveillance, contact precautions, standardizing UTI diagnosis, and antibiotic use). Second, we performed a narrative review to generate an overview of evidence and published recommendations in both acute care and nursing home settings to prevent UTI in catheterized and non-catheterized older adults, which is provided as a comprehensive reference table for clinicians and researchers choosing and refining interventions to reduce UTIs.

METHODS

The systematic review was performed according to the criteria of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis recommendations. The protocol was registered at the PROSPERO International Prospective Register of Systematic Reviews, (CRD42013005787). The narrative review was performed using the articles obtained from the systematic search and a targeted literature review by topic for a comprehensive list of interventions, including other interventions summarized in published reviews and guidelines.

 

 

Eligibility Criteria Review

Study Design. To address the breadth and depth of literature available to inform interventions to prevent UTI in nursing homes, broad eligibility criteria were applied with the expectation of varied designs and outcomes. All included studies for the systematic review were published manuscripts reporting a comparison group. We included randomized controlled trials as well as nonrandomized trials (pretest/posttest, with or without concurrent or nonconcurrent controls), with any duration of postintervention follow-up. Observational and retrospective studies were excluded.

Participants. We were interested in interventions and outcomes reported for nursing homes, defined as facilities providing short-stay skilled nursing care and/or rehabilitation, as well as long-term care. We also included evidence derived from rehabilitation facilities and spinal cord injury programs focused on reducing CAUTI risk for chronically catheterized residents. We excluded long-term acute care hospitals, hospice, psychiatric/mental health facilities, pediatric, and community dwelling/outpatient settings.

Interventions. We included interventions involving urinary catheter use such as improving appropriate use, aseptic placement, maintenance care, and prompting removal of unnecessary catheters. We included infection prevention strategies with a particular interest in hand hygiene, barrier precautions, infection control strategies, infection surveillance, use of standardized infection definitions, and interventions to improve antibiotic use. We included single and multiple interventions.

Outcomes
1. Healthcare-associated urinary tract infection: UTI occurring after admission to a healthcare facility, not identified specifically as catheter-associated. We categorized UTI outcomes with as much detail as provided, such as whether the reported outcome included only noncatheter-associated UTIs, the time required after admission (eg, more than 2 days), and whether the UTIs were defined by only laboratory criteria, clinically diagnosed infections, symptomatic, or long-term care specific surveillance definitions.

2. Catheter-associated urinary tract infection: UTI occurring in patients during or immediately after use of a urinary catheter. We noted whether CAUTI was defined by laboratory criteria, clinical symptoms, provider diagnosis, or antimicrobial treatment for case identification. We were primarily interested in CAUTI developing after placing an indwelling urinary catheter, commonly known as a Foley, but also in CAUTI occurring with other catheter types such as intermittent straight catheters, external or “condom” catheters, and suprapubic catheters.

3. Bacteriuria: We included the laboratory-based definition of bacteriuria as an outcome to include studies that reduced asymptomatic bacteriuria.

4. Urinary catheter use measures: This includes measures such as urinary catheter utilization ratios (catheter-days/patient-days), prevalence of urinary catheter use, or percentage of catheters with an appropriate indication.

Study Characteristics for Inclusion. Our systematic search included published papers in the English language. We did not exclude studies based on the number of facilities included or eligible, residents/patients included (based on age, gender, catheter use or type, or antibiotic use), intervention details, study withdrawal, loss to follow-up, death, or duration of pre-intervention and postintervention phases.

Figure

Data Sources and Searches

The following data sources were searched: Ovid MEDLINE (1950 to June 22, 2015), Cochrane Library via Wiley (1960 to June 22, 2015), CINAHL (1981 to June 22, 2015), Web of Science (1926 to June 22, 2015), and Embase.com (1946 to June 22, 2015). Two major systematic search strategies were performed for this review (Figure). Systematic search 1 was designed broadly using all data sources described above to identify interventions aimed at reducing all UTI events (defined under “Outcomes” above) or urinary catheter use (all types), focusing on interventions evaluated in nursing homes. Systematic search 2 was conducted in Ovid MEDLINE to identify studies to reduce UTI events or urinary catheter use measures for patients with a history of long-term or chronic catheter use, including nursing homes and other post-acute care settings such as rehabilitation units or hospitals and spinal cord injury programs, which have large populations of patients with chronic catheter needs. To inform the completeness of the broader systematic searches, supplemental systematic search strategies were performed for specific topics including hydration (supplemental search 1), published work by nursing home researchers known to the authors (supplemental search 2), and contact precautions (supplemental search 3). Search 1 is available at http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42013005787. Full search strategies for search 2 and supplemental searches are available upon request.

Study Selection

One author performed an initial screen of all records retrieved by the systematic searches by title and abstract and applied the initial exclusions (eg, non-human, no outcomes of interest), identified duplicate records, and assigned potentially relevant studies into groups such as review articles, epidemiology, interventions, and articles requiring further text review before categorization (Figure). After initial screening, Dr. Meddings reviewed the records by title/abstract. Reference lists were reviewed for potential articles for inclusion. Full-text article review informed the selection of those for dual abstraction and quality scoring performed by 2 authors, with discrepancies resolved by a third author. We requested additional information from authors from whom our search had generated only an abstract or brief report, or when additional information such as pre-intervention data was needed.12-18

 

 

Data Extraction and Quality Assessment

Relevant data regarding study design, participants, inclusion/exclusion criteria, outcomes, and quality criteria were abstracted independently by 2 authors. Methodological quality scores were assigned using a modification of the Quality index checklist developed by Downs and Black appropriate for assessing both randomized and nonrandomized studies of healthcare interventions.19 We also reviewed study funding sources and other potential quality concerns.

Data Analysis

Due to large trial heterogeneity among these studies about interventions and outcomes reported, outcome data could not be combined into summary measures for meta-analysis to give overall estimates of treatment effects.

RESULTS

Systematic Search Results and Study Selection

As detailed in the study flow diagram (Figure), 5794 total records were retrieved by systematic search 1 (4697 studies), search 2 (909 studies), and supplemental searches (188 studies). Hand searching of reference lists of 41 reviews (including narrative and systematic reviews) yielded 77 additional studies for consideration. Twenty-nine records on interventions that were the focus of systematic reviews, including topics of cranberry use, catheter coatings, antimicrobial prophylaxis, washout/irrigation strategies, and sterile versus clean intermittent straight catheterization, were excluded from dual abstraction. Two records were excluded after team discussion of the dual-abstraction results, because 1 study did not meet criteria as an intervention study and 1 study’s setting was not applicable in nursing homes. A total of 20 records15,20-38 (in which 19 studies were described) were selected for final inclusion for detailed assessment and reporting for the systematic review.

Table 1
Table 1 continued

Characteristics of Included Studies

Table 1 describes the 19 intervention studies in terms of design, participants, setting, and whether the study included specific categories of interventions expected to decrease UTI or catheter use. These studies included 8 randomized controlled trials (4 with cluster-randomization at the facility or unit level), 10 pre-post nonrandomized interventions, and 1 nonrandomized intervention with concurrent controls. Twelve studies included participants with or without catheters (ie, not limited to catheterized patients only) in nursing homes.15,20-31 Seven32-38 studies included catheterized patients only or settings with high expected catheterization rates; settings for these studies included spinal cord units (n=3), nursing homes (n=2), rehabilitation ward (n=1) and VA hospital (n=1), including acute care, nursing home, and rehabilitation units. Total quality scores for the studies ranged from 8 to 25 (median, 15), detailed in Supplemental Table 1.

As detailed in Table 1 and Supplemental Table 2, 7 studies22,24,26,31,32,35,36 involved single interventions and 12 studies15,20,21,23,25,27-30,33,34,37,38 included multiple interventions. Interventions to impact catheter use and care were evaluated in 13 studies, including appropriateness of use,21,25,29,30 improving catheter maintenance care,15,20,29,30 securement,15,29,30,32 prompting removal of unnecessary catheters,21,25,29,30 improving incontinence care,15,21,23,25 bladder scanners,37,38 catheter changes,35and comparing alternatives (condom catheter or intermittent straight catheter) to use of an indwelling catheter.36,38 None focused on improving aseptic insertion. General infection control practices studied included improving hand hygiene,20-22,29-31,33,34 improving antibiotic use,15,20,21,28,34 initiation of infection control programs,20,21,28 interventions to improve identification of UTIs/CAUTIs using infection symptom/sign criteria,15,20,21,34 infection surveillance as an intervention,28-30,33,34 and barrier precautions,33,34 including preemptive precautions for catheterized patients.34 Hydration was assessed in 3 studies.24-26

Table 2
Table 2 continued

Outcomes of Included Studies

Table 2 describes the studies’ outcomes reported for UTI, CAUTI, or bacteriuria.15,20-38 The outcome definitions of UTI and CAUTI varied widely. Only 2 studies22,39 reported UTI outcomes using definitions specific for nursing home settings such as McGeer’s criteria40 a detailed review and comparison of published CAUTI definitions used clinically and for surveillance in nursing homes is provided in Supplemental Table 3. Two studies reported symptomatic CAUTIs per 1000 catheter-days.32,34 Another study22 reported symptomatic CAUTIs per 1000 resident-days. Three reported symptomatic CAUTIs as counts.35,38 Saint et al36 reported CAUTIs as part of a combined outcome (ie, bacteriuria, CAUTI, or death).

The 19 studies (Table 2) reported 12 UTI outcomes,15,20,21,23,25-31,33 9 CAUTI outcomes,15,22,32,34,35,38 4 bacteriuria outcomes,24,36,38 and 5 catheter use outcomes.21,29,30,37,38 Five studies showed CAUTI reduction15,22,32,34,35 (1 significantly34); 9 studies showed UTI reduction13,18,19,21,23-25,27,28,31 (none significantly); 2 studies showed bacteriuria reduction (none significantly). One study36 reported 2 composite outcomes including bacteriuria or CAUTI or death, with statistically significant improvement reported for 1 composite measure. Four studies reported catheter use, with all showing reduced catheter use in the intervention group; however, only 1 achieved statistically significant reduction.37

Synthesis of Systematic Review Results

Overall, many studies reported decreases in UTI, CAUTI, and urinary catheter use measures but without statistical significance, with many studies likely underpowered for our outcomes of interest. Often, the outcomes of interest in this systematic review were not the main outcome for which the study was designed and originally powered. The interventions studied included several currently implemented as part of CAUTI bundles in the acute care setting, such as improving catheter use, and care and infection control strategies. Other included interventions target common challenges specific to the nursing home setting such as removing indwelling catheters upon admission to the nursing home from an acute-care facility21,25 and applying interventions to address incontinence by either general strategies21,23,25,30,38 or the use of an incontinence specialist23 to provide individual treatment plans. The only intervention that demonstrated a statistically significant reduction in CAUTI in chronically catheterized patients employed a comprehensive program to improve antimicrobial use, hand hygiene (including hand hygiene and gloves for catheter care), and preemptive precautions for patients with devices, along with promotion of standardized CAUTI definitions and active multidrug resistant organism surveillance.34

 

 

Narrative Review Results

Table 3 includes a comprehensive list of potential interventions that have been considered for prevention of UTI or CAUTI (including those in acute care and nursing home settings), as summarized from this systematic review and prior narrative or systematic reviews.43-115

Table 3
Table 3 continued
Table 3 continued

DISCUSSION

We performed a broad systematic review of strategies to decrease UTI, CAUTI, and urinary catheter use that may be helpful in nursing homes. While many studies reported decreased UTI, CAUTI, or urinary catheter use measures, few demonstrated statistically significant reductions perhaps because many were underpowered to assess statistical significance. Pooled analyses were not feasible to provide the expected impact of these interventions in the nursing home setting.

This review confirms that bundles of interventions for prevention of CAUTI have been implemented with some evidence of success in nursing home settings, with several components in common with those implemented in the acute care setting, such as hand hygiene and strategies to reduce and improve catheter use.41 Some studies focused on issues more common in nursing homes such as chronic catheterization and incontinence. A nursing home CAUTI bundle should be designed with the resources and challenges present in the nursing home environment in mind, and with recognition that, although the number of patients with catheters is less than in acute care, there will be more patients with chronic catheterization needs and incontinence.

Although catheter utilization in nursing homes is low, further reductions in catheter days and CAUTIs can be achieved. Catheter removal reminders and stop orders have demonstrated a greater than 50% reduction in CAUTIs in acute care settings;11 an example of a stop-order intervention in nursing homes is trial removal of indwelling catheters present at facility admission without clear urologic need present at the time of admission.25 Nursing home interventions to avoid catheter placement should include incontinence programs, discussion of alternatives to indwelling urinary catheters with patients, families, and frontline personnel, and urinary retention protocols. Programs to reduce CAUTI should include education to improve aseptic insertion, and to maintain awareness and proper care of catheters in place by regular assessment of catheter necessity, securement, hand hygiene, and preemptive barrier precautions for catheterized patients. Interventions that focus on improving appropriate use of urine tests and antibiotics to treat UTIs can also significantly affect the rates of reported symptomatic CAUTIs, with the potential to decrease unnecessary antibiotic use.20,21

The main limitation of this review is that many studies provided little information about their intervention and definition of outcomes. The strength of this review is the detailed and broad search strategy applied with generous inclusion of interventions and outcomes to highlight the available evidence and details of interventions that have been studied and implemented.

CONCLUSION

This review synthesizes the current state of evidence and proposes strategies to reduce UTIs in nursing homes. Interventions that motivate catheter avoidance and catheter removal to prevent CAUTI in acute care11 and nursing home settings are supported by the strongest available evidence, although the strength of that evidence is less in the nursing home setting. Limitations notwithstanding, interventions such as incontinence care planning and hydration programs can reduce UTI in this population and is important for overall wellbeing.

Acknowledgments

The authors appreciate the guidance that Vineet Chopra MD, MSc, provided regarding options for methodological quality assessment tools, and the assistance of Mary Rogers PhD, MS, in interpreting the published Downs and Black Quality Index items, which informed our modification of this tool for application in this study. The authors appreciate, also, the feedback provided by the Agency for Healthcare Research and Quality (AHRQ) Content and Materials Development Committee for the AHRQ Safety Program for Long-Term Care: Preventing CAUTI and other Healthcare-associated Infections.

 

Disclosures

Agency for Healthcare Research and Quality (AHRQ) contract #HHSA290201000025I provided funding for this study, which was developed in response to AHRQ Task Order #8 for ACTION II RFTO 26 CUSP for CAUTI in LTC. AHRQ developed the details of the task and provided comments on a draft report, which informed the report submitted to AHRQ in December 2013, used to inform the interventions for a national collaborative (http://www.hret.org/quality/projects/long-term-care-cauti.shtml). Dr. Meddings’s effort on this project was funded by concurrent effort from her AHRQ (K08 HS19767). Dr. Saint’s and Dr. Krein’s effort on this project was funded by concurrent effort from the Veterans Affairs National Center for Patient Safety, Ann Arbor Patient Safety Center of Inquiry. Dr. Meddings’s other research is funded by AHRQ (2R01HS018334-04), the NIH-LRP program, the VA National Center for Patient Safety, and the VA Ann Arbor Patient Safety Center of Inquiry. Dr. Krein’s other research is funded by a VA Health Services Research and Development Award (RCS 11-222). Dr. Mody’s other research is funded by VA Healthcare System Geriatric Research Clinical Care Center (GRECC), NIA-Pepper Center, NIA (R01AG032298, R01AG041780, K24AG050685-01). Dr. Saint has received fees for serving on advisory boards for Doximity and Jvion. All other authors report no financial conflicts of interest. The findings and conclusions in this report are those of the authors and do not necessarily represent those of the sponsor, the Agency for Healthcare Research and Quality, or the U.S. Department of Veterans Affairs. These analyses were presented in part as a poster presentation at the ID Week Annual Meeting on October 10, 2014 in Philadelphia, PA.

 

 

 

 

 

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78. Caljouw MAA, Van Den Hout WB, Putter H, Achterberg WP, Cools HJM, Gussekloo J. Effectiveness of cranberry capsules to prevent urinary tract infections in vulnerable older persons. A double-blind randomized placebo-controlled trial in long-term care facilities. Eur Geriatr Med. 2013;4:S118-S119. PubMed

79. Hout WB, Caljouw MAA, Putter H, Cools HJM, Gussekloo J. Cost-effectiveness of cranberry capsules to prevent urinary tract infection in long-term care facilities: economic evaluation with a randomized controlled trial. J Am Geriatr Soc. 2014;62(1):111-116. PubMed

80. Liu BA, McGeer A, McArthur MA, et al. Effect of multivitamin and mineral supplementation on episodes of infection in nursing home residents: a randomized, placebo-controlled study. J Am Geriatr Soc. 2007;55(1):35-42. PubMed

81. Eriksen B. A randomized, open, parallel-group study on the preventive effect of an estradiol-releasing vaginal ring (Estring) on recurrent urinary tract infections in postmenopausal women. Am J Obstet Gynecol. 1999;180:1072-1079. PubMed

82. Maloney C. Hormone replacement therapy in female nursing home residents with recurrent urinary tract infection. Ann Long-Term Care. 1998;6(3):77-82.

83. Gokula RM, Smith MA, Hickner J. Emergency room staff education and use of a urinary catheter indication sheet improves appropriate use of foley catheters. Am J Infect Control. 2007;35(9):589-593. PubMed

84. Salamon L. Catheter-associated urinary tract infections: a nurse-sensitive indicator in an inpatient rehabilitation program. Rehabil Nurs. 2009;34(6):237-241. PubMed

85. Gould CV, Umscheid CA, Agarwal RK, Kuntz G, Pegues DA. Guideline for prevention of catheter-associated urinary tract infections 2009. Infect Control Hosp Epidemiol. 2010;31(4):319-326. PubMed

86. American Medical Directors Association (AMDA). Appropriate indications for use of a chronic indwelling catheter in the long-term care setting. Columbia, MD; excerpted from AMDA's Clinical Practice Guideline: Urinary Incontinence. 2005.

87. Rannikko S, Kyllastinen M, Granqvist B. Comparison of long-term indwelling catheters and bed-pads in the treatment of urinary incontinence in elderly patients. J Infect. 1986;12(3):221-227. PubMed

88. Carapeti E, Andrews S, Bentley P. Randomised study of sterile versus non-sterile urethral catheterization. Ann R. Coll Surg Engl. 1996;78(1):59-60. PubMed

89. Hooton TM, Bradley SF, Cardenas DD, et al. Diagnosis, prevention, and treatment of catheter-associated urinary tract infection in adults: 2009 International Clinical Practice Guidelines from the Infectious Diseases Society of America. Clin Infect Dis. 2010;50(5):625-663. PubMed

90. Olsen-Scribner RJ, Hayes C, Pottinger P. Sustaining reduction of catheter-associated urinary tract infection (CAUTI)-outcomes after two educational methods in a regional university-affiliated medical center. Am J Infect Control. 2014;1:S22.

91. Duffy LM, Cleary J, Ahern S, et al. Clean intermittent catheterization: safe, cost-effective bladder management for male residents of VA nursing homes. J Am Geriatr Soc. 1995;43(8):865-870. PubMed

92. Joseph C, Jacobson C, Strausbaugh L, Maxwell M, French M, Colling J. Sterile vs clean urinary catheterization. J Am Geriatr Soc. 1991;39(10):1042-1043. PubMed

93. Moore KN, Burt J, Voaklander DC. Intermittent catheterization in the rehabilitation setting: a comparison of clean and sterile technique. Clin Rehabili. 2006;20(6):461-468. PubMed

94. Moore KN, Kelm M, Sinclair O, Cadrain G. Bacteriuria in intermittent catheterization users: the effect of sterile versus clean reused catheters. Rehabil Nurs J. 1993;18(5):306-309. PubMed

95. Niel-Weise BS, van den Broek PJ. Urinary catheter policies for short-term bladder drainage in adults. Cochrane Database Syst Rev. 2005(3):CD004203. PubMed

96. Ouslander JG, Greengold B, Chen S. External catheter use and urinary tract infections among incontinent male nursing home patients. J Am Geriatr Soc. 1987;35(12):1063-1070. PubMed

97. Wyndaele JJ, Brauner A, Geerlings SE, Bela K, Peter T, Bjerklund-Johanson TE. Clean intermittent catheterization and urinary tract infection: review and guide for future research. BJU Int. 2012;110(11 Pt C):E910-917. PubMed

98. Jahn P, Beutner K, Langer G. Types of indwelling urinary catheters for long-term bladder drainage in adults. Cochrane Database Syst Rev. 2012(10):CD004997. PubMed

99. Pickard R, Lam T, Maclennan G, et al. Antimicrobial catheters for reduction of symptomatic urinary tract infection in adults requiring short-term catheterisation in hospital: a multicentre randomised controlled trial. Lancet. 2012;380(9857):1927-1935. PubMed

100. Burke JP, Garibaldi RA, Britt MR, Jacobson JA, Conti M, Alling DW. Prevention of catheter-associated urinary tract infections. Efficacy of daily meatal care regimens. Am J Med. 1981;70(3):655-658. PubMed

101. Hagen S, Sinclair L, Cross S. Washout policies in long-term indwelling urinary catheterisation in adults. Cochrane Database Syst Rev. 2010(3). PubMed

102. Moore KN, Hunter KF, McGinnis R, et al. Do catheter washouts extend patency time in long-term indwelling urethral catheters? A randomized controlled trial of acidic washout solution, normal saline washout, or standard care. J Wound Ostomy Continence Nurs. 2009;36(1):82-90. PubMed

103. Muncie HL Jr, Hoopes JM, Damron DJ, Tenney JH, Warren JW. Once-daily irrigation of long-term urethral catheters with normal saline. Lack of benefit. Arch Intern Med. 1989;149(2):441- PubMed

104. Ruwaldt MM. Irrigation of indwelling urinary catheters. Urology. 1983;21(2):127-129. PubMed

105. Palka MA. Evidenced based review of recommendations addressing the frequency of changing long-term indwelling urinary catheters in older adults. Geriatr Nurs. 2014;35(5):357-363. PubMed

106. Warren JW. Catheter-associated urinary tract infections. Infect Dis Clin North Am. 1997;11(3):609-622. PubMed

107. Fryklund B, Haeggman S, Burman LG. Transmission of urinary bacterial strains between patients with indwelling catheters--nursing in the same room and in separate rooms compared. J Hosp Infect. 1997;36(2):147-153. PubMed

108. Anderson RU. Non-sterile intermittent catheterization with antibiotic prophylaxis in the acute spinal cord injured male patient. J Urol. 1980;124(3):392-394. PubMed

109. Anderson RU. Prophylaxis of bacteriuria during intermittent catheterization of the acute neurogenic bladder. J Urol. 1980;123(3):364-366. PubMed

110. Gribble MJ, Puterman ML. Prophylaxis of urinary tract infection in persons with recent spinal cord injury: a prospective, randomized, double-blind, placebo-controlled study of trimethoprim-sulfamethoxazole. Am J Med. 1993;95(2):141-152. PubMed

111. Rutschmann OT, Zwahlen A. Use of norfloxacin for prevention of symptomatic urinary tract infection in chronically catheterized patients. Eur J Clin Microbiol Infect Dis. 1995;14(5):441-444. PubMed

112. Jewes LA, Gillespie WA, Leadbetter A, et al. Bacteriuria and bacteraemia in patients with long-term indwelling catheters--a domiciliary study. J Med Microbiol. 1988;26(1):61-65. PubMed

113. Warren JW, Damron D, Tenney JH, Hoopes JM, Deforge B, Muncie HL, Jr. Fever, bacteremia, and death as complications of bacteriuria in women with long-term urethral catheters. J Infect Dis. 1987;155(6):1151-1158. PubMed

114. Prasad A, Cevallos ME, Riosa S, Darouiche RO, Trautner BW. A bacterial interference strategy for prevention of UTI in persons practicing intermittent catheterization. Spinal Cord. 2009;47(7):565-569. PubMed

 

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Given the limited number of geriatricians in the U.S., hospitalists commonly manage nursing home residents admitted for post-acute care.1-4 Urinary tract infection (UTI) is one of the most common infections in nursing homes, often leading to sepsis and readmission to acute care.5 Inappropriate use of antibiotics to treat asymptomatic bacteriuria is both common and hazardous to nursing home residents.6 Up to 10% of nursing home residents will have an indwelling urinary catheter at some point during their stay.7-9 Residents with indwelling urinary catheters are at increased risk for catheter-associated urinary tract infection (CAUTI) and bacteriuria, with an estimated 50% of catheterized residents developing symptomatic CAUTI.5 While urinary catheter prevalence is lower in nursing homes than in the acute care setting, duration of use is often prolonged.7,10 In a setting where utilization is low, but use is prolonged, interventions designed to reduce UTI in acutely ill patients11 may not be as helpful for preventing infection in nursing home residents.

Our objective was to review the available evidence to prevent UTIs in nursing home residents to inform both bedside care and research efforts. Two types of literature review and summary were performed. First, we conducted a systematic review of individual studies reporting outcomes of UTI, CAUTI, bacteriuria, or urinary catheter use after interventions for reducing catheter use, improving insertion and maintenance of catheters, and/or general infection prevention strategies (eg, improving hand hygiene, infection surveillance, contact precautions, standardizing UTI diagnosis, and antibiotic use). Second, we performed a narrative review to generate an overview of evidence and published recommendations in both acute care and nursing home settings to prevent UTI in catheterized and non-catheterized older adults, which is provided as a comprehensive reference table for clinicians and researchers choosing and refining interventions to reduce UTIs.

METHODS

The systematic review was performed according to the criteria of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis recommendations. The protocol was registered at the PROSPERO International Prospective Register of Systematic Reviews, (CRD42013005787). The narrative review was performed using the articles obtained from the systematic search and a targeted literature review by topic for a comprehensive list of interventions, including other interventions summarized in published reviews and guidelines.

 

 

Eligibility Criteria Review

Study Design. To address the breadth and depth of literature available to inform interventions to prevent UTI in nursing homes, broad eligibility criteria were applied with the expectation of varied designs and outcomes. All included studies for the systematic review were published manuscripts reporting a comparison group. We included randomized controlled trials as well as nonrandomized trials (pretest/posttest, with or without concurrent or nonconcurrent controls), with any duration of postintervention follow-up. Observational and retrospective studies were excluded.

Participants. We were interested in interventions and outcomes reported for nursing homes, defined as facilities providing short-stay skilled nursing care and/or rehabilitation, as well as long-term care. We also included evidence derived from rehabilitation facilities and spinal cord injury programs focused on reducing CAUTI risk for chronically catheterized residents. We excluded long-term acute care hospitals, hospice, psychiatric/mental health facilities, pediatric, and community dwelling/outpatient settings.

Interventions. We included interventions involving urinary catheter use such as improving appropriate use, aseptic placement, maintenance care, and prompting removal of unnecessary catheters. We included infection prevention strategies with a particular interest in hand hygiene, barrier precautions, infection control strategies, infection surveillance, use of standardized infection definitions, and interventions to improve antibiotic use. We included single and multiple interventions.

Outcomes
1. Healthcare-associated urinary tract infection: UTI occurring after admission to a healthcare facility, not identified specifically as catheter-associated. We categorized UTI outcomes with as much detail as provided, such as whether the reported outcome included only noncatheter-associated UTIs, the time required after admission (eg, more than 2 days), and whether the UTIs were defined by only laboratory criteria, clinically diagnosed infections, symptomatic, or long-term care specific surveillance definitions.

2. Catheter-associated urinary tract infection: UTI occurring in patients during or immediately after use of a urinary catheter. We noted whether CAUTI was defined by laboratory criteria, clinical symptoms, provider diagnosis, or antimicrobial treatment for case identification. We were primarily interested in CAUTI developing after placing an indwelling urinary catheter, commonly known as a Foley, but also in CAUTI occurring with other catheter types such as intermittent straight catheters, external or “condom” catheters, and suprapubic catheters.

3. Bacteriuria: We included the laboratory-based definition of bacteriuria as an outcome to include studies that reduced asymptomatic bacteriuria.

4. Urinary catheter use measures: This includes measures such as urinary catheter utilization ratios (catheter-days/patient-days), prevalence of urinary catheter use, or percentage of catheters with an appropriate indication.

Study Characteristics for Inclusion. Our systematic search included published papers in the English language. We did not exclude studies based on the number of facilities included or eligible, residents/patients included (based on age, gender, catheter use or type, or antibiotic use), intervention details, study withdrawal, loss to follow-up, death, or duration of pre-intervention and postintervention phases.

Figure

Data Sources and Searches

The following data sources were searched: Ovid MEDLINE (1950 to June 22, 2015), Cochrane Library via Wiley (1960 to June 22, 2015), CINAHL (1981 to June 22, 2015), Web of Science (1926 to June 22, 2015), and Embase.com (1946 to June 22, 2015). Two major systematic search strategies were performed for this review (Figure). Systematic search 1 was designed broadly using all data sources described above to identify interventions aimed at reducing all UTI events (defined under “Outcomes” above) or urinary catheter use (all types), focusing on interventions evaluated in nursing homes. Systematic search 2 was conducted in Ovid MEDLINE to identify studies to reduce UTI events or urinary catheter use measures for patients with a history of long-term or chronic catheter use, including nursing homes and other post-acute care settings such as rehabilitation units or hospitals and spinal cord injury programs, which have large populations of patients with chronic catheter needs. To inform the completeness of the broader systematic searches, supplemental systematic search strategies were performed for specific topics including hydration (supplemental search 1), published work by nursing home researchers known to the authors (supplemental search 2), and contact precautions (supplemental search 3). Search 1 is available at http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42013005787. Full search strategies for search 2 and supplemental searches are available upon request.

Study Selection

One author performed an initial screen of all records retrieved by the systematic searches by title and abstract and applied the initial exclusions (eg, non-human, no outcomes of interest), identified duplicate records, and assigned potentially relevant studies into groups such as review articles, epidemiology, interventions, and articles requiring further text review before categorization (Figure). After initial screening, Dr. Meddings reviewed the records by title/abstract. Reference lists were reviewed for potential articles for inclusion. Full-text article review informed the selection of those for dual abstraction and quality scoring performed by 2 authors, with discrepancies resolved by a third author. We requested additional information from authors from whom our search had generated only an abstract or brief report, or when additional information such as pre-intervention data was needed.12-18

 

 

Data Extraction and Quality Assessment

Relevant data regarding study design, participants, inclusion/exclusion criteria, outcomes, and quality criteria were abstracted independently by 2 authors. Methodological quality scores were assigned using a modification of the Quality index checklist developed by Downs and Black appropriate for assessing both randomized and nonrandomized studies of healthcare interventions.19 We also reviewed study funding sources and other potential quality concerns.

Data Analysis

Due to large trial heterogeneity among these studies about interventions and outcomes reported, outcome data could not be combined into summary measures for meta-analysis to give overall estimates of treatment effects.

RESULTS

Systematic Search Results and Study Selection

As detailed in the study flow diagram (Figure), 5794 total records were retrieved by systematic search 1 (4697 studies), search 2 (909 studies), and supplemental searches (188 studies). Hand searching of reference lists of 41 reviews (including narrative and systematic reviews) yielded 77 additional studies for consideration. Twenty-nine records on interventions that were the focus of systematic reviews, including topics of cranberry use, catheter coatings, antimicrobial prophylaxis, washout/irrigation strategies, and sterile versus clean intermittent straight catheterization, were excluded from dual abstraction. Two records were excluded after team discussion of the dual-abstraction results, because 1 study did not meet criteria as an intervention study and 1 study’s setting was not applicable in nursing homes. A total of 20 records15,20-38 (in which 19 studies were described) were selected for final inclusion for detailed assessment and reporting for the systematic review.

Table 1
Table 1 continued

Characteristics of Included Studies

Table 1 describes the 19 intervention studies in terms of design, participants, setting, and whether the study included specific categories of interventions expected to decrease UTI or catheter use. These studies included 8 randomized controlled trials (4 with cluster-randomization at the facility or unit level), 10 pre-post nonrandomized interventions, and 1 nonrandomized intervention with concurrent controls. Twelve studies included participants with or without catheters (ie, not limited to catheterized patients only) in nursing homes.15,20-31 Seven32-38 studies included catheterized patients only or settings with high expected catheterization rates; settings for these studies included spinal cord units (n=3), nursing homes (n=2), rehabilitation ward (n=1) and VA hospital (n=1), including acute care, nursing home, and rehabilitation units. Total quality scores for the studies ranged from 8 to 25 (median, 15), detailed in Supplemental Table 1.

As detailed in Table 1 and Supplemental Table 2, 7 studies22,24,26,31,32,35,36 involved single interventions and 12 studies15,20,21,23,25,27-30,33,34,37,38 included multiple interventions. Interventions to impact catheter use and care were evaluated in 13 studies, including appropriateness of use,21,25,29,30 improving catheter maintenance care,15,20,29,30 securement,15,29,30,32 prompting removal of unnecessary catheters,21,25,29,30 improving incontinence care,15,21,23,25 bladder scanners,37,38 catheter changes,35and comparing alternatives (condom catheter or intermittent straight catheter) to use of an indwelling catheter.36,38 None focused on improving aseptic insertion. General infection control practices studied included improving hand hygiene,20-22,29-31,33,34 improving antibiotic use,15,20,21,28,34 initiation of infection control programs,20,21,28 interventions to improve identification of UTIs/CAUTIs using infection symptom/sign criteria,15,20,21,34 infection surveillance as an intervention,28-30,33,34 and barrier precautions,33,34 including preemptive precautions for catheterized patients.34 Hydration was assessed in 3 studies.24-26

Table 2
Table 2 continued

Outcomes of Included Studies

Table 2 describes the studies’ outcomes reported for UTI, CAUTI, or bacteriuria.15,20-38 The outcome definitions of UTI and CAUTI varied widely. Only 2 studies22,39 reported UTI outcomes using definitions specific for nursing home settings such as McGeer’s criteria40 a detailed review and comparison of published CAUTI definitions used clinically and for surveillance in nursing homes is provided in Supplemental Table 3. Two studies reported symptomatic CAUTIs per 1000 catheter-days.32,34 Another study22 reported symptomatic CAUTIs per 1000 resident-days. Three reported symptomatic CAUTIs as counts.35,38 Saint et al36 reported CAUTIs as part of a combined outcome (ie, bacteriuria, CAUTI, or death).

The 19 studies (Table 2) reported 12 UTI outcomes,15,20,21,23,25-31,33 9 CAUTI outcomes,15,22,32,34,35,38 4 bacteriuria outcomes,24,36,38 and 5 catheter use outcomes.21,29,30,37,38 Five studies showed CAUTI reduction15,22,32,34,35 (1 significantly34); 9 studies showed UTI reduction13,18,19,21,23-25,27,28,31 (none significantly); 2 studies showed bacteriuria reduction (none significantly). One study36 reported 2 composite outcomes including bacteriuria or CAUTI or death, with statistically significant improvement reported for 1 composite measure. Four studies reported catheter use, with all showing reduced catheter use in the intervention group; however, only 1 achieved statistically significant reduction.37

Synthesis of Systematic Review Results

Overall, many studies reported decreases in UTI, CAUTI, and urinary catheter use measures but without statistical significance, with many studies likely underpowered for our outcomes of interest. Often, the outcomes of interest in this systematic review were not the main outcome for which the study was designed and originally powered. The interventions studied included several currently implemented as part of CAUTI bundles in the acute care setting, such as improving catheter use, and care and infection control strategies. Other included interventions target common challenges specific to the nursing home setting such as removing indwelling catheters upon admission to the nursing home from an acute-care facility21,25 and applying interventions to address incontinence by either general strategies21,23,25,30,38 or the use of an incontinence specialist23 to provide individual treatment plans. The only intervention that demonstrated a statistically significant reduction in CAUTI in chronically catheterized patients employed a comprehensive program to improve antimicrobial use, hand hygiene (including hand hygiene and gloves for catheter care), and preemptive precautions for patients with devices, along with promotion of standardized CAUTI definitions and active multidrug resistant organism surveillance.34

 

 

Narrative Review Results

Table 3 includes a comprehensive list of potential interventions that have been considered for prevention of UTI or CAUTI (including those in acute care and nursing home settings), as summarized from this systematic review and prior narrative or systematic reviews.43-115

Table 3
Table 3 continued
Table 3 continued

DISCUSSION

We performed a broad systematic review of strategies to decrease UTI, CAUTI, and urinary catheter use that may be helpful in nursing homes. While many studies reported decreased UTI, CAUTI, or urinary catheter use measures, few demonstrated statistically significant reductions perhaps because many were underpowered to assess statistical significance. Pooled analyses were not feasible to provide the expected impact of these interventions in the nursing home setting.

This review confirms that bundles of interventions for prevention of CAUTI have been implemented with some evidence of success in nursing home settings, with several components in common with those implemented in the acute care setting, such as hand hygiene and strategies to reduce and improve catheter use.41 Some studies focused on issues more common in nursing homes such as chronic catheterization and incontinence. A nursing home CAUTI bundle should be designed with the resources and challenges present in the nursing home environment in mind, and with recognition that, although the number of patients with catheters is less than in acute care, there will be more patients with chronic catheterization needs and incontinence.

Although catheter utilization in nursing homes is low, further reductions in catheter days and CAUTIs can be achieved. Catheter removal reminders and stop orders have demonstrated a greater than 50% reduction in CAUTIs in acute care settings;11 an example of a stop-order intervention in nursing homes is trial removal of indwelling catheters present at facility admission without clear urologic need present at the time of admission.25 Nursing home interventions to avoid catheter placement should include incontinence programs, discussion of alternatives to indwelling urinary catheters with patients, families, and frontline personnel, and urinary retention protocols. Programs to reduce CAUTI should include education to improve aseptic insertion, and to maintain awareness and proper care of catheters in place by regular assessment of catheter necessity, securement, hand hygiene, and preemptive barrier precautions for catheterized patients. Interventions that focus on improving appropriate use of urine tests and antibiotics to treat UTIs can also significantly affect the rates of reported symptomatic CAUTIs, with the potential to decrease unnecessary antibiotic use.20,21

The main limitation of this review is that many studies provided little information about their intervention and definition of outcomes. The strength of this review is the detailed and broad search strategy applied with generous inclusion of interventions and outcomes to highlight the available evidence and details of interventions that have been studied and implemented.

CONCLUSION

This review synthesizes the current state of evidence and proposes strategies to reduce UTIs in nursing homes. Interventions that motivate catheter avoidance and catheter removal to prevent CAUTI in acute care11 and nursing home settings are supported by the strongest available evidence, although the strength of that evidence is less in the nursing home setting. Limitations notwithstanding, interventions such as incontinence care planning and hydration programs can reduce UTI in this population and is important for overall wellbeing.

Acknowledgments

The authors appreciate the guidance that Vineet Chopra MD, MSc, provided regarding options for methodological quality assessment tools, and the assistance of Mary Rogers PhD, MS, in interpreting the published Downs and Black Quality Index items, which informed our modification of this tool for application in this study. The authors appreciate, also, the feedback provided by the Agency for Healthcare Research and Quality (AHRQ) Content and Materials Development Committee for the AHRQ Safety Program for Long-Term Care: Preventing CAUTI and other Healthcare-associated Infections.

 

Disclosures

Agency for Healthcare Research and Quality (AHRQ) contract #HHSA290201000025I provided funding for this study, which was developed in response to AHRQ Task Order #8 for ACTION II RFTO 26 CUSP for CAUTI in LTC. AHRQ developed the details of the task and provided comments on a draft report, which informed the report submitted to AHRQ in December 2013, used to inform the interventions for a national collaborative (http://www.hret.org/quality/projects/long-term-care-cauti.shtml). Dr. Meddings’s effort on this project was funded by concurrent effort from her AHRQ (K08 HS19767). Dr. Saint’s and Dr. Krein’s effort on this project was funded by concurrent effort from the Veterans Affairs National Center for Patient Safety, Ann Arbor Patient Safety Center of Inquiry. Dr. Meddings’s other research is funded by AHRQ (2R01HS018334-04), the NIH-LRP program, the VA National Center for Patient Safety, and the VA Ann Arbor Patient Safety Center of Inquiry. Dr. Krein’s other research is funded by a VA Health Services Research and Development Award (RCS 11-222). Dr. Mody’s other research is funded by VA Healthcare System Geriatric Research Clinical Care Center (GRECC), NIA-Pepper Center, NIA (R01AG032298, R01AG041780, K24AG050685-01). Dr. Saint has received fees for serving on advisory boards for Doximity and Jvion. All other authors report no financial conflicts of interest. The findings and conclusions in this report are those of the authors and do not necessarily represent those of the sponsor, the Agency for Healthcare Research and Quality, or the U.S. Department of Veterans Affairs. These analyses were presented in part as a poster presentation at the ID Week Annual Meeting on October 10, 2014 in Philadelphia, PA.

 

 

 

 

 

Given the limited number of geriatricians in the U.S., hospitalists commonly manage nursing home residents admitted for post-acute care.1-4 Urinary tract infection (UTI) is one of the most common infections in nursing homes, often leading to sepsis and readmission to acute care.5 Inappropriate use of antibiotics to treat asymptomatic bacteriuria is both common and hazardous to nursing home residents.6 Up to 10% of nursing home residents will have an indwelling urinary catheter at some point during their stay.7-9 Residents with indwelling urinary catheters are at increased risk for catheter-associated urinary tract infection (CAUTI) and bacteriuria, with an estimated 50% of catheterized residents developing symptomatic CAUTI.5 While urinary catheter prevalence is lower in nursing homes than in the acute care setting, duration of use is often prolonged.7,10 In a setting where utilization is low, but use is prolonged, interventions designed to reduce UTI in acutely ill patients11 may not be as helpful for preventing infection in nursing home residents.

Our objective was to review the available evidence to prevent UTIs in nursing home residents to inform both bedside care and research efforts. Two types of literature review and summary were performed. First, we conducted a systematic review of individual studies reporting outcomes of UTI, CAUTI, bacteriuria, or urinary catheter use after interventions for reducing catheter use, improving insertion and maintenance of catheters, and/or general infection prevention strategies (eg, improving hand hygiene, infection surveillance, contact precautions, standardizing UTI diagnosis, and antibiotic use). Second, we performed a narrative review to generate an overview of evidence and published recommendations in both acute care and nursing home settings to prevent UTI in catheterized and non-catheterized older adults, which is provided as a comprehensive reference table for clinicians and researchers choosing and refining interventions to reduce UTIs.

METHODS

The systematic review was performed according to the criteria of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis recommendations. The protocol was registered at the PROSPERO International Prospective Register of Systematic Reviews, (CRD42013005787). The narrative review was performed using the articles obtained from the systematic search and a targeted literature review by topic for a comprehensive list of interventions, including other interventions summarized in published reviews and guidelines.

 

 

Eligibility Criteria Review

Study Design. To address the breadth and depth of literature available to inform interventions to prevent UTI in nursing homes, broad eligibility criteria were applied with the expectation of varied designs and outcomes. All included studies for the systematic review were published manuscripts reporting a comparison group. We included randomized controlled trials as well as nonrandomized trials (pretest/posttest, with or without concurrent or nonconcurrent controls), with any duration of postintervention follow-up. Observational and retrospective studies were excluded.

Participants. We were interested in interventions and outcomes reported for nursing homes, defined as facilities providing short-stay skilled nursing care and/or rehabilitation, as well as long-term care. We also included evidence derived from rehabilitation facilities and spinal cord injury programs focused on reducing CAUTI risk for chronically catheterized residents. We excluded long-term acute care hospitals, hospice, psychiatric/mental health facilities, pediatric, and community dwelling/outpatient settings.

Interventions. We included interventions involving urinary catheter use such as improving appropriate use, aseptic placement, maintenance care, and prompting removal of unnecessary catheters. We included infection prevention strategies with a particular interest in hand hygiene, barrier precautions, infection control strategies, infection surveillance, use of standardized infection definitions, and interventions to improve antibiotic use. We included single and multiple interventions.

Outcomes
1. Healthcare-associated urinary tract infection: UTI occurring after admission to a healthcare facility, not identified specifically as catheter-associated. We categorized UTI outcomes with as much detail as provided, such as whether the reported outcome included only noncatheter-associated UTIs, the time required after admission (eg, more than 2 days), and whether the UTIs were defined by only laboratory criteria, clinically diagnosed infections, symptomatic, or long-term care specific surveillance definitions.

2. Catheter-associated urinary tract infection: UTI occurring in patients during or immediately after use of a urinary catheter. We noted whether CAUTI was defined by laboratory criteria, clinical symptoms, provider diagnosis, or antimicrobial treatment for case identification. We were primarily interested in CAUTI developing after placing an indwelling urinary catheter, commonly known as a Foley, but also in CAUTI occurring with other catheter types such as intermittent straight catheters, external or “condom” catheters, and suprapubic catheters.

3. Bacteriuria: We included the laboratory-based definition of bacteriuria as an outcome to include studies that reduced asymptomatic bacteriuria.

4. Urinary catheter use measures: This includes measures such as urinary catheter utilization ratios (catheter-days/patient-days), prevalence of urinary catheter use, or percentage of catheters with an appropriate indication.

Study Characteristics for Inclusion. Our systematic search included published papers in the English language. We did not exclude studies based on the number of facilities included or eligible, residents/patients included (based on age, gender, catheter use or type, or antibiotic use), intervention details, study withdrawal, loss to follow-up, death, or duration of pre-intervention and postintervention phases.

Figure

Data Sources and Searches

The following data sources were searched: Ovid MEDLINE (1950 to June 22, 2015), Cochrane Library via Wiley (1960 to June 22, 2015), CINAHL (1981 to June 22, 2015), Web of Science (1926 to June 22, 2015), and Embase.com (1946 to June 22, 2015). Two major systematic search strategies were performed for this review (Figure). Systematic search 1 was designed broadly using all data sources described above to identify interventions aimed at reducing all UTI events (defined under “Outcomes” above) or urinary catheter use (all types), focusing on interventions evaluated in nursing homes. Systematic search 2 was conducted in Ovid MEDLINE to identify studies to reduce UTI events or urinary catheter use measures for patients with a history of long-term or chronic catheter use, including nursing homes and other post-acute care settings such as rehabilitation units or hospitals and spinal cord injury programs, which have large populations of patients with chronic catheter needs. To inform the completeness of the broader systematic searches, supplemental systematic search strategies were performed for specific topics including hydration (supplemental search 1), published work by nursing home researchers known to the authors (supplemental search 2), and contact precautions (supplemental search 3). Search 1 is available at http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42013005787. Full search strategies for search 2 and supplemental searches are available upon request.

Study Selection

One author performed an initial screen of all records retrieved by the systematic searches by title and abstract and applied the initial exclusions (eg, non-human, no outcomes of interest), identified duplicate records, and assigned potentially relevant studies into groups such as review articles, epidemiology, interventions, and articles requiring further text review before categorization (Figure). After initial screening, Dr. Meddings reviewed the records by title/abstract. Reference lists were reviewed for potential articles for inclusion. Full-text article review informed the selection of those for dual abstraction and quality scoring performed by 2 authors, with discrepancies resolved by a third author. We requested additional information from authors from whom our search had generated only an abstract or brief report, or when additional information such as pre-intervention data was needed.12-18

 

 

Data Extraction and Quality Assessment

Relevant data regarding study design, participants, inclusion/exclusion criteria, outcomes, and quality criteria were abstracted independently by 2 authors. Methodological quality scores were assigned using a modification of the Quality index checklist developed by Downs and Black appropriate for assessing both randomized and nonrandomized studies of healthcare interventions.19 We also reviewed study funding sources and other potential quality concerns.

Data Analysis

Due to large trial heterogeneity among these studies about interventions and outcomes reported, outcome data could not be combined into summary measures for meta-analysis to give overall estimates of treatment effects.

RESULTS

Systematic Search Results and Study Selection

As detailed in the study flow diagram (Figure), 5794 total records were retrieved by systematic search 1 (4697 studies), search 2 (909 studies), and supplemental searches (188 studies). Hand searching of reference lists of 41 reviews (including narrative and systematic reviews) yielded 77 additional studies for consideration. Twenty-nine records on interventions that were the focus of systematic reviews, including topics of cranberry use, catheter coatings, antimicrobial prophylaxis, washout/irrigation strategies, and sterile versus clean intermittent straight catheterization, were excluded from dual abstraction. Two records were excluded after team discussion of the dual-abstraction results, because 1 study did not meet criteria as an intervention study and 1 study’s setting was not applicable in nursing homes. A total of 20 records15,20-38 (in which 19 studies were described) were selected for final inclusion for detailed assessment and reporting for the systematic review.

Table 1
Table 1 continued

Characteristics of Included Studies

Table 1 describes the 19 intervention studies in terms of design, participants, setting, and whether the study included specific categories of interventions expected to decrease UTI or catheter use. These studies included 8 randomized controlled trials (4 with cluster-randomization at the facility or unit level), 10 pre-post nonrandomized interventions, and 1 nonrandomized intervention with concurrent controls. Twelve studies included participants with or without catheters (ie, not limited to catheterized patients only) in nursing homes.15,20-31 Seven32-38 studies included catheterized patients only or settings with high expected catheterization rates; settings for these studies included spinal cord units (n=3), nursing homes (n=2), rehabilitation ward (n=1) and VA hospital (n=1), including acute care, nursing home, and rehabilitation units. Total quality scores for the studies ranged from 8 to 25 (median, 15), detailed in Supplemental Table 1.

As detailed in Table 1 and Supplemental Table 2, 7 studies22,24,26,31,32,35,36 involved single interventions and 12 studies15,20,21,23,25,27-30,33,34,37,38 included multiple interventions. Interventions to impact catheter use and care were evaluated in 13 studies, including appropriateness of use,21,25,29,30 improving catheter maintenance care,15,20,29,30 securement,15,29,30,32 prompting removal of unnecessary catheters,21,25,29,30 improving incontinence care,15,21,23,25 bladder scanners,37,38 catheter changes,35and comparing alternatives (condom catheter or intermittent straight catheter) to use of an indwelling catheter.36,38 None focused on improving aseptic insertion. General infection control practices studied included improving hand hygiene,20-22,29-31,33,34 improving antibiotic use,15,20,21,28,34 initiation of infection control programs,20,21,28 interventions to improve identification of UTIs/CAUTIs using infection symptom/sign criteria,15,20,21,34 infection surveillance as an intervention,28-30,33,34 and barrier precautions,33,34 including preemptive precautions for catheterized patients.34 Hydration was assessed in 3 studies.24-26

Table 2
Table 2 continued

Outcomes of Included Studies

Table 2 describes the studies’ outcomes reported for UTI, CAUTI, or bacteriuria.15,20-38 The outcome definitions of UTI and CAUTI varied widely. Only 2 studies22,39 reported UTI outcomes using definitions specific for nursing home settings such as McGeer’s criteria40 a detailed review and comparison of published CAUTI definitions used clinically and for surveillance in nursing homes is provided in Supplemental Table 3. Two studies reported symptomatic CAUTIs per 1000 catheter-days.32,34 Another study22 reported symptomatic CAUTIs per 1000 resident-days. Three reported symptomatic CAUTIs as counts.35,38 Saint et al36 reported CAUTIs as part of a combined outcome (ie, bacteriuria, CAUTI, or death).

The 19 studies (Table 2) reported 12 UTI outcomes,15,20,21,23,25-31,33 9 CAUTI outcomes,15,22,32,34,35,38 4 bacteriuria outcomes,24,36,38 and 5 catheter use outcomes.21,29,30,37,38 Five studies showed CAUTI reduction15,22,32,34,35 (1 significantly34); 9 studies showed UTI reduction13,18,19,21,23-25,27,28,31 (none significantly); 2 studies showed bacteriuria reduction (none significantly). One study36 reported 2 composite outcomes including bacteriuria or CAUTI or death, with statistically significant improvement reported for 1 composite measure. Four studies reported catheter use, with all showing reduced catheter use in the intervention group; however, only 1 achieved statistically significant reduction.37

Synthesis of Systematic Review Results

Overall, many studies reported decreases in UTI, CAUTI, and urinary catheter use measures but without statistical significance, with many studies likely underpowered for our outcomes of interest. Often, the outcomes of interest in this systematic review were not the main outcome for which the study was designed and originally powered. The interventions studied included several currently implemented as part of CAUTI bundles in the acute care setting, such as improving catheter use, and care and infection control strategies. Other included interventions target common challenges specific to the nursing home setting such as removing indwelling catheters upon admission to the nursing home from an acute-care facility21,25 and applying interventions to address incontinence by either general strategies21,23,25,30,38 or the use of an incontinence specialist23 to provide individual treatment plans. The only intervention that demonstrated a statistically significant reduction in CAUTI in chronically catheterized patients employed a comprehensive program to improve antimicrobial use, hand hygiene (including hand hygiene and gloves for catheter care), and preemptive precautions for patients with devices, along with promotion of standardized CAUTI definitions and active multidrug resistant organism surveillance.34

 

 

Narrative Review Results

Table 3 includes a comprehensive list of potential interventions that have been considered for prevention of UTI or CAUTI (including those in acute care and nursing home settings), as summarized from this systematic review and prior narrative or systematic reviews.43-115

Table 3
Table 3 continued
Table 3 continued

DISCUSSION

We performed a broad systematic review of strategies to decrease UTI, CAUTI, and urinary catheter use that may be helpful in nursing homes. While many studies reported decreased UTI, CAUTI, or urinary catheter use measures, few demonstrated statistically significant reductions perhaps because many were underpowered to assess statistical significance. Pooled analyses were not feasible to provide the expected impact of these interventions in the nursing home setting.

This review confirms that bundles of interventions for prevention of CAUTI have been implemented with some evidence of success in nursing home settings, with several components in common with those implemented in the acute care setting, such as hand hygiene and strategies to reduce and improve catheter use.41 Some studies focused on issues more common in nursing homes such as chronic catheterization and incontinence. A nursing home CAUTI bundle should be designed with the resources and challenges present in the nursing home environment in mind, and with recognition that, although the number of patients with catheters is less than in acute care, there will be more patients with chronic catheterization needs and incontinence.

Although catheter utilization in nursing homes is low, further reductions in catheter days and CAUTIs can be achieved. Catheter removal reminders and stop orders have demonstrated a greater than 50% reduction in CAUTIs in acute care settings;11 an example of a stop-order intervention in nursing homes is trial removal of indwelling catheters present at facility admission without clear urologic need present at the time of admission.25 Nursing home interventions to avoid catheter placement should include incontinence programs, discussion of alternatives to indwelling urinary catheters with patients, families, and frontline personnel, and urinary retention protocols. Programs to reduce CAUTI should include education to improve aseptic insertion, and to maintain awareness and proper care of catheters in place by regular assessment of catheter necessity, securement, hand hygiene, and preemptive barrier precautions for catheterized patients. Interventions that focus on improving appropriate use of urine tests and antibiotics to treat UTIs can also significantly affect the rates of reported symptomatic CAUTIs, with the potential to decrease unnecessary antibiotic use.20,21

The main limitation of this review is that many studies provided little information about their intervention and definition of outcomes. The strength of this review is the detailed and broad search strategy applied with generous inclusion of interventions and outcomes to highlight the available evidence and details of interventions that have been studied and implemented.

CONCLUSION

This review synthesizes the current state of evidence and proposes strategies to reduce UTIs in nursing homes. Interventions that motivate catheter avoidance and catheter removal to prevent CAUTI in acute care11 and nursing home settings are supported by the strongest available evidence, although the strength of that evidence is less in the nursing home setting. Limitations notwithstanding, interventions such as incontinence care planning and hydration programs can reduce UTI in this population and is important for overall wellbeing.

Acknowledgments

The authors appreciate the guidance that Vineet Chopra MD, MSc, provided regarding options for methodological quality assessment tools, and the assistance of Mary Rogers PhD, MS, in interpreting the published Downs and Black Quality Index items, which informed our modification of this tool for application in this study. The authors appreciate, also, the feedback provided by the Agency for Healthcare Research and Quality (AHRQ) Content and Materials Development Committee for the AHRQ Safety Program for Long-Term Care: Preventing CAUTI and other Healthcare-associated Infections.

 

Disclosures

Agency for Healthcare Research and Quality (AHRQ) contract #HHSA290201000025I provided funding for this study, which was developed in response to AHRQ Task Order #8 for ACTION II RFTO 26 CUSP for CAUTI in LTC. AHRQ developed the details of the task and provided comments on a draft report, which informed the report submitted to AHRQ in December 2013, used to inform the interventions for a national collaborative (http://www.hret.org/quality/projects/long-term-care-cauti.shtml). Dr. Meddings’s effort on this project was funded by concurrent effort from her AHRQ (K08 HS19767). Dr. Saint’s and Dr. Krein’s effort on this project was funded by concurrent effort from the Veterans Affairs National Center for Patient Safety, Ann Arbor Patient Safety Center of Inquiry. Dr. Meddings’s other research is funded by AHRQ (2R01HS018334-04), the NIH-LRP program, the VA National Center for Patient Safety, and the VA Ann Arbor Patient Safety Center of Inquiry. Dr. Krein’s other research is funded by a VA Health Services Research and Development Award (RCS 11-222). Dr. Mody’s other research is funded by VA Healthcare System Geriatric Research Clinical Care Center (GRECC), NIA-Pepper Center, NIA (R01AG032298, R01AG041780, K24AG050685-01). Dr. Saint has received fees for serving on advisory boards for Doximity and Jvion. All other authors report no financial conflicts of interest. The findings and conclusions in this report are those of the authors and do not necessarily represent those of the sponsor, the Agency for Healthcare Research and Quality, or the U.S. Department of Veterans Affairs. These analyses were presented in part as a poster presentation at the ID Week Annual Meeting on October 10, 2014 in Philadelphia, PA.

 

 

 

 

 

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100. Burke JP, Garibaldi RA, Britt MR, Jacobson JA, Conti M, Alling DW. Prevention of catheter-associated urinary tract infections. Efficacy of daily meatal care regimens. Am J Med. 1981;70(3):655-658. PubMed

101. Hagen S, Sinclair L, Cross S. Washout policies in long-term indwelling urinary catheterisation in adults. Cochrane Database Syst Rev. 2010(3). PubMed

102. Moore KN, Hunter KF, McGinnis R, et al. Do catheter washouts extend patency time in long-term indwelling urethral catheters? A randomized controlled trial of acidic washout solution, normal saline washout, or standard care. J Wound Ostomy Continence Nurs. 2009;36(1):82-90. PubMed

103. Muncie HL Jr, Hoopes JM, Damron DJ, Tenney JH, Warren JW. Once-daily irrigation of long-term urethral catheters with normal saline. Lack of benefit. Arch Intern Med. 1989;149(2):441- PubMed

104. Ruwaldt MM. Irrigation of indwelling urinary catheters. Urology. 1983;21(2):127-129. PubMed

105. Palka MA. Evidenced based review of recommendations addressing the frequency of changing long-term indwelling urinary catheters in older adults. Geriatr Nurs. 2014;35(5):357-363. PubMed

106. Warren JW. Catheter-associated urinary tract infections. Infect Dis Clin North Am. 1997;11(3):609-622. PubMed

107. Fryklund B, Haeggman S, Burman LG. Transmission of urinary bacterial strains between patients with indwelling catheters--nursing in the same room and in separate rooms compared. J Hosp Infect. 1997;36(2):147-153. PubMed

108. Anderson RU. Non-sterile intermittent catheterization with antibiotic prophylaxis in the acute spinal cord injured male patient. J Urol. 1980;124(3):392-394. PubMed

109. Anderson RU. Prophylaxis of bacteriuria during intermittent catheterization of the acute neurogenic bladder. J Urol. 1980;123(3):364-366. PubMed

110. Gribble MJ, Puterman ML. Prophylaxis of urinary tract infection in persons with recent spinal cord injury: a prospective, randomized, double-blind, placebo-controlled study of trimethoprim-sulfamethoxazole. Am J Med. 1993;95(2):141-152. PubMed

111. Rutschmann OT, Zwahlen A. Use of norfloxacin for prevention of symptomatic urinary tract infection in chronically catheterized patients. Eur J Clin Microbiol Infect Dis. 1995;14(5):441-444. PubMed

112. Jewes LA, Gillespie WA, Leadbetter A, et al. Bacteriuria and bacteraemia in patients with long-term indwelling catheters--a domiciliary study. J Med Microbiol. 1988;26(1):61-65. PubMed

113. Warren JW, Damron D, Tenney JH, Hoopes JM, Deforge B, Muncie HL, Jr. Fever, bacteremia, and death as complications of bacteriuria in women with long-term urethral catheters. J Infect Dis. 1987;155(6):1151-1158. PubMed

114. Prasad A, Cevallos ME, Riosa S, Darouiche RO, Trautner BW. A bacterial interference strategy for prevention of UTI in persons practicing intermittent catheterization. Spinal Cord. 2009;47(7):565-569. PubMed

 

References

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43. Nicolle LE. The chronic indwelling catheter and urinary infection in long-term-care facility residents. Infect Control Hosp Epidemiol. 2001;22(5):316-321. PubMed

44. Nicolle LE; SHEA Long-Term Care Committee. Urinary tract infections in long-term-care facilities. Infect Control Hosp Epidemiol. 2001;22(3):167-175. PubMed

45. Nicolle LE. Catheter-related urinary tract infection. Drug & Aging. 2005;22(8):627-639. PubMed

46. Cochran S. Care of the indwelling urinary catheter - Is it evidence based? J Wound Ostomy Cont Nurs. 2007;34(3):282-288. PubMed

47. Seiler WO, Stahelin HB. Practical management of catheter-associated UTIs. Geriatrics. 1988;43(8):43-50. PubMed

48. Stickler DJ, Chawla JC. The role of antiseptics in the management of patients with long-term indwelling bladder catheters. J Hosp Infect. 1987;10(3):219-228. PubMed

49. Gray M. Does the construction material affect outcomes in long-term catheterization? J Wound Ostomy Cont Nurs. 2006;33(2):116-121. PubMed

50. Trautner BW, Darouiche RO. Clinical review: prevention of urinary tract infection in patients with spinal cord injury. J Spinal Cord Med. 2002;2002(25):277-283. PubMed

51. Maloney C. Estrogen & recurrent UTI in postmenopausal women. Am J Nurs. 2002;102(8):44-52. PubMed

52. Raz R. Hormone replacement therapy or prophylaxis in postmenopausal women with recurrent urinary tract infection. J Infect Dis. 2001;183(suppl 1):S74-S76. PubMed

53. Godfrey H. Older people, continence care and catheters: dilemmas and resolutions. Br J Nurs. 2008;17(9):S4-S11. PubMed

54. Godfrey H, Evans A. Management of long-term urethral catheters: minimizing complications. Br J Nurs. 2000;9(2):74-76. PubMed

55. Kunin CM. Chemoprophylaxis and suppressive therapy in the management of urinary tract infections. J Antimicrob Chemother. 1994;33(suppl A):51-62. PubMed

56. Newman DK, Willson MM. Review of intermittent catheterization and current best practices. Urol Nurs. 2011;31(1):12-48. PubMed

57. Allan GM, Nicolle L. Cranberry for preventing urinary tract infection. Can Fam Physician. 2013;59(4):367. PubMed

58. Jepson RG, Williams G, Craig JC. Cranberries for preventing urinary tract infections. Cochrane Database Syst Rev. 2012;10:CD001321. PubMed

59. Wang CH, Fang CC, Chen NC, et al. Cranberry-containing products for prevention of urinary tract infections in susceptible populations: a systematic review and meta-analysis of randomized controlled trials. Arch Intern Med. 2012;172(13):988-996. PubMed

60. Moore KN, Fader M, Getliffe K. Long-term bladder management by intermittent catheterisation in adults and children. Cochrane Database Syst Rev. 2007(4):CD006008. PubMed

61. Li L, Ye WQ, Ruan H, Yang BY, Zhang SQ. Impact of hydrophilic catheters on urinary tract infections in people with spinal cord injury: systematic review and meta-analysis of randomized controlled trials. Arch Phys Med Rehabil. 2013;94(4):782-787. PubMed

62. Jamison J, Maguire S, McCann J. Catheter policies for management of long term voiding problems in adults with neurogenic bladder disorders. Cochrane Database Syst Rev. 2011(12):CD004375. PubMed

63. Gray M. What nursing interventions reduce the risk of symptomatic urinary tract infections in the patient with an indwelling catheter? J Wound Ostomy Cont Nurs. 2004;31(1):3-13. PubMed

64. Marschall J, Carpenter C, Fowler S, Trautner B. Antibiotic prophylaxis for urinary tract infections after removal of urinary catheter: meta-analysis. BMJ. 2013;346:f3147. PubMed

65. Sinclair L, Hagen S, Cross S. Washout policies in long-term indwelling urinary catheterization in adults: a short version Cochrane review. Neurourol Urodyn. 2011;30(7):1208-1212. PubMed

66. Hunter KF, Bharmal A, Moore KN. Long-term bladder drainage: suprapubic catheter versus other methods: a scoping review. Neurourol Urodyn. 2013;32(7):944-951. PubMed

67. Morton SC, Shekelle PG, Adams JL, et al. Antimicrobial prophylaxis for urinary tract infection in persons with spinal cord dysfunction. Arch Phys Med Rehabil. 2002;83(1):129-138. PubMed

68. Niël-Weise BS, van den Broek PJ, da Silva EM, Silva LA. Urinary catheter policies for long-term bladder drainage. Cochrane Database Syst Rev. 2012(8). PubMed

69. Jepson R, Craig J. Cranberries for preventing urinary tract infections. Cochrane Database Syst Rev. 2008;10(CD001321). PubMed

70. Avorn J, Monane M, Gurwitz JH, Glynn RJ, Choodnovskiy I, Lipsitz LA. Reduction of bacteriuria and pyuria after ingestion of cranberry juice. JAMA. 1994;271(10):751-754. PubMed

71. Bianco L, Perrelli E, Towle V, Van Ness PH, Juthani-Mehta M. Pilot randomized controlled dosing study of cranberry capsules for reduction of bacteriuria plus pyuria in female nursing home residents. J Am Geriatr Soc. 2012;60(6):1180-1181. PubMed

72. Lin SC, Wang CC, Shih SC, Tjung JJ, Tsou MT, Lin CJ. Prevention of Asymptomatic Bacteriuria with Cranberries and Roselle Juice in Home-care Patients with Long-term Urinary Catheterization. Int J Gerontol. 2014;8(3):152-156.

73. Juthani-Mehta M, Perley L, Chen S, Dziura J, Gupta K. Feasibility of cranberry capsule administration and clean-catch urine collection in long-term care residents. J Am Geriatr Soc. 2010;58(10):2028-2030. PubMed

74. Tully CL, Bastone P, Vaughan J, Ballentine L. Urinary tract infection prophylaxis with cranberry extract in the nursing home setting. J Am Geriatr Soc. 2004;52(4):S206-S206.

75. Woodward N. Use of cranberry extract for the prevention of UTIs in an at-risk population. 41st Annual Wound, Ostomy and Continence Nurses Annual Conference, St. Louis, Missouri, June 6-10, 2009. J Wound Ostomy Continence Nurs. 2009;36(3S):S62-S62.

76. Linsenmeyer TA, Harrison B, Oakley A, Kirshblum S, Stock JA, Millis SR. Evaluation of cranberry supplement for reduction of urinary tract infections in individuals with neurogenic bladders secondary to spinal cord injury. A prospective, double-blinded, placebo-controlled, crossover study. J Spinal Cord Med. 2004;27(1):29-34. PubMed

77. Waites KB, Canupp KC, Armstrong S, DeVivo MJ. Effect of cranberry extract on bacteriuria and pyuria in persons with neurogenic bladder secondary to spinal cord injury. J Spinal Cord Med. 2004;27(1):35-40. PubMed

78. Caljouw MAA, Van Den Hout WB, Putter H, Achterberg WP, Cools HJM, Gussekloo J. Effectiveness of cranberry capsules to prevent urinary tract infections in vulnerable older persons. A double-blind randomized placebo-controlled trial in long-term care facilities. Eur Geriatr Med. 2013;4:S118-S119. PubMed

79. Hout WB, Caljouw MAA, Putter H, Cools HJM, Gussekloo J. Cost-effectiveness of cranberry capsules to prevent urinary tract infection in long-term care facilities: economic evaluation with a randomized controlled trial. J Am Geriatr Soc. 2014;62(1):111-116. PubMed

80. Liu BA, McGeer A, McArthur MA, et al. Effect of multivitamin and mineral supplementation on episodes of infection in nursing home residents: a randomized, placebo-controlled study. J Am Geriatr Soc. 2007;55(1):35-42. PubMed

81. Eriksen B. A randomized, open, parallel-group study on the preventive effect of an estradiol-releasing vaginal ring (Estring) on recurrent urinary tract infections in postmenopausal women. Am J Obstet Gynecol. 1999;180:1072-1079. PubMed

82. Maloney C. Hormone replacement therapy in female nursing home residents with recurrent urinary tract infection. Ann Long-Term Care. 1998;6(3):77-82.

83. Gokula RM, Smith MA, Hickner J. Emergency room staff education and use of a urinary catheter indication sheet improves appropriate use of foley catheters. Am J Infect Control. 2007;35(9):589-593. PubMed

84. Salamon L. Catheter-associated urinary tract infections: a nurse-sensitive indicator in an inpatient rehabilitation program. Rehabil Nurs. 2009;34(6):237-241. PubMed

85. Gould CV, Umscheid CA, Agarwal RK, Kuntz G, Pegues DA. Guideline for prevention of catheter-associated urinary tract infections 2009. Infect Control Hosp Epidemiol. 2010;31(4):319-326. PubMed

86. American Medical Directors Association (AMDA). Appropriate indications for use of a chronic indwelling catheter in the long-term care setting. Columbia, MD; excerpted from AMDA's Clinical Practice Guideline: Urinary Incontinence. 2005.

87. Rannikko S, Kyllastinen M, Granqvist B. Comparison of long-term indwelling catheters and bed-pads in the treatment of urinary incontinence in elderly patients. J Infect. 1986;12(3):221-227. PubMed

88. Carapeti E, Andrews S, Bentley P. Randomised study of sterile versus non-sterile urethral catheterization. Ann R. Coll Surg Engl. 1996;78(1):59-60. PubMed

89. Hooton TM, Bradley SF, Cardenas DD, et al. Diagnosis, prevention, and treatment of catheter-associated urinary tract infection in adults: 2009 International Clinical Practice Guidelines from the Infectious Diseases Society of America. Clin Infect Dis. 2010;50(5):625-663. PubMed

90. Olsen-Scribner RJ, Hayes C, Pottinger P. Sustaining reduction of catheter-associated urinary tract infection (CAUTI)-outcomes after two educational methods in a regional university-affiliated medical center. Am J Infect Control. 2014;1:S22.

91. Duffy LM, Cleary J, Ahern S, et al. Clean intermittent catheterization: safe, cost-effective bladder management for male residents of VA nursing homes. J Am Geriatr Soc. 1995;43(8):865-870. PubMed

92. Joseph C, Jacobson C, Strausbaugh L, Maxwell M, French M, Colling J. Sterile vs clean urinary catheterization. J Am Geriatr Soc. 1991;39(10):1042-1043. PubMed

93. Moore KN, Burt J, Voaklander DC. Intermittent catheterization in the rehabilitation setting: a comparison of clean and sterile technique. Clin Rehabili. 2006;20(6):461-468. PubMed

94. Moore KN, Kelm M, Sinclair O, Cadrain G. Bacteriuria in intermittent catheterization users: the effect of sterile versus clean reused catheters. Rehabil Nurs J. 1993;18(5):306-309. PubMed

95. Niel-Weise BS, van den Broek PJ. Urinary catheter policies for short-term bladder drainage in adults. Cochrane Database Syst Rev. 2005(3):CD004203. PubMed

96. Ouslander JG, Greengold B, Chen S. External catheter use and urinary tract infections among incontinent male nursing home patients. J Am Geriatr Soc. 1987;35(12):1063-1070. PubMed

97. Wyndaele JJ, Brauner A, Geerlings SE, Bela K, Peter T, Bjerklund-Johanson TE. Clean intermittent catheterization and urinary tract infection: review and guide for future research. BJU Int. 2012;110(11 Pt C):E910-917. PubMed

98. Jahn P, Beutner K, Langer G. Types of indwelling urinary catheters for long-term bladder drainage in adults. Cochrane Database Syst Rev. 2012(10):CD004997. PubMed

99. Pickard R, Lam T, Maclennan G, et al. Antimicrobial catheters for reduction of symptomatic urinary tract infection in adults requiring short-term catheterisation in hospital: a multicentre randomised controlled trial. Lancet. 2012;380(9857):1927-1935. PubMed

100. Burke JP, Garibaldi RA, Britt MR, Jacobson JA, Conti M, Alling DW. Prevention of catheter-associated urinary tract infections. Efficacy of daily meatal care regimens. Am J Med. 1981;70(3):655-658. PubMed

101. Hagen S, Sinclair L, Cross S. Washout policies in long-term indwelling urinary catheterisation in adults. Cochrane Database Syst Rev. 2010(3). PubMed

102. Moore KN, Hunter KF, McGinnis R, et al. Do catheter washouts extend patency time in long-term indwelling urethral catheters? A randomized controlled trial of acidic washout solution, normal saline washout, or standard care. J Wound Ostomy Continence Nurs. 2009;36(1):82-90. PubMed

103. Muncie HL Jr, Hoopes JM, Damron DJ, Tenney JH, Warren JW. Once-daily irrigation of long-term urethral catheters with normal saline. Lack of benefit. Arch Intern Med. 1989;149(2):441- PubMed

104. Ruwaldt MM. Irrigation of indwelling urinary catheters. Urology. 1983;21(2):127-129. PubMed

105. Palka MA. Evidenced based review of recommendations addressing the frequency of changing long-term indwelling urinary catheters in older adults. Geriatr Nurs. 2014;35(5):357-363. PubMed

106. Warren JW. Catheter-associated urinary tract infections. Infect Dis Clin North Am. 1997;11(3):609-622. PubMed

107. Fryklund B, Haeggman S, Burman LG. Transmission of urinary bacterial strains between patients with indwelling catheters--nursing in the same room and in separate rooms compared. J Hosp Infect. 1997;36(2):147-153. PubMed

108. Anderson RU. Non-sterile intermittent catheterization with antibiotic prophylaxis in the acute spinal cord injured male patient. J Urol. 1980;124(3):392-394. PubMed

109. Anderson RU. Prophylaxis of bacteriuria during intermittent catheterization of the acute neurogenic bladder. J Urol. 1980;123(3):364-366. PubMed

110. Gribble MJ, Puterman ML. Prophylaxis of urinary tract infection in persons with recent spinal cord injury: a prospective, randomized, double-blind, placebo-controlled study of trimethoprim-sulfamethoxazole. Am J Med. 1993;95(2):141-152. PubMed

111. Rutschmann OT, Zwahlen A. Use of norfloxacin for prevention of symptomatic urinary tract infection in chronically catheterized patients. Eur J Clin Microbiol Infect Dis. 1995;14(5):441-444. PubMed

112. Jewes LA, Gillespie WA, Leadbetter A, et al. Bacteriuria and bacteraemia in patients with long-term indwelling catheters--a domiciliary study. J Med Microbiol. 1988;26(1):61-65. PubMed

113. Warren JW, Damron D, Tenney JH, Hoopes JM, Deforge B, Muncie HL, Jr. Fever, bacteremia, and death as complications of bacteriuria in women with long-term urethral catheters. J Infect Dis. 1987;155(6):1151-1158. PubMed

114. Prasad A, Cevallos ME, Riosa S, Darouiche RO, Trautner BW. A bacterial interference strategy for prevention of UTI in persons practicing intermittent catheterization. Spinal Cord. 2009;47(7):565-569. PubMed

 

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Systematic review of interventions to reduce urinary tract infection in nursing home residents
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Inpatient management of opioid use disorder: A review for hospitalists

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Inpatient management of opioid use disorder: A review for hospitalists

The United States is experiencing an epidemic of nonmedical opioid use. A concerted effort to better address pain increased the provision of prescription narcotics in the late 1990s and early 2000s.1 Since then, there has been significant growth of opioid use and acorresponding increase in overdose-related deaths.1-3 Public health officials have responded with initiatives to secure the opioid supply and improve outpatient treatment resources. However, the role of hospitalists in addressing opioid use disorder (OUD) is not well established. The inpatient needs for these individuals are complex and require a collaborative approach with input from outpatient clinicians, inpatient clinicians, addiction specialists, social workers, and case managers. Hospitals are often under-resourced to provide such comprehensive services. This frequently results in the hospitalist bearing significant responsibility for inpatient addiction management despite often insufficient addiction education or experience.4,5

Therefore, there is a need for hospitalists to become leaders in the inpatient management of OUD. In this review, we will discuss the hospitalist’s role in the inpatient management of individuals with OUD.

INPATIENT MANAGEMENT OF OPIOID USE DISORDER

Opioid use disorder is a medical illness resulting from neurobiological changes that cause drug tolerance, dependence, and cravings.6 It should be considered a treatable chronic medical condition, comparable to hypertension or diabetes,7 which requires a multifaceted treatment approach, including psychosocial, educational, and medical interventions.

Psychosocial Interventions

Individuals with OUD often have complicated social issues including stigmatization, involvement in the criminal justice system, unemployment, and homelessness,5,8-10 in addition to frequent comorbid mental health issues.11,12 Failure to address social or mental health barriers may lead to a lack of engagement in the treatment of OUD. The long-term management of OUD should involve outpatient psychotherapy and may include individual or group therapy, behavioral therapy, family counseling, or support groups.13 In the inpatient setting, hospitalists should use a collaborative approach to address psychosocial barriers. The authors recommend social work and case management consultations and consideration of psychiatric consultation when appropriate.

Management of Opioid Withdrawal

The prompt recognition and management of withdrawal is essential in hospitalized patients with OUD. The signs and symptoms of withdrawal can be evaluated by using the Clinical Opiate Withdrawal Scale or the Clinical Institute Narcotics Assessment, and may include lacrimation, rhinorrhea, diaphoresis, yawning, restlessness, insomnia, piloerection, myalgia, arthralgia, abdominal pain, nausea, vomiting, and diarrhea.4 Individuals using short-acting opioids, such as oxycodone or heroin, may develop withdrawal symptoms 8 to 12 hours after cessation of the opioid. Symptoms often peak on days 1 to 3 and can last for up to 10 days.14 Individuals taking long-acting opioids, such as methadone, may experience withdrawal symptoms for up to 21 days.14

While the goal of withdrawal treatment is to reduce the uncomfortable symptoms of withdrawal, there may be additional benefits. Around 16% of people who inject drugs will misuse drugs during their hospitalization, and 25% to 30% will be discharged against medical advice.15,16 In hospitalizations when patients are administered methadone for management of withdrawal, there is a significant reduction in discharges against medical advice.16 This may suggest that treatment of withdrawal has the added benefit of preventing discharges against medical advice, and the authors postulate that treatment may decrease surreptitious drug use during hospitalizations, although this has not been studied.

There are 2 approaches to treating opioid withdrawal—opioid substitution treatment and alpha2-adrenergic agonist treatment (Table 1).4,17-20 Of note, opioid substitution treatment, especially when using buprenorphine, should be started only when a patient has at least mild withdrawal symptoms.20

Treatment Options for Opioid Withdrawal
Table 1

An important exception to the treatment approach listed in Table 1 occurs when a patient is already taking methadone or buprenorphine maintenance therapy. In this circumstance, the outpatient dose should be continued after confirmation of dose and timing of last administration with outpatient clinicians. It is important that clear communication with the patient’s addiction clinician occurs at admission and discharge to prevent an inadvertently duplicated, or missed, dose.

Factors to consider when selecting a withdrawal treatment regimen include comorbidities, anticipated length of stay, anticipated discharge setting, medications, interest in long-term addiction treatment, and other patient-specific factors. In general, treatment with methadone or buprenorphine is preferred, because they are better tolerated and may be more effective than clonidine.21-24 The selection of methadone or buprenorphine is often based on physician or patient preference, presence of contraindications, or formulary restrictions, as they have similar efficacy in the treatment of opioid withdrawal.23 In cases where opioid replacement therapy is contraindicated, such as in an individual who has received naltrexone, clonidine should be used.24

Methadone and buprenorphine are controlled substances that can be prescribed only in outpatients by certified clinicians. Therefore, hospitalists are prohibited from prescribing these medications at discharge for the treatment of OUD. However, inpatient clinicians are exempt from these regulations and may provide both medications for maintenance and withdrawal treatment in the inpatient setting.

As such, while a 10 to 14-day taper may be optimal in preventing relapse and minimizing withdrawal, patients are often medically ready to leave the hospital before their taper is completed. In these cases, a rapid taper over 3 to 5 days can be considered. The disadvantage of a rapid taper is the potential for recrudescence of withdrawal symptoms after discharge. Individuals who do not tolerate a rapid taper should be treated with a slower taper, or transitioned to a clonidine taper.

Many hospitals have protocols to help guide the inpatient management of withdrawal, and in many cases, subspecialist consultation is not necessary. However, the authors recommend involvement of an addiction specialist for patients in whom management of withdrawal may be complicated. Further, we strongly encourage hospitalists to be involved in creation and maintenance of withdrawal treatment protocols.

 

 

Medication-Assisted Treatment

It is important to recognize that treatment of withdrawal is not adequate to prevent long-term opioid misuse.25 The optimal long-term management of OUD includes the use of medication-assisted treatment (MAT). The initiation and titration of MAT should always be done in conjunction with an addiction specialist or buprenorphine-waivered physician who will ensure continuation of MAT as an outpatient. This means that, while hospitalists may be critical in facilitating linkage to MAT, in general, they will not have a significant role in the long-term management of OUD. However, hospitalists should be knowledgeable about MAT because it is relatively common and can complicate hospitalizations.

There are two types of MAT: opioid-agonist treatment (OAT) and opioid-antagonist treatment. Opioid-agonist treatment involves the use of methadone, a long-acting opioid agonist, or buprenorphine, a long-acting partial opioid agonist. These medications decrease the amount and severity of cravings and limit the euphoric effects of subsequent opioid use.17 Compared to abstinence-based treatment, OAT has been associated with increased retention in addiction treatment and employment, and reductions in incarceration, human immunodeficiency virus transmission, illicit drug use, opioid-overdose events, and mortality.26-32An alternative to OAT is naltrexone, an opioid antagonist. Naltrexone for OUD is administered as a monthly depot injection that prevents the user from experiencing opioid intoxication or dependence, and is associated with sustained abstinence.17,33,34 The authors strongly recommend that hospitalists discuss the benefits of MAT with hospitalized individuals with OUD. In addition, when appropriate, patients should receive consultation with, or referral to, an addiction specialist.

Adverse Effects of Methadone, Buprenorphine, and Naltrexone

The benefits of MAT are substantial, but there are adverse effects, potential drug-to-drug interactions, and patient-specific characteristics that may impact the inpatient management of individuals on MAT. Selected adverse effects of OAT are listed in Table 1. The adverse effects of naltrexone include nausea, vomiting, and transaminitis. It should also be noted that the initiation of buprenorphine and naltrexone may induce opioid withdrawal when administered to an opioid-dependent patient with recent opioid use. To avoid precipitating withdrawal, buprenorphine should be used only in individuals who have at least mild withdrawal symptoms or have completed detoxification,20 and naltrexone should be used only in patients who have abstained from opioids for at least 7 to 10 days.35

Opioid-agonist treatments are primarily metabolized by the cytochrome P450 3A4 isoenzyme system. Medications that inhibit cytochrome P450 3A4 metabolism such as fluconazole can result in OAT toxicity, while medications that induce cytochrome P450 3A4 metabolism such as dexamethasone can lead to withdrawal symptoms.18 If these interactions are unavoidable, the dose of methadone or buprenorphine should be adjusted to prevent toxicity or withdrawal symptoms. The major drug interaction with naltrexone is ineffective analgesia from opioids.

Another major concern with MAT is the risk of overdose-related deaths. As an opioid agonist, large doses of methadone can result in respiratory depression, while buprenorphine alone, due to its partial agonist effect, is unlikely to result in respiratory depression. When methadone or buprenorphine are taken with other substances that cause respiratory depression, such as benzodiazepines or alcohol, the risk of respiratory depression and overdose is significantly increased.36,37 Overdose-related death with naltrexone usually occurs after the medication has metabolized and results from a loss of opioid tolerance.38

Special Populations

Medication-assisted treatment in individuals with acute pain. Maintenance treatment with OAT does not provide sufficient analgesia to treat episodes of acute pain.39 In patients on methadone maintenance, the maintenance dose should be continued and adjunctive analgesia should be provided with nonopioid analgesics or short-acting opioids.39 The management of acute pain in individuals on buprenorphine maintenance is more complicated since buprenorphine is a partial opioid agonist with high affinity to the opioid receptor, which limits the impact of adjunctive opioids. The options for analgesia in buprenorphine maintenance treatment include 1) continuing daily dosing of buprenorphine and providing nonopioid or opioid analgesics, 2) dividing buprenorphine dosing into a 3 or 4 times a day medication, 3) discontinuing buprenorphine and treating with opioid analgesics, 4) discontinuing buprenorphine and starting methadone with nonopioid or opioid analgesics.39 In cases where buprenorphine is discontinued, it should be restarted before discharge upon resolution of the acute pain episode. An individual with acute pain on naltrexone may require nonopioid analgesia or regional blocks. In these patients, adequate pain control may be challenging and require the consultation of an acute pain specialist.

Pregnant or breastfeeding individuals. Opioid misuse puts the individual and fetus at risk of complications, and abrupt discontinuation can cause preterm labor, fetal distress, or fetal demise.40 The current standard is to initiate methadone in consultation with an addiction specialist.40 There is evidence that buprenorphine can be used during pregnancy; however, buprenorphine-naloxone is discouraged.18,40 Of note, use of OAT in pregnancy can result in neonatal abstinence syndrome, an expected complication that can be managed by a pediatrician.40

Methadone and buprenorphine can be found in low concentrations in breast milk.41 However, according to the Academy of Breastfeeding Medicine’s clinical guidelines, women on stable doses of methadone and buprenorphine should be encouraged to breastfeed.41 Naltrexone enters breast milk and has potential adverse effects for the newborn. Either the mother should discontinue naltrexone or should not breastfeed.35

Treatment of polysubstance misuse. Individuals with OUD may also misuse other substances. The concomitant use of opioids and other central nervous system depressants, such as alcohol and benzodiazepines, is especially worrisome as they can potentiate respiratory depression. The presence of polysubstance misuse does not preclude the use of MAT for the treatment of OUD. In those with comorbid alcohol use disorder, the use of naltrexone may be appealing as it can treat both alcohol use disorder and OUD. Given the complexities of managing polysubstance misuse, addiction specialists should be involved in the care of these patients.42 In addition, patients should be educated on the risks of polysubstance misuse, especially when it involves 2 central nervous system depressants.

Comorbid medical disease. In general, medical comorbidities do not significantly affect the treatment of OUD; however, dysfunction of certain organ systems may necessitate a dose reduction or discontinuation of MAT. Severe liver disease may result in decreased hepatic metabolism of OAT.35,42 Prolonged QTc, or history of arrhythmia, may preclude the use of methadone.17,35,42 In addition, chronic hypercapnic respiratory failure or severe asthma may be contraindications for the use of methadone in an unmonitored setting.35 Kidney failure is not known to be a contraindication to MAT, and there is no consensus on the need for dose reduction of MAT with decreasing glomerular filtration rate; however, some authors recommend a 25% to 50% dose reduction of methadone when the glomerular filtration rate is less than 10 milliliters per minute.43 There is no such recommendation with buprenorphine, although it has not been adequately studied in individuals with renal failure. Close monitoring for evidence of toxicity is prudent in individuals on MAT with acute or chronic renal failure.35

Rural or resource-limited areas. There is a significant shortage of addiction treatment options in many regions of the United States. As of 2012, there were an estimated 2.3 million individuals with OUD; however, more than 1 million of these individuals do not have access to treatment.44 As a result, many addiction treatment programs have wait lists that can last months or even years.45 These shortages are especially apparent in rural areas, where individuals with OUD are particularly reliant upon buprenorphine treatment because of prohibitive travel times to urban-based programs.46 To address this problem, new models of care delivery are being developed, including models incorporating telemedicine to support rural primary care management of OUD.47

 

 

The Future of Medication-Assisted Treatment

Currently, MAT is initiated and managed by outpatient addiction specialists. However, evidence supports initiation of MAT as an inpatient.48 A recent study compared inpatient buprenorphine detoxification to inpatient buprenorphine induction, dose stabilization, and postdischarge linkage-of-care to outpatient opioid treatment clinics. Patients who received inpatient buprenorphine initiation and linkage-of-care had improved buprenorphine treatment retention and reported less illicit opioid use.48 The development of partnerships between hospitals, inpatient clinicians, and outpatient addiction specialists is essential and could lead to significant advances in treating hospitalized patients with OUD.

The initiation of MAT in hospitalized patients with immediate linkage-of-care shows great promise; however, at this point, the initiation of MAT should be done only in conjunction with addiction specialists in patients with confirmed outpatient follow-up. In cases where inpatient MAT initiation is pursued, education of staff including nurses and pharmacists is essential.

Harm Reduction Interventions

Ideally, management of OUD results in abstinence from opioid misuse; however, some individuals are not ready for treatment or, despite MAT, have relapses of opioid misuse. Given this, a secondary goal in the management of OUD is the reduction of harm that can result from opioid misuse.

Harm-Reduction Strategies
Table 2

Many individuals inject opioids, which is associated with increased rates of viral and bacterial infections secondary to nonsterile injection practices.49 Educating patients on sterile injection methods (Table 2),50 including the importance of sterile-injecting equipment and water, and cleaning the skin prior to injection, may mitigate the risk of infections and should be provided for all hospitalized people who inject drugs.

Syringe-exchange programs provide sterile-injecting equipment in exchange for used needles, with a goal of increasing access to sterile supplies and removing contaminated syringes from circulation.51 While controversial, these programs may reduce the incidence of human immunodeficiency virus, hepatitis C virus, and hepatitis B virus.51

In addition, syringe-exchange programs often provide addiction treatment referrals, counseling, testing, and prevention education for human immunodeficiency virus, hepatitis C virus, and sexually transmitted infections.49 In the United States, there are 226 programs in 33 states (see https://nasen.org/directory for a list of programs and locations. Inpatient clinicians should provide a list of local resources including syringe-exchange programs at the time of discharge for any people who inject drugs. In addition, individuals with OUD are at increased risk for overdose, especially in the postdischarge setting due to decreased opioid tolerance.52 In 2014, there were 28,647 opioid overdose-related deaths in the United States.2 To address this troubling epidemic, opioid overdose education and naloxone distribution has been championed to educate patients at risk of opioid overdose and potential first responders on how to counteract an overdose by using naloxone, an opioid antagonist (see Table 2 for more information on opioid overdose education). The use of opioid overdose education and naloxone distribution has been observed to reduce opioid overdose-related death rates.53

Hospitalists should provide opioid overdose education and naloxone to all individuals at risk of opioid overdose (including those with OUD), as well as potential first responders where the law allows (more information including individual state laws can be found at http://prescribetoprevent.org).20

Considerations at Discharge

There are a number of considerations for the hospitalist at discharge (see Table 3 for a recommended discharge checklist). In addition, it is important to appreciate, and minimize, the ways that hospitalists contribute to the opioid epidemic. For instance, prescribing opioids at discharge in opioid-naïve patients increases the risk of chronic opioid use.54 It is also essential to recognize that increased doses of opioids are associated with increased rates of opioid overdose-related deaths.55 As such, hospitalists should maximize the use of nonopioid analgesics, prescribe opioids only when necessary, use the smallest effective dose of opioids, limit the number of opioid pills distributed to patients, and check prescription-monitoring programs for evidence of misuse.

Discharge Checklist for Patients with Opioid Use Disorder
Table 3

CONCLUSION

Hospitalization serves as an important opportunity to address addiction in individuals with OUD. In addressing addiction, hospitalists should identify and intervene on psychosocial and mental health barriers, treat opioid withdrawal, and propagate harm reduction strategies. In addition, there is a growing role for hospitalists to be involved in the initiation of MAT and linkage-of-care to outpatient addiction treatment. If hospitalists become leaders in the inpatient management of OUD, they will significantly improve the care provided to this vulnerable patient population.

Disclosure

The authors report no financial conflicts of interest.

 

References

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15. Marks M, Pollock E, Armstrong M, et al. Needles and the damage done: reasons for admission and financial costs associated with injecting drug use in a Central London teaching hospital. J Infect. 2012;66(1):95-102. PubMed

16. Chan AC, Palepu A, Guh DP, et al. HIV-positive injection drug users who leave the hospital against medical advice: the mitigating role of methadone and social support. J Acquir Immune Defic Syndr. 2004;35(1):56-59. PubMed

17. Strain E. Pharmacotherapy for opioid use disorder. In: UpToDate, Herman R, ed. UpToDate, Waltham, MA. https://www.uptodate.com/contents/pharmacotherapy-for-opioid-use-disorderAccessed September 28, 2015.

18. Center for Substance Abuse Treatment. Clinical guidelines for the use of buprenorphine in the treatment of opioid addiction. Treatment Improvement Protocol (TIP) Series 40. DHHS Publication No. (SMA) 04-3939. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2004. PubMed

19. Weaver MF, Hopper JA. Medically supervised opioid withdrawal during treatment for addiction. In: UpToDate, Herman R, ed. UpToDate, Waltham, MA. https://www.uptodate.com/contents/medically-supervised-opioid-withdrawal-during-treatment-for-addiction Accessed on September 28, 2015.

20. Kampman K, Jarvis M. American Society of Addiction Medicine (ASAM) national practice guideline for the use of medications in the treatment of addiction involving opioid use. J Addict Med. 2015;9(5):358-367. PubMed

21. NICE Clinical Guidelines and National Collaborating Centre for Mental Health. Drug Misuse: Opioid Detoxification. British Psychological Society. 2008. https://www.nice.org.uk/guidance/cg52/evidence/drug-misuse-opioid-detoxification-full-guideline-196515037. Accessed April 12, 2017.

22. Amato L, Davoli M, Minozzi S, Ferroni E, Ali R, Ferri M. Methadone at tapered doses for the management of opioid withdrawal. Cochrane Database Syst Rev. 2013;2:CD003409. PubMed

23. Gowing L, Ali R, White J. Buprenorphine for the management of opioid withdrawal. Cochrane Database Syst Rev. 2009;3:CD002025. PubMed

24. Gowing L, Farrell M, Ali R, White JM. Alpha2-adrenergic agonists for the management of opioid withdrawal. Cochrane Database Syst Rev. 2016;5:CD002024. PubMed

25. Gossop M, Stewart D, Brown N, Marsden J. Factors associated with abstinence, lapse or relapse to heroin use after residential treatment: protective effect of coping responses. Addiction. 2002;97(10):1259-1267. PubMed

26. Farrell M, Ward J, Mattick R, et al. Methadone maintenance treatment in opiate dependence: a review. BMJ. 1994;309(6960):997-1001. PubMed

27. Connock M, Juarez Garcia A, Jowett S, et al. Methadone and buprenorphine for the management of opioid dependence: a systematic review and economic evaluation. Health Technol Assess. 2007;11(9):1–171. PubMed

28. Mattick RP, Breen C, Kimber J, Davoli M. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst Rev. 2009;3:CD002209. PubMed

29. Mattick RP, Breen C, Kimber J, Davoli M. Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database Syst Rev. 2014;2:CD002207. PubMed

30. Gowing LR, Farrell M, Bornemann R, Sullivan LE, Ali RL. Brief report: methadone treatment of injecting opioid users for prevention of HIV infection. J Gen Intern Med. 2006;21(2):193-195. PubMed

31. Nurco DN, Ball JC, Shaffer JW, Hanlon TE. The criminality of narcotic addicts. J Nerv Ment Dis. 1985;173(2):94-102. PubMed

32. Gibson A, Degenhardt L, Mattick RP, Ali R, White J, O’Brien S. Exposure to opioid maintenance treatment reduces long-term mortality. Addiction. 2008;103(3):462-468. PubMed

33. Minozzi S, Amato L, Vecchi S, Davoli M, Kirchmayer U, Verster A. Oral naltrexone maintenance treatment for opioid dependence. Cochrane Database Syst Rev. 2011;4:CD001333. PubMed

 

 

34. Krupitsky E, Nunes EV, Ling W, Illeperuma A, Gastfriend DR, Silverman BL. Injectable extended-release naltrexone for opioid dependence: a double-blind, placebo-controlled trial. Lancet. 2011;377(9776):1506-1513. PubMed

35. Substance Abuse and Mental Health Services Administration. Clinical Use of Extended-Release Injectable Naltrexone in the Treatment of Opioid Use Disorder: A Brief Guide. HHS Publication No. 14-4892R. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2015.

36. Caplehorn JR, Drummer OH. Fatal methadone toxicity: signs and circumstances, and the role of benzodiazepines. Aust N Z J Public Health. 2002;26(4):358-362. PubMed

37. Tracqui A, Kintz P, Ludes B. Buprenorphine-related deaths among drug addicts in France: a report on 20 fatalities. J Anal Toxicol. 1998;22(6):430-434. PubMed

38. Kelty E, Hulse G. Examination of mortality rates in a retrospective cohort of patients treated with oral or implant naltrexone for problematic opiate use. Addiction. 2012;107(1):1817-1824. PubMed

39. Alford DP, Compton P, Samet JH. Acute pain management for patients receiving maintenance methadone or buprenorphine therapy. Ann Intern Med. 2006;144(2):127-134. PubMed

40. ACOG Committee on Health Care for Underserved Women: American Society of Addiction Medicine. ACOG Committee Opinion No. 524: Opioid abuse, dependence, and addiction in pregnancy. Obstet Gynecol. 2012;119(5):1070-1076. PubMed

41. Reece-Stremtan S, Marinelli KA. ABM clinical protocol #21: guidelines for breastfeeding and substance use or substance use disorder, revised 2015. Breastfeed Med. 2015;10(3):135-141. PubMed

42. Center for Substance Abuse Treatment. Medication-Assisted Treatment for Opioid Addiction in Opioid Treatment Programs. Treatment Improvement Protocol (TIP) Series 43. HHS Publication No. 12-4214. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2005.

43. Brier ME, Aronoff GR (eds). Drug Prescribing in Renal Failure. 5thedition. Philadelphia, PA: American College of Physicians; 2007.

44. Jones CM, Campopiano M, Baldwin G, McCance-Katz E. National and state treatment need and capacity for opioid agonist medication-assisted treatment. Am J Public Health. 2015;105(8):e55-E63. PubMed

45. Sigmon SC. Access to treatment for opioid dependence in rural America: challenges and future directions. JAMA Psychiatry. 2014;71(4):359-360. PubMed

46. Rosenblatt RA, Andrilla CH, Catlin M, Larson EH. Geographic and specialty distribution of US physicians trained to treat opioid use disorder. Ann Fam Med. 2015;13(1):23-26. PubMed

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Journal of Hospital Medicine 12(5)
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The United States is experiencing an epidemic of nonmedical opioid use. A concerted effort to better address pain increased the provision of prescription narcotics in the late 1990s and early 2000s.1 Since then, there has been significant growth of opioid use and acorresponding increase in overdose-related deaths.1-3 Public health officials have responded with initiatives to secure the opioid supply and improve outpatient treatment resources. However, the role of hospitalists in addressing opioid use disorder (OUD) is not well established. The inpatient needs for these individuals are complex and require a collaborative approach with input from outpatient clinicians, inpatient clinicians, addiction specialists, social workers, and case managers. Hospitals are often under-resourced to provide such comprehensive services. This frequently results in the hospitalist bearing significant responsibility for inpatient addiction management despite often insufficient addiction education or experience.4,5

Therefore, there is a need for hospitalists to become leaders in the inpatient management of OUD. In this review, we will discuss the hospitalist’s role in the inpatient management of individuals with OUD.

INPATIENT MANAGEMENT OF OPIOID USE DISORDER

Opioid use disorder is a medical illness resulting from neurobiological changes that cause drug tolerance, dependence, and cravings.6 It should be considered a treatable chronic medical condition, comparable to hypertension or diabetes,7 which requires a multifaceted treatment approach, including psychosocial, educational, and medical interventions.

Psychosocial Interventions

Individuals with OUD often have complicated social issues including stigmatization, involvement in the criminal justice system, unemployment, and homelessness,5,8-10 in addition to frequent comorbid mental health issues.11,12 Failure to address social or mental health barriers may lead to a lack of engagement in the treatment of OUD. The long-term management of OUD should involve outpatient psychotherapy and may include individual or group therapy, behavioral therapy, family counseling, or support groups.13 In the inpatient setting, hospitalists should use a collaborative approach to address psychosocial barriers. The authors recommend social work and case management consultations and consideration of psychiatric consultation when appropriate.

Management of Opioid Withdrawal

The prompt recognition and management of withdrawal is essential in hospitalized patients with OUD. The signs and symptoms of withdrawal can be evaluated by using the Clinical Opiate Withdrawal Scale or the Clinical Institute Narcotics Assessment, and may include lacrimation, rhinorrhea, diaphoresis, yawning, restlessness, insomnia, piloerection, myalgia, arthralgia, abdominal pain, nausea, vomiting, and diarrhea.4 Individuals using short-acting opioids, such as oxycodone or heroin, may develop withdrawal symptoms 8 to 12 hours after cessation of the opioid. Symptoms often peak on days 1 to 3 and can last for up to 10 days.14 Individuals taking long-acting opioids, such as methadone, may experience withdrawal symptoms for up to 21 days.14

While the goal of withdrawal treatment is to reduce the uncomfortable symptoms of withdrawal, there may be additional benefits. Around 16% of people who inject drugs will misuse drugs during their hospitalization, and 25% to 30% will be discharged against medical advice.15,16 In hospitalizations when patients are administered methadone for management of withdrawal, there is a significant reduction in discharges against medical advice.16 This may suggest that treatment of withdrawal has the added benefit of preventing discharges against medical advice, and the authors postulate that treatment may decrease surreptitious drug use during hospitalizations, although this has not been studied.

There are 2 approaches to treating opioid withdrawal—opioid substitution treatment and alpha2-adrenergic agonist treatment (Table 1).4,17-20 Of note, opioid substitution treatment, especially when using buprenorphine, should be started only when a patient has at least mild withdrawal symptoms.20

Treatment Options for Opioid Withdrawal
Table 1

An important exception to the treatment approach listed in Table 1 occurs when a patient is already taking methadone or buprenorphine maintenance therapy. In this circumstance, the outpatient dose should be continued after confirmation of dose and timing of last administration with outpatient clinicians. It is important that clear communication with the patient’s addiction clinician occurs at admission and discharge to prevent an inadvertently duplicated, or missed, dose.

Factors to consider when selecting a withdrawal treatment regimen include comorbidities, anticipated length of stay, anticipated discharge setting, medications, interest in long-term addiction treatment, and other patient-specific factors. In general, treatment with methadone or buprenorphine is preferred, because they are better tolerated and may be more effective than clonidine.21-24 The selection of methadone or buprenorphine is often based on physician or patient preference, presence of contraindications, or formulary restrictions, as they have similar efficacy in the treatment of opioid withdrawal.23 In cases where opioid replacement therapy is contraindicated, such as in an individual who has received naltrexone, clonidine should be used.24

Methadone and buprenorphine are controlled substances that can be prescribed only in outpatients by certified clinicians. Therefore, hospitalists are prohibited from prescribing these medications at discharge for the treatment of OUD. However, inpatient clinicians are exempt from these regulations and may provide both medications for maintenance and withdrawal treatment in the inpatient setting.

As such, while a 10 to 14-day taper may be optimal in preventing relapse and minimizing withdrawal, patients are often medically ready to leave the hospital before their taper is completed. In these cases, a rapid taper over 3 to 5 days can be considered. The disadvantage of a rapid taper is the potential for recrudescence of withdrawal symptoms after discharge. Individuals who do not tolerate a rapid taper should be treated with a slower taper, or transitioned to a clonidine taper.

Many hospitals have protocols to help guide the inpatient management of withdrawal, and in many cases, subspecialist consultation is not necessary. However, the authors recommend involvement of an addiction specialist for patients in whom management of withdrawal may be complicated. Further, we strongly encourage hospitalists to be involved in creation and maintenance of withdrawal treatment protocols.

 

 

Medication-Assisted Treatment

It is important to recognize that treatment of withdrawal is not adequate to prevent long-term opioid misuse.25 The optimal long-term management of OUD includes the use of medication-assisted treatment (MAT). The initiation and titration of MAT should always be done in conjunction with an addiction specialist or buprenorphine-waivered physician who will ensure continuation of MAT as an outpatient. This means that, while hospitalists may be critical in facilitating linkage to MAT, in general, they will not have a significant role in the long-term management of OUD. However, hospitalists should be knowledgeable about MAT because it is relatively common and can complicate hospitalizations.

There are two types of MAT: opioid-agonist treatment (OAT) and opioid-antagonist treatment. Opioid-agonist treatment involves the use of methadone, a long-acting opioid agonist, or buprenorphine, a long-acting partial opioid agonist. These medications decrease the amount and severity of cravings and limit the euphoric effects of subsequent opioid use.17 Compared to abstinence-based treatment, OAT has been associated with increased retention in addiction treatment and employment, and reductions in incarceration, human immunodeficiency virus transmission, illicit drug use, opioid-overdose events, and mortality.26-32An alternative to OAT is naltrexone, an opioid antagonist. Naltrexone for OUD is administered as a monthly depot injection that prevents the user from experiencing opioid intoxication or dependence, and is associated with sustained abstinence.17,33,34 The authors strongly recommend that hospitalists discuss the benefits of MAT with hospitalized individuals with OUD. In addition, when appropriate, patients should receive consultation with, or referral to, an addiction specialist.

Adverse Effects of Methadone, Buprenorphine, and Naltrexone

The benefits of MAT are substantial, but there are adverse effects, potential drug-to-drug interactions, and patient-specific characteristics that may impact the inpatient management of individuals on MAT. Selected adverse effects of OAT are listed in Table 1. The adverse effects of naltrexone include nausea, vomiting, and transaminitis. It should also be noted that the initiation of buprenorphine and naltrexone may induce opioid withdrawal when administered to an opioid-dependent patient with recent opioid use. To avoid precipitating withdrawal, buprenorphine should be used only in individuals who have at least mild withdrawal symptoms or have completed detoxification,20 and naltrexone should be used only in patients who have abstained from opioids for at least 7 to 10 days.35

Opioid-agonist treatments are primarily metabolized by the cytochrome P450 3A4 isoenzyme system. Medications that inhibit cytochrome P450 3A4 metabolism such as fluconazole can result in OAT toxicity, while medications that induce cytochrome P450 3A4 metabolism such as dexamethasone can lead to withdrawal symptoms.18 If these interactions are unavoidable, the dose of methadone or buprenorphine should be adjusted to prevent toxicity or withdrawal symptoms. The major drug interaction with naltrexone is ineffective analgesia from opioids.

Another major concern with MAT is the risk of overdose-related deaths. As an opioid agonist, large doses of methadone can result in respiratory depression, while buprenorphine alone, due to its partial agonist effect, is unlikely to result in respiratory depression. When methadone or buprenorphine are taken with other substances that cause respiratory depression, such as benzodiazepines or alcohol, the risk of respiratory depression and overdose is significantly increased.36,37 Overdose-related death with naltrexone usually occurs after the medication has metabolized and results from a loss of opioid tolerance.38

Special Populations

Medication-assisted treatment in individuals with acute pain. Maintenance treatment with OAT does not provide sufficient analgesia to treat episodes of acute pain.39 In patients on methadone maintenance, the maintenance dose should be continued and adjunctive analgesia should be provided with nonopioid analgesics or short-acting opioids.39 The management of acute pain in individuals on buprenorphine maintenance is more complicated since buprenorphine is a partial opioid agonist with high affinity to the opioid receptor, which limits the impact of adjunctive opioids. The options for analgesia in buprenorphine maintenance treatment include 1) continuing daily dosing of buprenorphine and providing nonopioid or opioid analgesics, 2) dividing buprenorphine dosing into a 3 or 4 times a day medication, 3) discontinuing buprenorphine and treating with opioid analgesics, 4) discontinuing buprenorphine and starting methadone with nonopioid or opioid analgesics.39 In cases where buprenorphine is discontinued, it should be restarted before discharge upon resolution of the acute pain episode. An individual with acute pain on naltrexone may require nonopioid analgesia or regional blocks. In these patients, adequate pain control may be challenging and require the consultation of an acute pain specialist.

Pregnant or breastfeeding individuals. Opioid misuse puts the individual and fetus at risk of complications, and abrupt discontinuation can cause preterm labor, fetal distress, or fetal demise.40 The current standard is to initiate methadone in consultation with an addiction specialist.40 There is evidence that buprenorphine can be used during pregnancy; however, buprenorphine-naloxone is discouraged.18,40 Of note, use of OAT in pregnancy can result in neonatal abstinence syndrome, an expected complication that can be managed by a pediatrician.40

Methadone and buprenorphine can be found in low concentrations in breast milk.41 However, according to the Academy of Breastfeeding Medicine’s clinical guidelines, women on stable doses of methadone and buprenorphine should be encouraged to breastfeed.41 Naltrexone enters breast milk and has potential adverse effects for the newborn. Either the mother should discontinue naltrexone or should not breastfeed.35

Treatment of polysubstance misuse. Individuals with OUD may also misuse other substances. The concomitant use of opioids and other central nervous system depressants, such as alcohol and benzodiazepines, is especially worrisome as they can potentiate respiratory depression. The presence of polysubstance misuse does not preclude the use of MAT for the treatment of OUD. In those with comorbid alcohol use disorder, the use of naltrexone may be appealing as it can treat both alcohol use disorder and OUD. Given the complexities of managing polysubstance misuse, addiction specialists should be involved in the care of these patients.42 In addition, patients should be educated on the risks of polysubstance misuse, especially when it involves 2 central nervous system depressants.

Comorbid medical disease. In general, medical comorbidities do not significantly affect the treatment of OUD; however, dysfunction of certain organ systems may necessitate a dose reduction or discontinuation of MAT. Severe liver disease may result in decreased hepatic metabolism of OAT.35,42 Prolonged QTc, or history of arrhythmia, may preclude the use of methadone.17,35,42 In addition, chronic hypercapnic respiratory failure or severe asthma may be contraindications for the use of methadone in an unmonitored setting.35 Kidney failure is not known to be a contraindication to MAT, and there is no consensus on the need for dose reduction of MAT with decreasing glomerular filtration rate; however, some authors recommend a 25% to 50% dose reduction of methadone when the glomerular filtration rate is less than 10 milliliters per minute.43 There is no such recommendation with buprenorphine, although it has not been adequately studied in individuals with renal failure. Close monitoring for evidence of toxicity is prudent in individuals on MAT with acute or chronic renal failure.35

Rural or resource-limited areas. There is a significant shortage of addiction treatment options in many regions of the United States. As of 2012, there were an estimated 2.3 million individuals with OUD; however, more than 1 million of these individuals do not have access to treatment.44 As a result, many addiction treatment programs have wait lists that can last months or even years.45 These shortages are especially apparent in rural areas, where individuals with OUD are particularly reliant upon buprenorphine treatment because of prohibitive travel times to urban-based programs.46 To address this problem, new models of care delivery are being developed, including models incorporating telemedicine to support rural primary care management of OUD.47

 

 

The Future of Medication-Assisted Treatment

Currently, MAT is initiated and managed by outpatient addiction specialists. However, evidence supports initiation of MAT as an inpatient.48 A recent study compared inpatient buprenorphine detoxification to inpatient buprenorphine induction, dose stabilization, and postdischarge linkage-of-care to outpatient opioid treatment clinics. Patients who received inpatient buprenorphine initiation and linkage-of-care had improved buprenorphine treatment retention and reported less illicit opioid use.48 The development of partnerships between hospitals, inpatient clinicians, and outpatient addiction specialists is essential and could lead to significant advances in treating hospitalized patients with OUD.

The initiation of MAT in hospitalized patients with immediate linkage-of-care shows great promise; however, at this point, the initiation of MAT should be done only in conjunction with addiction specialists in patients with confirmed outpatient follow-up. In cases where inpatient MAT initiation is pursued, education of staff including nurses and pharmacists is essential.

Harm Reduction Interventions

Ideally, management of OUD results in abstinence from opioid misuse; however, some individuals are not ready for treatment or, despite MAT, have relapses of opioid misuse. Given this, a secondary goal in the management of OUD is the reduction of harm that can result from opioid misuse.

Harm-Reduction Strategies
Table 2

Many individuals inject opioids, which is associated with increased rates of viral and bacterial infections secondary to nonsterile injection practices.49 Educating patients on sterile injection methods (Table 2),50 including the importance of sterile-injecting equipment and water, and cleaning the skin prior to injection, may mitigate the risk of infections and should be provided for all hospitalized people who inject drugs.

Syringe-exchange programs provide sterile-injecting equipment in exchange for used needles, with a goal of increasing access to sterile supplies and removing contaminated syringes from circulation.51 While controversial, these programs may reduce the incidence of human immunodeficiency virus, hepatitis C virus, and hepatitis B virus.51

In addition, syringe-exchange programs often provide addiction treatment referrals, counseling, testing, and prevention education for human immunodeficiency virus, hepatitis C virus, and sexually transmitted infections.49 In the United States, there are 226 programs in 33 states (see https://nasen.org/directory for a list of programs and locations. Inpatient clinicians should provide a list of local resources including syringe-exchange programs at the time of discharge for any people who inject drugs. In addition, individuals with OUD are at increased risk for overdose, especially in the postdischarge setting due to decreased opioid tolerance.52 In 2014, there were 28,647 opioid overdose-related deaths in the United States.2 To address this troubling epidemic, opioid overdose education and naloxone distribution has been championed to educate patients at risk of opioid overdose and potential first responders on how to counteract an overdose by using naloxone, an opioid antagonist (see Table 2 for more information on opioid overdose education). The use of opioid overdose education and naloxone distribution has been observed to reduce opioid overdose-related death rates.53

Hospitalists should provide opioid overdose education and naloxone to all individuals at risk of opioid overdose (including those with OUD), as well as potential first responders where the law allows (more information including individual state laws can be found at http://prescribetoprevent.org).20

Considerations at Discharge

There are a number of considerations for the hospitalist at discharge (see Table 3 for a recommended discharge checklist). In addition, it is important to appreciate, and minimize, the ways that hospitalists contribute to the opioid epidemic. For instance, prescribing opioids at discharge in opioid-naïve patients increases the risk of chronic opioid use.54 It is also essential to recognize that increased doses of opioids are associated with increased rates of opioid overdose-related deaths.55 As such, hospitalists should maximize the use of nonopioid analgesics, prescribe opioids only when necessary, use the smallest effective dose of opioids, limit the number of opioid pills distributed to patients, and check prescription-monitoring programs for evidence of misuse.

Discharge Checklist for Patients with Opioid Use Disorder
Table 3

CONCLUSION

Hospitalization serves as an important opportunity to address addiction in individuals with OUD. In addressing addiction, hospitalists should identify and intervene on psychosocial and mental health barriers, treat opioid withdrawal, and propagate harm reduction strategies. In addition, there is a growing role for hospitalists to be involved in the initiation of MAT and linkage-of-care to outpatient addiction treatment. If hospitalists become leaders in the inpatient management of OUD, they will significantly improve the care provided to this vulnerable patient population.

Disclosure

The authors report no financial conflicts of interest.

 

The United States is experiencing an epidemic of nonmedical opioid use. A concerted effort to better address pain increased the provision of prescription narcotics in the late 1990s and early 2000s.1 Since then, there has been significant growth of opioid use and acorresponding increase in overdose-related deaths.1-3 Public health officials have responded with initiatives to secure the opioid supply and improve outpatient treatment resources. However, the role of hospitalists in addressing opioid use disorder (OUD) is not well established. The inpatient needs for these individuals are complex and require a collaborative approach with input from outpatient clinicians, inpatient clinicians, addiction specialists, social workers, and case managers. Hospitals are often under-resourced to provide such comprehensive services. This frequently results in the hospitalist bearing significant responsibility for inpatient addiction management despite often insufficient addiction education or experience.4,5

Therefore, there is a need for hospitalists to become leaders in the inpatient management of OUD. In this review, we will discuss the hospitalist’s role in the inpatient management of individuals with OUD.

INPATIENT MANAGEMENT OF OPIOID USE DISORDER

Opioid use disorder is a medical illness resulting from neurobiological changes that cause drug tolerance, dependence, and cravings.6 It should be considered a treatable chronic medical condition, comparable to hypertension or diabetes,7 which requires a multifaceted treatment approach, including psychosocial, educational, and medical interventions.

Psychosocial Interventions

Individuals with OUD often have complicated social issues including stigmatization, involvement in the criminal justice system, unemployment, and homelessness,5,8-10 in addition to frequent comorbid mental health issues.11,12 Failure to address social or mental health barriers may lead to a lack of engagement in the treatment of OUD. The long-term management of OUD should involve outpatient psychotherapy and may include individual or group therapy, behavioral therapy, family counseling, or support groups.13 In the inpatient setting, hospitalists should use a collaborative approach to address psychosocial barriers. The authors recommend social work and case management consultations and consideration of psychiatric consultation when appropriate.

Management of Opioid Withdrawal

The prompt recognition and management of withdrawal is essential in hospitalized patients with OUD. The signs and symptoms of withdrawal can be evaluated by using the Clinical Opiate Withdrawal Scale or the Clinical Institute Narcotics Assessment, and may include lacrimation, rhinorrhea, diaphoresis, yawning, restlessness, insomnia, piloerection, myalgia, arthralgia, abdominal pain, nausea, vomiting, and diarrhea.4 Individuals using short-acting opioids, such as oxycodone or heroin, may develop withdrawal symptoms 8 to 12 hours after cessation of the opioid. Symptoms often peak on days 1 to 3 and can last for up to 10 days.14 Individuals taking long-acting opioids, such as methadone, may experience withdrawal symptoms for up to 21 days.14

While the goal of withdrawal treatment is to reduce the uncomfortable symptoms of withdrawal, there may be additional benefits. Around 16% of people who inject drugs will misuse drugs during their hospitalization, and 25% to 30% will be discharged against medical advice.15,16 In hospitalizations when patients are administered methadone for management of withdrawal, there is a significant reduction in discharges against medical advice.16 This may suggest that treatment of withdrawal has the added benefit of preventing discharges against medical advice, and the authors postulate that treatment may decrease surreptitious drug use during hospitalizations, although this has not been studied.

There are 2 approaches to treating opioid withdrawal—opioid substitution treatment and alpha2-adrenergic agonist treatment (Table 1).4,17-20 Of note, opioid substitution treatment, especially when using buprenorphine, should be started only when a patient has at least mild withdrawal symptoms.20

Treatment Options for Opioid Withdrawal
Table 1

An important exception to the treatment approach listed in Table 1 occurs when a patient is already taking methadone or buprenorphine maintenance therapy. In this circumstance, the outpatient dose should be continued after confirmation of dose and timing of last administration with outpatient clinicians. It is important that clear communication with the patient’s addiction clinician occurs at admission and discharge to prevent an inadvertently duplicated, or missed, dose.

Factors to consider when selecting a withdrawal treatment regimen include comorbidities, anticipated length of stay, anticipated discharge setting, medications, interest in long-term addiction treatment, and other patient-specific factors. In general, treatment with methadone or buprenorphine is preferred, because they are better tolerated and may be more effective than clonidine.21-24 The selection of methadone or buprenorphine is often based on physician or patient preference, presence of contraindications, or formulary restrictions, as they have similar efficacy in the treatment of opioid withdrawal.23 In cases where opioid replacement therapy is contraindicated, such as in an individual who has received naltrexone, clonidine should be used.24

Methadone and buprenorphine are controlled substances that can be prescribed only in outpatients by certified clinicians. Therefore, hospitalists are prohibited from prescribing these medications at discharge for the treatment of OUD. However, inpatient clinicians are exempt from these regulations and may provide both medications for maintenance and withdrawal treatment in the inpatient setting.

As such, while a 10 to 14-day taper may be optimal in preventing relapse and minimizing withdrawal, patients are often medically ready to leave the hospital before their taper is completed. In these cases, a rapid taper over 3 to 5 days can be considered. The disadvantage of a rapid taper is the potential for recrudescence of withdrawal symptoms after discharge. Individuals who do not tolerate a rapid taper should be treated with a slower taper, or transitioned to a clonidine taper.

Many hospitals have protocols to help guide the inpatient management of withdrawal, and in many cases, subspecialist consultation is not necessary. However, the authors recommend involvement of an addiction specialist for patients in whom management of withdrawal may be complicated. Further, we strongly encourage hospitalists to be involved in creation and maintenance of withdrawal treatment protocols.

 

 

Medication-Assisted Treatment

It is important to recognize that treatment of withdrawal is not adequate to prevent long-term opioid misuse.25 The optimal long-term management of OUD includes the use of medication-assisted treatment (MAT). The initiation and titration of MAT should always be done in conjunction with an addiction specialist or buprenorphine-waivered physician who will ensure continuation of MAT as an outpatient. This means that, while hospitalists may be critical in facilitating linkage to MAT, in general, they will not have a significant role in the long-term management of OUD. However, hospitalists should be knowledgeable about MAT because it is relatively common and can complicate hospitalizations.

There are two types of MAT: opioid-agonist treatment (OAT) and opioid-antagonist treatment. Opioid-agonist treatment involves the use of methadone, a long-acting opioid agonist, or buprenorphine, a long-acting partial opioid agonist. These medications decrease the amount and severity of cravings and limit the euphoric effects of subsequent opioid use.17 Compared to abstinence-based treatment, OAT has been associated with increased retention in addiction treatment and employment, and reductions in incarceration, human immunodeficiency virus transmission, illicit drug use, opioid-overdose events, and mortality.26-32An alternative to OAT is naltrexone, an opioid antagonist. Naltrexone for OUD is administered as a monthly depot injection that prevents the user from experiencing opioid intoxication or dependence, and is associated with sustained abstinence.17,33,34 The authors strongly recommend that hospitalists discuss the benefits of MAT with hospitalized individuals with OUD. In addition, when appropriate, patients should receive consultation with, or referral to, an addiction specialist.

Adverse Effects of Methadone, Buprenorphine, and Naltrexone

The benefits of MAT are substantial, but there are adverse effects, potential drug-to-drug interactions, and patient-specific characteristics that may impact the inpatient management of individuals on MAT. Selected adverse effects of OAT are listed in Table 1. The adverse effects of naltrexone include nausea, vomiting, and transaminitis. It should also be noted that the initiation of buprenorphine and naltrexone may induce opioid withdrawal when administered to an opioid-dependent patient with recent opioid use. To avoid precipitating withdrawal, buprenorphine should be used only in individuals who have at least mild withdrawal symptoms or have completed detoxification,20 and naltrexone should be used only in patients who have abstained from opioids for at least 7 to 10 days.35

Opioid-agonist treatments are primarily metabolized by the cytochrome P450 3A4 isoenzyme system. Medications that inhibit cytochrome P450 3A4 metabolism such as fluconazole can result in OAT toxicity, while medications that induce cytochrome P450 3A4 metabolism such as dexamethasone can lead to withdrawal symptoms.18 If these interactions are unavoidable, the dose of methadone or buprenorphine should be adjusted to prevent toxicity or withdrawal symptoms. The major drug interaction with naltrexone is ineffective analgesia from opioids.

Another major concern with MAT is the risk of overdose-related deaths. As an opioid agonist, large doses of methadone can result in respiratory depression, while buprenorphine alone, due to its partial agonist effect, is unlikely to result in respiratory depression. When methadone or buprenorphine are taken with other substances that cause respiratory depression, such as benzodiazepines or alcohol, the risk of respiratory depression and overdose is significantly increased.36,37 Overdose-related death with naltrexone usually occurs after the medication has metabolized and results from a loss of opioid tolerance.38

Special Populations

Medication-assisted treatment in individuals with acute pain. Maintenance treatment with OAT does not provide sufficient analgesia to treat episodes of acute pain.39 In patients on methadone maintenance, the maintenance dose should be continued and adjunctive analgesia should be provided with nonopioid analgesics or short-acting opioids.39 The management of acute pain in individuals on buprenorphine maintenance is more complicated since buprenorphine is a partial opioid agonist with high affinity to the opioid receptor, which limits the impact of adjunctive opioids. The options for analgesia in buprenorphine maintenance treatment include 1) continuing daily dosing of buprenorphine and providing nonopioid or opioid analgesics, 2) dividing buprenorphine dosing into a 3 or 4 times a day medication, 3) discontinuing buprenorphine and treating with opioid analgesics, 4) discontinuing buprenorphine and starting methadone with nonopioid or opioid analgesics.39 In cases where buprenorphine is discontinued, it should be restarted before discharge upon resolution of the acute pain episode. An individual with acute pain on naltrexone may require nonopioid analgesia or regional blocks. In these patients, adequate pain control may be challenging and require the consultation of an acute pain specialist.

Pregnant or breastfeeding individuals. Opioid misuse puts the individual and fetus at risk of complications, and abrupt discontinuation can cause preterm labor, fetal distress, or fetal demise.40 The current standard is to initiate methadone in consultation with an addiction specialist.40 There is evidence that buprenorphine can be used during pregnancy; however, buprenorphine-naloxone is discouraged.18,40 Of note, use of OAT in pregnancy can result in neonatal abstinence syndrome, an expected complication that can be managed by a pediatrician.40

Methadone and buprenorphine can be found in low concentrations in breast milk.41 However, according to the Academy of Breastfeeding Medicine’s clinical guidelines, women on stable doses of methadone and buprenorphine should be encouraged to breastfeed.41 Naltrexone enters breast milk and has potential adverse effects for the newborn. Either the mother should discontinue naltrexone or should not breastfeed.35

Treatment of polysubstance misuse. Individuals with OUD may also misuse other substances. The concomitant use of opioids and other central nervous system depressants, such as alcohol and benzodiazepines, is especially worrisome as they can potentiate respiratory depression. The presence of polysubstance misuse does not preclude the use of MAT for the treatment of OUD. In those with comorbid alcohol use disorder, the use of naltrexone may be appealing as it can treat both alcohol use disorder and OUD. Given the complexities of managing polysubstance misuse, addiction specialists should be involved in the care of these patients.42 In addition, patients should be educated on the risks of polysubstance misuse, especially when it involves 2 central nervous system depressants.

Comorbid medical disease. In general, medical comorbidities do not significantly affect the treatment of OUD; however, dysfunction of certain organ systems may necessitate a dose reduction or discontinuation of MAT. Severe liver disease may result in decreased hepatic metabolism of OAT.35,42 Prolonged QTc, or history of arrhythmia, may preclude the use of methadone.17,35,42 In addition, chronic hypercapnic respiratory failure or severe asthma may be contraindications for the use of methadone in an unmonitored setting.35 Kidney failure is not known to be a contraindication to MAT, and there is no consensus on the need for dose reduction of MAT with decreasing glomerular filtration rate; however, some authors recommend a 25% to 50% dose reduction of methadone when the glomerular filtration rate is less than 10 milliliters per minute.43 There is no such recommendation with buprenorphine, although it has not been adequately studied in individuals with renal failure. Close monitoring for evidence of toxicity is prudent in individuals on MAT with acute or chronic renal failure.35

Rural or resource-limited areas. There is a significant shortage of addiction treatment options in many regions of the United States. As of 2012, there were an estimated 2.3 million individuals with OUD; however, more than 1 million of these individuals do not have access to treatment.44 As a result, many addiction treatment programs have wait lists that can last months or even years.45 These shortages are especially apparent in rural areas, where individuals with OUD are particularly reliant upon buprenorphine treatment because of prohibitive travel times to urban-based programs.46 To address this problem, new models of care delivery are being developed, including models incorporating telemedicine to support rural primary care management of OUD.47

 

 

The Future of Medication-Assisted Treatment

Currently, MAT is initiated and managed by outpatient addiction specialists. However, evidence supports initiation of MAT as an inpatient.48 A recent study compared inpatient buprenorphine detoxification to inpatient buprenorphine induction, dose stabilization, and postdischarge linkage-of-care to outpatient opioid treatment clinics. Patients who received inpatient buprenorphine initiation and linkage-of-care had improved buprenorphine treatment retention and reported less illicit opioid use.48 The development of partnerships between hospitals, inpatient clinicians, and outpatient addiction specialists is essential and could lead to significant advances in treating hospitalized patients with OUD.

The initiation of MAT in hospitalized patients with immediate linkage-of-care shows great promise; however, at this point, the initiation of MAT should be done only in conjunction with addiction specialists in patients with confirmed outpatient follow-up. In cases where inpatient MAT initiation is pursued, education of staff including nurses and pharmacists is essential.

Harm Reduction Interventions

Ideally, management of OUD results in abstinence from opioid misuse; however, some individuals are not ready for treatment or, despite MAT, have relapses of opioid misuse. Given this, a secondary goal in the management of OUD is the reduction of harm that can result from opioid misuse.

Harm-Reduction Strategies
Table 2

Many individuals inject opioids, which is associated with increased rates of viral and bacterial infections secondary to nonsterile injection practices.49 Educating patients on sterile injection methods (Table 2),50 including the importance of sterile-injecting equipment and water, and cleaning the skin prior to injection, may mitigate the risk of infections and should be provided for all hospitalized people who inject drugs.

Syringe-exchange programs provide sterile-injecting equipment in exchange for used needles, with a goal of increasing access to sterile supplies and removing contaminated syringes from circulation.51 While controversial, these programs may reduce the incidence of human immunodeficiency virus, hepatitis C virus, and hepatitis B virus.51

In addition, syringe-exchange programs often provide addiction treatment referrals, counseling, testing, and prevention education for human immunodeficiency virus, hepatitis C virus, and sexually transmitted infections.49 In the United States, there are 226 programs in 33 states (see https://nasen.org/directory for a list of programs and locations. Inpatient clinicians should provide a list of local resources including syringe-exchange programs at the time of discharge for any people who inject drugs. In addition, individuals with OUD are at increased risk for overdose, especially in the postdischarge setting due to decreased opioid tolerance.52 In 2014, there were 28,647 opioid overdose-related deaths in the United States.2 To address this troubling epidemic, opioid overdose education and naloxone distribution has been championed to educate patients at risk of opioid overdose and potential first responders on how to counteract an overdose by using naloxone, an opioid antagonist (see Table 2 for more information on opioid overdose education). The use of opioid overdose education and naloxone distribution has been observed to reduce opioid overdose-related death rates.53

Hospitalists should provide opioid overdose education and naloxone to all individuals at risk of opioid overdose (including those with OUD), as well as potential first responders where the law allows (more information including individual state laws can be found at http://prescribetoprevent.org).20

Considerations at Discharge

There are a number of considerations for the hospitalist at discharge (see Table 3 for a recommended discharge checklist). In addition, it is important to appreciate, and minimize, the ways that hospitalists contribute to the opioid epidemic. For instance, prescribing opioids at discharge in opioid-naïve patients increases the risk of chronic opioid use.54 It is also essential to recognize that increased doses of opioids are associated with increased rates of opioid overdose-related deaths.55 As such, hospitalists should maximize the use of nonopioid analgesics, prescribe opioids only when necessary, use the smallest effective dose of opioids, limit the number of opioid pills distributed to patients, and check prescription-monitoring programs for evidence of misuse.

Discharge Checklist for Patients with Opioid Use Disorder
Table 3

CONCLUSION

Hospitalization serves as an important opportunity to address addiction in individuals with OUD. In addressing addiction, hospitalists should identify and intervene on psychosocial and mental health barriers, treat opioid withdrawal, and propagate harm reduction strategies. In addition, there is a growing role for hospitalists to be involved in the initiation of MAT and linkage-of-care to outpatient addiction treatment. If hospitalists become leaders in the inpatient management of OUD, they will significantly improve the care provided to this vulnerable patient population.

Disclosure

The authors report no financial conflicts of interest.

 

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22. Amato L, Davoli M, Minozzi S, Ferroni E, Ali R, Ferri M. Methadone at tapered doses for the management of opioid withdrawal. Cochrane Database Syst Rev. 2013;2:CD003409. PubMed

23. Gowing L, Ali R, White J. Buprenorphine for the management of opioid withdrawal. Cochrane Database Syst Rev. 2009;3:CD002025. PubMed

24. Gowing L, Farrell M, Ali R, White JM. Alpha2-adrenergic agonists for the management of opioid withdrawal. Cochrane Database Syst Rev. 2016;5:CD002024. PubMed

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28. Mattick RP, Breen C, Kimber J, Davoli M. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst Rev. 2009;3:CD002209. PubMed

29. Mattick RP, Breen C, Kimber J, Davoli M. Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database Syst Rev. 2014;2:CD002207. PubMed

30. Gowing LR, Farrell M, Bornemann R, Sullivan LE, Ali RL. Brief report: methadone treatment of injecting opioid users for prevention of HIV infection. J Gen Intern Med. 2006;21(2):193-195. PubMed

31. Nurco DN, Ball JC, Shaffer JW, Hanlon TE. The criminality of narcotic addicts. J Nerv Ment Dis. 1985;173(2):94-102. PubMed

32. Gibson A, Degenhardt L, Mattick RP, Ali R, White J, O’Brien S. Exposure to opioid maintenance treatment reduces long-term mortality. Addiction. 2008;103(3):462-468. PubMed

33. Minozzi S, Amato L, Vecchi S, Davoli M, Kirchmayer U, Verster A. Oral naltrexone maintenance treatment for opioid dependence. Cochrane Database Syst Rev. 2011;4:CD001333. PubMed

 

 

34. Krupitsky E, Nunes EV, Ling W, Illeperuma A, Gastfriend DR, Silverman BL. Injectable extended-release naltrexone for opioid dependence: a double-blind, placebo-controlled trial. Lancet. 2011;377(9776):1506-1513. PubMed

35. Substance Abuse and Mental Health Services Administration. Clinical Use of Extended-Release Injectable Naltrexone in the Treatment of Opioid Use Disorder: A Brief Guide. HHS Publication No. 14-4892R. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2015.

36. Caplehorn JR, Drummer OH. Fatal methadone toxicity: signs and circumstances, and the role of benzodiazepines. Aust N Z J Public Health. 2002;26(4):358-362. PubMed

37. Tracqui A, Kintz P, Ludes B. Buprenorphine-related deaths among drug addicts in France: a report on 20 fatalities. J Anal Toxicol. 1998;22(6):430-434. PubMed

38. Kelty E, Hulse G. Examination of mortality rates in a retrospective cohort of patients treated with oral or implant naltrexone for problematic opiate use. Addiction. 2012;107(1):1817-1824. PubMed

39. Alford DP, Compton P, Samet JH. Acute pain management for patients receiving maintenance methadone or buprenorphine therapy. Ann Intern Med. 2006;144(2):127-134. PubMed

40. ACOG Committee on Health Care for Underserved Women: American Society of Addiction Medicine. ACOG Committee Opinion No. 524: Opioid abuse, dependence, and addiction in pregnancy. Obstet Gynecol. 2012;119(5):1070-1076. PubMed

41. Reece-Stremtan S, Marinelli KA. ABM clinical protocol #21: guidelines for breastfeeding and substance use or substance use disorder, revised 2015. Breastfeed Med. 2015;10(3):135-141. PubMed

42. Center for Substance Abuse Treatment. Medication-Assisted Treatment for Opioid Addiction in Opioid Treatment Programs. Treatment Improvement Protocol (TIP) Series 43. HHS Publication No. 12-4214. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2005.

43. Brier ME, Aronoff GR (eds). Drug Prescribing in Renal Failure. 5thedition. Philadelphia, PA: American College of Physicians; 2007.

44. Jones CM, Campopiano M, Baldwin G, McCance-Katz E. National and state treatment need and capacity for opioid agonist medication-assisted treatment. Am J Public Health. 2015;105(8):e55-E63. PubMed

45. Sigmon SC. Access to treatment for opioid dependence in rural America: challenges and future directions. JAMA Psychiatry. 2014;71(4):359-360. PubMed

46. Rosenblatt RA, Andrilla CH, Catlin M, Larson EH. Geographic and specialty distribution of US physicians trained to treat opioid use disorder. Ann Fam Med. 2015;13(1):23-26. PubMed

47. Komaromy M, Duhigg D, Metcalf A, et al. Project ECHO (Extension for Community Healthcare Outcomes): A new model for educating primary care providers about treatment of substance use disorders. Subst Abus. 2016;37(1):20-24. PubMed

48. Liebschutz JM, Crooks D, Herman D, et al. Buprenorphine treatment for hospitalized, opioid-dependent patients: a randomized clinical trial. JAMA Intern Med. 2014;174(8):1369-1376. PubMed

49. Centers for Disease Control and Prevention (CDC). Syringe exchange programs – United States, 2008. MMWR Morb Mortal Wkly Rep. 2010;59(45):1488-1491. PubMed

50. Harm Reduction Coalition. Getting off right: A safety manual for injection drug users. New York, NY: Harm Reduction Coalition; 1998.

51. Vlahov D, Junge B. The role of needle exchange programs in HIV prevention. Public Health Rep. 1998.113(suppl 1):75-80. PubMed

52. Strang J, McCambridge J, Best D, et al. Loss of tolerance and overdose mortality after inpatient opiate detoxification: follow up study. BMJ. 2003;326(7396):959-960. PubMed

53. Walley AY, Xuan Z, Hackman HH, et al. Opioid overdose rates and implementation of overdose education and nasal naloxone distribution in Massachusetts: interrupted time series analysis. BMJ. 2013;346:f174. PubMed

54. Calcaterra SL, Yamashita TE, Min SJ, Keniston A, Frank JW, Binswnager IA. Opioid prescribing at hospital discharge contributes to chronic opioid use. J Gen Intern Med. 2016;31(5):478-485. PubMed

55. Dunn KM, Saunders KW, Rutter CM, Banta-Green CJ, Merrill JO, Sullivan MD, et al. Opioid prescriptions for chronic pain and overdose: a cohort study. Ann Intern Med. 2010;152(2):85-92. PubMed

 

 

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17. Strain E. Pharmacotherapy for opioid use disorder. In: UpToDate, Herman R, ed. UpToDate, Waltham, MA. https://www.uptodate.com/contents/pharmacotherapy-for-opioid-use-disorderAccessed September 28, 2015.

18. Center for Substance Abuse Treatment. Clinical guidelines for the use of buprenorphine in the treatment of opioid addiction. Treatment Improvement Protocol (TIP) Series 40. DHHS Publication No. (SMA) 04-3939. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2004. PubMed

19. Weaver MF, Hopper JA. Medically supervised opioid withdrawal during treatment for addiction. In: UpToDate, Herman R, ed. UpToDate, Waltham, MA. https://www.uptodate.com/contents/medically-supervised-opioid-withdrawal-during-treatment-for-addiction Accessed on September 28, 2015.

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21. NICE Clinical Guidelines and National Collaborating Centre for Mental Health. Drug Misuse: Opioid Detoxification. British Psychological Society. 2008. https://www.nice.org.uk/guidance/cg52/evidence/drug-misuse-opioid-detoxification-full-guideline-196515037. Accessed April 12, 2017.

22. Amato L, Davoli M, Minozzi S, Ferroni E, Ali R, Ferri M. Methadone at tapered doses for the management of opioid withdrawal. Cochrane Database Syst Rev. 2013;2:CD003409. PubMed

23. Gowing L, Ali R, White J. Buprenorphine for the management of opioid withdrawal. Cochrane Database Syst Rev. 2009;3:CD002025. PubMed

24. Gowing L, Farrell M, Ali R, White JM. Alpha2-adrenergic agonists for the management of opioid withdrawal. Cochrane Database Syst Rev. 2016;5:CD002024. PubMed

25. Gossop M, Stewart D, Brown N, Marsden J. Factors associated with abstinence, lapse or relapse to heroin use after residential treatment: protective effect of coping responses. Addiction. 2002;97(10):1259-1267. PubMed

26. Farrell M, Ward J, Mattick R, et al. Methadone maintenance treatment in opiate dependence: a review. BMJ. 1994;309(6960):997-1001. PubMed

27. Connock M, Juarez Garcia A, Jowett S, et al. Methadone and buprenorphine for the management of opioid dependence: a systematic review and economic evaluation. Health Technol Assess. 2007;11(9):1–171. PubMed

28. Mattick RP, Breen C, Kimber J, Davoli M. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst Rev. 2009;3:CD002209. PubMed

29. Mattick RP, Breen C, Kimber J, Davoli M. Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database Syst Rev. 2014;2:CD002207. PubMed

30. Gowing LR, Farrell M, Bornemann R, Sullivan LE, Ali RL. Brief report: methadone treatment of injecting opioid users for prevention of HIV infection. J Gen Intern Med. 2006;21(2):193-195. PubMed

31. Nurco DN, Ball JC, Shaffer JW, Hanlon TE. The criminality of narcotic addicts. J Nerv Ment Dis. 1985;173(2):94-102. PubMed

32. Gibson A, Degenhardt L, Mattick RP, Ali R, White J, O’Brien S. Exposure to opioid maintenance treatment reduces long-term mortality. Addiction. 2008;103(3):462-468. PubMed

33. Minozzi S, Amato L, Vecchi S, Davoli M, Kirchmayer U, Verster A. Oral naltrexone maintenance treatment for opioid dependence. Cochrane Database Syst Rev. 2011;4:CD001333. PubMed

 

 

34. Krupitsky E, Nunes EV, Ling W, Illeperuma A, Gastfriend DR, Silverman BL. Injectable extended-release naltrexone for opioid dependence: a double-blind, placebo-controlled trial. Lancet. 2011;377(9776):1506-1513. PubMed

35. Substance Abuse and Mental Health Services Administration. Clinical Use of Extended-Release Injectable Naltrexone in the Treatment of Opioid Use Disorder: A Brief Guide. HHS Publication No. 14-4892R. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2015.

36. Caplehorn JR, Drummer OH. Fatal methadone toxicity: signs and circumstances, and the role of benzodiazepines. Aust N Z J Public Health. 2002;26(4):358-362. PubMed

37. Tracqui A, Kintz P, Ludes B. Buprenorphine-related deaths among drug addicts in France: a report on 20 fatalities. J Anal Toxicol. 1998;22(6):430-434. PubMed

38. Kelty E, Hulse G. Examination of mortality rates in a retrospective cohort of patients treated with oral or implant naltrexone for problematic opiate use. Addiction. 2012;107(1):1817-1824. PubMed

39. Alford DP, Compton P, Samet JH. Acute pain management for patients receiving maintenance methadone or buprenorphine therapy. Ann Intern Med. 2006;144(2):127-134. PubMed

40. ACOG Committee on Health Care for Underserved Women: American Society of Addiction Medicine. ACOG Committee Opinion No. 524: Opioid abuse, dependence, and addiction in pregnancy. Obstet Gynecol. 2012;119(5):1070-1076. PubMed

41. Reece-Stremtan S, Marinelli KA. ABM clinical protocol #21: guidelines for breastfeeding and substance use or substance use disorder, revised 2015. Breastfeed Med. 2015;10(3):135-141. PubMed

42. Center for Substance Abuse Treatment. Medication-Assisted Treatment for Opioid Addiction in Opioid Treatment Programs. Treatment Improvement Protocol (TIP) Series 43. HHS Publication No. 12-4214. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2005.

43. Brier ME, Aronoff GR (eds). Drug Prescribing in Renal Failure. 5thedition. Philadelphia, PA: American College of Physicians; 2007.

44. Jones CM, Campopiano M, Baldwin G, McCance-Katz E. National and state treatment need and capacity for opioid agonist medication-assisted treatment. Am J Public Health. 2015;105(8):e55-E63. PubMed

45. Sigmon SC. Access to treatment for opioid dependence in rural America: challenges and future directions. JAMA Psychiatry. 2014;71(4):359-360. PubMed

46. Rosenblatt RA, Andrilla CH, Catlin M, Larson EH. Geographic and specialty distribution of US physicians trained to treat opioid use disorder. Ann Fam Med. 2015;13(1):23-26. PubMed

47. Komaromy M, Duhigg D, Metcalf A, et al. Project ECHO (Extension for Community Healthcare Outcomes): A new model for educating primary care providers about treatment of substance use disorders. Subst Abus. 2016;37(1):20-24. PubMed

48. Liebschutz JM, Crooks D, Herman D, et al. Buprenorphine treatment for hospitalized, opioid-dependent patients: a randomized clinical trial. JAMA Intern Med. 2014;174(8):1369-1376. PubMed

49. Centers for Disease Control and Prevention (CDC). Syringe exchange programs – United States, 2008. MMWR Morb Mortal Wkly Rep. 2010;59(45):1488-1491. PubMed

50. Harm Reduction Coalition. Getting off right: A safety manual for injection drug users. New York, NY: Harm Reduction Coalition; 1998.

51. Vlahov D, Junge B. The role of needle exchange programs in HIV prevention. Public Health Rep. 1998.113(suppl 1):75-80. PubMed

52. Strang J, McCambridge J, Best D, et al. Loss of tolerance and overdose mortality after inpatient opiate detoxification: follow up study. BMJ. 2003;326(7396):959-960. PubMed

53. Walley AY, Xuan Z, Hackman HH, et al. Opioid overdose rates and implementation of overdose education and nasal naloxone distribution in Massachusetts: interrupted time series analysis. BMJ. 2013;346:f174. PubMed

54. Calcaterra SL, Yamashita TE, Min SJ, Keniston A, Frank JW, Binswnager IA. Opioid prescribing at hospital discharge contributes to chronic opioid use. J Gen Intern Med. 2016;31(5):478-485. PubMed

55. Dunn KM, Saunders KW, Rutter CM, Banta-Green CJ, Merrill JO, Sullivan MD, et al. Opioid prescriptions for chronic pain and overdose: a cohort study. Ann Intern Med. 2010;152(2):85-92. PubMed

 

 

Issue
Journal of Hospital Medicine 12(5)
Issue
Journal of Hospital Medicine 12(5)
Page Number
369-374
Page Number
369-374
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Inpatient management of opioid use disorder: A review for hospitalists
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Inpatient management of opioid use disorder: A review for hospitalists
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