Hypoglycemia in ICU

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Delay in blood glucose monitoring during an insulin infusion protocol is associated with increased risk of hypoglycemia in intensive care units

Since publication of the first randomized controlled trial of insulin infusion therapy in surgical intensive care unit (ICU) patients,1 most institutions have implemented insulin infusion protocols (IIP) for tight glycemic control in their ICUs.29 The major problem with tight glycemic control is the risk of hypoglycemia. In the randomized controlled trial involving medical ICU patients, 18.7% patients experienced at least 1 episode of blood glucose (BG) <40 mg/dL.10 Recently, a major insulin infusion trial involving patients with severe sepsis was stopped due to unacceptably high risk of hypoglycemia.11 Potential benefits of BG control may be offset by potential risks of hypoglycemia. While there can be multiple factors that could contribute to the risk of hypoglycemia, suboptimal protocol implementation is relatively amenable to correction.

Most IIPs are nurse driven. Nurses monitor BG levels every 30 to 60 minutes and make adjustments in insulin infusion rates. Each point of care testing and insulin dose adjustment takes about 5 minutes of nursing time.12 Given the numerous other nursing responsibilities for monitoring and documentation in very sick patients, nurses may not always be able check BGs at the recommended times. We investigated whether a delay in BG monitoring during insulin infusion therapy is associated with higher risk of hypoglycemia.

Methods

Data were collected for 50 consecutive patients treated with Brigham and Women's Hospital's insulin infusion protocol (BHIP) between September 27, 2006 and October 13, 2006. The investigation was part of the hospital's ongoing diabetes quality improvement program. Partners‐Health Human Research Committee approved the study. Patient demographics, history of diabetes mellitus, and glycosylated hemoglobin (A1C) were obtained from paper and electronic medical records. Point‐of‐care BG values were obtained from the bedside paper flow sheets. The exact times of individual BG measurements were ascertained from Point of Care Precision Web (QCM3.0; Abbott, Inc.).

Target BG range with BHIP is 80 to 110 mg/dL. BHIP requires BG testing every 60 minutes unless a BG value of <60 mg/dL is obtained; in which case, testing is required every 30 minutes. A time violation was assumed to have occurred if the BG was measured >70 minutes after a previous value of 60 mg/dL or >40 minutes after a previous BG value of <60 mg/dL (ie, >10 minutes after the recommended time for measurement). Although the choice of 10 minutes was arbitrary, we think it is a reasonable and practical time frame for getting a BG measurement. If a measurement was obtained earlier than the recommended time, it was not considered a time violation. However, measurements obtained within 30 minutes of a previous BG value (overwhelmingly drawn for confirmation of a previous BG value) were excluded from analysis.

BG values were divided into 2 categories: values following time violation and values following no time violation. The numbers of values in different BG ranges (<80, 80110, >110 mg/dL) were compared in the 2 categories using a chi square test. Data are presented as mean standard deviation (SD), median and numbers with percentage. Statistical significance was set at P < 0.05.

Results

Mean age of the 50 patients treated with BHIP was 64.0 13.6 years. There were 27 men and 23 women. Eighteen patients had preexisting diabetes (1 had type 1 and 17 had type 2 diabetes, mean A1C 7.1 1.7%) and 32 patients had no previous history of diabetes (mean A1C 5.9 0.9%). Mean serum creatinine was 1.34 1.0 mg/dL. Mean BG at the start of BHIP was 173 69.6 mg/dL; median 167.5 mg/dL. Mean BG during insulin infusion was 117.3 43.1 mg/dL; median 107 mg/dL. Mean BG during insulin infusion was higher in diabetic patients compared to nondiabetic patients (125.2 57.8 versus 113.4 38.8 mg/dL; P < 0.01). Monitoring for BGs was done with similar frequency in all patients. Overall, 40.2% of the total 2,605 BG values were in a range of 80 to 110 mg/dL. A total of 1.5% of values were below 60 mg/dL; only 4 values were <40 mg/dL.

A total of 2,309 values could be studied for time violations. The remaining 296 values were either obtained within 30 minutes of the previous test or the exact time of measurement could not be ascertained. A total of 1,474 (63.9%) measurements had been obtained at the recommended time or earlier than the recommended time; 835 (36.1%) measurements had been obtained >10 minutes after the recommended time for measurement (time violation). The proportion of BG values below the target (<80 mg/dL) was significantly higher following the time violation as compared to no time violation (Table 1). On the other hand, values >110 mg/dL were not more common following a time violation, compared to instances when no time violation occurred.

Time Violations and Blood Glucose Values during BHIP
Time Violation [n = 835 (100%)] No Time Violation [n = 1,474 (100%)] P Value
  • Abbreviation: NS, statistically nonsignificant.

BG values <80 mg/dL 149 (17.8) 171 (11.6) <0.001
BG values 80110 mg/dL 316 (37.8) 596 (40.4) NS
BG values >110 mg/dL 370 (44.3) 708 (47.8) NS

Frequency of time violation was similar in subgroups of patients divided according to gender, presence of diabetes and the type of ICU (Table 2). Comparison among subgroups of admission diagnoses was not possible due to the small number of patients. Overall, the proportion of low BG values was lower in diabetic patients compared to nondiabetic patients (11.9% versus 15.0%, P = 0.03). An increased rate of hypoglycemia following time violations was present in all subgroups except for the diabetic subgroup (Table 3).

Patient Characteristics and Frequency of Time Violation
Characteristic Number of Patients % of BG Values Associated with Time Violations P Value
  • Abbreviation: NS, statistically nonsignificant.

Gender NS
Male 27 36
Female 23 36
Diabetes status NS
Known diabetes 18 37
No known diabetes 32 35
Type of ICU NS
Medical 20 38
Surgical 30 35
Admission diagnosis
Cardiovascular disease 7 35
Gastrointestinal disease 4 43
Malignant disorder 8 32
Neurological disease 7 36
Orthopedic problem 2 51
Respiratory disease 13 33
Renal failure 3 46
Sepsis 6 36
Patient Characteristic and Relation of Time Violation to Hypoglycemia
% BG Values <80
Characteristic Time Violation No Time Violation P Value
  • Abbreviation: NS, statistically nonsignificant.

Male 19.1 11.9 <0.001
Female 16.1 11.2 0.03
Known diabetes 13.3 11.1 NS
No diabetes 20 11.9 <0.001
Medical ICU 19.2 11.9 0.002
Surgical ICU 16.8 11.3 0.004
Cardiovascular diseases 21.1 14.1
Gastrointestinal diseases 22.1 14.8
Malignant disorders 22.0 11.7
Neurological diseases 7.5 5.0
Orthopedic problems 6.2 6.6
Respiratory diseases 11.9 10.4
Renal failure 35.7 15.6
Sepsis 19.7 13.5

Discussion

Our study shows that a delay in BG testing during BHIP is associated with higher chances of a low BG value. This effect was consistent in multiple subgroups. However, the effect was nonsignificant in diabetic patients, probably due to higher mean BG levels and less frequent low BG values. Over one‐third of all BG measurements were obtained after a time violation. Protocol violations in our study are no different from those reported by others.7, 13, 14 Our patient characteristics of severe hypoglycemic episodes and the overall BG control achieved with BHIP were also similar to those reported by others with similar protocols.5, 7, 1517 While the results of this study may still be specific to BHIP, we think they are applicable to other similar protocols.

Because a delay in testing by itself is unlikely to cause hypoglycemia, a more likely explanation for these results is that hypoglycemia occurred when insulin infusion adjustments were not made in a timely fashion due to prolonged BG monitoring intervals. Insulin infusions are the preferred treatment in rapidly changing clinical settings because changes in insulin doses can be made frequently. Most IIPs are designed with the assumption that insulin dose adjustments will be made regularly and frequently, based on BG measurements. Although there is no gold standard for the optimal BG test frequency, in most protocols BG testing is performed every hour in order to ensure safety as well as efficacy. Our results are consistent with the intuitive assumption that a timely measurement of the BG is important for successful implementation of an IIP.

It was somewhat surprising that high BG values were not more frequent following a time violation. We can only speculate as to the reason for this. It is possible that critically ill patients are near maximally insulin resistant and, once an effective insulin infusion rate is achieved, further increases are not as frequently required. On the other hand, insulin requirements may decrease rapidly as contributors to insulin resistance resolve. Another possibility is that there may be a limit to hepatic glucose production during acute illness making patients more prone to hypoglycemia. It is also possible that the nurses tend to test more promptly when the BG levels are running high. Thus, the insulin doses may be increased at proper times until BG levels are in the target range. However, when BG levels are in the target range, nurses may become less vigilant, leading to a delay in testing. As a result a decrease in insulin dose, when required, does not happen as promptly as an increase in dose.

In our study the absolute risk of hypoglycemia associated with time violation was 6%. Avoiding this hypoglycemia may have an impact on glycemic control in the ICU and may change clinical outcomes. Moreover, this is 1 of the few factors that are potentially amenable to correction. Therefore, measures to improve adherence to protocols, eg, prompts for BG testing and better nurse training regarding importance of timely testing, may reduce the risk of hypoglycemia.

References
  1. van den Berghe G,Wouters P,Weekers F, et al.Intensive insulin therapy in the surgical intensive care unit.N Engl J Med.2001;345(19):13591367.
  2. Krinsley JS.Effect of an intensive glucose management protocol on the mortality of critically ill adult patients.Mayo Clin Proc.2004;79(8):9921000.
  3. Laver S,Preston S,Turner D,McKinstry C,Padkin A.Implementing intensive insulin therapy: development and audit of the Bath insulin protocol.Anaesth Intensive Care.2004;32(3):311316.
  4. Lien LF,Spratt SE,Woods Z,Osborne KK,Feinglos MN.Optimizing hospital use of intravenous insulin therapy: improved management of hyperglycemia and error reduction with a new nomogram.Endocr Pract.2005;11(4):240253.
  5. Taylor BE,Schallom ME,Sona CS, et al.Efficacy and safety of an insulin infusion protocol in a surgical ICU.J Am Coll Surg.2006;202(1):19.
  6. Goldberg PA,Siegel MD,Sherwin RS, et al.Implementation of a safe and effective insulin infusion protocol in a medical intensive care unit.Diabetes Care.2004;27(2):461467.
  7. DeSantis AJ,Schmeltz LR,Schmidt K, et al.Inpatient management of hyperglycemia: the Northwestern experience.Endocr Pract.2006;12(5):491505.
  8. Rea RS,Donihi AC,Bobeck M, et al.Implementing an intravenous insulin infusion protocol in the intensive care unit.Am J Health Syst Pharm.2007;64(4):385395.
  9. Quinn JA,Snyder SL,Berghoff JL,Colombo CS,Jacobi J.A practical approach to hyperglycemia management in the intensive care unit: evaluation of an intensive insulin infusion protocol.Pharmacotherapy.2006;26(10):14101420.
  10. Van den Berghe G,Wilmer A,Hermans G, et al.Intensive insulin therapy in the medical ICU.N Engl J Med.2006;354(5):449461.
  11. Brunkhorst FM,Engel C,Bloos F, et al.Intensive insulin therapy and pentastarch resuscitation in severe sepsis.N Engl J Med.2008;358(2):125139.
  12. Aragon D.Evaluation of nursing work effort and perceptions about blood glucose testing in tight glycemic control.Am J Crit Care.2006;15(4):370377.
  13. Oeyen SG,Hoste EA,Roosens CD,Decruyenaere JM,Blot SI.Adherence to and efficacy and safety of an insulin protocol in the critically ill: a prospective observational study.Am J Crit Care.2007;16(6):599608.
  14. Clayton SB,Mazur JE,Condren S,Hermayer KL,Strange C.Evaluation of an intensive insulin protocol for septic patients in a medical intensive care unit.Crit Care Med.2006;34(12):29742978.
  15. Collier B,Diaz J,Forbes R, et al.The impact of a normoglycemic management protocol on clinical outcomes in the trauma intensive care unit.JPEN J Parenter Enteral Nutr.2005;29(5):353358.
  16. Kanji S,Singh A,Tierney M,Meggison H,McIntyre L,Hebert PC.Standardization of intravenous insulin therapy improves the efficiency and safety of blood glucose control in critically ill adults.Intensive Care Med.2004;30(5):804810.
  17. Bland DK,Fankhanel Y,Langford E, et al.Intensive versus modified conventional control of blood glucose level in medical intensive care patients: a pilot study.Am J Crit Care.2005;14(5):370376.
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Journal of Hospital Medicine - 4(6)
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E5-E7
Legacy Keywords
hypoglycemia, ICU, insulin infusion
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Article PDF

Since publication of the first randomized controlled trial of insulin infusion therapy in surgical intensive care unit (ICU) patients,1 most institutions have implemented insulin infusion protocols (IIP) for tight glycemic control in their ICUs.29 The major problem with tight glycemic control is the risk of hypoglycemia. In the randomized controlled trial involving medical ICU patients, 18.7% patients experienced at least 1 episode of blood glucose (BG) <40 mg/dL.10 Recently, a major insulin infusion trial involving patients with severe sepsis was stopped due to unacceptably high risk of hypoglycemia.11 Potential benefits of BG control may be offset by potential risks of hypoglycemia. While there can be multiple factors that could contribute to the risk of hypoglycemia, suboptimal protocol implementation is relatively amenable to correction.

Most IIPs are nurse driven. Nurses monitor BG levels every 30 to 60 minutes and make adjustments in insulin infusion rates. Each point of care testing and insulin dose adjustment takes about 5 minutes of nursing time.12 Given the numerous other nursing responsibilities for monitoring and documentation in very sick patients, nurses may not always be able check BGs at the recommended times. We investigated whether a delay in BG monitoring during insulin infusion therapy is associated with higher risk of hypoglycemia.

Methods

Data were collected for 50 consecutive patients treated with Brigham and Women's Hospital's insulin infusion protocol (BHIP) between September 27, 2006 and October 13, 2006. The investigation was part of the hospital's ongoing diabetes quality improvement program. Partners‐Health Human Research Committee approved the study. Patient demographics, history of diabetes mellitus, and glycosylated hemoglobin (A1C) were obtained from paper and electronic medical records. Point‐of‐care BG values were obtained from the bedside paper flow sheets. The exact times of individual BG measurements were ascertained from Point of Care Precision Web (QCM3.0; Abbott, Inc.).

Target BG range with BHIP is 80 to 110 mg/dL. BHIP requires BG testing every 60 minutes unless a BG value of <60 mg/dL is obtained; in which case, testing is required every 30 minutes. A time violation was assumed to have occurred if the BG was measured >70 minutes after a previous value of 60 mg/dL or >40 minutes after a previous BG value of <60 mg/dL (ie, >10 minutes after the recommended time for measurement). Although the choice of 10 minutes was arbitrary, we think it is a reasonable and practical time frame for getting a BG measurement. If a measurement was obtained earlier than the recommended time, it was not considered a time violation. However, measurements obtained within 30 minutes of a previous BG value (overwhelmingly drawn for confirmation of a previous BG value) were excluded from analysis.

BG values were divided into 2 categories: values following time violation and values following no time violation. The numbers of values in different BG ranges (<80, 80110, >110 mg/dL) were compared in the 2 categories using a chi square test. Data are presented as mean standard deviation (SD), median and numbers with percentage. Statistical significance was set at P < 0.05.

Results

Mean age of the 50 patients treated with BHIP was 64.0 13.6 years. There were 27 men and 23 women. Eighteen patients had preexisting diabetes (1 had type 1 and 17 had type 2 diabetes, mean A1C 7.1 1.7%) and 32 patients had no previous history of diabetes (mean A1C 5.9 0.9%). Mean serum creatinine was 1.34 1.0 mg/dL. Mean BG at the start of BHIP was 173 69.6 mg/dL; median 167.5 mg/dL. Mean BG during insulin infusion was 117.3 43.1 mg/dL; median 107 mg/dL. Mean BG during insulin infusion was higher in diabetic patients compared to nondiabetic patients (125.2 57.8 versus 113.4 38.8 mg/dL; P < 0.01). Monitoring for BGs was done with similar frequency in all patients. Overall, 40.2% of the total 2,605 BG values were in a range of 80 to 110 mg/dL. A total of 1.5% of values were below 60 mg/dL; only 4 values were <40 mg/dL.

A total of 2,309 values could be studied for time violations. The remaining 296 values were either obtained within 30 minutes of the previous test or the exact time of measurement could not be ascertained. A total of 1,474 (63.9%) measurements had been obtained at the recommended time or earlier than the recommended time; 835 (36.1%) measurements had been obtained >10 minutes after the recommended time for measurement (time violation). The proportion of BG values below the target (<80 mg/dL) was significantly higher following the time violation as compared to no time violation (Table 1). On the other hand, values >110 mg/dL were not more common following a time violation, compared to instances when no time violation occurred.

Time Violations and Blood Glucose Values during BHIP
Time Violation [n = 835 (100%)] No Time Violation [n = 1,474 (100%)] P Value
  • Abbreviation: NS, statistically nonsignificant.

BG values <80 mg/dL 149 (17.8) 171 (11.6) <0.001
BG values 80110 mg/dL 316 (37.8) 596 (40.4) NS
BG values >110 mg/dL 370 (44.3) 708 (47.8) NS

Frequency of time violation was similar in subgroups of patients divided according to gender, presence of diabetes and the type of ICU (Table 2). Comparison among subgroups of admission diagnoses was not possible due to the small number of patients. Overall, the proportion of low BG values was lower in diabetic patients compared to nondiabetic patients (11.9% versus 15.0%, P = 0.03). An increased rate of hypoglycemia following time violations was present in all subgroups except for the diabetic subgroup (Table 3).

Patient Characteristics and Frequency of Time Violation
Characteristic Number of Patients % of BG Values Associated with Time Violations P Value
  • Abbreviation: NS, statistically nonsignificant.

Gender NS
Male 27 36
Female 23 36
Diabetes status NS
Known diabetes 18 37
No known diabetes 32 35
Type of ICU NS
Medical 20 38
Surgical 30 35
Admission diagnosis
Cardiovascular disease 7 35
Gastrointestinal disease 4 43
Malignant disorder 8 32
Neurological disease 7 36
Orthopedic problem 2 51
Respiratory disease 13 33
Renal failure 3 46
Sepsis 6 36
Patient Characteristic and Relation of Time Violation to Hypoglycemia
% BG Values <80
Characteristic Time Violation No Time Violation P Value
  • Abbreviation: NS, statistically nonsignificant.

Male 19.1 11.9 <0.001
Female 16.1 11.2 0.03
Known diabetes 13.3 11.1 NS
No diabetes 20 11.9 <0.001
Medical ICU 19.2 11.9 0.002
Surgical ICU 16.8 11.3 0.004
Cardiovascular diseases 21.1 14.1
Gastrointestinal diseases 22.1 14.8
Malignant disorders 22.0 11.7
Neurological diseases 7.5 5.0
Orthopedic problems 6.2 6.6
Respiratory diseases 11.9 10.4
Renal failure 35.7 15.6
Sepsis 19.7 13.5

Discussion

Our study shows that a delay in BG testing during BHIP is associated with higher chances of a low BG value. This effect was consistent in multiple subgroups. However, the effect was nonsignificant in diabetic patients, probably due to higher mean BG levels and less frequent low BG values. Over one‐third of all BG measurements were obtained after a time violation. Protocol violations in our study are no different from those reported by others.7, 13, 14 Our patient characteristics of severe hypoglycemic episodes and the overall BG control achieved with BHIP were also similar to those reported by others with similar protocols.5, 7, 1517 While the results of this study may still be specific to BHIP, we think they are applicable to other similar protocols.

Because a delay in testing by itself is unlikely to cause hypoglycemia, a more likely explanation for these results is that hypoglycemia occurred when insulin infusion adjustments were not made in a timely fashion due to prolonged BG monitoring intervals. Insulin infusions are the preferred treatment in rapidly changing clinical settings because changes in insulin doses can be made frequently. Most IIPs are designed with the assumption that insulin dose adjustments will be made regularly and frequently, based on BG measurements. Although there is no gold standard for the optimal BG test frequency, in most protocols BG testing is performed every hour in order to ensure safety as well as efficacy. Our results are consistent with the intuitive assumption that a timely measurement of the BG is important for successful implementation of an IIP.

It was somewhat surprising that high BG values were not more frequent following a time violation. We can only speculate as to the reason for this. It is possible that critically ill patients are near maximally insulin resistant and, once an effective insulin infusion rate is achieved, further increases are not as frequently required. On the other hand, insulin requirements may decrease rapidly as contributors to insulin resistance resolve. Another possibility is that there may be a limit to hepatic glucose production during acute illness making patients more prone to hypoglycemia. It is also possible that the nurses tend to test more promptly when the BG levels are running high. Thus, the insulin doses may be increased at proper times until BG levels are in the target range. However, when BG levels are in the target range, nurses may become less vigilant, leading to a delay in testing. As a result a decrease in insulin dose, when required, does not happen as promptly as an increase in dose.

In our study the absolute risk of hypoglycemia associated with time violation was 6%. Avoiding this hypoglycemia may have an impact on glycemic control in the ICU and may change clinical outcomes. Moreover, this is 1 of the few factors that are potentially amenable to correction. Therefore, measures to improve adherence to protocols, eg, prompts for BG testing and better nurse training regarding importance of timely testing, may reduce the risk of hypoglycemia.

Since publication of the first randomized controlled trial of insulin infusion therapy in surgical intensive care unit (ICU) patients,1 most institutions have implemented insulin infusion protocols (IIP) for tight glycemic control in their ICUs.29 The major problem with tight glycemic control is the risk of hypoglycemia. In the randomized controlled trial involving medical ICU patients, 18.7% patients experienced at least 1 episode of blood glucose (BG) <40 mg/dL.10 Recently, a major insulin infusion trial involving patients with severe sepsis was stopped due to unacceptably high risk of hypoglycemia.11 Potential benefits of BG control may be offset by potential risks of hypoglycemia. While there can be multiple factors that could contribute to the risk of hypoglycemia, suboptimal protocol implementation is relatively amenable to correction.

Most IIPs are nurse driven. Nurses monitor BG levels every 30 to 60 minutes and make adjustments in insulin infusion rates. Each point of care testing and insulin dose adjustment takes about 5 minutes of nursing time.12 Given the numerous other nursing responsibilities for monitoring and documentation in very sick patients, nurses may not always be able check BGs at the recommended times. We investigated whether a delay in BG monitoring during insulin infusion therapy is associated with higher risk of hypoglycemia.

Methods

Data were collected for 50 consecutive patients treated with Brigham and Women's Hospital's insulin infusion protocol (BHIP) between September 27, 2006 and October 13, 2006. The investigation was part of the hospital's ongoing diabetes quality improvement program. Partners‐Health Human Research Committee approved the study. Patient demographics, history of diabetes mellitus, and glycosylated hemoglobin (A1C) were obtained from paper and electronic medical records. Point‐of‐care BG values were obtained from the bedside paper flow sheets. The exact times of individual BG measurements were ascertained from Point of Care Precision Web (QCM3.0; Abbott, Inc.).

Target BG range with BHIP is 80 to 110 mg/dL. BHIP requires BG testing every 60 minutes unless a BG value of <60 mg/dL is obtained; in which case, testing is required every 30 minutes. A time violation was assumed to have occurred if the BG was measured >70 minutes after a previous value of 60 mg/dL or >40 minutes after a previous BG value of <60 mg/dL (ie, >10 minutes after the recommended time for measurement). Although the choice of 10 minutes was arbitrary, we think it is a reasonable and practical time frame for getting a BG measurement. If a measurement was obtained earlier than the recommended time, it was not considered a time violation. However, measurements obtained within 30 minutes of a previous BG value (overwhelmingly drawn for confirmation of a previous BG value) were excluded from analysis.

BG values were divided into 2 categories: values following time violation and values following no time violation. The numbers of values in different BG ranges (<80, 80110, >110 mg/dL) were compared in the 2 categories using a chi square test. Data are presented as mean standard deviation (SD), median and numbers with percentage. Statistical significance was set at P < 0.05.

Results

Mean age of the 50 patients treated with BHIP was 64.0 13.6 years. There were 27 men and 23 women. Eighteen patients had preexisting diabetes (1 had type 1 and 17 had type 2 diabetes, mean A1C 7.1 1.7%) and 32 patients had no previous history of diabetes (mean A1C 5.9 0.9%). Mean serum creatinine was 1.34 1.0 mg/dL. Mean BG at the start of BHIP was 173 69.6 mg/dL; median 167.5 mg/dL. Mean BG during insulin infusion was 117.3 43.1 mg/dL; median 107 mg/dL. Mean BG during insulin infusion was higher in diabetic patients compared to nondiabetic patients (125.2 57.8 versus 113.4 38.8 mg/dL; P < 0.01). Monitoring for BGs was done with similar frequency in all patients. Overall, 40.2% of the total 2,605 BG values were in a range of 80 to 110 mg/dL. A total of 1.5% of values were below 60 mg/dL; only 4 values were <40 mg/dL.

A total of 2,309 values could be studied for time violations. The remaining 296 values were either obtained within 30 minutes of the previous test or the exact time of measurement could not be ascertained. A total of 1,474 (63.9%) measurements had been obtained at the recommended time or earlier than the recommended time; 835 (36.1%) measurements had been obtained >10 minutes after the recommended time for measurement (time violation). The proportion of BG values below the target (<80 mg/dL) was significantly higher following the time violation as compared to no time violation (Table 1). On the other hand, values >110 mg/dL were not more common following a time violation, compared to instances when no time violation occurred.

Time Violations and Blood Glucose Values during BHIP
Time Violation [n = 835 (100%)] No Time Violation [n = 1,474 (100%)] P Value
  • Abbreviation: NS, statistically nonsignificant.

BG values <80 mg/dL 149 (17.8) 171 (11.6) <0.001
BG values 80110 mg/dL 316 (37.8) 596 (40.4) NS
BG values >110 mg/dL 370 (44.3) 708 (47.8) NS

Frequency of time violation was similar in subgroups of patients divided according to gender, presence of diabetes and the type of ICU (Table 2). Comparison among subgroups of admission diagnoses was not possible due to the small number of patients. Overall, the proportion of low BG values was lower in diabetic patients compared to nondiabetic patients (11.9% versus 15.0%, P = 0.03). An increased rate of hypoglycemia following time violations was present in all subgroups except for the diabetic subgroup (Table 3).

Patient Characteristics and Frequency of Time Violation
Characteristic Number of Patients % of BG Values Associated with Time Violations P Value
  • Abbreviation: NS, statistically nonsignificant.

Gender NS
Male 27 36
Female 23 36
Diabetes status NS
Known diabetes 18 37
No known diabetes 32 35
Type of ICU NS
Medical 20 38
Surgical 30 35
Admission diagnosis
Cardiovascular disease 7 35
Gastrointestinal disease 4 43
Malignant disorder 8 32
Neurological disease 7 36
Orthopedic problem 2 51
Respiratory disease 13 33
Renal failure 3 46
Sepsis 6 36
Patient Characteristic and Relation of Time Violation to Hypoglycemia
% BG Values <80
Characteristic Time Violation No Time Violation P Value
  • Abbreviation: NS, statistically nonsignificant.

Male 19.1 11.9 <0.001
Female 16.1 11.2 0.03
Known diabetes 13.3 11.1 NS
No diabetes 20 11.9 <0.001
Medical ICU 19.2 11.9 0.002
Surgical ICU 16.8 11.3 0.004
Cardiovascular diseases 21.1 14.1
Gastrointestinal diseases 22.1 14.8
Malignant disorders 22.0 11.7
Neurological diseases 7.5 5.0
Orthopedic problems 6.2 6.6
Respiratory diseases 11.9 10.4
Renal failure 35.7 15.6
Sepsis 19.7 13.5

Discussion

Our study shows that a delay in BG testing during BHIP is associated with higher chances of a low BG value. This effect was consistent in multiple subgroups. However, the effect was nonsignificant in diabetic patients, probably due to higher mean BG levels and less frequent low BG values. Over one‐third of all BG measurements were obtained after a time violation. Protocol violations in our study are no different from those reported by others.7, 13, 14 Our patient characteristics of severe hypoglycemic episodes and the overall BG control achieved with BHIP were also similar to those reported by others with similar protocols.5, 7, 1517 While the results of this study may still be specific to BHIP, we think they are applicable to other similar protocols.

Because a delay in testing by itself is unlikely to cause hypoglycemia, a more likely explanation for these results is that hypoglycemia occurred when insulin infusion adjustments were not made in a timely fashion due to prolonged BG monitoring intervals. Insulin infusions are the preferred treatment in rapidly changing clinical settings because changes in insulin doses can be made frequently. Most IIPs are designed with the assumption that insulin dose adjustments will be made regularly and frequently, based on BG measurements. Although there is no gold standard for the optimal BG test frequency, in most protocols BG testing is performed every hour in order to ensure safety as well as efficacy. Our results are consistent with the intuitive assumption that a timely measurement of the BG is important for successful implementation of an IIP.

It was somewhat surprising that high BG values were not more frequent following a time violation. We can only speculate as to the reason for this. It is possible that critically ill patients are near maximally insulin resistant and, once an effective insulin infusion rate is achieved, further increases are not as frequently required. On the other hand, insulin requirements may decrease rapidly as contributors to insulin resistance resolve. Another possibility is that there may be a limit to hepatic glucose production during acute illness making patients more prone to hypoglycemia. It is also possible that the nurses tend to test more promptly when the BG levels are running high. Thus, the insulin doses may be increased at proper times until BG levels are in the target range. However, when BG levels are in the target range, nurses may become less vigilant, leading to a delay in testing. As a result a decrease in insulin dose, when required, does not happen as promptly as an increase in dose.

In our study the absolute risk of hypoglycemia associated with time violation was 6%. Avoiding this hypoglycemia may have an impact on glycemic control in the ICU and may change clinical outcomes. Moreover, this is 1 of the few factors that are potentially amenable to correction. Therefore, measures to improve adherence to protocols, eg, prompts for BG testing and better nurse training regarding importance of timely testing, may reduce the risk of hypoglycemia.

References
  1. van den Berghe G,Wouters P,Weekers F, et al.Intensive insulin therapy in the surgical intensive care unit.N Engl J Med.2001;345(19):13591367.
  2. Krinsley JS.Effect of an intensive glucose management protocol on the mortality of critically ill adult patients.Mayo Clin Proc.2004;79(8):9921000.
  3. Laver S,Preston S,Turner D,McKinstry C,Padkin A.Implementing intensive insulin therapy: development and audit of the Bath insulin protocol.Anaesth Intensive Care.2004;32(3):311316.
  4. Lien LF,Spratt SE,Woods Z,Osborne KK,Feinglos MN.Optimizing hospital use of intravenous insulin therapy: improved management of hyperglycemia and error reduction with a new nomogram.Endocr Pract.2005;11(4):240253.
  5. Taylor BE,Schallom ME,Sona CS, et al.Efficacy and safety of an insulin infusion protocol in a surgical ICU.J Am Coll Surg.2006;202(1):19.
  6. Goldberg PA,Siegel MD,Sherwin RS, et al.Implementation of a safe and effective insulin infusion protocol in a medical intensive care unit.Diabetes Care.2004;27(2):461467.
  7. DeSantis AJ,Schmeltz LR,Schmidt K, et al.Inpatient management of hyperglycemia: the Northwestern experience.Endocr Pract.2006;12(5):491505.
  8. Rea RS,Donihi AC,Bobeck M, et al.Implementing an intravenous insulin infusion protocol in the intensive care unit.Am J Health Syst Pharm.2007;64(4):385395.
  9. Quinn JA,Snyder SL,Berghoff JL,Colombo CS,Jacobi J.A practical approach to hyperglycemia management in the intensive care unit: evaluation of an intensive insulin infusion protocol.Pharmacotherapy.2006;26(10):14101420.
  10. Van den Berghe G,Wilmer A,Hermans G, et al.Intensive insulin therapy in the medical ICU.N Engl J Med.2006;354(5):449461.
  11. Brunkhorst FM,Engel C,Bloos F, et al.Intensive insulin therapy and pentastarch resuscitation in severe sepsis.N Engl J Med.2008;358(2):125139.
  12. Aragon D.Evaluation of nursing work effort and perceptions about blood glucose testing in tight glycemic control.Am J Crit Care.2006;15(4):370377.
  13. Oeyen SG,Hoste EA,Roosens CD,Decruyenaere JM,Blot SI.Adherence to and efficacy and safety of an insulin protocol in the critically ill: a prospective observational study.Am J Crit Care.2007;16(6):599608.
  14. Clayton SB,Mazur JE,Condren S,Hermayer KL,Strange C.Evaluation of an intensive insulin protocol for septic patients in a medical intensive care unit.Crit Care Med.2006;34(12):29742978.
  15. Collier B,Diaz J,Forbes R, et al.The impact of a normoglycemic management protocol on clinical outcomes in the trauma intensive care unit.JPEN J Parenter Enteral Nutr.2005;29(5):353358.
  16. Kanji S,Singh A,Tierney M,Meggison H,McIntyre L,Hebert PC.Standardization of intravenous insulin therapy improves the efficiency and safety of blood glucose control in critically ill adults.Intensive Care Med.2004;30(5):804810.
  17. Bland DK,Fankhanel Y,Langford E, et al.Intensive versus modified conventional control of blood glucose level in medical intensive care patients: a pilot study.Am J Crit Care.2005;14(5):370376.
References
  1. van den Berghe G,Wouters P,Weekers F, et al.Intensive insulin therapy in the surgical intensive care unit.N Engl J Med.2001;345(19):13591367.
  2. Krinsley JS.Effect of an intensive glucose management protocol on the mortality of critically ill adult patients.Mayo Clin Proc.2004;79(8):9921000.
  3. Laver S,Preston S,Turner D,McKinstry C,Padkin A.Implementing intensive insulin therapy: development and audit of the Bath insulin protocol.Anaesth Intensive Care.2004;32(3):311316.
  4. Lien LF,Spratt SE,Woods Z,Osborne KK,Feinglos MN.Optimizing hospital use of intravenous insulin therapy: improved management of hyperglycemia and error reduction with a new nomogram.Endocr Pract.2005;11(4):240253.
  5. Taylor BE,Schallom ME,Sona CS, et al.Efficacy and safety of an insulin infusion protocol in a surgical ICU.J Am Coll Surg.2006;202(1):19.
  6. Goldberg PA,Siegel MD,Sherwin RS, et al.Implementation of a safe and effective insulin infusion protocol in a medical intensive care unit.Diabetes Care.2004;27(2):461467.
  7. DeSantis AJ,Schmeltz LR,Schmidt K, et al.Inpatient management of hyperglycemia: the Northwestern experience.Endocr Pract.2006;12(5):491505.
  8. Rea RS,Donihi AC,Bobeck M, et al.Implementing an intravenous insulin infusion protocol in the intensive care unit.Am J Health Syst Pharm.2007;64(4):385395.
  9. Quinn JA,Snyder SL,Berghoff JL,Colombo CS,Jacobi J.A practical approach to hyperglycemia management in the intensive care unit: evaluation of an intensive insulin infusion protocol.Pharmacotherapy.2006;26(10):14101420.
  10. Van den Berghe G,Wilmer A,Hermans G, et al.Intensive insulin therapy in the medical ICU.N Engl J Med.2006;354(5):449461.
  11. Brunkhorst FM,Engel C,Bloos F, et al.Intensive insulin therapy and pentastarch resuscitation in severe sepsis.N Engl J Med.2008;358(2):125139.
  12. Aragon D.Evaluation of nursing work effort and perceptions about blood glucose testing in tight glycemic control.Am J Crit Care.2006;15(4):370377.
  13. Oeyen SG,Hoste EA,Roosens CD,Decruyenaere JM,Blot SI.Adherence to and efficacy and safety of an insulin protocol in the critically ill: a prospective observational study.Am J Crit Care.2007;16(6):599608.
  14. Clayton SB,Mazur JE,Condren S,Hermayer KL,Strange C.Evaluation of an intensive insulin protocol for septic patients in a medical intensive care unit.Crit Care Med.2006;34(12):29742978.
  15. Collier B,Diaz J,Forbes R, et al.The impact of a normoglycemic management protocol on clinical outcomes in the trauma intensive care unit.JPEN J Parenter Enteral Nutr.2005;29(5):353358.
  16. Kanji S,Singh A,Tierney M,Meggison H,McIntyre L,Hebert PC.Standardization of intravenous insulin therapy improves the efficiency and safety of blood glucose control in critically ill adults.Intensive Care Med.2004;30(5):804810.
  17. Bland DK,Fankhanel Y,Langford E, et al.Intensive versus modified conventional control of blood glucose level in medical intensive care patients: a pilot study.Am J Crit Care.2005;14(5):370376.
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Delay in blood glucose monitoring during an insulin infusion protocol is associated with increased risk of hypoglycemia in intensive care units
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Approach to Peripheral Neuropathies

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Peripheral neuropathies: A practical approach for the hospitalist

Early diagnosis of peripheral neuropathies can lead to life‐saving or limb‐saving intervention. While infrequently a cause for concern in the hospital setting, peripheral neuropathies are commonoccurring in up to 10% of the general population.1 The hospitalist needs to expeditiously identify acute and life‐threatening or limb‐threatening causes among an immense set of differentials. Fortunately, with an informed and careful approach, most neuropathies in need of urgent intervention can be readily identified. A thorough history and examination, with the addition of electrodiagnostic testing, comprise the mainstays of this process. Inpatient neurology consultation should be sought for any rapidly progressing or acute onset neuropathy. The aim of this review is to equip the general hospitalist with a solid framework for efficiently evaluating peripheral neuropathies in urgent cases.

Literature Review

Search Strategy

A PubMed search was conducted using the title word peripheral, the medical subject heading major topic peripheral nervous system diseases/diagnosis, and algorithm or diagnosis, differential or diagnostic techniques, neurological or neurologic examination or evaluation or evaluating. The search was limited to English language review articles published between January 2002 and November 2007. Articles were included in this review if they provided an overview of an approach to the diagnosis of peripheral neuropathies. References listed in these articles were cross‐checked and additional articles meeting these criteria were included. Articles specific to subtypes of neuropathies or diagnostic tools were excluded.

Search Results

No single guideline or algorithm has been widely endorsed for the approach to diagnosing peripheral neuropathies. Several are suggested in the literature, but none are directed at the hospitalist. In general, acute and multifocal neuropathies are characterized as neurologic emergencies requiring immediate evaluation.2, 3

Several articles underscore the importance of pattern recognition in diagnosing peripheral neuropathies.2, 4, 5 Many articles present essential questions in evaluating peripheral neuropathy; some suggest an ordered approach.13, 511 The nature of these questions and recommended order of inquiry varies among authors (Table 1). Three essentials common to all articles include: 1) noting the onset of symptoms; 2) determining the distribution of nerve involvement; and 3) identifying the pathology as axonal, demyelinating, or mixed. All articles underscore the importance of the physical examination in determining and confirming distribution and nerve type. A thorough examination evaluating for systemic signs of etiologic possibilities is strongly recommended. Electrodiagnostic testing provides confirmation of the distribution of nerve involvement and further characterizes a neuropathy as demyelinating, axonal, or mixed.

Summary of Approaches to Diagnostic Evaluation
Article (Publication Year) Essentials of Recommended Approach
Lunn3 (2007) Details 6 essential questions in the history, highlighting: 1. Temporal evolution; 2. Autonomic involvement; 3. Nerve involvement (sensory/motor); 4. Cranial nerve involvement; 5. Family history; and 6. Coexistent disease
Examination should confirm findings expected from history
Acute and multifocal neuropathies merit urgent evaluation
Electrodiagnostic testing and neurology consultation should ensue if no diagnosis identified from above
Burns et al.6 (2006) Focuses on evaluation of polyneuropathy
Poses 4 questions: 1. Nerve involvement (sensory/motor); 2. Distribution; 3. Onset; 4. Associated factors (family history, exposures, associated systemic symptoms)
Recommends electrodiagnostic testing
Laboratory testing as indicated
Scott and Kothari5 (2005) Highlights importance of pattern recognition in the history and on examination
Ordered approach: 1. Localize site of neuropathic lesion, 2. Perform electrodiagnostic testing to determine pathology
Bromberg1 (2005) Proposes 7 layers to consider in investigation: 1. Localizing to peripheral nervous system; 2. Distribution; 3. Onset; 4. Nerve involvement (sensory/motor); 5. Pathology (axonal/demyelinating); 6. Other associated features; and 7. Epidemiologic features
Kelly4 (2004) Highlights pattern recognition and features distribution, onset, and pathology in developing the differential diagnosis
Younger10 (2004) Several key elements, including: timing, nerve involvement (sensory/motor/autonomic), distribution, and pathology (axonal/demyelinating)
England and Asbury7 (2004) Details to determine: 1. Distribution; 2. Pathology (axonal/demyelinating); and 3. Timing
Smith and Bromberg9 (2003) Suggest an algorithm: 1. Confirm the localization (history, examination and electrodiagnostic testing); 2. Identify atypical patterns; and 3. Recognize prototypic neuropathy and perform focused laboratory testing
Bromberg and Smith11 (2002) 4 basic steps: 1. Nerve involvement (sensory/motor); 2. Distribution; 3. Timing; and 4. Pathology (axonal/demyelinating)
Hughes2 (2002) Pattern recognition
Suggests staged investigation: 1. Basic laboratory tests; 2. Electrodiagnostic testing and further laboratory tests; and 3. Additional laboratory tests, imaging, and specialized testing
Pourmand8 (2002) Offers 7 key questions/steps highlighting: 1. Onset; 2. Course; 3. Distribution; 4. Nerve involvement (sensory/motor); 5. Nerve fiber type (large/small); 6. Autonomic involvement; and 7. Pathology (axonal/demyelinating)

A General Approach for the Hospitalist

Pattern recognition and employing the essentials outlined above are key tools in the hospitalist's evaluation of peripheral neuropathy. Pattern recognition relies on a familiarity with the more common acute and severe neuropathies. For circumstances in which the diagnosis is not immediately recognizable, a systematic approach expedites evaluation. Figure 1 presents an algorithm for evaluating peripheral neuropathies in the acutely ill patient.

Figure 1
A practical approach to evaluating symptoms of peripheral neuropathy for the hospitalist.

Pattern Recognition

In general, most acute or subacute and rapidly progressive neuropathies merit urgent neurology consultation. Patterns to be aware of in the acutely ill patient include Guillan‐Barr syndrome, vasculitis, ischemia, toxins, medication exposures, paraneoplastic syndromes, acute intermittent porphyria, diphtheria, and critical illness neuropathy. Any neuropathy presenting with associated respiratory symptoms or signs, such as shortness of breath, rapid shallow breathing, or hypoxia or hypercarbia, should also trigger urgent neurology consultation. As timely diagnosis of concerning entities relies heavily on pattern recognition, the typical presentation of more common etiologies and clues to their diagnosis are reviewed in Table 2.

Typical Presentations of Acute and Concerning Peripheral Neuropathies
Etiology Typical Presentation Onset Distribution Electrodiagnostic Findings
  • Abbreviations: AIDP, acute inflammatory demyelinating polyneuropathy; GBS, Guillan‐Barr syndrome; GI, gastrointestinal; URI, upper respiratory infection.

Traumatic neuropathy Weakness and numbness in a limb following injury Sudden Asymmetric Axonal
Guillan‐Barr syndrome Acute inflammatory demyelinating polyneuropathy is most common but several variants exist; often follows URI or GI illness by 1‐3 weeks Days to weeks Ascending, symmetric Usually demyelinating, largely motor
Diphtheria Tonsillopharyngeal pseudomembrane Days to weeks Bulbar, descending, symmetric Mostly demyelinating
Vasculitis Waxing and waning, painful Days to weeks Asymmetric Axonal
Acute intermittent porphyria Can be associated with seizures/encephalopathy, abdominal pain Days to weeks Ascending, symmetric Axonal, largely motor
Ischemic neuropathy May follow vascular procedure by days to months; can be associated with poor peripheral pulses Days to weeks Asymmetric Axonal
Toxins/drugs Temporal association with offending agent: heavy metals: arsenic, lead, thallium; biologic toxins: ciguatera and shellfish poisoning. Medications: chemotherapies (ie, vincristine), colchicine, statins, nitrofurantoin, chloroquine Days to months Symmetric Axonal
Critical illness neuropathy Quadriparesis in the setting of sepsis/corticosteroids/neuromuscular blockade Weeks Symmetric Axonal, largely motor
Paraneoplastic Sensory ataxia most common; symptoms may precede cancer diagnosis; frequently associated tumors: small cell carcinoma of the lung; breast, ovarian, stomach cancers Weeks Symmetric Axonal, largely sensory
Proximal diabetic neuropathy Also known as diabetic lumbosacral plexopathy or Bruns‐Garland; leg pain followed by weakness/wasting Weeks to months Asymmetric Axonal, largely motor

For example, neuropathy from acute intermittent porphyria classically presents with pain in the back and limbs and progressive limb weakness (often more pronounced in the upper extremities). Respiratory failure may follow. A key to this history is that symptoms frequently follow within days of the colicky abdominal pain and encephalopathy of an attack. Additionally, attacks typically follow a precipitating event or drug exposure. These patients do not have the skin changes seen in other forms of porphyria. Treatment of this condition requires recognition and removal of any offending drug, correction of associated metabolic abnormalities, and the administration of hematin.12

Another, though rare, diagnosis that relies on pattern recognition is Bruns‐Garland syndrome (also known as proximal diabetic neuropathy). This condition is usually self‐limited, yet patients can be referred for unnecessary spinal surgery due to the severity of its symptoms. The clinical triad of severe thigh pain, absent knee jerk, and weakness in the lumbar vertebrae L3‐L4 distribution in a patient with diabetes should raise concern for this syndrome. The contralateral lower extremity can become involved in the following weeks. This syndrome is typified by a combination of injuries to the nerve root, the lumbar plexus, and the peripheral nerve. Electrodiagnostic testing confirms the syndrome, thus avoiding an unwarranted surgery.13

A Systematic Evaluation

When the etiology is not immediately evident, the essential questions identified in the review above are useful, and can be simplified for the hospitalist. First, understand the onset and timing of symptoms. Second, localize the symptoms to and within the peripheral nervous system (including classifying the distribution of nerve involvement). For acute, rapidly progressing or multifocal neuropathies urgent inpatient electrodiagnostic testing and neurology consultation should be obtained. Further testing, including laboratory testing, should be directed by these first steps.

Step 1

Delineating onset, timing and progression is of tremendous utility in establishing the diagnosis. Abrupt onset is typical of trauma, compression, thermal injury, and ischemia (due to vasculitis or other circulatory compromise). Guillan‐Barr syndrome, porphyria, critical illness neuropathy, and diphtheria can also present acutely with profound weakness. Neuropathies developing suddenly or over days to weeks merit urgent inpatient evaluation. Metabolic, paraneoplastic, and toxic causes tend to present with progressive symptoms over weeks to months. Chronic, insidious onset is most characteristic of hereditary neuropathies and some metabolic diseases such as diabetes mellitus. Evaluation of chronic neuropathies can be deferred to the outpatient setting.

Nonneuropathy causes of acute generalized weakness to consider in the differential diagnosis include: 1) muscle disorders such as periodic paralyses, metabolic defects, and myopathies (including acute viral and Lyme disease); 2) disorders of the neuromuscular junction such as myasthenia gravis, Eaton‐Lambert syndrome, organophosphate poisoning, and botulism; 3) central nervous system disorders such as brainstem ischemia, global ischemia, or multiple sclerosis; and 4) electrolyte disturbances such as hyperkalemia or hypercalcemia.14

Step 2

It is important to localize symptoms to the peripheral nervous system. Cortical lesions are unlikely to cause focal or positive sensory symptoms (ie, pain), and more frequently involve the face or upper and lower unilateral limb (ie, in the case of a stroke). Hyperreflexia can accompany cortical lesions. Conversely, peripheral nerve lesions often localize to a discrete region of a single limb or involve the contralateral limb in a symmetric fashion (ie, a stocking‐glove distribution or the ascending symmetric pattern seen in Guillan‐Barr syndrome).

With a thorough history and neurological examination the clinician can localize and classify the neuropathic lesion. Noting a motor or sensory predominance can narrow the diagnosis; for example, motor predominance is seen in Guillan‐Barr syndrome, critical illness neuropathy, and acute intermittent porphyria. Associated symptoms and signs discovered in a thorough review and physical examination of all systems can indicate the specific diagnosis. For example, a careful skin examination may find signs of vasculitis or Mees' lines (transverse white lines across the nails that can indicate heavy metal poisoning).12 Helpful tips for this evaluation are included in Table 3.

Keys and Clues to Localizing Acute Neuropathic Lesions
History Examination
  • Abbreviations: GBS, Guillian‐Barr syndrome; GI, gastrointestinal.

Ask the patient to outline the region involved General findings
Dermatome radiculopathy Screening for malignancy
Stocking‐glove polyneuropathy Evaluate for vascular sufficiency
Single peripheral nerve mononeuropathy Pes cavus suggests inherited disease
Asymmetry vasculitic neuropathy or other mononeuropathy multiplex Skin exam for signs of vasculitis, Mees' lines
Associated symptoms Neurologic findings: For each of the following, noting the distribution of abnormality will help classify the neuropathic lesion
Constitutional neoplasm Decreased sensation (often the earliest sign)
Recent respiratory or GI illness GBS Weakness without atrophy indicates recent axonal neuropathy or isolated demyelinating disease
Respiratory difficulties GBS Marked atrophy indicates severe axonal damage
Autonomic symptoms GBS, porphyria Decreased reflexes often present (except when only small sensory fibers are involved)
Colicky abdominal pain, encephalopathy
Porphyria

The hospitalist should be able to classify the distribution as a mononeuropathy (involving a single nerve), a polyneuropathy (symmetric involvement of multiple nerves), or a mononeuropathy multiplex (asymmetric involvement of multiple nerves). Multifocal and proximal symmetric neuropathies commonly merit urgent evaluation.

The most devastating polyneuropathy is Guillan‐Barr syndrome, which can be fatal but is often reversible with early plasmapheresis. Vasculitis is another potentially treatable diagnosis that is critical to establish early; it most often presents as a mononeuropathy multiplex. Ischemic and traumatic mononeuropathies may be overshadowed by other illnesses and injuries, but finding these early can result in dramatically improved patient outcomes.

Step 3

Inpatient electrodiagnostic testing and neurology consultation should be ordered for any neuropathy with rapid onset, progression or severe symptoms or any neuropathy following one of the patterns described above. Electrodiagnostic testing characterizes the pathologic cause of the neuropathy as axonal, demyelinating, or mixed. It also assesses severity, chronicity, location, and symmetry of the neuropathy.15 It is imperative to have localized the neuropathy by history and examination prior to electrodiagnostic evaluation to ensure that the involved nerves are tested.

Step 4

Focused, further testing may be ordered more efficiently subsequent to the above data collection. Directed laboratory examination should be performed when indicated rather than cast as an initial broad diagnostic net. Ultrasound, magnetic resonance imaging (MRI), computed tomographypositron emission tomography (CT‐PET), and nerve biopsy are diagnostic modalities available to the clinician. In general, nerve biopsy should be reserved for suspected vasculitis, sarcoidosis, lymphoma, leprosy, or amyloidosis.

In summary, symptoms and signs of multifocal or proximal nerve involvement, acute onset, or rapid progression demand immediate diagnostic attention. Pattern recognition and a systematic approach expedite the diagnostic process, focusing necessary testing and decreasing overall cost. Focused steps in a systematic approach include: (1) delineating timing and onset of symptoms; (2) localizing and classifying the neuropathy; (3) obtaining electrodiagnostic testing and neurology consultation; and (4) further testing as directed by the preceding steps. Early diagnosis of acute peripheral neuropathies can lead to life‐saving or limb‐saving therapy.

References
  1. Bromberg MB.An approach to the evaluation of peripheral neuropathies.Semin Neurol.2005;25:153159.
  2. Hughes RA.Peripheral neuropathy.BMJ.2002;324:466469.
  3. Lunn MP.Pinpointing peripheral neuropathies.Practitioner.2007;251:6768,7174,67 passim.
  4. Kelly JJ.The evaluation of peripheral neuropathy. Part I: Clinical and laboratory evidence.Rev Neurol Dis.2004;1:133140.
  5. Scott K,Kothari MJ.Evaluating the patient with peripheral nervous system complaints.J Am Osteopath Assoc.2005;105:7183.
  6. Burns JM,Mauermann ML,Burns TM.An easy approach to evaluating peripheral neuropathy.J Fam Pract.2006;55:853861.
  7. England JD,Asbury AK.Peripheral neuropathy.Lancet.2004;363:21512161.
  8. Pourmand R.Evaluating patients with suspected peripheral neuropathy: do the right thing, not everything.Muscle Nerve.2002;26:288290.
  9. Smith AG,Bromberg MB.A rational diagnostic approach to peripheral neuropathy.J Clin Neuromuscul Dis.2003;4:190198.
  10. Younger DS.Peripheral nerve disorders.Prim Care.2004;31:6783.
  11. Bromberg MB,Smith AG.Toward an efficient method to evaluate peripheral neuropathies.J Clin Neuromuscul Dis.2002;3:172182.
  12. Pascuzzi RM.Peripheral neuropathies in clinical practice.Med Clin North Am.2003;87:697724.
  13. Kelly JJ.The evaluation of peripheral neuropathy. Part II: Identifying common clinical syndromes.Rev Neurol Dis.2004;1:190201.
  14. Barnabe C.Acute generalized weakness due to thyrotoxic periodic paralysis.CMAJ.2005;172:471472.
  15. Chemali KR,Tsao B.Electrodiagnostic testing of nerves and muscles: when, why, and how to order.Cleve Clin J Med.2005;72:3748.
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Early diagnosis of peripheral neuropathies can lead to life‐saving or limb‐saving intervention. While infrequently a cause for concern in the hospital setting, peripheral neuropathies are commonoccurring in up to 10% of the general population.1 The hospitalist needs to expeditiously identify acute and life‐threatening or limb‐threatening causes among an immense set of differentials. Fortunately, with an informed and careful approach, most neuropathies in need of urgent intervention can be readily identified. A thorough history and examination, with the addition of electrodiagnostic testing, comprise the mainstays of this process. Inpatient neurology consultation should be sought for any rapidly progressing or acute onset neuropathy. The aim of this review is to equip the general hospitalist with a solid framework for efficiently evaluating peripheral neuropathies in urgent cases.

Literature Review

Search Strategy

A PubMed search was conducted using the title word peripheral, the medical subject heading major topic peripheral nervous system diseases/diagnosis, and algorithm or diagnosis, differential or diagnostic techniques, neurological or neurologic examination or evaluation or evaluating. The search was limited to English language review articles published between January 2002 and November 2007. Articles were included in this review if they provided an overview of an approach to the diagnosis of peripheral neuropathies. References listed in these articles were cross‐checked and additional articles meeting these criteria were included. Articles specific to subtypes of neuropathies or diagnostic tools were excluded.

Search Results

No single guideline or algorithm has been widely endorsed for the approach to diagnosing peripheral neuropathies. Several are suggested in the literature, but none are directed at the hospitalist. In general, acute and multifocal neuropathies are characterized as neurologic emergencies requiring immediate evaluation.2, 3

Several articles underscore the importance of pattern recognition in diagnosing peripheral neuropathies.2, 4, 5 Many articles present essential questions in evaluating peripheral neuropathy; some suggest an ordered approach.13, 511 The nature of these questions and recommended order of inquiry varies among authors (Table 1). Three essentials common to all articles include: 1) noting the onset of symptoms; 2) determining the distribution of nerve involvement; and 3) identifying the pathology as axonal, demyelinating, or mixed. All articles underscore the importance of the physical examination in determining and confirming distribution and nerve type. A thorough examination evaluating for systemic signs of etiologic possibilities is strongly recommended. Electrodiagnostic testing provides confirmation of the distribution of nerve involvement and further characterizes a neuropathy as demyelinating, axonal, or mixed.

Summary of Approaches to Diagnostic Evaluation
Article (Publication Year) Essentials of Recommended Approach
Lunn3 (2007) Details 6 essential questions in the history, highlighting: 1. Temporal evolution; 2. Autonomic involvement; 3. Nerve involvement (sensory/motor); 4. Cranial nerve involvement; 5. Family history; and 6. Coexistent disease
Examination should confirm findings expected from history
Acute and multifocal neuropathies merit urgent evaluation
Electrodiagnostic testing and neurology consultation should ensue if no diagnosis identified from above
Burns et al.6 (2006) Focuses on evaluation of polyneuropathy
Poses 4 questions: 1. Nerve involvement (sensory/motor); 2. Distribution; 3. Onset; 4. Associated factors (family history, exposures, associated systemic symptoms)
Recommends electrodiagnostic testing
Laboratory testing as indicated
Scott and Kothari5 (2005) Highlights importance of pattern recognition in the history and on examination
Ordered approach: 1. Localize site of neuropathic lesion, 2. Perform electrodiagnostic testing to determine pathology
Bromberg1 (2005) Proposes 7 layers to consider in investigation: 1. Localizing to peripheral nervous system; 2. Distribution; 3. Onset; 4. Nerve involvement (sensory/motor); 5. Pathology (axonal/demyelinating); 6. Other associated features; and 7. Epidemiologic features
Kelly4 (2004) Highlights pattern recognition and features distribution, onset, and pathology in developing the differential diagnosis
Younger10 (2004) Several key elements, including: timing, nerve involvement (sensory/motor/autonomic), distribution, and pathology (axonal/demyelinating)
England and Asbury7 (2004) Details to determine: 1. Distribution; 2. Pathology (axonal/demyelinating); and 3. Timing
Smith and Bromberg9 (2003) Suggest an algorithm: 1. Confirm the localization (history, examination and electrodiagnostic testing); 2. Identify atypical patterns; and 3. Recognize prototypic neuropathy and perform focused laboratory testing
Bromberg and Smith11 (2002) 4 basic steps: 1. Nerve involvement (sensory/motor); 2. Distribution; 3. Timing; and 4. Pathology (axonal/demyelinating)
Hughes2 (2002) Pattern recognition
Suggests staged investigation: 1. Basic laboratory tests; 2. Electrodiagnostic testing and further laboratory tests; and 3. Additional laboratory tests, imaging, and specialized testing
Pourmand8 (2002) Offers 7 key questions/steps highlighting: 1. Onset; 2. Course; 3. Distribution; 4. Nerve involvement (sensory/motor); 5. Nerve fiber type (large/small); 6. Autonomic involvement; and 7. Pathology (axonal/demyelinating)

A General Approach for the Hospitalist

Pattern recognition and employing the essentials outlined above are key tools in the hospitalist's evaluation of peripheral neuropathy. Pattern recognition relies on a familiarity with the more common acute and severe neuropathies. For circumstances in which the diagnosis is not immediately recognizable, a systematic approach expedites evaluation. Figure 1 presents an algorithm for evaluating peripheral neuropathies in the acutely ill patient.

Figure 1
A practical approach to evaluating symptoms of peripheral neuropathy for the hospitalist.

Pattern Recognition

In general, most acute or subacute and rapidly progressive neuropathies merit urgent neurology consultation. Patterns to be aware of in the acutely ill patient include Guillan‐Barr syndrome, vasculitis, ischemia, toxins, medication exposures, paraneoplastic syndromes, acute intermittent porphyria, diphtheria, and critical illness neuropathy. Any neuropathy presenting with associated respiratory symptoms or signs, such as shortness of breath, rapid shallow breathing, or hypoxia or hypercarbia, should also trigger urgent neurology consultation. As timely diagnosis of concerning entities relies heavily on pattern recognition, the typical presentation of more common etiologies and clues to their diagnosis are reviewed in Table 2.

Typical Presentations of Acute and Concerning Peripheral Neuropathies
Etiology Typical Presentation Onset Distribution Electrodiagnostic Findings
  • Abbreviations: AIDP, acute inflammatory demyelinating polyneuropathy; GBS, Guillan‐Barr syndrome; GI, gastrointestinal; URI, upper respiratory infection.

Traumatic neuropathy Weakness and numbness in a limb following injury Sudden Asymmetric Axonal
Guillan‐Barr syndrome Acute inflammatory demyelinating polyneuropathy is most common but several variants exist; often follows URI or GI illness by 1‐3 weeks Days to weeks Ascending, symmetric Usually demyelinating, largely motor
Diphtheria Tonsillopharyngeal pseudomembrane Days to weeks Bulbar, descending, symmetric Mostly demyelinating
Vasculitis Waxing and waning, painful Days to weeks Asymmetric Axonal
Acute intermittent porphyria Can be associated with seizures/encephalopathy, abdominal pain Days to weeks Ascending, symmetric Axonal, largely motor
Ischemic neuropathy May follow vascular procedure by days to months; can be associated with poor peripheral pulses Days to weeks Asymmetric Axonal
Toxins/drugs Temporal association with offending agent: heavy metals: arsenic, lead, thallium; biologic toxins: ciguatera and shellfish poisoning. Medications: chemotherapies (ie, vincristine), colchicine, statins, nitrofurantoin, chloroquine Days to months Symmetric Axonal
Critical illness neuropathy Quadriparesis in the setting of sepsis/corticosteroids/neuromuscular blockade Weeks Symmetric Axonal, largely motor
Paraneoplastic Sensory ataxia most common; symptoms may precede cancer diagnosis; frequently associated tumors: small cell carcinoma of the lung; breast, ovarian, stomach cancers Weeks Symmetric Axonal, largely sensory
Proximal diabetic neuropathy Also known as diabetic lumbosacral plexopathy or Bruns‐Garland; leg pain followed by weakness/wasting Weeks to months Asymmetric Axonal, largely motor

For example, neuropathy from acute intermittent porphyria classically presents with pain in the back and limbs and progressive limb weakness (often more pronounced in the upper extremities). Respiratory failure may follow. A key to this history is that symptoms frequently follow within days of the colicky abdominal pain and encephalopathy of an attack. Additionally, attacks typically follow a precipitating event or drug exposure. These patients do not have the skin changes seen in other forms of porphyria. Treatment of this condition requires recognition and removal of any offending drug, correction of associated metabolic abnormalities, and the administration of hematin.12

Another, though rare, diagnosis that relies on pattern recognition is Bruns‐Garland syndrome (also known as proximal diabetic neuropathy). This condition is usually self‐limited, yet patients can be referred for unnecessary spinal surgery due to the severity of its symptoms. The clinical triad of severe thigh pain, absent knee jerk, and weakness in the lumbar vertebrae L3‐L4 distribution in a patient with diabetes should raise concern for this syndrome. The contralateral lower extremity can become involved in the following weeks. This syndrome is typified by a combination of injuries to the nerve root, the lumbar plexus, and the peripheral nerve. Electrodiagnostic testing confirms the syndrome, thus avoiding an unwarranted surgery.13

A Systematic Evaluation

When the etiology is not immediately evident, the essential questions identified in the review above are useful, and can be simplified for the hospitalist. First, understand the onset and timing of symptoms. Second, localize the symptoms to and within the peripheral nervous system (including classifying the distribution of nerve involvement). For acute, rapidly progressing or multifocal neuropathies urgent inpatient electrodiagnostic testing and neurology consultation should be obtained. Further testing, including laboratory testing, should be directed by these first steps.

Step 1

Delineating onset, timing and progression is of tremendous utility in establishing the diagnosis. Abrupt onset is typical of trauma, compression, thermal injury, and ischemia (due to vasculitis or other circulatory compromise). Guillan‐Barr syndrome, porphyria, critical illness neuropathy, and diphtheria can also present acutely with profound weakness. Neuropathies developing suddenly or over days to weeks merit urgent inpatient evaluation. Metabolic, paraneoplastic, and toxic causes tend to present with progressive symptoms over weeks to months. Chronic, insidious onset is most characteristic of hereditary neuropathies and some metabolic diseases such as diabetes mellitus. Evaluation of chronic neuropathies can be deferred to the outpatient setting.

Nonneuropathy causes of acute generalized weakness to consider in the differential diagnosis include: 1) muscle disorders such as periodic paralyses, metabolic defects, and myopathies (including acute viral and Lyme disease); 2) disorders of the neuromuscular junction such as myasthenia gravis, Eaton‐Lambert syndrome, organophosphate poisoning, and botulism; 3) central nervous system disorders such as brainstem ischemia, global ischemia, or multiple sclerosis; and 4) electrolyte disturbances such as hyperkalemia or hypercalcemia.14

Step 2

It is important to localize symptoms to the peripheral nervous system. Cortical lesions are unlikely to cause focal or positive sensory symptoms (ie, pain), and more frequently involve the face or upper and lower unilateral limb (ie, in the case of a stroke). Hyperreflexia can accompany cortical lesions. Conversely, peripheral nerve lesions often localize to a discrete region of a single limb or involve the contralateral limb in a symmetric fashion (ie, a stocking‐glove distribution or the ascending symmetric pattern seen in Guillan‐Barr syndrome).

With a thorough history and neurological examination the clinician can localize and classify the neuropathic lesion. Noting a motor or sensory predominance can narrow the diagnosis; for example, motor predominance is seen in Guillan‐Barr syndrome, critical illness neuropathy, and acute intermittent porphyria. Associated symptoms and signs discovered in a thorough review and physical examination of all systems can indicate the specific diagnosis. For example, a careful skin examination may find signs of vasculitis or Mees' lines (transverse white lines across the nails that can indicate heavy metal poisoning).12 Helpful tips for this evaluation are included in Table 3.

Keys and Clues to Localizing Acute Neuropathic Lesions
History Examination
  • Abbreviations: GBS, Guillian‐Barr syndrome; GI, gastrointestinal.

Ask the patient to outline the region involved General findings
Dermatome radiculopathy Screening for malignancy
Stocking‐glove polyneuropathy Evaluate for vascular sufficiency
Single peripheral nerve mononeuropathy Pes cavus suggests inherited disease
Asymmetry vasculitic neuropathy or other mononeuropathy multiplex Skin exam for signs of vasculitis, Mees' lines
Associated symptoms Neurologic findings: For each of the following, noting the distribution of abnormality will help classify the neuropathic lesion
Constitutional neoplasm Decreased sensation (often the earliest sign)
Recent respiratory or GI illness GBS Weakness without atrophy indicates recent axonal neuropathy or isolated demyelinating disease
Respiratory difficulties GBS Marked atrophy indicates severe axonal damage
Autonomic symptoms GBS, porphyria Decreased reflexes often present (except when only small sensory fibers are involved)
Colicky abdominal pain, encephalopathy
Porphyria

The hospitalist should be able to classify the distribution as a mononeuropathy (involving a single nerve), a polyneuropathy (symmetric involvement of multiple nerves), or a mononeuropathy multiplex (asymmetric involvement of multiple nerves). Multifocal and proximal symmetric neuropathies commonly merit urgent evaluation.

The most devastating polyneuropathy is Guillan‐Barr syndrome, which can be fatal but is often reversible with early plasmapheresis. Vasculitis is another potentially treatable diagnosis that is critical to establish early; it most often presents as a mononeuropathy multiplex. Ischemic and traumatic mononeuropathies may be overshadowed by other illnesses and injuries, but finding these early can result in dramatically improved patient outcomes.

Step 3

Inpatient electrodiagnostic testing and neurology consultation should be ordered for any neuropathy with rapid onset, progression or severe symptoms or any neuropathy following one of the patterns described above. Electrodiagnostic testing characterizes the pathologic cause of the neuropathy as axonal, demyelinating, or mixed. It also assesses severity, chronicity, location, and symmetry of the neuropathy.15 It is imperative to have localized the neuropathy by history and examination prior to electrodiagnostic evaluation to ensure that the involved nerves are tested.

Step 4

Focused, further testing may be ordered more efficiently subsequent to the above data collection. Directed laboratory examination should be performed when indicated rather than cast as an initial broad diagnostic net. Ultrasound, magnetic resonance imaging (MRI), computed tomographypositron emission tomography (CT‐PET), and nerve biopsy are diagnostic modalities available to the clinician. In general, nerve biopsy should be reserved for suspected vasculitis, sarcoidosis, lymphoma, leprosy, or amyloidosis.

In summary, symptoms and signs of multifocal or proximal nerve involvement, acute onset, or rapid progression demand immediate diagnostic attention. Pattern recognition and a systematic approach expedite the diagnostic process, focusing necessary testing and decreasing overall cost. Focused steps in a systematic approach include: (1) delineating timing and onset of symptoms; (2) localizing and classifying the neuropathy; (3) obtaining electrodiagnostic testing and neurology consultation; and (4) further testing as directed by the preceding steps. Early diagnosis of acute peripheral neuropathies can lead to life‐saving or limb‐saving therapy.

Early diagnosis of peripheral neuropathies can lead to life‐saving or limb‐saving intervention. While infrequently a cause for concern in the hospital setting, peripheral neuropathies are commonoccurring in up to 10% of the general population.1 The hospitalist needs to expeditiously identify acute and life‐threatening or limb‐threatening causes among an immense set of differentials. Fortunately, with an informed and careful approach, most neuropathies in need of urgent intervention can be readily identified. A thorough history and examination, with the addition of electrodiagnostic testing, comprise the mainstays of this process. Inpatient neurology consultation should be sought for any rapidly progressing or acute onset neuropathy. The aim of this review is to equip the general hospitalist with a solid framework for efficiently evaluating peripheral neuropathies in urgent cases.

Literature Review

Search Strategy

A PubMed search was conducted using the title word peripheral, the medical subject heading major topic peripheral nervous system diseases/diagnosis, and algorithm or diagnosis, differential or diagnostic techniques, neurological or neurologic examination or evaluation or evaluating. The search was limited to English language review articles published between January 2002 and November 2007. Articles were included in this review if they provided an overview of an approach to the diagnosis of peripheral neuropathies. References listed in these articles were cross‐checked and additional articles meeting these criteria were included. Articles specific to subtypes of neuropathies or diagnostic tools were excluded.

Search Results

No single guideline or algorithm has been widely endorsed for the approach to diagnosing peripheral neuropathies. Several are suggested in the literature, but none are directed at the hospitalist. In general, acute and multifocal neuropathies are characterized as neurologic emergencies requiring immediate evaluation.2, 3

Several articles underscore the importance of pattern recognition in diagnosing peripheral neuropathies.2, 4, 5 Many articles present essential questions in evaluating peripheral neuropathy; some suggest an ordered approach.13, 511 The nature of these questions and recommended order of inquiry varies among authors (Table 1). Three essentials common to all articles include: 1) noting the onset of symptoms; 2) determining the distribution of nerve involvement; and 3) identifying the pathology as axonal, demyelinating, or mixed. All articles underscore the importance of the physical examination in determining and confirming distribution and nerve type. A thorough examination evaluating for systemic signs of etiologic possibilities is strongly recommended. Electrodiagnostic testing provides confirmation of the distribution of nerve involvement and further characterizes a neuropathy as demyelinating, axonal, or mixed.

Summary of Approaches to Diagnostic Evaluation
Article (Publication Year) Essentials of Recommended Approach
Lunn3 (2007) Details 6 essential questions in the history, highlighting: 1. Temporal evolution; 2. Autonomic involvement; 3. Nerve involvement (sensory/motor); 4. Cranial nerve involvement; 5. Family history; and 6. Coexistent disease
Examination should confirm findings expected from history
Acute and multifocal neuropathies merit urgent evaluation
Electrodiagnostic testing and neurology consultation should ensue if no diagnosis identified from above
Burns et al.6 (2006) Focuses on evaluation of polyneuropathy
Poses 4 questions: 1. Nerve involvement (sensory/motor); 2. Distribution; 3. Onset; 4. Associated factors (family history, exposures, associated systemic symptoms)
Recommends electrodiagnostic testing
Laboratory testing as indicated
Scott and Kothari5 (2005) Highlights importance of pattern recognition in the history and on examination
Ordered approach: 1. Localize site of neuropathic lesion, 2. Perform electrodiagnostic testing to determine pathology
Bromberg1 (2005) Proposes 7 layers to consider in investigation: 1. Localizing to peripheral nervous system; 2. Distribution; 3. Onset; 4. Nerve involvement (sensory/motor); 5. Pathology (axonal/demyelinating); 6. Other associated features; and 7. Epidemiologic features
Kelly4 (2004) Highlights pattern recognition and features distribution, onset, and pathology in developing the differential diagnosis
Younger10 (2004) Several key elements, including: timing, nerve involvement (sensory/motor/autonomic), distribution, and pathology (axonal/demyelinating)
England and Asbury7 (2004) Details to determine: 1. Distribution; 2. Pathology (axonal/demyelinating); and 3. Timing
Smith and Bromberg9 (2003) Suggest an algorithm: 1. Confirm the localization (history, examination and electrodiagnostic testing); 2. Identify atypical patterns; and 3. Recognize prototypic neuropathy and perform focused laboratory testing
Bromberg and Smith11 (2002) 4 basic steps: 1. Nerve involvement (sensory/motor); 2. Distribution; 3. Timing; and 4. Pathology (axonal/demyelinating)
Hughes2 (2002) Pattern recognition
Suggests staged investigation: 1. Basic laboratory tests; 2. Electrodiagnostic testing and further laboratory tests; and 3. Additional laboratory tests, imaging, and specialized testing
Pourmand8 (2002) Offers 7 key questions/steps highlighting: 1. Onset; 2. Course; 3. Distribution; 4. Nerve involvement (sensory/motor); 5. Nerve fiber type (large/small); 6. Autonomic involvement; and 7. Pathology (axonal/demyelinating)

A General Approach for the Hospitalist

Pattern recognition and employing the essentials outlined above are key tools in the hospitalist's evaluation of peripheral neuropathy. Pattern recognition relies on a familiarity with the more common acute and severe neuropathies. For circumstances in which the diagnosis is not immediately recognizable, a systematic approach expedites evaluation. Figure 1 presents an algorithm for evaluating peripheral neuropathies in the acutely ill patient.

Figure 1
A practical approach to evaluating symptoms of peripheral neuropathy for the hospitalist.

Pattern Recognition

In general, most acute or subacute and rapidly progressive neuropathies merit urgent neurology consultation. Patterns to be aware of in the acutely ill patient include Guillan‐Barr syndrome, vasculitis, ischemia, toxins, medication exposures, paraneoplastic syndromes, acute intermittent porphyria, diphtheria, and critical illness neuropathy. Any neuropathy presenting with associated respiratory symptoms or signs, such as shortness of breath, rapid shallow breathing, or hypoxia or hypercarbia, should also trigger urgent neurology consultation. As timely diagnosis of concerning entities relies heavily on pattern recognition, the typical presentation of more common etiologies and clues to their diagnosis are reviewed in Table 2.

Typical Presentations of Acute and Concerning Peripheral Neuropathies
Etiology Typical Presentation Onset Distribution Electrodiagnostic Findings
  • Abbreviations: AIDP, acute inflammatory demyelinating polyneuropathy; GBS, Guillan‐Barr syndrome; GI, gastrointestinal; URI, upper respiratory infection.

Traumatic neuropathy Weakness and numbness in a limb following injury Sudden Asymmetric Axonal
Guillan‐Barr syndrome Acute inflammatory demyelinating polyneuropathy is most common but several variants exist; often follows URI or GI illness by 1‐3 weeks Days to weeks Ascending, symmetric Usually demyelinating, largely motor
Diphtheria Tonsillopharyngeal pseudomembrane Days to weeks Bulbar, descending, symmetric Mostly demyelinating
Vasculitis Waxing and waning, painful Days to weeks Asymmetric Axonal
Acute intermittent porphyria Can be associated with seizures/encephalopathy, abdominal pain Days to weeks Ascending, symmetric Axonal, largely motor
Ischemic neuropathy May follow vascular procedure by days to months; can be associated with poor peripheral pulses Days to weeks Asymmetric Axonal
Toxins/drugs Temporal association with offending agent: heavy metals: arsenic, lead, thallium; biologic toxins: ciguatera and shellfish poisoning. Medications: chemotherapies (ie, vincristine), colchicine, statins, nitrofurantoin, chloroquine Days to months Symmetric Axonal
Critical illness neuropathy Quadriparesis in the setting of sepsis/corticosteroids/neuromuscular blockade Weeks Symmetric Axonal, largely motor
Paraneoplastic Sensory ataxia most common; symptoms may precede cancer diagnosis; frequently associated tumors: small cell carcinoma of the lung; breast, ovarian, stomach cancers Weeks Symmetric Axonal, largely sensory
Proximal diabetic neuropathy Also known as diabetic lumbosacral plexopathy or Bruns‐Garland; leg pain followed by weakness/wasting Weeks to months Asymmetric Axonal, largely motor

For example, neuropathy from acute intermittent porphyria classically presents with pain in the back and limbs and progressive limb weakness (often more pronounced in the upper extremities). Respiratory failure may follow. A key to this history is that symptoms frequently follow within days of the colicky abdominal pain and encephalopathy of an attack. Additionally, attacks typically follow a precipitating event or drug exposure. These patients do not have the skin changes seen in other forms of porphyria. Treatment of this condition requires recognition and removal of any offending drug, correction of associated metabolic abnormalities, and the administration of hematin.12

Another, though rare, diagnosis that relies on pattern recognition is Bruns‐Garland syndrome (also known as proximal diabetic neuropathy). This condition is usually self‐limited, yet patients can be referred for unnecessary spinal surgery due to the severity of its symptoms. The clinical triad of severe thigh pain, absent knee jerk, and weakness in the lumbar vertebrae L3‐L4 distribution in a patient with diabetes should raise concern for this syndrome. The contralateral lower extremity can become involved in the following weeks. This syndrome is typified by a combination of injuries to the nerve root, the lumbar plexus, and the peripheral nerve. Electrodiagnostic testing confirms the syndrome, thus avoiding an unwarranted surgery.13

A Systematic Evaluation

When the etiology is not immediately evident, the essential questions identified in the review above are useful, and can be simplified for the hospitalist. First, understand the onset and timing of symptoms. Second, localize the symptoms to and within the peripheral nervous system (including classifying the distribution of nerve involvement). For acute, rapidly progressing or multifocal neuropathies urgent inpatient electrodiagnostic testing and neurology consultation should be obtained. Further testing, including laboratory testing, should be directed by these first steps.

Step 1

Delineating onset, timing and progression is of tremendous utility in establishing the diagnosis. Abrupt onset is typical of trauma, compression, thermal injury, and ischemia (due to vasculitis or other circulatory compromise). Guillan‐Barr syndrome, porphyria, critical illness neuropathy, and diphtheria can also present acutely with profound weakness. Neuropathies developing suddenly or over days to weeks merit urgent inpatient evaluation. Metabolic, paraneoplastic, and toxic causes tend to present with progressive symptoms over weeks to months. Chronic, insidious onset is most characteristic of hereditary neuropathies and some metabolic diseases such as diabetes mellitus. Evaluation of chronic neuropathies can be deferred to the outpatient setting.

Nonneuropathy causes of acute generalized weakness to consider in the differential diagnosis include: 1) muscle disorders such as periodic paralyses, metabolic defects, and myopathies (including acute viral and Lyme disease); 2) disorders of the neuromuscular junction such as myasthenia gravis, Eaton‐Lambert syndrome, organophosphate poisoning, and botulism; 3) central nervous system disorders such as brainstem ischemia, global ischemia, or multiple sclerosis; and 4) electrolyte disturbances such as hyperkalemia or hypercalcemia.14

Step 2

It is important to localize symptoms to the peripheral nervous system. Cortical lesions are unlikely to cause focal or positive sensory symptoms (ie, pain), and more frequently involve the face or upper and lower unilateral limb (ie, in the case of a stroke). Hyperreflexia can accompany cortical lesions. Conversely, peripheral nerve lesions often localize to a discrete region of a single limb or involve the contralateral limb in a symmetric fashion (ie, a stocking‐glove distribution or the ascending symmetric pattern seen in Guillan‐Barr syndrome).

With a thorough history and neurological examination the clinician can localize and classify the neuropathic lesion. Noting a motor or sensory predominance can narrow the diagnosis; for example, motor predominance is seen in Guillan‐Barr syndrome, critical illness neuropathy, and acute intermittent porphyria. Associated symptoms and signs discovered in a thorough review and physical examination of all systems can indicate the specific diagnosis. For example, a careful skin examination may find signs of vasculitis or Mees' lines (transverse white lines across the nails that can indicate heavy metal poisoning).12 Helpful tips for this evaluation are included in Table 3.

Keys and Clues to Localizing Acute Neuropathic Lesions
History Examination
  • Abbreviations: GBS, Guillian‐Barr syndrome; GI, gastrointestinal.

Ask the patient to outline the region involved General findings
Dermatome radiculopathy Screening for malignancy
Stocking‐glove polyneuropathy Evaluate for vascular sufficiency
Single peripheral nerve mononeuropathy Pes cavus suggests inherited disease
Asymmetry vasculitic neuropathy or other mononeuropathy multiplex Skin exam for signs of vasculitis, Mees' lines
Associated symptoms Neurologic findings: For each of the following, noting the distribution of abnormality will help classify the neuropathic lesion
Constitutional neoplasm Decreased sensation (often the earliest sign)
Recent respiratory or GI illness GBS Weakness without atrophy indicates recent axonal neuropathy or isolated demyelinating disease
Respiratory difficulties GBS Marked atrophy indicates severe axonal damage
Autonomic symptoms GBS, porphyria Decreased reflexes often present (except when only small sensory fibers are involved)
Colicky abdominal pain, encephalopathy
Porphyria

The hospitalist should be able to classify the distribution as a mononeuropathy (involving a single nerve), a polyneuropathy (symmetric involvement of multiple nerves), or a mononeuropathy multiplex (asymmetric involvement of multiple nerves). Multifocal and proximal symmetric neuropathies commonly merit urgent evaluation.

The most devastating polyneuropathy is Guillan‐Barr syndrome, which can be fatal but is often reversible with early plasmapheresis. Vasculitis is another potentially treatable diagnosis that is critical to establish early; it most often presents as a mononeuropathy multiplex. Ischemic and traumatic mononeuropathies may be overshadowed by other illnesses and injuries, but finding these early can result in dramatically improved patient outcomes.

Step 3

Inpatient electrodiagnostic testing and neurology consultation should be ordered for any neuropathy with rapid onset, progression or severe symptoms or any neuropathy following one of the patterns described above. Electrodiagnostic testing characterizes the pathologic cause of the neuropathy as axonal, demyelinating, or mixed. It also assesses severity, chronicity, location, and symmetry of the neuropathy.15 It is imperative to have localized the neuropathy by history and examination prior to electrodiagnostic evaluation to ensure that the involved nerves are tested.

Step 4

Focused, further testing may be ordered more efficiently subsequent to the above data collection. Directed laboratory examination should be performed when indicated rather than cast as an initial broad diagnostic net. Ultrasound, magnetic resonance imaging (MRI), computed tomographypositron emission tomography (CT‐PET), and nerve biopsy are diagnostic modalities available to the clinician. In general, nerve biopsy should be reserved for suspected vasculitis, sarcoidosis, lymphoma, leprosy, or amyloidosis.

In summary, symptoms and signs of multifocal or proximal nerve involvement, acute onset, or rapid progression demand immediate diagnostic attention. Pattern recognition and a systematic approach expedite the diagnostic process, focusing necessary testing and decreasing overall cost. Focused steps in a systematic approach include: (1) delineating timing and onset of symptoms; (2) localizing and classifying the neuropathy; (3) obtaining electrodiagnostic testing and neurology consultation; and (4) further testing as directed by the preceding steps. Early diagnosis of acute peripheral neuropathies can lead to life‐saving or limb‐saving therapy.

References
  1. Bromberg MB.An approach to the evaluation of peripheral neuropathies.Semin Neurol.2005;25:153159.
  2. Hughes RA.Peripheral neuropathy.BMJ.2002;324:466469.
  3. Lunn MP.Pinpointing peripheral neuropathies.Practitioner.2007;251:6768,7174,67 passim.
  4. Kelly JJ.The evaluation of peripheral neuropathy. Part I: Clinical and laboratory evidence.Rev Neurol Dis.2004;1:133140.
  5. Scott K,Kothari MJ.Evaluating the patient with peripheral nervous system complaints.J Am Osteopath Assoc.2005;105:7183.
  6. Burns JM,Mauermann ML,Burns TM.An easy approach to evaluating peripheral neuropathy.J Fam Pract.2006;55:853861.
  7. England JD,Asbury AK.Peripheral neuropathy.Lancet.2004;363:21512161.
  8. Pourmand R.Evaluating patients with suspected peripheral neuropathy: do the right thing, not everything.Muscle Nerve.2002;26:288290.
  9. Smith AG,Bromberg MB.A rational diagnostic approach to peripheral neuropathy.J Clin Neuromuscul Dis.2003;4:190198.
  10. Younger DS.Peripheral nerve disorders.Prim Care.2004;31:6783.
  11. Bromberg MB,Smith AG.Toward an efficient method to evaluate peripheral neuropathies.J Clin Neuromuscul Dis.2002;3:172182.
  12. Pascuzzi RM.Peripheral neuropathies in clinical practice.Med Clin North Am.2003;87:697724.
  13. Kelly JJ.The evaluation of peripheral neuropathy. Part II: Identifying common clinical syndromes.Rev Neurol Dis.2004;1:190201.
  14. Barnabe C.Acute generalized weakness due to thyrotoxic periodic paralysis.CMAJ.2005;172:471472.
  15. Chemali KR,Tsao B.Electrodiagnostic testing of nerves and muscles: when, why, and how to order.Cleve Clin J Med.2005;72:3748.
References
  1. Bromberg MB.An approach to the evaluation of peripheral neuropathies.Semin Neurol.2005;25:153159.
  2. Hughes RA.Peripheral neuropathy.BMJ.2002;324:466469.
  3. Lunn MP.Pinpointing peripheral neuropathies.Practitioner.2007;251:6768,7174,67 passim.
  4. Kelly JJ.The evaluation of peripheral neuropathy. Part I: Clinical and laboratory evidence.Rev Neurol Dis.2004;1:133140.
  5. Scott K,Kothari MJ.Evaluating the patient with peripheral nervous system complaints.J Am Osteopath Assoc.2005;105:7183.
  6. Burns JM,Mauermann ML,Burns TM.An easy approach to evaluating peripheral neuropathy.J Fam Pract.2006;55:853861.
  7. England JD,Asbury AK.Peripheral neuropathy.Lancet.2004;363:21512161.
  8. Pourmand R.Evaluating patients with suspected peripheral neuropathy: do the right thing, not everything.Muscle Nerve.2002;26:288290.
  9. Smith AG,Bromberg MB.A rational diagnostic approach to peripheral neuropathy.J Clin Neuromuscul Dis.2003;4:190198.
  10. Younger DS.Peripheral nerve disorders.Prim Care.2004;31:6783.
  11. Bromberg MB,Smith AG.Toward an efficient method to evaluate peripheral neuropathies.J Clin Neuromuscul Dis.2002;3:172182.
  12. Pascuzzi RM.Peripheral neuropathies in clinical practice.Med Clin North Am.2003;87:697724.
  13. Kelly JJ.The evaluation of peripheral neuropathy. Part II: Identifying common clinical syndromes.Rev Neurol Dis.2004;1:190201.
  14. Barnabe C.Acute generalized weakness due to thyrotoxic periodic paralysis.CMAJ.2005;172:471472.
  15. Chemali KR,Tsao B.Electrodiagnostic testing of nerves and muscles: when, why, and how to order.Cleve Clin J Med.2005;72:3748.
Issue
Journal of Hospital Medicine - 4(6)
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Journal of Hospital Medicine - 4(6)
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Peripheral neuropathies: A practical approach for the hospitalist
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Peripheral neuropathies: A practical approach for the hospitalist
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Male with Arthritis and Scaly Skin Rash

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Thirty‐two‐year‐old male with arthritis and a scaly skin rash

A 32‐year‐old male presented to the emergency department complaining of pain and swelling in the right knee and left hand, along with a skin rash on both feet. He denied any fever or recent history of travel. Symptoms started 1 week before presentation. Recent medical history was significant for Chlamydia trachomatis urethritis 10 weeks prior, which had been successfully treated.

Physical examination revealed right knee effusion, dactylitis manifested by both swelling of the digits of the left hand and finger‐tip ulcerations (Figure 1), as well as hyperkeratotic plaques with erythematous bases on the soles of both feet, consistent with keratoderma blenorrhagica (Figure 2). Furthermore, scaly erythematous lesions over the penis and the scrotum were recognized, indicating circinate balanitis (Figure 3).

Figure 1
Dactylitis.
Figure 2
Keratoderma blenorrhagica.
Figure 3
Circinate balanitis.

Laboratory tests including human immunodeficiency virus (HIV) were unremarkable aside from an elevated sedimentation rate and positive human leukocyte antigen (HLA)‐B27.

The patient was diagnosed with reactive arthritis (Reiter's syndrome). A treatment regimen was initiated consisting of nonsteroidal antiinflammatory drugs (NSAIDs), prednisone, and sulfasalazine. Close outpatient follow‐up was established. Four months later, the patient remained debilitated by the disease, and etanercept was added resulting in significant improvement.

Reactive arthritis, also known as Reiter's syndrome, is an autoimmune disease that usually develops 2 to 4 weeks after a genitourinary or gastrointestinal infection. The classic triad of arthritis, urethritis, and conjunctivitis does not occur in all patients. Diagnosis is made by medical history and clinical findings. Numerous therapeutic modalities have been used with variable success, including short‐term antibiotics, NSAIDs, systemic corticosteroids, sulfasalazine, methotrexate, cyclosporine, etretinate, and tumor‐necrosis factor (TNF) inhibitors.

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Journal of Hospital Medicine - 4(6)
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A 32‐year‐old male presented to the emergency department complaining of pain and swelling in the right knee and left hand, along with a skin rash on both feet. He denied any fever or recent history of travel. Symptoms started 1 week before presentation. Recent medical history was significant for Chlamydia trachomatis urethritis 10 weeks prior, which had been successfully treated.

Physical examination revealed right knee effusion, dactylitis manifested by both swelling of the digits of the left hand and finger‐tip ulcerations (Figure 1), as well as hyperkeratotic plaques with erythematous bases on the soles of both feet, consistent with keratoderma blenorrhagica (Figure 2). Furthermore, scaly erythematous lesions over the penis and the scrotum were recognized, indicating circinate balanitis (Figure 3).

Figure 1
Dactylitis.
Figure 2
Keratoderma blenorrhagica.
Figure 3
Circinate balanitis.

Laboratory tests including human immunodeficiency virus (HIV) were unremarkable aside from an elevated sedimentation rate and positive human leukocyte antigen (HLA)‐B27.

The patient was diagnosed with reactive arthritis (Reiter's syndrome). A treatment regimen was initiated consisting of nonsteroidal antiinflammatory drugs (NSAIDs), prednisone, and sulfasalazine. Close outpatient follow‐up was established. Four months later, the patient remained debilitated by the disease, and etanercept was added resulting in significant improvement.

Reactive arthritis, also known as Reiter's syndrome, is an autoimmune disease that usually develops 2 to 4 weeks after a genitourinary or gastrointestinal infection. The classic triad of arthritis, urethritis, and conjunctivitis does not occur in all patients. Diagnosis is made by medical history and clinical findings. Numerous therapeutic modalities have been used with variable success, including short‐term antibiotics, NSAIDs, systemic corticosteroids, sulfasalazine, methotrexate, cyclosporine, etretinate, and tumor‐necrosis factor (TNF) inhibitors.

A 32‐year‐old male presented to the emergency department complaining of pain and swelling in the right knee and left hand, along with a skin rash on both feet. He denied any fever or recent history of travel. Symptoms started 1 week before presentation. Recent medical history was significant for Chlamydia trachomatis urethritis 10 weeks prior, which had been successfully treated.

Physical examination revealed right knee effusion, dactylitis manifested by both swelling of the digits of the left hand and finger‐tip ulcerations (Figure 1), as well as hyperkeratotic plaques with erythematous bases on the soles of both feet, consistent with keratoderma blenorrhagica (Figure 2). Furthermore, scaly erythematous lesions over the penis and the scrotum were recognized, indicating circinate balanitis (Figure 3).

Figure 1
Dactylitis.
Figure 2
Keratoderma blenorrhagica.
Figure 3
Circinate balanitis.

Laboratory tests including human immunodeficiency virus (HIV) were unremarkable aside from an elevated sedimentation rate and positive human leukocyte antigen (HLA)‐B27.

The patient was diagnosed with reactive arthritis (Reiter's syndrome). A treatment regimen was initiated consisting of nonsteroidal antiinflammatory drugs (NSAIDs), prednisone, and sulfasalazine. Close outpatient follow‐up was established. Four months later, the patient remained debilitated by the disease, and etanercept was added resulting in significant improvement.

Reactive arthritis, also known as Reiter's syndrome, is an autoimmune disease that usually develops 2 to 4 weeks after a genitourinary or gastrointestinal infection. The classic triad of arthritis, urethritis, and conjunctivitis does not occur in all patients. Diagnosis is made by medical history and clinical findings. Numerous therapeutic modalities have been used with variable success, including short‐term antibiotics, NSAIDs, systemic corticosteroids, sulfasalazine, methotrexate, cyclosporine, etretinate, and tumor‐necrosis factor (TNF) inhibitors.

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Thirty‐two‐year‐old male with arthritis and a scaly skin rash
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New Initiative: Defibrillator Delays

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New Initiative: Defibrillator Delays

A new report that hints stress factors like case volume and academic status of a hospital do not explain the wide disparities in defibrillation response times in hospitals has at least one hospitalist convinced HM leaders can help solve the problem.

Traditional hospital pressures do not predict whether patients with cardiac arrest are likely to experience delays in receiving defibrillation, according to a July 27 report in the Archives of Internal Medicine (2009;169(14):1260-1261). Such factors as the number of beds and where the cardiac unit was located were found to have more impact, the study found.

“This is a very simple thing,” says hospitalist Jason Persoff, MD, FHM, assistant professor of medicine at the Mayo Clinic in Jacksonville, Fla. "What are the barriers to shocking the patient? This doesn’t require huge committees. The question is, 'Why isn’t this happening?' … This paper is a call to arms."

According to the study, rates of delayed defibrillation, which were defined as longer than the two-minute standard, ranged from 2.4% to 50.9%. The authors state that standardizing defibrillation times to meet the two-minute standard set by the American Hospital Association could be a quality initiative focus for HM groups.

“Now that we’ve identified the problem, that helps us identify how to move forward,” Dr. Persoff says. “We are in dire need of improving our system when it comes to cardiac care. The hospitalists are in the best position to do that because we are able to work closest with the nurses.”

Jane Kelly-Cummings, RN, CPHQ, SHM's senior director of quality initiatives, agrees there is room for improvement in the survival rate of in-hospital cardiac patients. "In order to make those improvements, hospitals will need to make changes to their cardiac resuscitation processes and procedures," she says. "Hospitalists are integral and central players on cardiac resuscitation teams at a great majority of hospitals with hospital medicine programs. They act as change agents at these and many other facilities."

For more information on HM's role in cardiac resuscitation of hospitalized patients, visit the Emergency Procedures section of the "Core Competencies in Hospital Medicine."a

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The Hospitalist - 2009(08)
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A new report that hints stress factors like case volume and academic status of a hospital do not explain the wide disparities in defibrillation response times in hospitals has at least one hospitalist convinced HM leaders can help solve the problem.

Traditional hospital pressures do not predict whether patients with cardiac arrest are likely to experience delays in receiving defibrillation, according to a July 27 report in the Archives of Internal Medicine (2009;169(14):1260-1261). Such factors as the number of beds and where the cardiac unit was located were found to have more impact, the study found.

“This is a very simple thing,” says hospitalist Jason Persoff, MD, FHM, assistant professor of medicine at the Mayo Clinic in Jacksonville, Fla. "What are the barriers to shocking the patient? This doesn’t require huge committees. The question is, 'Why isn’t this happening?' … This paper is a call to arms."

According to the study, rates of delayed defibrillation, which were defined as longer than the two-minute standard, ranged from 2.4% to 50.9%. The authors state that standardizing defibrillation times to meet the two-minute standard set by the American Hospital Association could be a quality initiative focus for HM groups.

“Now that we’ve identified the problem, that helps us identify how to move forward,” Dr. Persoff says. “We are in dire need of improving our system when it comes to cardiac care. The hospitalists are in the best position to do that because we are able to work closest with the nurses.”

Jane Kelly-Cummings, RN, CPHQ, SHM's senior director of quality initiatives, agrees there is room for improvement in the survival rate of in-hospital cardiac patients. "In order to make those improvements, hospitals will need to make changes to their cardiac resuscitation processes and procedures," she says. "Hospitalists are integral and central players on cardiac resuscitation teams at a great majority of hospitals with hospital medicine programs. They act as change agents at these and many other facilities."

For more information on HM's role in cardiac resuscitation of hospitalized patients, visit the Emergency Procedures section of the "Core Competencies in Hospital Medicine."a

A new report that hints stress factors like case volume and academic status of a hospital do not explain the wide disparities in defibrillation response times in hospitals has at least one hospitalist convinced HM leaders can help solve the problem.

Traditional hospital pressures do not predict whether patients with cardiac arrest are likely to experience delays in receiving defibrillation, according to a July 27 report in the Archives of Internal Medicine (2009;169(14):1260-1261). Such factors as the number of beds and where the cardiac unit was located were found to have more impact, the study found.

“This is a very simple thing,” says hospitalist Jason Persoff, MD, FHM, assistant professor of medicine at the Mayo Clinic in Jacksonville, Fla. "What are the barriers to shocking the patient? This doesn’t require huge committees. The question is, 'Why isn’t this happening?' … This paper is a call to arms."

According to the study, rates of delayed defibrillation, which were defined as longer than the two-minute standard, ranged from 2.4% to 50.9%. The authors state that standardizing defibrillation times to meet the two-minute standard set by the American Hospital Association could be a quality initiative focus for HM groups.

“Now that we’ve identified the problem, that helps us identify how to move forward,” Dr. Persoff says. “We are in dire need of improving our system when it comes to cardiac care. The hospitalists are in the best position to do that because we are able to work closest with the nurses.”

Jane Kelly-Cummings, RN, CPHQ, SHM's senior director of quality initiatives, agrees there is room for improvement in the survival rate of in-hospital cardiac patients. "In order to make those improvements, hospitals will need to make changes to their cardiac resuscitation processes and procedures," she says. "Hospitalists are integral and central players on cardiac resuscitation teams at a great majority of hospitals with hospital medicine programs. They act as change agents at these and many other facilities."

For more information on HM's role in cardiac resuscitation of hospitalized patients, visit the Emergency Procedures section of the "Core Competencies in Hospital Medicine."a

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In the Lit: Research You Need to Know

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Clinical question: Does tailoring the duration of anticoagulation based on the persistence of residual thrombus following conventional duration therapy reduce rates of recurrent venous thromboembolism (VTE) in adults with proximal deep-venous thrombosis (DVT)?

Background: The optimal duration of oral anticoagulation therapy in adults with proximal DVT remains uncertain. This study was designed to ascertain if tailoring the duration of therapy based on ultrasonographic findings improves outcomes through a reduction in recurrent VTE.

Study design: Parallel, open-label, randomized trial with independent and blinded assessment of study outcomes.

Setting: Nine university and hospital centers in Italy.

Synopsis: Five hundred thirty-eight patients with proximal DVT who completed three months of anticoagulation were randomly assigned to fixed-duration or flexible-duration therapy. Patients in the fixed-duration group with provoked DVT received no further therapy; those with unprovoked DVT received an additional three months of anticoagulation. Patients in the flexible-duration group had no further therapy if ultrasonography demonstrated recanalized veins, and received further therapy (up to nine to 21 months for provoked and unprovoked DVT, respectively) if persistent thrombi were demonstrated. Patients were followed over three years for the primary outcomes of recurrent VTE and major bleeding events.

Significantly fewer recurrent VTE occurred in the ultrasound guided, flexible-duration treatment group (11.9% vs. 17.2%; HR 0.64; 95% CI 0.39 to 0.99). There was no significant difference in major bleeding events between the two groups.

Limitations of this study include the lack of a double-blind design and the relatively small sample size.

Bottom line: Tailoring the duration of anticoagulation in adults with proximal DVT based on ultrasonographic demonstration of residual thrombi reduces rates of recurrent VTE without increasing major bleeding events.

Citation: Prandoni P, Prins MH, Lensing AW, et al. Residual thrombosis on ultrasonography to guide the duration of anticoagulation in patients with deep venous thrombosis: a randomized trial. Ann Intern Med. 2009;150(9):577-585.

Reviewed for TH eWire by Alexander R. Carbo, MD, FHM; Suzanne Bertisch, MD, MPH; Lauren Doctoroff, MD; John Fani Srour, MD; Caleb Hale, MD; Nancy Torres-Finnerty, MD, FHM, Hospital Medicine Program, Beth Israel Deaconess Medical Center, Boston

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Clinical question: Does tailoring the duration of anticoagulation based on the persistence of residual thrombus following conventional duration therapy reduce rates of recurrent venous thromboembolism (VTE) in adults with proximal deep-venous thrombosis (DVT)?

Background: The optimal duration of oral anticoagulation therapy in adults with proximal DVT remains uncertain. This study was designed to ascertain if tailoring the duration of therapy based on ultrasonographic findings improves outcomes through a reduction in recurrent VTE.

Study design: Parallel, open-label, randomized trial with independent and blinded assessment of study outcomes.

Setting: Nine university and hospital centers in Italy.

Synopsis: Five hundred thirty-eight patients with proximal DVT who completed three months of anticoagulation were randomly assigned to fixed-duration or flexible-duration therapy. Patients in the fixed-duration group with provoked DVT received no further therapy; those with unprovoked DVT received an additional three months of anticoagulation. Patients in the flexible-duration group had no further therapy if ultrasonography demonstrated recanalized veins, and received further therapy (up to nine to 21 months for provoked and unprovoked DVT, respectively) if persistent thrombi were demonstrated. Patients were followed over three years for the primary outcomes of recurrent VTE and major bleeding events.

Significantly fewer recurrent VTE occurred in the ultrasound guided, flexible-duration treatment group (11.9% vs. 17.2%; HR 0.64; 95% CI 0.39 to 0.99). There was no significant difference in major bleeding events between the two groups.

Limitations of this study include the lack of a double-blind design and the relatively small sample size.

Bottom line: Tailoring the duration of anticoagulation in adults with proximal DVT based on ultrasonographic demonstration of residual thrombi reduces rates of recurrent VTE without increasing major bleeding events.

Citation: Prandoni P, Prins MH, Lensing AW, et al. Residual thrombosis on ultrasonography to guide the duration of anticoagulation in patients with deep venous thrombosis: a randomized trial. Ann Intern Med. 2009;150(9):577-585.

Reviewed for TH eWire by Alexander R. Carbo, MD, FHM; Suzanne Bertisch, MD, MPH; Lauren Doctoroff, MD; John Fani Srour, MD; Caleb Hale, MD; Nancy Torres-Finnerty, MD, FHM, Hospital Medicine Program, Beth Israel Deaconess Medical Center, Boston

Clinical question: Does tailoring the duration of anticoagulation based on the persistence of residual thrombus following conventional duration therapy reduce rates of recurrent venous thromboembolism (VTE) in adults with proximal deep-venous thrombosis (DVT)?

Background: The optimal duration of oral anticoagulation therapy in adults with proximal DVT remains uncertain. This study was designed to ascertain if tailoring the duration of therapy based on ultrasonographic findings improves outcomes through a reduction in recurrent VTE.

Study design: Parallel, open-label, randomized trial with independent and blinded assessment of study outcomes.

Setting: Nine university and hospital centers in Italy.

Synopsis: Five hundred thirty-eight patients with proximal DVT who completed three months of anticoagulation were randomly assigned to fixed-duration or flexible-duration therapy. Patients in the fixed-duration group with provoked DVT received no further therapy; those with unprovoked DVT received an additional three months of anticoagulation. Patients in the flexible-duration group had no further therapy if ultrasonography demonstrated recanalized veins, and received further therapy (up to nine to 21 months for provoked and unprovoked DVT, respectively) if persistent thrombi were demonstrated. Patients were followed over three years for the primary outcomes of recurrent VTE and major bleeding events.

Significantly fewer recurrent VTE occurred in the ultrasound guided, flexible-duration treatment group (11.9% vs. 17.2%; HR 0.64; 95% CI 0.39 to 0.99). There was no significant difference in major bleeding events between the two groups.

Limitations of this study include the lack of a double-blind design and the relatively small sample size.

Bottom line: Tailoring the duration of anticoagulation in adults with proximal DVT based on ultrasonographic demonstration of residual thrombi reduces rates of recurrent VTE without increasing major bleeding events.

Citation: Prandoni P, Prins MH, Lensing AW, et al. Residual thrombosis on ultrasonography to guide the duration of anticoagulation in patients with deep venous thrombosis: a randomized trial. Ann Intern Med. 2009;150(9):577-585.

Reviewed for TH eWire by Alexander R. Carbo, MD, FHM; Suzanne Bertisch, MD, MPH; Lauren Doctoroff, MD; John Fani Srour, MD; Caleb Hale, MD; Nancy Torres-Finnerty, MD, FHM, Hospital Medicine Program, Beth Israel Deaconess Medical Center, Boston

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Afraid in the Hospital

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Afraid in the hospital: Parental concern for errors during a child's hospitalization

The Institute of Medicine report linking between 48,000 and 98,000 deaths annually to medical errors1 has raised awareness about medical errors across all areas of medicine. In pediatrics, medical errors in hospitalized children are associated with significant increases in length of stay, healthcare costs, and death.2, 3 While much attention has been paid to the use of hospital systems to prevent medical errors, there has been considerably less focus on the experiences of patients and their potential role in preventing errors.

Studies have suggested that a significant majority of adult patients are concerned about medical errors during hospitalization.4, 5 However, a similar assessment of parents' concerns about medical errors in pediatrics is lacking. Admittedly, for concern to be constructive it must be linked to action. The Joint Commission and the Agency for Healthcare Research and Quality (AHRQ) currently recommend that parents help prevent errors by becoming active, involved and informed members of their healthcare team and taking part in every decision about (their) child's health care.6, 7 However, the extent to which parental concern about medical errors is related to a parent's self‐efficacy, or confidence, interacting with physicians is unknown.

Self‐efficacy is a construct used in social cognitive theory to explain behavior change.8 It refers to an individual's belief in (his/her) capabilities to organize and execute the courses of action required to produce given attainments or a desired outcome.9 Self‐efficacy is not a general concept; it must be discussed in reference to a specific activity. In healthcare it has been associated not only with willingness to adopt preventive strategies,10 but also with treatment adherence,11, 12 behavior change,13 and with greater patient participation in healthcare decision‐making.14, 15

In this study we had 2 objectives. First, we sought to assess the proportion of parents of hospitalized children who are concerned about medical errors. Second, we attempted to examine whether a parent's self‐efficacy interacting with physicians was associated with their concern about medical errors for their child. Given that parents with greater self‐efficacy interacting with physicians might feel more empowered to prevent errors and, as such, be more inclined to take an active role to do so, we hypothesized that such parents would be less concerned about medical errors during a pediatric hospitalization.

Subjects and Methods

Population

We surveyed parents of children <18 years of age (including 2 grandparents who will hereafter be referred to as parents) who were admitted to the general medical service of the Children's Hospital & Regional Medical Center (CHRMC) in Seattle, WA, from July through September 2005. This study was approved by the CHRMC Institutional Review Board. Due to stipulations of the Health Insurance Portability and Accountability Act (HIPAA), we were unable to collect extensive information on those parents who were missed or those who refused to participate in the study.

Exclusions

We excluded parents if: (1) they did not feel comfortable answering a written survey in English or Spanish; (2) their child was transferred to the general medical unit either from the intensive care unit (ICU) or from the inpatient unit of another hospital; or (3) they were not present during the hospitalization.

Study Design

We conducted a cross‐sectional self‐administered written survey of parents. The survey was translated into Spanish by a certified Spanish translator. A second independent translator confirmed the accuracy of the translation. Informed consent was obtained from parents before administration of the survey.

Data Collection

Parents were surveyed with a consecutive sampling methodology Tuesday through Friday from July 2005 through September 2005. We surveyed parents within 48 hours of admission of their child to the hospital, but after they had an opportunity to speak with the inpatient medical team that was caring for their child. A more detailed discussion of the data collection process has been published previously.16

Dependent Variables

Parental Concern About the Need to Watch for Medical Errors

We assessed parental concerns about medical errors during hospitalization by measuring responses to the statement When my child is in the hospital I feel that I have to watch over the care that he/she is receiving to make sure that mistakes aren't made. Parents reported their agreement/disagreement with this statement using a 5‐point Likert scale. For our analysis we dichotomized the dependent variable into those parents who responded Strongly Agree or Agree vs. those who responded Strongly Disagree or Disagree. We chose to focus on parents who expressed a directional response (eg, agree or disagree) because we felt that such responses were more likely to be correlated with behavior. As a result, we excluded from our primary analysis those participants who responded Unsure. In order to determine the effect of exclusion on our results (given its size), we conducted separate post‐hoc analyses in which we included the Unsure respondents in Agree and Disagree categories, respectively.

Independent Variables

Self‐Efficacy in Patient‐Physician Interactions

The Joint Commission's Speak Up initiative7 recommends that patients and parents interact with their healthcare providers in order to prevent errors. We gauged a parent's confidence of interacting with healthcare providers using an adapted scale of the Perceived Efficacy in Patient‐Physician Interactions (PEPPI) self‐efficacy scale. The PEPPI is a 50‐point self‐efficacy scale that has been validated in older adults.17 The response to each question is recorded on a 5‐point Likert scale ranging from 1 to 5 where 1 represents not at all confident and 5 represents very confident. Higher scores on this scale have been associated with greater participation in treatment decisions by women with breast cancer.18 We adapted this scale for use in pediatrics (Appendix 1).

Covariates

Prior Hospitalizations and Chronic Illness History

We asked parents to report how many times their child had been hospitalized prior to this current admission (not including birth). We chose to query parents directly because a search of our institutions' medical record database would not capture hospitalizations at other facilities. We categorized the variable for previous hospitalizations as follows: none, 1, 2, 3.

We asked parents to report if prior to this hospitalization they had ever been told by a nurse or doctor that their child had any of a list of chronic medical conditions such as chronic respiratory disease, mental retardation, and seizure disorder, among others. We gave parents the opportunity to specify a medical condition not provided on this list. The list of conditions was the same as that used in the Child Health Questionnaire PF‐28,19 which has been used in national and international studies to measure quality of life in children with and without chronic conditions20, 21 (Appendix 2).

Limited English Proficiency

We assessed the potential for a language barrier to impede communication between parent and healthcare providers by asking parents the following question: How comfortable are you that you can express your concerns and ask questions of your child's doctors in English? We measured parental responses on a 5‐point Likert scale (very comfortable vs. somewhat comfortable, not sure, somewhat uncomfortable, very uncomfortable). For our analyses, we dichotomized responses into those who reported being very comfortable vs. those who chose any other response category.

Social Desirability

We measured the potential for social desirability to bias responses using the Marlowe‐Crowne 2(10) Scale of Social Desirability.22 The Marlowe‐Crowne 2(10) Scale of Social Desirability is a shorter, validated version of the Marlowe‐Crowne Scale.23 This scale has been recommended by the National Institutes of Health (NIH)'s Behavior Change Consortium for use in behavioral change research related to health.24 It has been used in previous studies to account for social desirability bias in studies which involve patient self‐report of attitudes and beliefs.25 We analyzed scores on a continuous scale with higher scores representing greater social desirability bias in responses.

Demographics

We collected the following demographic data on parents: age, gender, race/ethnicity (white non‐Hispanic vs. other), education (high school or less, some college, college or higher). We also recorded the child's age and gender.

Statistical Analysis

Parental Concern for Medical Errors

Univariate statistics were used to report proportions of parents who were concerned about medical errors and to summarize the data for covariates and demographics. We conducted bivariate logistic regression analyses to assess the association between our outcome variable and the independent variable and each covariate, respectively. We used a Fisher's exact test to examine the association between limited English proficiency and our outcome variable because the absence of participants (eg, a zero cell) who were not very comfortable with English and not concerned about errors precluded the use of bivariate logistic regression. Therefore, to explore the relationship between race and language we used a Fischer's exact test to compare concern about medical errors between white and non‐white participants who were very comfortable with English.

We used multivariate logistic regression to test our hypothesis that greater self‐efficacy would be associated with less concern about medical errors after adjusting for the aforementioned covariates and demographics, excluding child gender. We had no a priori reason to expect that child gender would affect parental self‐efficacy or parental concern about errors and did not include it in the regression model. In order to provide a more clinically relevant interpretation of our results, we calculated adjusted predicted probabilities for the 25%, 50%, and 75% PEPPI scores using the mean for all other variables in the model.

We conducted post‐hoc analysis using a likelihood‐ratio test to determine if the hospitalization variable was significant in the multivariate regression model. We conducted additional post‐hoc analysis using bivariate logistic regression to explore the relationship between concern about medical errors and the following independent variables: hospitalization for >3 days after birth (yes/no); previous hospitalization for >1 week (yes/no); parents' experience with the hospital system (a lot, some, not sure, a little, none); overall perception of child's health (excellent, very good, good, fair); previous hospitalizations for other children (yes, no, no other children); rating of care that child has received (excellent vs. other [very good, good, fair]). We incorporated any significant associations (P < 0.05) into our preexisting multivariate model.

Results

During the time period of our study, 278 parents were eligible to participate. Eighty‐five parents could not be surveyed either because they could not be reached despite multiple attempts (eg, out of the room, speaking with physicians) or because the child had already been discharged. Of the 193 parents approached, 130 agreed to take the survey. Two parents who agreed to complete the survey forgot to return it before their children were discharged. Demographics of respondents and nonparticipants are presented in Table 1. The distribution of self‐efficacy scores was skewed, with a mean score of 45 (median 46, range 5‐50) on a 50‐point scale, consistent with previous studies in adults.18

Study Population Characteristics
CharacteristicsRespondents (n = 130)Number Missed (n = 85)Number Refused (n = 61)
  • Abbreviation: NA, not available; SD, standard deviation.

Parent's mean age34 years (range: 18‐51)NANA
Parent sex female, n (%)105 (80.8)NANA
Parental education, n (%)   
College or higher65 (50.4)  
Some college34 (26.4)  
High school or less30 (23.3)NANA
Parental race, n (%)   
White86 (67.2)  
Non‐White42 (32.8)NANA
Parent's social desirability score, mean (SD)7.0 (2.0)NANA
Child's median age21.4 months (range: 1 day‐17.8 years)24 months24 months
Child's sex female, n (%)63 (48.5)36 (42)35 (57)
Number of previous hospitalizations (child), n (%)   
None68 (53.1)  
126 (20.3)  
219 (14.8)  
315 (11.7)NANA
Number of chronic medical conditions (child), n (%)   
None56 (48.7)  
134 (29.6)  
225 (21.8)NANA
Parent's comfort expressing concerns in English, n (%) NANA
Very comfortable109 (83.9)  
Less than very comfortable21 (16.1)  
Self‐efficacy score (parent), mean (SD)45 (6.3)NANA

Eighty‐two parents (63% of respondents) Agreed or Strongly Agreed with the statement When my child is in the hospital I feel that I need to watch over his/her care in order to make sure that mistakes aren't made (Figure 1). In bivariate analyses, non‐white race (Table 2) and English proficiency (P = 0.002) were significantly associated with parental concern about medical errors. Notably, all respondents who were not very comfortable with English agreed that they felt the need to watch over their child's care to ensure that mistakes do not happen. The association between self‐efficacy with physician interactions and concern was nearly significant (Table 2).

Figure 1
Response to statement “When my child is in the hospital I feel that I have to watch over the care that he/she is receiving to make sure that mistakes aren't made.” [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Bivariate and Multivariate Logistic Regression of Factors Associated with Parental Concern for Medical Errors
VariableCrude Odds RatioConfidence IntervalP ValueAdjusted Odds RatioConfidence IntervalP Value
  • NOTE: Results of multivariate logistic regression.

  • P < 0.01.

  • P < 0.05.

Parent age (years)1.010.95‐1.060.791.050.95‐1.150.36
Parent gender      
FemaleReferent     
Male0.860.32‐2.350.770.760.20‐2.790.68
Age of child (months)1.000.99‐1.010.971.000.99‐1.010.83
Parental education      
College or higherReferent  Referent  
Some college0.480.18‐1.260.140.30.07‐1.130.07
High school or less1.390.48‐4.000.550.50.1‐2.20.38
Parental race      
WhiteReferent  Referent  
Non‐White5.00*1.61‐15.560.0054.91.19‐20.40.03
Previous hospitalization (child)      
NoneReferent  Referent  
10.440.16‐1.200.110.160.04‐0.690.01
20.890.27‐2.870.840.600.13‐2.830.5
30.910.21‐3.840.900.790.12‐5.060.8
Number of chronic medical conditions0.860.67‐1.110.261.050.74‐1.500.78
Social desirability score (parent)0.990.81‐1.210.920.990.76‐1.290.9
Self‐efficacy score (parent)0.900.81‐1.000.060.830.73‐0.950.006*

In multivariate analysis, self‐efficacy was independently associated with parental report about the need to watch over a child's care (odds ratio [OR], 0.83; 95% confidence interval [CI], 0.72‐0.92). In prediction models, with self‐efficacy scores of 44 (25th percentile), 46 (50th percentile), and 49 (75th percentile), about 72.2% (59.1‐82.3), 64.2% (51.8‐75.0), and 50.8% (35.3‐66.2) of parents, respectively, would feel the need to watch over their child's care to prevent medical errors.

While respondents of non‐white race had the greatest independent odds of reporting a concern for medical errors occurring while their child was hospitalized (OR, 4.9; 95% CI, 1.19‐20.4), we could not reliably determine how much of this effect was due to language instead of to race because the vast majority of parents who reported being less than very comfortable with English were also non‐white (non‐white 90.5% vs. white 9.5%, P < 0.001). In additional analyses we were unable to find a difference in concern about medical errors between white and non‐white parents who were very comfortable with English (data not shown).

Of note, while having 1 hospitalization compared to none was significantly associated with having decreased concern about medical errors (Table 2), the variable hospitalizations was not significant in the model (P = 0.07).

In post‐hoc analysis, we found no association between hospitalization for >3 days after birth, previous hospitalization for >1 week, parents' experience with the hospital system, and overall perception of child's health, previous hospitalizations for other children. While rating of care that child received was significantly associated with parents' concern about medical errors in the bivariate analysis, it did not remain significant in multivariate analysis and did not substantially change the magnitude or significance of previous associations.

Discussion

In our study, we found that nearly two‐thirds of parents of children admitted to the general pediatric service of a tertiary care children's hospital felt the need to watch over their child's care to ensure that mistakes would not be made. We also found that a parent's self‐efficacy interacting with physicians was associated with less parental concern for medical errors.

To our knowledge, this is the first study to systematically survey parents' concerns about medical errors during a child's hospitalization and to evaluate factors associated with this concern. The immediate question prompted by our findings is whether the fact that 63% of parents are concerned is alarming because it is too low or too high. Some might contend that concern about medical errors is an appropriate and desirable response because it may motivate parents to become more vigilant about the medical care that their child is receiving. However, others may challenge that such concern may indicate a feeling of powerlessness to act to prevent potential errors. In our study, the relationship between higher self‐efficacy and less parental concern raises the possibility that parents with higher levels of self‐efficacy with physician interactions may feel more comfortable communicating with physicians, which in turn may temper parents' concerns about medical errors during hospitalization.

It is equally plausible that concern about medical errors during hospitalization may motivate parents to become involved in their child's medical care and, in turn, lead them to feel empowered to prevent medical errors and so ease their concerns. It is conceivable that experience with past medical errors may fuel a parent's need to watch over their child's care to prevent additional medical errors. Future studies should address the independent effect of past medical errors on parental concern about medical errors.

In this study, all parents who reported being very uncomfortable with English and parents of non‐white race felt the need to watch over their child's care to help prevent errors. A previous survey of a nationally representative sample of U.S. adults found greater proportion of non‐white adults were very concerned about errors or mistakes happening when receiving care at a hospital (blacks 62%, Hispanics 57%, whites 44%).26 However, in our study, the relationship between race and concern is likely mediated by language since many of the parents who described themselves as other than white also reported being not very comfortable with English and we could not find an effect of race on concern among parents who were very comfortable with English. Indeed, previous studies have linked decreased English proficiency to medical errors with potential clinical consequence.27

Given our previous investigation of the relationship between self‐efficacy and parent participation in medical decisions during a child's hospitalization, we conducted post‐hoc analyses exploring the association between parents' self‐report of participation in medical decisions and concern about medical errors during their child's hospitalization.16 Using a simple logistic regression we did not find any association. However, we advise caution in interpreting and generalizing these results because the study was not powered to adequately evaluate this association.

There are additional limitations in our study to be noted. First, this question has not been used previously to assess parental concern about medical errors, so future work will need to focus on assessing its reliability and validity. Second, it is also possible that parents' concern for medical errors is mitigated by the complexity of their child's healthcare.5 We attempted to address this issue by controlling for the child's number of chronic illnesses. However, it is possible that our metric did not capture the level of complexity associated with different types of chronic conditions. Moreover, additional variables such as health insurance type, parental physical and mental health, and quality of interactions with the nursing staff may confound the relationships that we observed. Future studies should examine the effect of these variables on parents' self‐efficacy and their concern about medical errors.

Third, we surveyed parents at a single institution and, as such, differences in demographics and hospital‐specific practices related to patient‐physician interactions may prevent generalization of our findings to other institutions. For example, the parents in our survey had a higher average education level than the general population and the racial makeup of our population was not nationally representative. Also, due to HIPAA constraints, we were unable to collect extensive demographic information on parents and children who were missed or those who refused to participate in the study, which also could conceivably influence the strength of our findings.

Fourth, we adapted a validated adult measure of self‐efficacy for use in pediatrics. The patient‐physician self‐efficacy scale, the PEPPI, did have a skewed distribution in our study, although this performance is consistent with adult studies18 and in post‐hoc analyses, outlier PEPPI scores did not have a significant effect on the magnitude of the relationship we observed between self‐efficacy and parental concern about medical errors. However, the reading level of this instrument is ninth grade, which may impact the generalization of our findings to populations with lower literacy levels.

Fifth, we excluded parents who were unsure about their concern from our analyses. In post‐hoc multivariate regression analyses, reassignment of unsure responses to either agree or disagree did not result in any change in odds ratio for any endpoint.

Finally, it is possible that parental concern was influenced by social desirability bias in that parents may have been less likely to report concern about medical errors during a hospitalization because of fear of the implications it might have for their child's care. We attempted to control for this effect by adjusting for social desirability bias using the Marlowe‐Crowne scale. This scale is commonly used in behavioral science research to account for such response bias and has been recommended by the NIH Consortium on Behavior Change for use in behavioral change research related to health.24

Within the context of these limitations, we feel that our study contributes an important first step toward characterizing the scope of parental concern about medical errors during pediatric hospitalizations and understanding the relationship of self‐efficacy with physician interactions to this concern. Devising a quality initiative program to improve parents' self‐efficacy interacting with physicians might help to temper parents' concerns about medical errors while also encouraging their involvement in their child's medical care. Such a program would likely prove most beneficial if it sought to improve self‐efficacy among parents with lower English proficiency given that this group had the highest concern for medical errors. Possible interventions might include more ready access to interpreters or use of visual aids.

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References
  1. Institute of Medicine Committee on Quality of Health Care in America.Crossing the Quality Chasm: A New Health System for the 21st Century.Washington, DC:National Academy Press;2001.
  2. Kaushal R,Bates DW,Landrigan C, et al.Medication errors and adverse drug events in pediatric inpatients.JAMA.2001;285(16):21142120.
  3. Miller MR,Zhan C.Pediatric patient safety in hospitals: a national picture in 2000.Pediatrics.2004;113(6):17411746.
  4. Waterman AD,Gallagher TH,Garbutt J,Waterman BM,Fraser V,Burroughs TE.Brief report: hospitalized patients' attitudes about and participation in error prevention.J Gen Intern Med.2006;21(4):367370.
  5. Burroughs TE,Waterman AD,Gallagher TH, et al.Patients' concerns about medical errors during hospitalization.Jt Comm J Qual Patient Saf.2007;33(1):514.
  6. Agency for Healthcare Research and Quality.20 Tips to Help Prevent Medical Errors in Children. Patient Fact Sheet. 2009, AHRQ Publication No. 02‐P034.Rockville, MD:Agency for Healthcare Research and Quality.
  7. Joint Commission on Accreditation of Healthcare Organizations. Speak Up Initiatives. Available at: http://www.jointcommission.org/PatientSafety/SpeakUp. Accessed May 2009.
  8. Bandura A.Self‐efficacy: toward a unifying theory of behavioral change.Psychol Rev.1977;84(2):191215.
  9. Bandura A.Self‐Efficacy: The Exercise of Control.New York, NY:W.H. Freeman and Company;1997.
  10. Strauss RS,Rodzilsky D,Burack G,Colin M.Psychosocial correlates of physical activity in healthy children.Arch Pediatr Adolesc Med.2001;155(8):897902.
  11. Ott J,Greening L,Palardy N,Holderby A,DeBell WK.Self‐efficacy as a mediator variable for adolescents' adherence to treatment for insulin‐dependent diabetes mellitus.Children's Health Care.2000;29(1):4763.
  12. McCaul KD,Glasgow RE,Schafer LC.Diabetes regimen behaviors. Predicting adherence.Med Care.1987;25(9):868881.
  13. Cabana MD,Rand C,Slish K,Nan B,Davis MM,Clark N.Pediatrician self‐efficacy for counseling parents of asthmatic children to quit smoking.Pediatrics.2004;113(1 Pt 1):7881.
  14. Arora NK,Ayanian JZ,Guadagnoli E.Examining the relationship of patients' attitudes and beliefs with their self‐reported level of participation in medical decision‐making.Med Care.2005;43(9):865872.
  15. Janz NK,Wren PA,Copeland LA,Lowery JC,Goldfarb SL,Wilkins EG.Patient‐physician concordance: preferences, perceptions, and factors influencing the breast cancer surgical decision.J Clin Oncol.2004;22(15):30913098.
  16. Tarini BA,Christakis DA,Lozano P.Toward family‐centered inpatient medical care: the role of parents as participants in medical decisions.J Pediatr.2007;151(6):690695.
  17. Maly RC,Frank JC,Marshall GN,DiMatteo MR,Reuben DB.Perceived efficacy in patient‐physician interactions (PEPPI): validation of an instrument in older persons.J Am Geriatr Soc.1998;46(7):889894.
  18. Maly RC,Umezawa Y,Leake B,Silliman RA.Determinants of participation in treatment decision‐making by older breast cancer patients.Breast Cancer Res Treat.2004;85(3):201209.
  19. Landgraf JM AL,Ware JE.The CHQ: A User's Manual (2nd printing).Boston, MA:HealthAct;1999.
  20. Waters EB,Salmon LA,Wake M,Wright M,Hesketh KD.The health and well‐being of adolescents: a school‐based population study of the self‐report Child Health Questionnaire.J Adolesc Health.2001;29(2):140149.
  21. Wake M,Hesketh K,Cameron F.The Child Health Questionnaire in children with diabetes: cross‐sectional survey of parent and adolescent‐reported functional health status.Diabet Med.2000;17(10):700707.
  22. Strahan R,Gerbasi KC.Semantic style variance in personality questionnaires.J Psychol.1973;85:109118.
  23. Crowne DP,Marlowe D.A new scale of social desirability independent of psychopathology.J Consult Psychol.1960;24:349354.
  24. National Institutes of Health. Behavior Change Consortium‐Recommended Nutrition Measures. Available at:http://www1.od.nih.gov/behaviorchange/measures/nutrition.htm. Accessed May 2009.
  25. Bardwell WA,Ancoli‐Israel S,Dimsdale JE.Response bias influences mental health symptom reporting in patients with obstructive sleep apnea.Ann Behav Med.2001;23(4):313317.
  26. Kaiser Family Foundation, Agency for Healthcare Research and Quality.Americans as Health Care Consumers: Update on the Role of Quality Information.Rockville, MD:Agency for Healthcare Research and Quality;2000.
  27. Flores G,Laws MB,Mayo SJ, et al.Errors in medical interpretation and their potential clinical consequences in pediatric encounters.Pediatrics.2003;111(1):614.
Article PDF
Issue
Journal of Hospital Medicine - 4(9)
Page Number
521-527
Legacy Keywords
medical errors, self‐efficiency, pediatric hospitalization, language
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Article PDF
Article PDF

The Institute of Medicine report linking between 48,000 and 98,000 deaths annually to medical errors1 has raised awareness about medical errors across all areas of medicine. In pediatrics, medical errors in hospitalized children are associated with significant increases in length of stay, healthcare costs, and death.2, 3 While much attention has been paid to the use of hospital systems to prevent medical errors, there has been considerably less focus on the experiences of patients and their potential role in preventing errors.

Studies have suggested that a significant majority of adult patients are concerned about medical errors during hospitalization.4, 5 However, a similar assessment of parents' concerns about medical errors in pediatrics is lacking. Admittedly, for concern to be constructive it must be linked to action. The Joint Commission and the Agency for Healthcare Research and Quality (AHRQ) currently recommend that parents help prevent errors by becoming active, involved and informed members of their healthcare team and taking part in every decision about (their) child's health care.6, 7 However, the extent to which parental concern about medical errors is related to a parent's self‐efficacy, or confidence, interacting with physicians is unknown.

Self‐efficacy is a construct used in social cognitive theory to explain behavior change.8 It refers to an individual's belief in (his/her) capabilities to organize and execute the courses of action required to produce given attainments or a desired outcome.9 Self‐efficacy is not a general concept; it must be discussed in reference to a specific activity. In healthcare it has been associated not only with willingness to adopt preventive strategies,10 but also with treatment adherence,11, 12 behavior change,13 and with greater patient participation in healthcare decision‐making.14, 15

In this study we had 2 objectives. First, we sought to assess the proportion of parents of hospitalized children who are concerned about medical errors. Second, we attempted to examine whether a parent's self‐efficacy interacting with physicians was associated with their concern about medical errors for their child. Given that parents with greater self‐efficacy interacting with physicians might feel more empowered to prevent errors and, as such, be more inclined to take an active role to do so, we hypothesized that such parents would be less concerned about medical errors during a pediatric hospitalization.

Subjects and Methods

Population

We surveyed parents of children <18 years of age (including 2 grandparents who will hereafter be referred to as parents) who were admitted to the general medical service of the Children's Hospital & Regional Medical Center (CHRMC) in Seattle, WA, from July through September 2005. This study was approved by the CHRMC Institutional Review Board. Due to stipulations of the Health Insurance Portability and Accountability Act (HIPAA), we were unable to collect extensive information on those parents who were missed or those who refused to participate in the study.

Exclusions

We excluded parents if: (1) they did not feel comfortable answering a written survey in English or Spanish; (2) their child was transferred to the general medical unit either from the intensive care unit (ICU) or from the inpatient unit of another hospital; or (3) they were not present during the hospitalization.

Study Design

We conducted a cross‐sectional self‐administered written survey of parents. The survey was translated into Spanish by a certified Spanish translator. A second independent translator confirmed the accuracy of the translation. Informed consent was obtained from parents before administration of the survey.

Data Collection

Parents were surveyed with a consecutive sampling methodology Tuesday through Friday from July 2005 through September 2005. We surveyed parents within 48 hours of admission of their child to the hospital, but after they had an opportunity to speak with the inpatient medical team that was caring for their child. A more detailed discussion of the data collection process has been published previously.16

Dependent Variables

Parental Concern About the Need to Watch for Medical Errors

We assessed parental concerns about medical errors during hospitalization by measuring responses to the statement When my child is in the hospital I feel that I have to watch over the care that he/she is receiving to make sure that mistakes aren't made. Parents reported their agreement/disagreement with this statement using a 5‐point Likert scale. For our analysis we dichotomized the dependent variable into those parents who responded Strongly Agree or Agree vs. those who responded Strongly Disagree or Disagree. We chose to focus on parents who expressed a directional response (eg, agree or disagree) because we felt that such responses were more likely to be correlated with behavior. As a result, we excluded from our primary analysis those participants who responded Unsure. In order to determine the effect of exclusion on our results (given its size), we conducted separate post‐hoc analyses in which we included the Unsure respondents in Agree and Disagree categories, respectively.

Independent Variables

Self‐Efficacy in Patient‐Physician Interactions

The Joint Commission's Speak Up initiative7 recommends that patients and parents interact with their healthcare providers in order to prevent errors. We gauged a parent's confidence of interacting with healthcare providers using an adapted scale of the Perceived Efficacy in Patient‐Physician Interactions (PEPPI) self‐efficacy scale. The PEPPI is a 50‐point self‐efficacy scale that has been validated in older adults.17 The response to each question is recorded on a 5‐point Likert scale ranging from 1 to 5 where 1 represents not at all confident and 5 represents very confident. Higher scores on this scale have been associated with greater participation in treatment decisions by women with breast cancer.18 We adapted this scale for use in pediatrics (Appendix 1).

Covariates

Prior Hospitalizations and Chronic Illness History

We asked parents to report how many times their child had been hospitalized prior to this current admission (not including birth). We chose to query parents directly because a search of our institutions' medical record database would not capture hospitalizations at other facilities. We categorized the variable for previous hospitalizations as follows: none, 1, 2, 3.

We asked parents to report if prior to this hospitalization they had ever been told by a nurse or doctor that their child had any of a list of chronic medical conditions such as chronic respiratory disease, mental retardation, and seizure disorder, among others. We gave parents the opportunity to specify a medical condition not provided on this list. The list of conditions was the same as that used in the Child Health Questionnaire PF‐28,19 which has been used in national and international studies to measure quality of life in children with and without chronic conditions20, 21 (Appendix 2).

Limited English Proficiency

We assessed the potential for a language barrier to impede communication between parent and healthcare providers by asking parents the following question: How comfortable are you that you can express your concerns and ask questions of your child's doctors in English? We measured parental responses on a 5‐point Likert scale (very comfortable vs. somewhat comfortable, not sure, somewhat uncomfortable, very uncomfortable). For our analyses, we dichotomized responses into those who reported being very comfortable vs. those who chose any other response category.

Social Desirability

We measured the potential for social desirability to bias responses using the Marlowe‐Crowne 2(10) Scale of Social Desirability.22 The Marlowe‐Crowne 2(10) Scale of Social Desirability is a shorter, validated version of the Marlowe‐Crowne Scale.23 This scale has been recommended by the National Institutes of Health (NIH)'s Behavior Change Consortium for use in behavioral change research related to health.24 It has been used in previous studies to account for social desirability bias in studies which involve patient self‐report of attitudes and beliefs.25 We analyzed scores on a continuous scale with higher scores representing greater social desirability bias in responses.

Demographics

We collected the following demographic data on parents: age, gender, race/ethnicity (white non‐Hispanic vs. other), education (high school or less, some college, college or higher). We also recorded the child's age and gender.

Statistical Analysis

Parental Concern for Medical Errors

Univariate statistics were used to report proportions of parents who were concerned about medical errors and to summarize the data for covariates and demographics. We conducted bivariate logistic regression analyses to assess the association between our outcome variable and the independent variable and each covariate, respectively. We used a Fisher's exact test to examine the association between limited English proficiency and our outcome variable because the absence of participants (eg, a zero cell) who were not very comfortable with English and not concerned about errors precluded the use of bivariate logistic regression. Therefore, to explore the relationship between race and language we used a Fischer's exact test to compare concern about medical errors between white and non‐white participants who were very comfortable with English.

We used multivariate logistic regression to test our hypothesis that greater self‐efficacy would be associated with less concern about medical errors after adjusting for the aforementioned covariates and demographics, excluding child gender. We had no a priori reason to expect that child gender would affect parental self‐efficacy or parental concern about errors and did not include it in the regression model. In order to provide a more clinically relevant interpretation of our results, we calculated adjusted predicted probabilities for the 25%, 50%, and 75% PEPPI scores using the mean for all other variables in the model.

We conducted post‐hoc analysis using a likelihood‐ratio test to determine if the hospitalization variable was significant in the multivariate regression model. We conducted additional post‐hoc analysis using bivariate logistic regression to explore the relationship between concern about medical errors and the following independent variables: hospitalization for >3 days after birth (yes/no); previous hospitalization for >1 week (yes/no); parents' experience with the hospital system (a lot, some, not sure, a little, none); overall perception of child's health (excellent, very good, good, fair); previous hospitalizations for other children (yes, no, no other children); rating of care that child has received (excellent vs. other [very good, good, fair]). We incorporated any significant associations (P < 0.05) into our preexisting multivariate model.

Results

During the time period of our study, 278 parents were eligible to participate. Eighty‐five parents could not be surveyed either because they could not be reached despite multiple attempts (eg, out of the room, speaking with physicians) or because the child had already been discharged. Of the 193 parents approached, 130 agreed to take the survey. Two parents who agreed to complete the survey forgot to return it before their children were discharged. Demographics of respondents and nonparticipants are presented in Table 1. The distribution of self‐efficacy scores was skewed, with a mean score of 45 (median 46, range 5‐50) on a 50‐point scale, consistent with previous studies in adults.18

Study Population Characteristics
CharacteristicsRespondents (n = 130)Number Missed (n = 85)Number Refused (n = 61)
  • Abbreviation: NA, not available; SD, standard deviation.

Parent's mean age34 years (range: 18‐51)NANA
Parent sex female, n (%)105 (80.8)NANA
Parental education, n (%)   
College or higher65 (50.4)  
Some college34 (26.4)  
High school or less30 (23.3)NANA
Parental race, n (%)   
White86 (67.2)  
Non‐White42 (32.8)NANA
Parent's social desirability score, mean (SD)7.0 (2.0)NANA
Child's median age21.4 months (range: 1 day‐17.8 years)24 months24 months
Child's sex female, n (%)63 (48.5)36 (42)35 (57)
Number of previous hospitalizations (child), n (%)   
None68 (53.1)  
126 (20.3)  
219 (14.8)  
315 (11.7)NANA
Number of chronic medical conditions (child), n (%)   
None56 (48.7)  
134 (29.6)  
225 (21.8)NANA
Parent's comfort expressing concerns in English, n (%) NANA
Very comfortable109 (83.9)  
Less than very comfortable21 (16.1)  
Self‐efficacy score (parent), mean (SD)45 (6.3)NANA

Eighty‐two parents (63% of respondents) Agreed or Strongly Agreed with the statement When my child is in the hospital I feel that I need to watch over his/her care in order to make sure that mistakes aren't made (Figure 1). In bivariate analyses, non‐white race (Table 2) and English proficiency (P = 0.002) were significantly associated with parental concern about medical errors. Notably, all respondents who were not very comfortable with English agreed that they felt the need to watch over their child's care to ensure that mistakes do not happen. The association between self‐efficacy with physician interactions and concern was nearly significant (Table 2).

Figure 1
Response to statement “When my child is in the hospital I feel that I have to watch over the care that he/she is receiving to make sure that mistakes aren't made.” [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Bivariate and Multivariate Logistic Regression of Factors Associated with Parental Concern for Medical Errors
VariableCrude Odds RatioConfidence IntervalP ValueAdjusted Odds RatioConfidence IntervalP Value
  • NOTE: Results of multivariate logistic regression.

  • P < 0.01.

  • P < 0.05.

Parent age (years)1.010.95‐1.060.791.050.95‐1.150.36
Parent gender      
FemaleReferent     
Male0.860.32‐2.350.770.760.20‐2.790.68
Age of child (months)1.000.99‐1.010.971.000.99‐1.010.83
Parental education      
College or higherReferent  Referent  
Some college0.480.18‐1.260.140.30.07‐1.130.07
High school or less1.390.48‐4.000.550.50.1‐2.20.38
Parental race      
WhiteReferent  Referent  
Non‐White5.00*1.61‐15.560.0054.91.19‐20.40.03
Previous hospitalization (child)      
NoneReferent  Referent  
10.440.16‐1.200.110.160.04‐0.690.01
20.890.27‐2.870.840.600.13‐2.830.5
30.910.21‐3.840.900.790.12‐5.060.8
Number of chronic medical conditions0.860.67‐1.110.261.050.74‐1.500.78
Social desirability score (parent)0.990.81‐1.210.920.990.76‐1.290.9
Self‐efficacy score (parent)0.900.81‐1.000.060.830.73‐0.950.006*

In multivariate analysis, self‐efficacy was independently associated with parental report about the need to watch over a child's care (odds ratio [OR], 0.83; 95% confidence interval [CI], 0.72‐0.92). In prediction models, with self‐efficacy scores of 44 (25th percentile), 46 (50th percentile), and 49 (75th percentile), about 72.2% (59.1‐82.3), 64.2% (51.8‐75.0), and 50.8% (35.3‐66.2) of parents, respectively, would feel the need to watch over their child's care to prevent medical errors.

While respondents of non‐white race had the greatest independent odds of reporting a concern for medical errors occurring while their child was hospitalized (OR, 4.9; 95% CI, 1.19‐20.4), we could not reliably determine how much of this effect was due to language instead of to race because the vast majority of parents who reported being less than very comfortable with English were also non‐white (non‐white 90.5% vs. white 9.5%, P < 0.001). In additional analyses we were unable to find a difference in concern about medical errors between white and non‐white parents who were very comfortable with English (data not shown).

Of note, while having 1 hospitalization compared to none was significantly associated with having decreased concern about medical errors (Table 2), the variable hospitalizations was not significant in the model (P = 0.07).

In post‐hoc analysis, we found no association between hospitalization for >3 days after birth, previous hospitalization for >1 week, parents' experience with the hospital system, and overall perception of child's health, previous hospitalizations for other children. While rating of care that child received was significantly associated with parents' concern about medical errors in the bivariate analysis, it did not remain significant in multivariate analysis and did not substantially change the magnitude or significance of previous associations.

Discussion

In our study, we found that nearly two‐thirds of parents of children admitted to the general pediatric service of a tertiary care children's hospital felt the need to watch over their child's care to ensure that mistakes would not be made. We also found that a parent's self‐efficacy interacting with physicians was associated with less parental concern for medical errors.

To our knowledge, this is the first study to systematically survey parents' concerns about medical errors during a child's hospitalization and to evaluate factors associated with this concern. The immediate question prompted by our findings is whether the fact that 63% of parents are concerned is alarming because it is too low or too high. Some might contend that concern about medical errors is an appropriate and desirable response because it may motivate parents to become more vigilant about the medical care that their child is receiving. However, others may challenge that such concern may indicate a feeling of powerlessness to act to prevent potential errors. In our study, the relationship between higher self‐efficacy and less parental concern raises the possibility that parents with higher levels of self‐efficacy with physician interactions may feel more comfortable communicating with physicians, which in turn may temper parents' concerns about medical errors during hospitalization.

It is equally plausible that concern about medical errors during hospitalization may motivate parents to become involved in their child's medical care and, in turn, lead them to feel empowered to prevent medical errors and so ease their concerns. It is conceivable that experience with past medical errors may fuel a parent's need to watch over their child's care to prevent additional medical errors. Future studies should address the independent effect of past medical errors on parental concern about medical errors.

In this study, all parents who reported being very uncomfortable with English and parents of non‐white race felt the need to watch over their child's care to help prevent errors. A previous survey of a nationally representative sample of U.S. adults found greater proportion of non‐white adults were very concerned about errors or mistakes happening when receiving care at a hospital (blacks 62%, Hispanics 57%, whites 44%).26 However, in our study, the relationship between race and concern is likely mediated by language since many of the parents who described themselves as other than white also reported being not very comfortable with English and we could not find an effect of race on concern among parents who were very comfortable with English. Indeed, previous studies have linked decreased English proficiency to medical errors with potential clinical consequence.27

Given our previous investigation of the relationship between self‐efficacy and parent participation in medical decisions during a child's hospitalization, we conducted post‐hoc analyses exploring the association between parents' self‐report of participation in medical decisions and concern about medical errors during their child's hospitalization.16 Using a simple logistic regression we did not find any association. However, we advise caution in interpreting and generalizing these results because the study was not powered to adequately evaluate this association.

There are additional limitations in our study to be noted. First, this question has not been used previously to assess parental concern about medical errors, so future work will need to focus on assessing its reliability and validity. Second, it is also possible that parents' concern for medical errors is mitigated by the complexity of their child's healthcare.5 We attempted to address this issue by controlling for the child's number of chronic illnesses. However, it is possible that our metric did not capture the level of complexity associated with different types of chronic conditions. Moreover, additional variables such as health insurance type, parental physical and mental health, and quality of interactions with the nursing staff may confound the relationships that we observed. Future studies should examine the effect of these variables on parents' self‐efficacy and their concern about medical errors.

Third, we surveyed parents at a single institution and, as such, differences in demographics and hospital‐specific practices related to patient‐physician interactions may prevent generalization of our findings to other institutions. For example, the parents in our survey had a higher average education level than the general population and the racial makeup of our population was not nationally representative. Also, due to HIPAA constraints, we were unable to collect extensive demographic information on parents and children who were missed or those who refused to participate in the study, which also could conceivably influence the strength of our findings.

Fourth, we adapted a validated adult measure of self‐efficacy for use in pediatrics. The patient‐physician self‐efficacy scale, the PEPPI, did have a skewed distribution in our study, although this performance is consistent with adult studies18 and in post‐hoc analyses, outlier PEPPI scores did not have a significant effect on the magnitude of the relationship we observed between self‐efficacy and parental concern about medical errors. However, the reading level of this instrument is ninth grade, which may impact the generalization of our findings to populations with lower literacy levels.

Fifth, we excluded parents who were unsure about their concern from our analyses. In post‐hoc multivariate regression analyses, reassignment of unsure responses to either agree or disagree did not result in any change in odds ratio for any endpoint.

Finally, it is possible that parental concern was influenced by social desirability bias in that parents may have been less likely to report concern about medical errors during a hospitalization because of fear of the implications it might have for their child's care. We attempted to control for this effect by adjusting for social desirability bias using the Marlowe‐Crowne scale. This scale is commonly used in behavioral science research to account for such response bias and has been recommended by the NIH Consortium on Behavior Change for use in behavioral change research related to health.24

Within the context of these limitations, we feel that our study contributes an important first step toward characterizing the scope of parental concern about medical errors during pediatric hospitalizations and understanding the relationship of self‐efficacy with physician interactions to this concern. Devising a quality initiative program to improve parents' self‐efficacy interacting with physicians might help to temper parents' concerns about medical errors while also encouraging their involvement in their child's medical care. Such a program would likely prove most beneficial if it sought to improve self‐efficacy among parents with lower English proficiency given that this group had the highest concern for medical errors. Possible interventions might include more ready access to interpreters or use of visual aids.

The Institute of Medicine report linking between 48,000 and 98,000 deaths annually to medical errors1 has raised awareness about medical errors across all areas of medicine. In pediatrics, medical errors in hospitalized children are associated with significant increases in length of stay, healthcare costs, and death.2, 3 While much attention has been paid to the use of hospital systems to prevent medical errors, there has been considerably less focus on the experiences of patients and their potential role in preventing errors.

Studies have suggested that a significant majority of adult patients are concerned about medical errors during hospitalization.4, 5 However, a similar assessment of parents' concerns about medical errors in pediatrics is lacking. Admittedly, for concern to be constructive it must be linked to action. The Joint Commission and the Agency for Healthcare Research and Quality (AHRQ) currently recommend that parents help prevent errors by becoming active, involved and informed members of their healthcare team and taking part in every decision about (their) child's health care.6, 7 However, the extent to which parental concern about medical errors is related to a parent's self‐efficacy, or confidence, interacting with physicians is unknown.

Self‐efficacy is a construct used in social cognitive theory to explain behavior change.8 It refers to an individual's belief in (his/her) capabilities to organize and execute the courses of action required to produce given attainments or a desired outcome.9 Self‐efficacy is not a general concept; it must be discussed in reference to a specific activity. In healthcare it has been associated not only with willingness to adopt preventive strategies,10 but also with treatment adherence,11, 12 behavior change,13 and with greater patient participation in healthcare decision‐making.14, 15

In this study we had 2 objectives. First, we sought to assess the proportion of parents of hospitalized children who are concerned about medical errors. Second, we attempted to examine whether a parent's self‐efficacy interacting with physicians was associated with their concern about medical errors for their child. Given that parents with greater self‐efficacy interacting with physicians might feel more empowered to prevent errors and, as such, be more inclined to take an active role to do so, we hypothesized that such parents would be less concerned about medical errors during a pediatric hospitalization.

Subjects and Methods

Population

We surveyed parents of children <18 years of age (including 2 grandparents who will hereafter be referred to as parents) who were admitted to the general medical service of the Children's Hospital & Regional Medical Center (CHRMC) in Seattle, WA, from July through September 2005. This study was approved by the CHRMC Institutional Review Board. Due to stipulations of the Health Insurance Portability and Accountability Act (HIPAA), we were unable to collect extensive information on those parents who were missed or those who refused to participate in the study.

Exclusions

We excluded parents if: (1) they did not feel comfortable answering a written survey in English or Spanish; (2) their child was transferred to the general medical unit either from the intensive care unit (ICU) or from the inpatient unit of another hospital; or (3) they were not present during the hospitalization.

Study Design

We conducted a cross‐sectional self‐administered written survey of parents. The survey was translated into Spanish by a certified Spanish translator. A second independent translator confirmed the accuracy of the translation. Informed consent was obtained from parents before administration of the survey.

Data Collection

Parents were surveyed with a consecutive sampling methodology Tuesday through Friday from July 2005 through September 2005. We surveyed parents within 48 hours of admission of their child to the hospital, but after they had an opportunity to speak with the inpatient medical team that was caring for their child. A more detailed discussion of the data collection process has been published previously.16

Dependent Variables

Parental Concern About the Need to Watch for Medical Errors

We assessed parental concerns about medical errors during hospitalization by measuring responses to the statement When my child is in the hospital I feel that I have to watch over the care that he/she is receiving to make sure that mistakes aren't made. Parents reported their agreement/disagreement with this statement using a 5‐point Likert scale. For our analysis we dichotomized the dependent variable into those parents who responded Strongly Agree or Agree vs. those who responded Strongly Disagree or Disagree. We chose to focus on parents who expressed a directional response (eg, agree or disagree) because we felt that such responses were more likely to be correlated with behavior. As a result, we excluded from our primary analysis those participants who responded Unsure. In order to determine the effect of exclusion on our results (given its size), we conducted separate post‐hoc analyses in which we included the Unsure respondents in Agree and Disagree categories, respectively.

Independent Variables

Self‐Efficacy in Patient‐Physician Interactions

The Joint Commission's Speak Up initiative7 recommends that patients and parents interact with their healthcare providers in order to prevent errors. We gauged a parent's confidence of interacting with healthcare providers using an adapted scale of the Perceived Efficacy in Patient‐Physician Interactions (PEPPI) self‐efficacy scale. The PEPPI is a 50‐point self‐efficacy scale that has been validated in older adults.17 The response to each question is recorded on a 5‐point Likert scale ranging from 1 to 5 where 1 represents not at all confident and 5 represents very confident. Higher scores on this scale have been associated with greater participation in treatment decisions by women with breast cancer.18 We adapted this scale for use in pediatrics (Appendix 1).

Covariates

Prior Hospitalizations and Chronic Illness History

We asked parents to report how many times their child had been hospitalized prior to this current admission (not including birth). We chose to query parents directly because a search of our institutions' medical record database would not capture hospitalizations at other facilities. We categorized the variable for previous hospitalizations as follows: none, 1, 2, 3.

We asked parents to report if prior to this hospitalization they had ever been told by a nurse or doctor that their child had any of a list of chronic medical conditions such as chronic respiratory disease, mental retardation, and seizure disorder, among others. We gave parents the opportunity to specify a medical condition not provided on this list. The list of conditions was the same as that used in the Child Health Questionnaire PF‐28,19 which has been used in national and international studies to measure quality of life in children with and without chronic conditions20, 21 (Appendix 2).

Limited English Proficiency

We assessed the potential for a language barrier to impede communication between parent and healthcare providers by asking parents the following question: How comfortable are you that you can express your concerns and ask questions of your child's doctors in English? We measured parental responses on a 5‐point Likert scale (very comfortable vs. somewhat comfortable, not sure, somewhat uncomfortable, very uncomfortable). For our analyses, we dichotomized responses into those who reported being very comfortable vs. those who chose any other response category.

Social Desirability

We measured the potential for social desirability to bias responses using the Marlowe‐Crowne 2(10) Scale of Social Desirability.22 The Marlowe‐Crowne 2(10) Scale of Social Desirability is a shorter, validated version of the Marlowe‐Crowne Scale.23 This scale has been recommended by the National Institutes of Health (NIH)'s Behavior Change Consortium for use in behavioral change research related to health.24 It has been used in previous studies to account for social desirability bias in studies which involve patient self‐report of attitudes and beliefs.25 We analyzed scores on a continuous scale with higher scores representing greater social desirability bias in responses.

Demographics

We collected the following demographic data on parents: age, gender, race/ethnicity (white non‐Hispanic vs. other), education (high school or less, some college, college or higher). We also recorded the child's age and gender.

Statistical Analysis

Parental Concern for Medical Errors

Univariate statistics were used to report proportions of parents who were concerned about medical errors and to summarize the data for covariates and demographics. We conducted bivariate logistic regression analyses to assess the association between our outcome variable and the independent variable and each covariate, respectively. We used a Fisher's exact test to examine the association between limited English proficiency and our outcome variable because the absence of participants (eg, a zero cell) who were not very comfortable with English and not concerned about errors precluded the use of bivariate logistic regression. Therefore, to explore the relationship between race and language we used a Fischer's exact test to compare concern about medical errors between white and non‐white participants who were very comfortable with English.

We used multivariate logistic regression to test our hypothesis that greater self‐efficacy would be associated with less concern about medical errors after adjusting for the aforementioned covariates and demographics, excluding child gender. We had no a priori reason to expect that child gender would affect parental self‐efficacy or parental concern about errors and did not include it in the regression model. In order to provide a more clinically relevant interpretation of our results, we calculated adjusted predicted probabilities for the 25%, 50%, and 75% PEPPI scores using the mean for all other variables in the model.

We conducted post‐hoc analysis using a likelihood‐ratio test to determine if the hospitalization variable was significant in the multivariate regression model. We conducted additional post‐hoc analysis using bivariate logistic regression to explore the relationship between concern about medical errors and the following independent variables: hospitalization for >3 days after birth (yes/no); previous hospitalization for >1 week (yes/no); parents' experience with the hospital system (a lot, some, not sure, a little, none); overall perception of child's health (excellent, very good, good, fair); previous hospitalizations for other children (yes, no, no other children); rating of care that child has received (excellent vs. other [very good, good, fair]). We incorporated any significant associations (P < 0.05) into our preexisting multivariate model.

Results

During the time period of our study, 278 parents were eligible to participate. Eighty‐five parents could not be surveyed either because they could not be reached despite multiple attempts (eg, out of the room, speaking with physicians) or because the child had already been discharged. Of the 193 parents approached, 130 agreed to take the survey. Two parents who agreed to complete the survey forgot to return it before their children were discharged. Demographics of respondents and nonparticipants are presented in Table 1. The distribution of self‐efficacy scores was skewed, with a mean score of 45 (median 46, range 5‐50) on a 50‐point scale, consistent with previous studies in adults.18

Study Population Characteristics
CharacteristicsRespondents (n = 130)Number Missed (n = 85)Number Refused (n = 61)
  • Abbreviation: NA, not available; SD, standard deviation.

Parent's mean age34 years (range: 18‐51)NANA
Parent sex female, n (%)105 (80.8)NANA
Parental education, n (%)   
College or higher65 (50.4)  
Some college34 (26.4)  
High school or less30 (23.3)NANA
Parental race, n (%)   
White86 (67.2)  
Non‐White42 (32.8)NANA
Parent's social desirability score, mean (SD)7.0 (2.0)NANA
Child's median age21.4 months (range: 1 day‐17.8 years)24 months24 months
Child's sex female, n (%)63 (48.5)36 (42)35 (57)
Number of previous hospitalizations (child), n (%)   
None68 (53.1)  
126 (20.3)  
219 (14.8)  
315 (11.7)NANA
Number of chronic medical conditions (child), n (%)   
None56 (48.7)  
134 (29.6)  
225 (21.8)NANA
Parent's comfort expressing concerns in English, n (%) NANA
Very comfortable109 (83.9)  
Less than very comfortable21 (16.1)  
Self‐efficacy score (parent), mean (SD)45 (6.3)NANA

Eighty‐two parents (63% of respondents) Agreed or Strongly Agreed with the statement When my child is in the hospital I feel that I need to watch over his/her care in order to make sure that mistakes aren't made (Figure 1). In bivariate analyses, non‐white race (Table 2) and English proficiency (P = 0.002) were significantly associated with parental concern about medical errors. Notably, all respondents who were not very comfortable with English agreed that they felt the need to watch over their child's care to ensure that mistakes do not happen. The association between self‐efficacy with physician interactions and concern was nearly significant (Table 2).

Figure 1
Response to statement “When my child is in the hospital I feel that I have to watch over the care that he/she is receiving to make sure that mistakes aren't made.” [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Bivariate and Multivariate Logistic Regression of Factors Associated with Parental Concern for Medical Errors
VariableCrude Odds RatioConfidence IntervalP ValueAdjusted Odds RatioConfidence IntervalP Value
  • NOTE: Results of multivariate logistic regression.

  • P < 0.01.

  • P < 0.05.

Parent age (years)1.010.95‐1.060.791.050.95‐1.150.36
Parent gender      
FemaleReferent     
Male0.860.32‐2.350.770.760.20‐2.790.68
Age of child (months)1.000.99‐1.010.971.000.99‐1.010.83
Parental education      
College or higherReferent  Referent  
Some college0.480.18‐1.260.140.30.07‐1.130.07
High school or less1.390.48‐4.000.550.50.1‐2.20.38
Parental race      
WhiteReferent  Referent  
Non‐White5.00*1.61‐15.560.0054.91.19‐20.40.03
Previous hospitalization (child)      
NoneReferent  Referent  
10.440.16‐1.200.110.160.04‐0.690.01
20.890.27‐2.870.840.600.13‐2.830.5
30.910.21‐3.840.900.790.12‐5.060.8
Number of chronic medical conditions0.860.67‐1.110.261.050.74‐1.500.78
Social desirability score (parent)0.990.81‐1.210.920.990.76‐1.290.9
Self‐efficacy score (parent)0.900.81‐1.000.060.830.73‐0.950.006*

In multivariate analysis, self‐efficacy was independently associated with parental report about the need to watch over a child's care (odds ratio [OR], 0.83; 95% confidence interval [CI], 0.72‐0.92). In prediction models, with self‐efficacy scores of 44 (25th percentile), 46 (50th percentile), and 49 (75th percentile), about 72.2% (59.1‐82.3), 64.2% (51.8‐75.0), and 50.8% (35.3‐66.2) of parents, respectively, would feel the need to watch over their child's care to prevent medical errors.

While respondents of non‐white race had the greatest independent odds of reporting a concern for medical errors occurring while their child was hospitalized (OR, 4.9; 95% CI, 1.19‐20.4), we could not reliably determine how much of this effect was due to language instead of to race because the vast majority of parents who reported being less than very comfortable with English were also non‐white (non‐white 90.5% vs. white 9.5%, P < 0.001). In additional analyses we were unable to find a difference in concern about medical errors between white and non‐white parents who were very comfortable with English (data not shown).

Of note, while having 1 hospitalization compared to none was significantly associated with having decreased concern about medical errors (Table 2), the variable hospitalizations was not significant in the model (P = 0.07).

In post‐hoc analysis, we found no association between hospitalization for >3 days after birth, previous hospitalization for >1 week, parents' experience with the hospital system, and overall perception of child's health, previous hospitalizations for other children. While rating of care that child received was significantly associated with parents' concern about medical errors in the bivariate analysis, it did not remain significant in multivariate analysis and did not substantially change the magnitude or significance of previous associations.

Discussion

In our study, we found that nearly two‐thirds of parents of children admitted to the general pediatric service of a tertiary care children's hospital felt the need to watch over their child's care to ensure that mistakes would not be made. We also found that a parent's self‐efficacy interacting with physicians was associated with less parental concern for medical errors.

To our knowledge, this is the first study to systematically survey parents' concerns about medical errors during a child's hospitalization and to evaluate factors associated with this concern. The immediate question prompted by our findings is whether the fact that 63% of parents are concerned is alarming because it is too low or too high. Some might contend that concern about medical errors is an appropriate and desirable response because it may motivate parents to become more vigilant about the medical care that their child is receiving. However, others may challenge that such concern may indicate a feeling of powerlessness to act to prevent potential errors. In our study, the relationship between higher self‐efficacy and less parental concern raises the possibility that parents with higher levels of self‐efficacy with physician interactions may feel more comfortable communicating with physicians, which in turn may temper parents' concerns about medical errors during hospitalization.

It is equally plausible that concern about medical errors during hospitalization may motivate parents to become involved in their child's medical care and, in turn, lead them to feel empowered to prevent medical errors and so ease their concerns. It is conceivable that experience with past medical errors may fuel a parent's need to watch over their child's care to prevent additional medical errors. Future studies should address the independent effect of past medical errors on parental concern about medical errors.

In this study, all parents who reported being very uncomfortable with English and parents of non‐white race felt the need to watch over their child's care to help prevent errors. A previous survey of a nationally representative sample of U.S. adults found greater proportion of non‐white adults were very concerned about errors or mistakes happening when receiving care at a hospital (blacks 62%, Hispanics 57%, whites 44%).26 However, in our study, the relationship between race and concern is likely mediated by language since many of the parents who described themselves as other than white also reported being not very comfortable with English and we could not find an effect of race on concern among parents who were very comfortable with English. Indeed, previous studies have linked decreased English proficiency to medical errors with potential clinical consequence.27

Given our previous investigation of the relationship between self‐efficacy and parent participation in medical decisions during a child's hospitalization, we conducted post‐hoc analyses exploring the association between parents' self‐report of participation in medical decisions and concern about medical errors during their child's hospitalization.16 Using a simple logistic regression we did not find any association. However, we advise caution in interpreting and generalizing these results because the study was not powered to adequately evaluate this association.

There are additional limitations in our study to be noted. First, this question has not been used previously to assess parental concern about medical errors, so future work will need to focus on assessing its reliability and validity. Second, it is also possible that parents' concern for medical errors is mitigated by the complexity of their child's healthcare.5 We attempted to address this issue by controlling for the child's number of chronic illnesses. However, it is possible that our metric did not capture the level of complexity associated with different types of chronic conditions. Moreover, additional variables such as health insurance type, parental physical and mental health, and quality of interactions with the nursing staff may confound the relationships that we observed. Future studies should examine the effect of these variables on parents' self‐efficacy and their concern about medical errors.

Third, we surveyed parents at a single institution and, as such, differences in demographics and hospital‐specific practices related to patient‐physician interactions may prevent generalization of our findings to other institutions. For example, the parents in our survey had a higher average education level than the general population and the racial makeup of our population was not nationally representative. Also, due to HIPAA constraints, we were unable to collect extensive demographic information on parents and children who were missed or those who refused to participate in the study, which also could conceivably influence the strength of our findings.

Fourth, we adapted a validated adult measure of self‐efficacy for use in pediatrics. The patient‐physician self‐efficacy scale, the PEPPI, did have a skewed distribution in our study, although this performance is consistent with adult studies18 and in post‐hoc analyses, outlier PEPPI scores did not have a significant effect on the magnitude of the relationship we observed between self‐efficacy and parental concern about medical errors. However, the reading level of this instrument is ninth grade, which may impact the generalization of our findings to populations with lower literacy levels.

Fifth, we excluded parents who were unsure about their concern from our analyses. In post‐hoc multivariate regression analyses, reassignment of unsure responses to either agree or disagree did not result in any change in odds ratio for any endpoint.

Finally, it is possible that parental concern was influenced by social desirability bias in that parents may have been less likely to report concern about medical errors during a hospitalization because of fear of the implications it might have for their child's care. We attempted to control for this effect by adjusting for social desirability bias using the Marlowe‐Crowne scale. This scale is commonly used in behavioral science research to account for such response bias and has been recommended by the NIH Consortium on Behavior Change for use in behavioral change research related to health.24

Within the context of these limitations, we feel that our study contributes an important first step toward characterizing the scope of parental concern about medical errors during pediatric hospitalizations and understanding the relationship of self‐efficacy with physician interactions to this concern. Devising a quality initiative program to improve parents' self‐efficacy interacting with physicians might help to temper parents' concerns about medical errors while also encouraging their involvement in their child's medical care. Such a program would likely prove most beneficial if it sought to improve self‐efficacy among parents with lower English proficiency given that this group had the highest concern for medical errors. Possible interventions might include more ready access to interpreters or use of visual aids.

References
  1. Institute of Medicine Committee on Quality of Health Care in America.Crossing the Quality Chasm: A New Health System for the 21st Century.Washington, DC:National Academy Press;2001.
  2. Kaushal R,Bates DW,Landrigan C, et al.Medication errors and adverse drug events in pediatric inpatients.JAMA.2001;285(16):21142120.
  3. Miller MR,Zhan C.Pediatric patient safety in hospitals: a national picture in 2000.Pediatrics.2004;113(6):17411746.
  4. Waterman AD,Gallagher TH,Garbutt J,Waterman BM,Fraser V,Burroughs TE.Brief report: hospitalized patients' attitudes about and participation in error prevention.J Gen Intern Med.2006;21(4):367370.
  5. Burroughs TE,Waterman AD,Gallagher TH, et al.Patients' concerns about medical errors during hospitalization.Jt Comm J Qual Patient Saf.2007;33(1):514.
  6. Agency for Healthcare Research and Quality.20 Tips to Help Prevent Medical Errors in Children. Patient Fact Sheet. 2009, AHRQ Publication No. 02‐P034.Rockville, MD:Agency for Healthcare Research and Quality.
  7. Joint Commission on Accreditation of Healthcare Organizations. Speak Up Initiatives. Available at: http://www.jointcommission.org/PatientSafety/SpeakUp. Accessed May 2009.
  8. Bandura A.Self‐efficacy: toward a unifying theory of behavioral change.Psychol Rev.1977;84(2):191215.
  9. Bandura A.Self‐Efficacy: The Exercise of Control.New York, NY:W.H. Freeman and Company;1997.
  10. Strauss RS,Rodzilsky D,Burack G,Colin M.Psychosocial correlates of physical activity in healthy children.Arch Pediatr Adolesc Med.2001;155(8):897902.
  11. Ott J,Greening L,Palardy N,Holderby A,DeBell WK.Self‐efficacy as a mediator variable for adolescents' adherence to treatment for insulin‐dependent diabetes mellitus.Children's Health Care.2000;29(1):4763.
  12. McCaul KD,Glasgow RE,Schafer LC.Diabetes regimen behaviors. Predicting adherence.Med Care.1987;25(9):868881.
  13. Cabana MD,Rand C,Slish K,Nan B,Davis MM,Clark N.Pediatrician self‐efficacy for counseling parents of asthmatic children to quit smoking.Pediatrics.2004;113(1 Pt 1):7881.
  14. Arora NK,Ayanian JZ,Guadagnoli E.Examining the relationship of patients' attitudes and beliefs with their self‐reported level of participation in medical decision‐making.Med Care.2005;43(9):865872.
  15. Janz NK,Wren PA,Copeland LA,Lowery JC,Goldfarb SL,Wilkins EG.Patient‐physician concordance: preferences, perceptions, and factors influencing the breast cancer surgical decision.J Clin Oncol.2004;22(15):30913098.
  16. Tarini BA,Christakis DA,Lozano P.Toward family‐centered inpatient medical care: the role of parents as participants in medical decisions.J Pediatr.2007;151(6):690695.
  17. Maly RC,Frank JC,Marshall GN,DiMatteo MR,Reuben DB.Perceived efficacy in patient‐physician interactions (PEPPI): validation of an instrument in older persons.J Am Geriatr Soc.1998;46(7):889894.
  18. Maly RC,Umezawa Y,Leake B,Silliman RA.Determinants of participation in treatment decision‐making by older breast cancer patients.Breast Cancer Res Treat.2004;85(3):201209.
  19. Landgraf JM AL,Ware JE.The CHQ: A User's Manual (2nd printing).Boston, MA:HealthAct;1999.
  20. Waters EB,Salmon LA,Wake M,Wright M,Hesketh KD.The health and well‐being of adolescents: a school‐based population study of the self‐report Child Health Questionnaire.J Adolesc Health.2001;29(2):140149.
  21. Wake M,Hesketh K,Cameron F.The Child Health Questionnaire in children with diabetes: cross‐sectional survey of parent and adolescent‐reported functional health status.Diabet Med.2000;17(10):700707.
  22. Strahan R,Gerbasi KC.Semantic style variance in personality questionnaires.J Psychol.1973;85:109118.
  23. Crowne DP,Marlowe D.A new scale of social desirability independent of psychopathology.J Consult Psychol.1960;24:349354.
  24. National Institutes of Health. Behavior Change Consortium‐Recommended Nutrition Measures. Available at:http://www1.od.nih.gov/behaviorchange/measures/nutrition.htm. Accessed May 2009.
  25. Bardwell WA,Ancoli‐Israel S,Dimsdale JE.Response bias influences mental health symptom reporting in patients with obstructive sleep apnea.Ann Behav Med.2001;23(4):313317.
  26. Kaiser Family Foundation, Agency for Healthcare Research and Quality.Americans as Health Care Consumers: Update on the Role of Quality Information.Rockville, MD:Agency for Healthcare Research and Quality;2000.
  27. Flores G,Laws MB,Mayo SJ, et al.Errors in medical interpretation and their potential clinical consequences in pediatric encounters.Pediatrics.2003;111(1):614.
References
  1. Institute of Medicine Committee on Quality of Health Care in America.Crossing the Quality Chasm: A New Health System for the 21st Century.Washington, DC:National Academy Press;2001.
  2. Kaushal R,Bates DW,Landrigan C, et al.Medication errors and adverse drug events in pediatric inpatients.JAMA.2001;285(16):21142120.
  3. Miller MR,Zhan C.Pediatric patient safety in hospitals: a national picture in 2000.Pediatrics.2004;113(6):17411746.
  4. Waterman AD,Gallagher TH,Garbutt J,Waterman BM,Fraser V,Burroughs TE.Brief report: hospitalized patients' attitudes about and participation in error prevention.J Gen Intern Med.2006;21(4):367370.
  5. Burroughs TE,Waterman AD,Gallagher TH, et al.Patients' concerns about medical errors during hospitalization.Jt Comm J Qual Patient Saf.2007;33(1):514.
  6. Agency for Healthcare Research and Quality.20 Tips to Help Prevent Medical Errors in Children. Patient Fact Sheet. 2009, AHRQ Publication No. 02‐P034.Rockville, MD:Agency for Healthcare Research and Quality.
  7. Joint Commission on Accreditation of Healthcare Organizations. Speak Up Initiatives. Available at: http://www.jointcommission.org/PatientSafety/SpeakUp. Accessed May 2009.
  8. Bandura A.Self‐efficacy: toward a unifying theory of behavioral change.Psychol Rev.1977;84(2):191215.
  9. Bandura A.Self‐Efficacy: The Exercise of Control.New York, NY:W.H. Freeman and Company;1997.
  10. Strauss RS,Rodzilsky D,Burack G,Colin M.Psychosocial correlates of physical activity in healthy children.Arch Pediatr Adolesc Med.2001;155(8):897902.
  11. Ott J,Greening L,Palardy N,Holderby A,DeBell WK.Self‐efficacy as a mediator variable for adolescents' adherence to treatment for insulin‐dependent diabetes mellitus.Children's Health Care.2000;29(1):4763.
  12. McCaul KD,Glasgow RE,Schafer LC.Diabetes regimen behaviors. Predicting adherence.Med Care.1987;25(9):868881.
  13. Cabana MD,Rand C,Slish K,Nan B,Davis MM,Clark N.Pediatrician self‐efficacy for counseling parents of asthmatic children to quit smoking.Pediatrics.2004;113(1 Pt 1):7881.
  14. Arora NK,Ayanian JZ,Guadagnoli E.Examining the relationship of patients' attitudes and beliefs with their self‐reported level of participation in medical decision‐making.Med Care.2005;43(9):865872.
  15. Janz NK,Wren PA,Copeland LA,Lowery JC,Goldfarb SL,Wilkins EG.Patient‐physician concordance: preferences, perceptions, and factors influencing the breast cancer surgical decision.J Clin Oncol.2004;22(15):30913098.
  16. Tarini BA,Christakis DA,Lozano P.Toward family‐centered inpatient medical care: the role of parents as participants in medical decisions.J Pediatr.2007;151(6):690695.
  17. Maly RC,Frank JC,Marshall GN,DiMatteo MR,Reuben DB.Perceived efficacy in patient‐physician interactions (PEPPI): validation of an instrument in older persons.J Am Geriatr Soc.1998;46(7):889894.
  18. Maly RC,Umezawa Y,Leake B,Silliman RA.Determinants of participation in treatment decision‐making by older breast cancer patients.Breast Cancer Res Treat.2004;85(3):201209.
  19. Landgraf JM AL,Ware JE.The CHQ: A User's Manual (2nd printing).Boston, MA:HealthAct;1999.
  20. Waters EB,Salmon LA,Wake M,Wright M,Hesketh KD.The health and well‐being of adolescents: a school‐based population study of the self‐report Child Health Questionnaire.J Adolesc Health.2001;29(2):140149.
  21. Wake M,Hesketh K,Cameron F.The Child Health Questionnaire in children with diabetes: cross‐sectional survey of parent and adolescent‐reported functional health status.Diabet Med.2000;17(10):700707.
  22. Strahan R,Gerbasi KC.Semantic style variance in personality questionnaires.J Psychol.1973;85:109118.
  23. Crowne DP,Marlowe D.A new scale of social desirability independent of psychopathology.J Consult Psychol.1960;24:349354.
  24. National Institutes of Health. Behavior Change Consortium‐Recommended Nutrition Measures. Available at:http://www1.od.nih.gov/behaviorchange/measures/nutrition.htm. Accessed May 2009.
  25. Bardwell WA,Ancoli‐Israel S,Dimsdale JE.Response bias influences mental health symptom reporting in patients with obstructive sleep apnea.Ann Behav Med.2001;23(4):313317.
  26. Kaiser Family Foundation, Agency for Healthcare Research and Quality.Americans as Health Care Consumers: Update on the Role of Quality Information.Rockville, MD:Agency for Healthcare Research and Quality;2000.
  27. Flores G,Laws MB,Mayo SJ, et al.Errors in medical interpretation and their potential clinical consequences in pediatric encounters.Pediatrics.2003;111(1):614.
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Journal of Hospital Medicine - 4(9)
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Afraid in the hospital: Parental concern for errors during a child's hospitalization
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Think Twice Before Accepting an Expert Witness Offer

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Think Twice Before Accepting an Expert Witness Offer

AMANE KANEKO

Think Twice Before Accepting an Expert Witness Offer

A medical malpractice attorney recently contacted me, asking if I would be interested in reviewing a case. They are looking for a hospitalist “expert witness.” I’ve never done this before and don’t know if I’m qualified. Can you tell me about the benefits and risks of being a medical expert witness?

R. Jones, MD

Miami

ASK Dr. Hospitalist

Do you have a problem or concern that you’d like Dr. Hospitalist to address? E-mail your questions to [email protected].

Dr. Hospitalist responds: Most physicians complete medical school and postgraduate training without firsthand knowledge of our legal system. Unfortunately, a number of physicians become defendants in medical lawsuits during their professional careers. I hear with increasing frequency about hospitalists being sued for alleged medical malpractice. I am not surprised. This is not an indictment against hospital HM, but more a matter of probability. There are at least tenfold more hospitalists today than 10 years ago.

To be clear, I am not an attorney, nor do I have any formal legal training. I suggest you speak with an attorney if you have questions about the law.

Laws vary from state to state, but for the most part, plaintiff attorneys and defense attorneys retain expert witnesses to help them determine the merits of a lawsuit. Did the defendant have a duty to treat the patient? Was there a breach of the standard of care? What were the damages, and were they due to the defendant’s actions or lack of action?

Understand that our judicial system holds that a physician in the same field as the defendant is the most qualified to determine whether the defendant met the standard of care. Standard of care is what is reasonably expected of a physician in that field given the circumstances. So if the defendant is a hospitalist, the attorneys are looking for an expert witness who is also a hospitalist. Seems like a reasonable system, right? Individuals are judged by their peers. But the system is far from perfect.

Critics point out the system is inherently flawed when we rely on “experts” to help us determine the standard of care. Aside from working in a given field of medicine, there are no specific qualifications to be an expert witness. Unfortunately, not all experts are experts, and not all experts are completely honest. And there can be a lot of money at stake. Plaintiffs attorneys and defense attorneys, along with expert witnesses for both sides, stand to profit from lawsuits. All of this drives up the cost of medical malpractice premiums.

I will not tell you not to become an expert witness. Until we see real, sustainable tort reform, we have to live with the system. If I am sued, my defense attorney would seek an expert witness’s opinion. If a patient is hurt because of alleged negligence, the patient’s attorney would seek the opinion of an expert witness. So we need honest physicians to provide honest opinions as expert witnesses. This goes for defendants and plaintiffs.

Many expert witnesses find gratification in knowing they helped a patient or a physician. As I mentioned previously, an expert-witness gig can be financially lucrative, but it is not without its drawbacks. Expert witnesses are subject to the code of ethics set forth by the medical society and state board of registration in medicine. Any sworn testimony you provide is discoverable. It is easier than you might think for others (e.g., opposition attorneys) to believe you have contradicted yourself when you give your opinion on the same subject in more than one case. As an expert witness, know that you will be cross-examined by an attorney, either in deposition or at trial. Testifying under oath can be a grueling experience.

 

 

Most expert witnesses are reputable physicians in their fields. You should feel honored for being asked to participate as an expert witness, but think carefully before you accept the offer. Understand what is being asked of you before you take on this responsibility. TH

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AMANE KANEKO

Think Twice Before Accepting an Expert Witness Offer

A medical malpractice attorney recently contacted me, asking if I would be interested in reviewing a case. They are looking for a hospitalist “expert witness.” I’ve never done this before and don’t know if I’m qualified. Can you tell me about the benefits and risks of being a medical expert witness?

R. Jones, MD

Miami

ASK Dr. Hospitalist

Do you have a problem or concern that you’d like Dr. Hospitalist to address? E-mail your questions to [email protected].

Dr. Hospitalist responds: Most physicians complete medical school and postgraduate training without firsthand knowledge of our legal system. Unfortunately, a number of physicians become defendants in medical lawsuits during their professional careers. I hear with increasing frequency about hospitalists being sued for alleged medical malpractice. I am not surprised. This is not an indictment against hospital HM, but more a matter of probability. There are at least tenfold more hospitalists today than 10 years ago.

To be clear, I am not an attorney, nor do I have any formal legal training. I suggest you speak with an attorney if you have questions about the law.

Laws vary from state to state, but for the most part, plaintiff attorneys and defense attorneys retain expert witnesses to help them determine the merits of a lawsuit. Did the defendant have a duty to treat the patient? Was there a breach of the standard of care? What were the damages, and were they due to the defendant’s actions or lack of action?

Understand that our judicial system holds that a physician in the same field as the defendant is the most qualified to determine whether the defendant met the standard of care. Standard of care is what is reasonably expected of a physician in that field given the circumstances. So if the defendant is a hospitalist, the attorneys are looking for an expert witness who is also a hospitalist. Seems like a reasonable system, right? Individuals are judged by their peers. But the system is far from perfect.

Critics point out the system is inherently flawed when we rely on “experts” to help us determine the standard of care. Aside from working in a given field of medicine, there are no specific qualifications to be an expert witness. Unfortunately, not all experts are experts, and not all experts are completely honest. And there can be a lot of money at stake. Plaintiffs attorneys and defense attorneys, along with expert witnesses for both sides, stand to profit from lawsuits. All of this drives up the cost of medical malpractice premiums.

I will not tell you not to become an expert witness. Until we see real, sustainable tort reform, we have to live with the system. If I am sued, my defense attorney would seek an expert witness’s opinion. If a patient is hurt because of alleged negligence, the patient’s attorney would seek the opinion of an expert witness. So we need honest physicians to provide honest opinions as expert witnesses. This goes for defendants and plaintiffs.

Many expert witnesses find gratification in knowing they helped a patient or a physician. As I mentioned previously, an expert-witness gig can be financially lucrative, but it is not without its drawbacks. Expert witnesses are subject to the code of ethics set forth by the medical society and state board of registration in medicine. Any sworn testimony you provide is discoverable. It is easier than you might think for others (e.g., opposition attorneys) to believe you have contradicted yourself when you give your opinion on the same subject in more than one case. As an expert witness, know that you will be cross-examined by an attorney, either in deposition or at trial. Testifying under oath can be a grueling experience.

 

 

Most expert witnesses are reputable physicians in their fields. You should feel honored for being asked to participate as an expert witness, but think carefully before you accept the offer. Understand what is being asked of you before you take on this responsibility. TH

AMANE KANEKO

Think Twice Before Accepting an Expert Witness Offer

A medical malpractice attorney recently contacted me, asking if I would be interested in reviewing a case. They are looking for a hospitalist “expert witness.” I’ve never done this before and don’t know if I’m qualified. Can you tell me about the benefits and risks of being a medical expert witness?

R. Jones, MD

Miami

ASK Dr. Hospitalist

Do you have a problem or concern that you’d like Dr. Hospitalist to address? E-mail your questions to [email protected].

Dr. Hospitalist responds: Most physicians complete medical school and postgraduate training without firsthand knowledge of our legal system. Unfortunately, a number of physicians become defendants in medical lawsuits during their professional careers. I hear with increasing frequency about hospitalists being sued for alleged medical malpractice. I am not surprised. This is not an indictment against hospital HM, but more a matter of probability. There are at least tenfold more hospitalists today than 10 years ago.

To be clear, I am not an attorney, nor do I have any formal legal training. I suggest you speak with an attorney if you have questions about the law.

Laws vary from state to state, but for the most part, plaintiff attorneys and defense attorneys retain expert witnesses to help them determine the merits of a lawsuit. Did the defendant have a duty to treat the patient? Was there a breach of the standard of care? What were the damages, and were they due to the defendant’s actions or lack of action?

Understand that our judicial system holds that a physician in the same field as the defendant is the most qualified to determine whether the defendant met the standard of care. Standard of care is what is reasonably expected of a physician in that field given the circumstances. So if the defendant is a hospitalist, the attorneys are looking for an expert witness who is also a hospitalist. Seems like a reasonable system, right? Individuals are judged by their peers. But the system is far from perfect.

Critics point out the system is inherently flawed when we rely on “experts” to help us determine the standard of care. Aside from working in a given field of medicine, there are no specific qualifications to be an expert witness. Unfortunately, not all experts are experts, and not all experts are completely honest. And there can be a lot of money at stake. Plaintiffs attorneys and defense attorneys, along with expert witnesses for both sides, stand to profit from lawsuits. All of this drives up the cost of medical malpractice premiums.

I will not tell you not to become an expert witness. Until we see real, sustainable tort reform, we have to live with the system. If I am sued, my defense attorney would seek an expert witness’s opinion. If a patient is hurt because of alleged negligence, the patient’s attorney would seek the opinion of an expert witness. So we need honest physicians to provide honest opinions as expert witnesses. This goes for defendants and plaintiffs.

Many expert witnesses find gratification in knowing they helped a patient or a physician. As I mentioned previously, an expert-witness gig can be financially lucrative, but it is not without its drawbacks. Expert witnesses are subject to the code of ethics set forth by the medical society and state board of registration in medicine. Any sworn testimony you provide is discoverable. It is easier than you might think for others (e.g., opposition attorneys) to believe you have contradicted yourself when you give your opinion on the same subject in more than one case. As an expert witness, know that you will be cross-examined by an attorney, either in deposition or at trial. Testifying under oath can be a grueling experience.

 

 

Most expert witnesses are reputable physicians in their fields. You should feel honored for being asked to participate as an expert witness, but think carefully before you accept the offer. Understand what is being asked of you before you take on this responsibility. TH

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Think Twice Before Accepting an Expert Witness Offer
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Volume Variables

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At sold-out HM09 in Chicago in May, I had the pleasure of moderating a panel discussion titled “Who Says 15 Patients a Day is the Right Number?” As you might guess, each panelist (including me) said, in effect, “No one says 15 patients a day is the right number.”

Despite being a very important issue to SHM, the society doesn’t have an official position on the “right” or optimal daily patient volume or workload for a hospitalist. SHM generates and disseminates a lot of information to help each practice make decisions about workload, including SHM’s 2007-2008 “Bi-annual Survey on the State of the Hospital Medicine Movement,” articles available at www.hospitalmedicine.org, and articles in The Hospitalist. But all practices, and individual hospitalists, will have to decide what level of patient volume enables safe care, a sustainable and satisfying workload, and reasonable economic performance.

Of course, billable encounters fail to perfectly describe our workloads, but until someone comes up with a better metric that is universally understood and applicable across all settings, billable encounters is the best metric we have.

Workload Metrics

A problem that makes any workload discussion difficult is that many terms are sometimes used to mean different things. For example, “daily census” is used when comparing workloads between practices, but “daily encounters” is nearly always a more informative metric. Remember, daily encounters for a practice will always be higher (though on rare occasion, the same) than daily census.

The only definition of encounters that can be reliably compared between practices is billable encounters. Confusion arises when one person is reporting billable encounters, and another person is counting as one encounter each time a hospitalist interacted with a patient (e.g., went into the patient’s room or made a chart entry) and reports a higher encounter volume despite having the same workload and patient volume. Of course, billable encounters fail to perfectly describe our workloads, but until someone comes up with a better metric that is universally understood and applicable across all settings, billable encounters is the best metric we have.

Both billable encounters and census can be tricky. We might be convinced that because she averages 17 billable encounters per day, Dr. Krause has a higher workload than Dr. Palmer, who averages 15. But it turns out that Dr. Palmer works 210 shifts annually, generating 3,150 annual encounters; Dr. Krause’s 181 annual shifts generate 3,077 encounters. So while Dr. Krause does indeed work harder on the average day, she has lower annual productivity. My experience is that by failing to compare workloads over long periods, such as a year, many attempts to compare workloads yield misleading conclusions.

Comparing encounter volume from one practice to the next fails to capture other ways workloads differ. Dr. Krause may be the principal caregiver for a number of ICU patients; Dr. Plant might turn such patients over to intensivists. For this reason, work relative value units (wRVUs), which attempt to capture the complexity of each encounter, usually are a more meaningful—though still imperfect—metric.

Apples vs. Apples

Any truly valid method of comparing workloads should sum the annual workload for the entire practice and divide by the total provider full-time equivalents (FTEs). Yet problems arise because night shifts usually are less productive than day shifts. Consider a practice that has a distinct night shift worked by a doctor who does no day-shift work the day before or after. There is a tendency to leave this night shift out of the analysis of average workload per FTE, which makes the practice appear more productive than it really is.

 

 

For example, the practice I am part of has dedicated nocturnists who don’t work day shifts. So when thinking about how hard we’re working, we tend to sum each “day” doctor’s wRVUs for the year and divide by the number of day doctors. Calculated this way, our day doctors appear to be more productive than SHM data might indicate, but when including our nocturnists’ production and FTEs in the analysis, the overall workload per FTE in the practice is similar to the data.

Productivity Per FTE

While I think productivity per FTE per year is the best metric to use when comparing a practice to external survey data or comparing one practice to another, it is confounded by two sticky problems: inconsistent definitions of what constitutes an FTE, and the lack of an agreed-upon method of accounting for the contribution of nonphysician providers.

The most common definitions of what constitutes an FTE are based on the number of hours or shifts worked. One practice might define an FTE as 2,000 hours of work annually; another might use 180 annual shifts. Unless each shift has a clearly defined duration, it will be very difficult to reach conclusions. Although each practice might make sound decisions about how they define an FTE, they’re ultimately making arbitrary choices that aren’t consistent from one practice to the next. Controlling for this issue is very difficult.

Even trickier is how to compare the contributions of physician assistants (PAs) and nurse practitioners (NPs) from one practice to the next. In the above example, Dr. Plant’s practice has eight physician FTEs and four NPPs, and Dr. Krause’s group has eight MDs and no NPPs. How much more productive should we expect Dr. Plant’s practice to be? (NPPs make many valuable contributions, in addition to increasing productivity, but these are outside the scope of this article.)

Though survey data offer some clues, there is no established standard for increased productivity expected of PAs and NPs. One approach I use is to compare an NPP’s total compensation (salary and benefits) with that of the average physician FTE. If the cost of each NPP is 60% of an MD, then one could say that each NPP represents 0.6 “physician FTE equivalents” and could be expected to increase the productivity of the practice proportionately. So Dr. Plant’s group might be expected to have the productivity of 10.2 physician FTEs (4 NPPs X 0.6 = 2.2 “physician FTE equivalents,” added to the eight physician FTEs). (Note: While I think converting NPP FTEs into “physician equivalents” is useful in analyzing the effect of workloads on budgets, there are clearly many other very important issues when trying to quantify the contribution of NPPs to a practice.)

Judgment Rules

There are dozens of additional issues, such as the effect on productivity resulting from inefficient hospital systems (e.g., a clunky electronic health record, typed admit notes aren’t available for a few days compared with records available within two to four hours of dictation), activities such as attending Rapid Response Team activations, and differences in the social complexity of the patient population. None of these would show up in wRVU reports, so they are missing from the analysis I’ve described above.

I think it is impossible to control for all of the differences between practices that influence the definition of appropriate workload. This is the main reason SHM probably will never have a firm position on exactly what is the right or optimal number.

Although 15 patients a day is a reasonable starting point (I prefer to see fewer patients daily, but work more days/shifts annually), things get complicated in a hurry, and there will always be significant variation. TH

 

 

Dr. Nelson has been a practicing hospitalist since 1988 and is co-founder and past president of SHM. He is a principal in Nelson/Flores Associates, a national hospitalist practice management consulting firm. He also is faculty for SHM’s “Best Practices in Managing a Hospital Medicine Program” course. This column represents his views and is not intended to reflect an official position of SHM.

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At sold-out HM09 in Chicago in May, I had the pleasure of moderating a panel discussion titled “Who Says 15 Patients a Day is the Right Number?” As you might guess, each panelist (including me) said, in effect, “No one says 15 patients a day is the right number.”

Despite being a very important issue to SHM, the society doesn’t have an official position on the “right” or optimal daily patient volume or workload for a hospitalist. SHM generates and disseminates a lot of information to help each practice make decisions about workload, including SHM’s 2007-2008 “Bi-annual Survey on the State of the Hospital Medicine Movement,” articles available at www.hospitalmedicine.org, and articles in The Hospitalist. But all practices, and individual hospitalists, will have to decide what level of patient volume enables safe care, a sustainable and satisfying workload, and reasonable economic performance.

Of course, billable encounters fail to perfectly describe our workloads, but until someone comes up with a better metric that is universally understood and applicable across all settings, billable encounters is the best metric we have.

Workload Metrics

A problem that makes any workload discussion difficult is that many terms are sometimes used to mean different things. For example, “daily census” is used when comparing workloads between practices, but “daily encounters” is nearly always a more informative metric. Remember, daily encounters for a practice will always be higher (though on rare occasion, the same) than daily census.

The only definition of encounters that can be reliably compared between practices is billable encounters. Confusion arises when one person is reporting billable encounters, and another person is counting as one encounter each time a hospitalist interacted with a patient (e.g., went into the patient’s room or made a chart entry) and reports a higher encounter volume despite having the same workload and patient volume. Of course, billable encounters fail to perfectly describe our workloads, but until someone comes up with a better metric that is universally understood and applicable across all settings, billable encounters is the best metric we have.

Both billable encounters and census can be tricky. We might be convinced that because she averages 17 billable encounters per day, Dr. Krause has a higher workload than Dr. Palmer, who averages 15. But it turns out that Dr. Palmer works 210 shifts annually, generating 3,150 annual encounters; Dr. Krause’s 181 annual shifts generate 3,077 encounters. So while Dr. Krause does indeed work harder on the average day, she has lower annual productivity. My experience is that by failing to compare workloads over long periods, such as a year, many attempts to compare workloads yield misleading conclusions.

Comparing encounter volume from one practice to the next fails to capture other ways workloads differ. Dr. Krause may be the principal caregiver for a number of ICU patients; Dr. Plant might turn such patients over to intensivists. For this reason, work relative value units (wRVUs), which attempt to capture the complexity of each encounter, usually are a more meaningful—though still imperfect—metric.

Apples vs. Apples

Any truly valid method of comparing workloads should sum the annual workload for the entire practice and divide by the total provider full-time equivalents (FTEs). Yet problems arise because night shifts usually are less productive than day shifts. Consider a practice that has a distinct night shift worked by a doctor who does no day-shift work the day before or after. There is a tendency to leave this night shift out of the analysis of average workload per FTE, which makes the practice appear more productive than it really is.

 

 

For example, the practice I am part of has dedicated nocturnists who don’t work day shifts. So when thinking about how hard we’re working, we tend to sum each “day” doctor’s wRVUs for the year and divide by the number of day doctors. Calculated this way, our day doctors appear to be more productive than SHM data might indicate, but when including our nocturnists’ production and FTEs in the analysis, the overall workload per FTE in the practice is similar to the data.

Productivity Per FTE

While I think productivity per FTE per year is the best metric to use when comparing a practice to external survey data or comparing one practice to another, it is confounded by two sticky problems: inconsistent definitions of what constitutes an FTE, and the lack of an agreed-upon method of accounting for the contribution of nonphysician providers.

The most common definitions of what constitutes an FTE are based on the number of hours or shifts worked. One practice might define an FTE as 2,000 hours of work annually; another might use 180 annual shifts. Unless each shift has a clearly defined duration, it will be very difficult to reach conclusions. Although each practice might make sound decisions about how they define an FTE, they’re ultimately making arbitrary choices that aren’t consistent from one practice to the next. Controlling for this issue is very difficult.

Even trickier is how to compare the contributions of physician assistants (PAs) and nurse practitioners (NPs) from one practice to the next. In the above example, Dr. Plant’s practice has eight physician FTEs and four NPPs, and Dr. Krause’s group has eight MDs and no NPPs. How much more productive should we expect Dr. Plant’s practice to be? (NPPs make many valuable contributions, in addition to increasing productivity, but these are outside the scope of this article.)

Though survey data offer some clues, there is no established standard for increased productivity expected of PAs and NPs. One approach I use is to compare an NPP’s total compensation (salary and benefits) with that of the average physician FTE. If the cost of each NPP is 60% of an MD, then one could say that each NPP represents 0.6 “physician FTE equivalents” and could be expected to increase the productivity of the practice proportionately. So Dr. Plant’s group might be expected to have the productivity of 10.2 physician FTEs (4 NPPs X 0.6 = 2.2 “physician FTE equivalents,” added to the eight physician FTEs). (Note: While I think converting NPP FTEs into “physician equivalents” is useful in analyzing the effect of workloads on budgets, there are clearly many other very important issues when trying to quantify the contribution of NPPs to a practice.)

Judgment Rules

There are dozens of additional issues, such as the effect on productivity resulting from inefficient hospital systems (e.g., a clunky electronic health record, typed admit notes aren’t available for a few days compared with records available within two to four hours of dictation), activities such as attending Rapid Response Team activations, and differences in the social complexity of the patient population. None of these would show up in wRVU reports, so they are missing from the analysis I’ve described above.

I think it is impossible to control for all of the differences between practices that influence the definition of appropriate workload. This is the main reason SHM probably will never have a firm position on exactly what is the right or optimal number.

Although 15 patients a day is a reasonable starting point (I prefer to see fewer patients daily, but work more days/shifts annually), things get complicated in a hurry, and there will always be significant variation. TH

 

 

Dr. Nelson has been a practicing hospitalist since 1988 and is co-founder and past president of SHM. He is a principal in Nelson/Flores Associates, a national hospitalist practice management consulting firm. He also is faculty for SHM’s “Best Practices in Managing a Hospital Medicine Program” course. This column represents his views and is not intended to reflect an official position of SHM.

At sold-out HM09 in Chicago in May, I had the pleasure of moderating a panel discussion titled “Who Says 15 Patients a Day is the Right Number?” As you might guess, each panelist (including me) said, in effect, “No one says 15 patients a day is the right number.”

Despite being a very important issue to SHM, the society doesn’t have an official position on the “right” or optimal daily patient volume or workload for a hospitalist. SHM generates and disseminates a lot of information to help each practice make decisions about workload, including SHM’s 2007-2008 “Bi-annual Survey on the State of the Hospital Medicine Movement,” articles available at www.hospitalmedicine.org, and articles in The Hospitalist. But all practices, and individual hospitalists, will have to decide what level of patient volume enables safe care, a sustainable and satisfying workload, and reasonable economic performance.

Of course, billable encounters fail to perfectly describe our workloads, but until someone comes up with a better metric that is universally understood and applicable across all settings, billable encounters is the best metric we have.

Workload Metrics

A problem that makes any workload discussion difficult is that many terms are sometimes used to mean different things. For example, “daily census” is used when comparing workloads between practices, but “daily encounters” is nearly always a more informative metric. Remember, daily encounters for a practice will always be higher (though on rare occasion, the same) than daily census.

The only definition of encounters that can be reliably compared between practices is billable encounters. Confusion arises when one person is reporting billable encounters, and another person is counting as one encounter each time a hospitalist interacted with a patient (e.g., went into the patient’s room or made a chart entry) and reports a higher encounter volume despite having the same workload and patient volume. Of course, billable encounters fail to perfectly describe our workloads, but until someone comes up with a better metric that is universally understood and applicable across all settings, billable encounters is the best metric we have.

Both billable encounters and census can be tricky. We might be convinced that because she averages 17 billable encounters per day, Dr. Krause has a higher workload than Dr. Palmer, who averages 15. But it turns out that Dr. Palmer works 210 shifts annually, generating 3,150 annual encounters; Dr. Krause’s 181 annual shifts generate 3,077 encounters. So while Dr. Krause does indeed work harder on the average day, she has lower annual productivity. My experience is that by failing to compare workloads over long periods, such as a year, many attempts to compare workloads yield misleading conclusions.

Comparing encounter volume from one practice to the next fails to capture other ways workloads differ. Dr. Krause may be the principal caregiver for a number of ICU patients; Dr. Plant might turn such patients over to intensivists. For this reason, work relative value units (wRVUs), which attempt to capture the complexity of each encounter, usually are a more meaningful—though still imperfect—metric.

Apples vs. Apples

Any truly valid method of comparing workloads should sum the annual workload for the entire practice and divide by the total provider full-time equivalents (FTEs). Yet problems arise because night shifts usually are less productive than day shifts. Consider a practice that has a distinct night shift worked by a doctor who does no day-shift work the day before or after. There is a tendency to leave this night shift out of the analysis of average workload per FTE, which makes the practice appear more productive than it really is.

 

 

For example, the practice I am part of has dedicated nocturnists who don’t work day shifts. So when thinking about how hard we’re working, we tend to sum each “day” doctor’s wRVUs for the year and divide by the number of day doctors. Calculated this way, our day doctors appear to be more productive than SHM data might indicate, but when including our nocturnists’ production and FTEs in the analysis, the overall workload per FTE in the practice is similar to the data.

Productivity Per FTE

While I think productivity per FTE per year is the best metric to use when comparing a practice to external survey data or comparing one practice to another, it is confounded by two sticky problems: inconsistent definitions of what constitutes an FTE, and the lack of an agreed-upon method of accounting for the contribution of nonphysician providers.

The most common definitions of what constitutes an FTE are based on the number of hours or shifts worked. One practice might define an FTE as 2,000 hours of work annually; another might use 180 annual shifts. Unless each shift has a clearly defined duration, it will be very difficult to reach conclusions. Although each practice might make sound decisions about how they define an FTE, they’re ultimately making arbitrary choices that aren’t consistent from one practice to the next. Controlling for this issue is very difficult.

Even trickier is how to compare the contributions of physician assistants (PAs) and nurse practitioners (NPs) from one practice to the next. In the above example, Dr. Plant’s practice has eight physician FTEs and four NPPs, and Dr. Krause’s group has eight MDs and no NPPs. How much more productive should we expect Dr. Plant’s practice to be? (NPPs make many valuable contributions, in addition to increasing productivity, but these are outside the scope of this article.)

Though survey data offer some clues, there is no established standard for increased productivity expected of PAs and NPs. One approach I use is to compare an NPP’s total compensation (salary and benefits) with that of the average physician FTE. If the cost of each NPP is 60% of an MD, then one could say that each NPP represents 0.6 “physician FTE equivalents” and could be expected to increase the productivity of the practice proportionately. So Dr. Plant’s group might be expected to have the productivity of 10.2 physician FTEs (4 NPPs X 0.6 = 2.2 “physician FTE equivalents,” added to the eight physician FTEs). (Note: While I think converting NPP FTEs into “physician equivalents” is useful in analyzing the effect of workloads on budgets, there are clearly many other very important issues when trying to quantify the contribution of NPPs to a practice.)

Judgment Rules

There are dozens of additional issues, such as the effect on productivity resulting from inefficient hospital systems (e.g., a clunky electronic health record, typed admit notes aren’t available for a few days compared with records available within two to four hours of dictation), activities such as attending Rapid Response Team activations, and differences in the social complexity of the patient population. None of these would show up in wRVU reports, so they are missing from the analysis I’ve described above.

I think it is impossible to control for all of the differences between practices that influence the definition of appropriate workload. This is the main reason SHM probably will never have a firm position on exactly what is the right or optimal number.

Although 15 patients a day is a reasonable starting point (I prefer to see fewer patients daily, but work more days/shifts annually), things get complicated in a hurry, and there will always be significant variation. TH

 

 

Dr. Nelson has been a practicing hospitalist since 1988 and is co-founder and past president of SHM. He is a principal in Nelson/Flores Associates, a national hospitalist practice management consulting firm. He also is faculty for SHM’s “Best Practices in Managing a Hospital Medicine Program” course. This column represents his views and is not intended to reflect an official position of SHM.

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The Anvil of Indecision

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The Anvil of Indecision

Lying in bed, I’m jarred by what can only be an anvil dropping heavily upon my chest. Wakefulness reveals a more canine, cranium-like object. Staring deep into cataract-smudged eyes, I ponder the question that has occupied my mind for nearly two weeks: What would Hogan want?

My Dog Has Cancer

More accurately, he has a tumor—or, I guess, what appears to be a tumor on his chest X-ray. It was discovered, incidentally, on a liver ultrasound that was being done for abnormal liver function test results. That study revealed nothing wrong with his liver, but led to a follow-up radiograph showing a 4.9-cm, right-lower-lobe lung mass. Also uncovered in this process was a tangle of complex emotions, turmoil, and uncertainty surrounding my first personal foray into end-of-life decision-making.

Hogan, my now-presumed-cancer-ridden, 10-year-old Weimaraner, came into my life permanently when he was all of 8 weeks old. I first met him during a visit to the breeder when his litter was only three days old. Over the successive weeks, I visited him often, anxious for the day I’d be able to take my new companion home.

So, on the advent of his 10th birthday, we are asked to decide how many resources, how much physical distress, how much intervention we afford to an older, sleep-most-of-the-day arthritic dog.

I picked up Hogan on Fourth of July weekend during my chief year of residency—sort of a gift for completing my grueling training. He was the first dog I raised, trained, and cared for by myself. And while we had our share of eaten walls, destroyed comforters, and chewed bits of Jeep Cherokee, this was no “Marley & Me” relationship. We were more like roommates, best friends. We hiked, camped, and went everywhere together—either an idyllic boy-and-his-dog relationship or a sad, pitifully lonely, soul-in-need-of-a-girlfriend existence, depending on your point of view, I suppose.

In the end, the two viewpoints melded as Hogan eventually brought my wife and I together, a story that shall not be printed in these pages.

Through the years, Hogan bore witness to many personal and family milestones. My chief residency, my first grand rounds (his constant audience during my preparation brought him unparalleled expertise in canine zoonoses), my first house, our marriage, a horribly flailing attempt to recapture the magic of my first dog through a second Weim named Grady (definitely “Marley & Me” mixed with a healthy dose of “Dumb & Dumber”), and the birth of our first child.

It was during this time that Hogan began a long journey toward today. He became a little long in the tooth, droopy in the belly, and slow on the trail. His limitless energy and boundless passion for chasing tennis balls gave way to such leisurely pursuits as park pooping and command disobedience. His fluid, sinew-laced limbs became arthritic shells of their former selves, betraying the youthful grace that still echoed inside of him. I distinctly recall the first time Grady beat him to a tennis ball, a moment that clearly represented a passing of the baton—a crestfallen 6-year-old canine eclipsed by the 2-year-old whippersnapper. The youngster sprinted back, bursting with a mouthful of tennis ball and pride. The elder took a decidedly more tortuous and tortured route back—a carriage of nonchalance that failed in its attempt to convey the message that “chasing tennis balls is stupid.”

Hogan hiking the Rockies.

On the advice of our veterinarian, we stopped throwing Frisbees at Hogan at age 8, out of concern that an awkward jump might result in a paralytic shift in his progressively stenosing spine. While Hogan is otherwise healthy, his hips and forepaws are riddled with osteoarthritis, his eyes carry the cottony haze of cataracts, and his abdomen and skin are home to lumpy lipomas. So, on the advent of his 10th birthday, we are asked to decide how many resources, how much physical distress, how much intervention we afford to an older, sleep-most-of-the-day arthritic dog.

 

 

This scenario is complicated by the idiosyncrasies and mores of veterinary medicine. Unlike human medicine, which is replete with tomes of data steeped in decades of experience, our veterinarian counterparts often are left with gaping treatment holes and inadequately studied interventions. This is not a knock against the profession. In fact, I have had nothing short of fantastic experiences with the veterinary professionals with whom I’ve interacted. Rather, there just aren’t prospective, randomized, controlled trials to inform whether intervention will enhance Hogan’s quantity and quality of life.

Then there are the economic realities of the situation. As one who has rarely been ill and always been insured, I was staggered by the cost of medicine for the uninsured. Two-hundred-dollar antibiotics, $500 ultrasounds, $1,500 CT scans, and up to $10,000 operative and surgical ICU stays would have invoked, “you’re joking, right?” exclamations from me prior to this experience. Now they are just another variable that complicates this already emotionally complex discussion—the variable that makes you feel hollow inside for considering it, foolhardy for not.

Questions Abound

What price would I pay to have another few years with my best friend? What if it’s only a year, six months? Would the money be better spent funding my child’s 529 account? What if this is a benign process and intervention is for naught? What if this tumor is metastatic and intervention is futile? Should we spend the extra money on an upfront staging CT scan that has much lower sensitivity than those we routinely utilize?

If we intervene, should we attempt a costly, CT-guided biopsy to rule in malignant disease, or go straight to lobectomy? What if the surgery negatively alters his quality of life? What if he dies on the table? What do I know about the surgical outcomes of the two centers I’m considering? Should we attempt an open or laparoscopic approach to this tumor?

Can we achieve a cure? If we do, what does that mean for a dog in the twilight years of his life? Should we just let the disease progress to its natural endpoint?

What Would Hogan Want?

These are the questions that haunt me. As I stare into Hogan’s eyes, a portal to my companion’s soul, I am tormented by the cauldron of emotions, the indecision bred by incomplete information and the guilt that comes from knowing that Hogan unconditionally trusts that I will do what is right for him.

Will I? My eyes continue to ask Hogan what he would want until finally the answer becomes obvious.

Hogan wants his breakfast. TH

Dr. Glasheen is associate professor of medicine and director of the hospital medicine group and hospitalist training program at the University of Colorado at Denver.

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Lying in bed, I’m jarred by what can only be an anvil dropping heavily upon my chest. Wakefulness reveals a more canine, cranium-like object. Staring deep into cataract-smudged eyes, I ponder the question that has occupied my mind for nearly two weeks: What would Hogan want?

My Dog Has Cancer

More accurately, he has a tumor—or, I guess, what appears to be a tumor on his chest X-ray. It was discovered, incidentally, on a liver ultrasound that was being done for abnormal liver function test results. That study revealed nothing wrong with his liver, but led to a follow-up radiograph showing a 4.9-cm, right-lower-lobe lung mass. Also uncovered in this process was a tangle of complex emotions, turmoil, and uncertainty surrounding my first personal foray into end-of-life decision-making.

Hogan, my now-presumed-cancer-ridden, 10-year-old Weimaraner, came into my life permanently when he was all of 8 weeks old. I first met him during a visit to the breeder when his litter was only three days old. Over the successive weeks, I visited him often, anxious for the day I’d be able to take my new companion home.

So, on the advent of his 10th birthday, we are asked to decide how many resources, how much physical distress, how much intervention we afford to an older, sleep-most-of-the-day arthritic dog.

I picked up Hogan on Fourth of July weekend during my chief year of residency—sort of a gift for completing my grueling training. He was the first dog I raised, trained, and cared for by myself. And while we had our share of eaten walls, destroyed comforters, and chewed bits of Jeep Cherokee, this was no “Marley & Me” relationship. We were more like roommates, best friends. We hiked, camped, and went everywhere together—either an idyllic boy-and-his-dog relationship or a sad, pitifully lonely, soul-in-need-of-a-girlfriend existence, depending on your point of view, I suppose.

In the end, the two viewpoints melded as Hogan eventually brought my wife and I together, a story that shall not be printed in these pages.

Through the years, Hogan bore witness to many personal and family milestones. My chief residency, my first grand rounds (his constant audience during my preparation brought him unparalleled expertise in canine zoonoses), my first house, our marriage, a horribly flailing attempt to recapture the magic of my first dog through a second Weim named Grady (definitely “Marley & Me” mixed with a healthy dose of “Dumb & Dumber”), and the birth of our first child.

It was during this time that Hogan began a long journey toward today. He became a little long in the tooth, droopy in the belly, and slow on the trail. His limitless energy and boundless passion for chasing tennis balls gave way to such leisurely pursuits as park pooping and command disobedience. His fluid, sinew-laced limbs became arthritic shells of their former selves, betraying the youthful grace that still echoed inside of him. I distinctly recall the first time Grady beat him to a tennis ball, a moment that clearly represented a passing of the baton—a crestfallen 6-year-old canine eclipsed by the 2-year-old whippersnapper. The youngster sprinted back, bursting with a mouthful of tennis ball and pride. The elder took a decidedly more tortuous and tortured route back—a carriage of nonchalance that failed in its attempt to convey the message that “chasing tennis balls is stupid.”

Hogan hiking the Rockies.

On the advice of our veterinarian, we stopped throwing Frisbees at Hogan at age 8, out of concern that an awkward jump might result in a paralytic shift in his progressively stenosing spine. While Hogan is otherwise healthy, his hips and forepaws are riddled with osteoarthritis, his eyes carry the cottony haze of cataracts, and his abdomen and skin are home to lumpy lipomas. So, on the advent of his 10th birthday, we are asked to decide how many resources, how much physical distress, how much intervention we afford to an older, sleep-most-of-the-day arthritic dog.

 

 

This scenario is complicated by the idiosyncrasies and mores of veterinary medicine. Unlike human medicine, which is replete with tomes of data steeped in decades of experience, our veterinarian counterparts often are left with gaping treatment holes and inadequately studied interventions. This is not a knock against the profession. In fact, I have had nothing short of fantastic experiences with the veterinary professionals with whom I’ve interacted. Rather, there just aren’t prospective, randomized, controlled trials to inform whether intervention will enhance Hogan’s quantity and quality of life.

Then there are the economic realities of the situation. As one who has rarely been ill and always been insured, I was staggered by the cost of medicine for the uninsured. Two-hundred-dollar antibiotics, $500 ultrasounds, $1,500 CT scans, and up to $10,000 operative and surgical ICU stays would have invoked, “you’re joking, right?” exclamations from me prior to this experience. Now they are just another variable that complicates this already emotionally complex discussion—the variable that makes you feel hollow inside for considering it, foolhardy for not.

Questions Abound

What price would I pay to have another few years with my best friend? What if it’s only a year, six months? Would the money be better spent funding my child’s 529 account? What if this is a benign process and intervention is for naught? What if this tumor is metastatic and intervention is futile? Should we spend the extra money on an upfront staging CT scan that has much lower sensitivity than those we routinely utilize?

If we intervene, should we attempt a costly, CT-guided biopsy to rule in malignant disease, or go straight to lobectomy? What if the surgery negatively alters his quality of life? What if he dies on the table? What do I know about the surgical outcomes of the two centers I’m considering? Should we attempt an open or laparoscopic approach to this tumor?

Can we achieve a cure? If we do, what does that mean for a dog in the twilight years of his life? Should we just let the disease progress to its natural endpoint?

What Would Hogan Want?

These are the questions that haunt me. As I stare into Hogan’s eyes, a portal to my companion’s soul, I am tormented by the cauldron of emotions, the indecision bred by incomplete information and the guilt that comes from knowing that Hogan unconditionally trusts that I will do what is right for him.

Will I? My eyes continue to ask Hogan what he would want until finally the answer becomes obvious.

Hogan wants his breakfast. TH

Dr. Glasheen is associate professor of medicine and director of the hospital medicine group and hospitalist training program at the University of Colorado at Denver.

Lying in bed, I’m jarred by what can only be an anvil dropping heavily upon my chest. Wakefulness reveals a more canine, cranium-like object. Staring deep into cataract-smudged eyes, I ponder the question that has occupied my mind for nearly two weeks: What would Hogan want?

My Dog Has Cancer

More accurately, he has a tumor—or, I guess, what appears to be a tumor on his chest X-ray. It was discovered, incidentally, on a liver ultrasound that was being done for abnormal liver function test results. That study revealed nothing wrong with his liver, but led to a follow-up radiograph showing a 4.9-cm, right-lower-lobe lung mass. Also uncovered in this process was a tangle of complex emotions, turmoil, and uncertainty surrounding my first personal foray into end-of-life decision-making.

Hogan, my now-presumed-cancer-ridden, 10-year-old Weimaraner, came into my life permanently when he was all of 8 weeks old. I first met him during a visit to the breeder when his litter was only three days old. Over the successive weeks, I visited him often, anxious for the day I’d be able to take my new companion home.

So, on the advent of his 10th birthday, we are asked to decide how many resources, how much physical distress, how much intervention we afford to an older, sleep-most-of-the-day arthritic dog.

I picked up Hogan on Fourth of July weekend during my chief year of residency—sort of a gift for completing my grueling training. He was the first dog I raised, trained, and cared for by myself. And while we had our share of eaten walls, destroyed comforters, and chewed bits of Jeep Cherokee, this was no “Marley & Me” relationship. We were more like roommates, best friends. We hiked, camped, and went everywhere together—either an idyllic boy-and-his-dog relationship or a sad, pitifully lonely, soul-in-need-of-a-girlfriend existence, depending on your point of view, I suppose.

In the end, the two viewpoints melded as Hogan eventually brought my wife and I together, a story that shall not be printed in these pages.

Through the years, Hogan bore witness to many personal and family milestones. My chief residency, my first grand rounds (his constant audience during my preparation brought him unparalleled expertise in canine zoonoses), my first house, our marriage, a horribly flailing attempt to recapture the magic of my first dog through a second Weim named Grady (definitely “Marley & Me” mixed with a healthy dose of “Dumb & Dumber”), and the birth of our first child.

It was during this time that Hogan began a long journey toward today. He became a little long in the tooth, droopy in the belly, and slow on the trail. His limitless energy and boundless passion for chasing tennis balls gave way to such leisurely pursuits as park pooping and command disobedience. His fluid, sinew-laced limbs became arthritic shells of their former selves, betraying the youthful grace that still echoed inside of him. I distinctly recall the first time Grady beat him to a tennis ball, a moment that clearly represented a passing of the baton—a crestfallen 6-year-old canine eclipsed by the 2-year-old whippersnapper. The youngster sprinted back, bursting with a mouthful of tennis ball and pride. The elder took a decidedly more tortuous and tortured route back—a carriage of nonchalance that failed in its attempt to convey the message that “chasing tennis balls is stupid.”

Hogan hiking the Rockies.

On the advice of our veterinarian, we stopped throwing Frisbees at Hogan at age 8, out of concern that an awkward jump might result in a paralytic shift in his progressively stenosing spine. While Hogan is otherwise healthy, his hips and forepaws are riddled with osteoarthritis, his eyes carry the cottony haze of cataracts, and his abdomen and skin are home to lumpy lipomas. So, on the advent of his 10th birthday, we are asked to decide how many resources, how much physical distress, how much intervention we afford to an older, sleep-most-of-the-day arthritic dog.

 

 

This scenario is complicated by the idiosyncrasies and mores of veterinary medicine. Unlike human medicine, which is replete with tomes of data steeped in decades of experience, our veterinarian counterparts often are left with gaping treatment holes and inadequately studied interventions. This is not a knock against the profession. In fact, I have had nothing short of fantastic experiences with the veterinary professionals with whom I’ve interacted. Rather, there just aren’t prospective, randomized, controlled trials to inform whether intervention will enhance Hogan’s quantity and quality of life.

Then there are the economic realities of the situation. As one who has rarely been ill and always been insured, I was staggered by the cost of medicine for the uninsured. Two-hundred-dollar antibiotics, $500 ultrasounds, $1,500 CT scans, and up to $10,000 operative and surgical ICU stays would have invoked, “you’re joking, right?” exclamations from me prior to this experience. Now they are just another variable that complicates this already emotionally complex discussion—the variable that makes you feel hollow inside for considering it, foolhardy for not.

Questions Abound

What price would I pay to have another few years with my best friend? What if it’s only a year, six months? Would the money be better spent funding my child’s 529 account? What if this is a benign process and intervention is for naught? What if this tumor is metastatic and intervention is futile? Should we spend the extra money on an upfront staging CT scan that has much lower sensitivity than those we routinely utilize?

If we intervene, should we attempt a costly, CT-guided biopsy to rule in malignant disease, or go straight to lobectomy? What if the surgery negatively alters his quality of life? What if he dies on the table? What do I know about the surgical outcomes of the two centers I’m considering? Should we attempt an open or laparoscopic approach to this tumor?

Can we achieve a cure? If we do, what does that mean for a dog in the twilight years of his life? Should we just let the disease progress to its natural endpoint?

What Would Hogan Want?

These are the questions that haunt me. As I stare into Hogan’s eyes, a portal to my companion’s soul, I am tormented by the cauldron of emotions, the indecision bred by incomplete information and the guilt that comes from knowing that Hogan unconditionally trusts that I will do what is right for him.

Will I? My eyes continue to ask Hogan what he would want until finally the answer becomes obvious.

Hogan wants his breakfast. TH

Dr. Glasheen is associate professor of medicine and director of the hospital medicine group and hospitalist training program at the University of Colorado at Denver.

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Life under the Big Tent

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SHM prides itself on being a “big tent” organization—inclusive of care providers with different training backgrounds, from varied clinical settings, and representing a multitude of hospital roles. SHM’s diversity expands beyond care providers to include other key stakeholders, such as administrators of hospitalist programs or departments. The diversity was highlighted in the society’s 2007-2008 “Bi-annual Survey on the State of the Hospital Medicine Movement,” which shows that 40% of our members are hospital-employed, 20% are from academic settings, about 15% work in large multistate management companies, and the remaining 25% are equally split between multispecialty practices and local hospitalist groups. The diversity extends to internists, pediatricians, family practitioners, nurse practitioners, physician assistants, specialists—the list goes on.

All of us at SHM appreciate that diversity and routinely try to nurture it. Our board of directors includes physicians from all the aforementioned practice settings and includes dedicated seats for such key constituencies as pediatrics. We have more than 25 committees and task-force groups representing all the key factions of our membership. These groups address issues of relevance to every type of hospitalist and hospitalist group. Our annual meeting has evolved to meet the needs of this diverse membership by addressing an enormous volume of topics and incorporating a variety of tracks that cater to general hospitalists, quality experts, academics, and pediatricians.

One notable area in which we lack diversity: age. We are a young specialty; the average hospitalist is 40 years old.

SHM’s organizational diversity creates challenges; new issues surface every year. One key issue is the balance between academic hospitalists and community hospitalists. Academic hospitalists have wanted SHM to more aggressively support their interests. Community hospitalists want SHM to advocate for their interests, as well as develop programs and projects to meet their needs.

With my election as president and the recent election of another academic hospitalist to serve as SHM president in 2010-2011, there might be some concern that community hospitalists could get lost in an academic agenda. Interestingly, academic hospitalists might have raised similar concerns several years ago following the election of a second consecutive community hospitalist as society president. We have been fortunate to have leaders who can see the whole HM picture, regardless of their professional backgrounds.

We have been fortunate to have leaders who can see the whole HM picture, regardless of their professional backgrounds.

One Tent, Many Spikes in the Ground

The issues are more complex than simply the differences between academic and community hospitalists. Appropriately, each of our members wants their groups’ issues discussed and addressed. Although workforce might be an issue for private-practice hospitalists, academic hospitalists share these same issues—just in a different environment. Pediatricians see SHM develop core competencies for adult medicine, then want their own pediatric core competencies; SHM needs to look for a way to make this happen. Nurse practitioners (NPs), physician assistants (PAs), and administrators have looked to SHM to represent not just physicians in HM, but also their interests.

As a result, SHM has developed committees and approaches to engage the professional societies representing PAs and NPs, along with the Medical Group Management Association, to design specific projects and programs. At any point in time, there might be a group of members who see a need for SHM to pay attention to “their” issue or perceive that a current approach, while relevant to one group, falls short of the needs of another. As our diversity grows, the frequency of these situations will increase.

So, is this worrisome? Quite the contrary. I believe it is healthy.

 

 

Having an established organization with members of differing opinions and backgrounds helps challenge our assumptions. It refines our approach to complex problems, highlights issues or concerns we did not anticipate, and, most importantly, guards against “groupthink”—the tendency to agree with one another all the time. SHM’s board of directors is committed to this type of inclusive leadership.

We do need to be cautious and think quite a bit about this issue in the coming years. The big tent is filling up quickly. It’s becoming more diverse by the week. The concern is that in trying to work at a level that keeps all our constituents happy, we might please no one. If all our activities have to be justified as being relevant to every distinct group that makes up SHM, then we might dilute our effectiveness.

Alternatively, we do not currently have the bandwidth as an organization to initiate in-depth projects in areas relevant to all our members. So far, our approach has been to focus on areas core to every hospitalist: quality and safety, process improvement, leadership, practice management, care transitions, networking, and education.

As unique problems or issues arise that are relevant to only a subset of members, we will weigh the importance. In many cases, we have created task-force groups to clarify and tackle the problem. We provide the support, but the members of the group create the solution. It has worked well so far.

One Voice, One Goal

But can we stick to this strategy as the diversity of membership expands and the number of relevant issues grows? I don’t know. What I do know is that there is strength in numbers, and even though we all have different issues we deem more important, there are times when it helps to come together and speak as one very big, very loud voice.

Older specialties like endocrinology, allergy, and others have split into a variety of organizations and potentially diluted their message. SHM needs to look for creative ways to be relevant to many constituencies within the specialty. In the meantime, we must pay close attention to the big-tent issues. An academic hospitalist in leadership needs to listen to the voices of hospitalists in the community, work to understand them, and support efforts to address problems relevant to them.

In the past, SHM leadership from the community hospitalist setting has worked to help address and solve issues relevant to academic hospitalists. We need to understand and respect the diversity within SHM’s tent, and we need to work to keep us all together. I firmly believe that is the way forward, and I assure you that is the goal of SHM’s leadership.

As President Kennedy said, “If we cannot end now our differences, at least we can help make the world safe for diversity.” I pledge to keep SHM your organization, regardless of how you were trained or where you practice HM. I can’t hope to know all of your important issues, but I can commit to stand ready to hear your concerns and do what SHM has always done—give your request a thoughtful response and all of our energy.

SHM is your organization. Let me know the direction you think SHM should go. Send me an e-mail at [email protected]. TH

Dr. Flanders is president of SHM.

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SHM prides itself on being a “big tent” organization—inclusive of care providers with different training backgrounds, from varied clinical settings, and representing a multitude of hospital roles. SHM’s diversity expands beyond care providers to include other key stakeholders, such as administrators of hospitalist programs or departments. The diversity was highlighted in the society’s 2007-2008 “Bi-annual Survey on the State of the Hospital Medicine Movement,” which shows that 40% of our members are hospital-employed, 20% are from academic settings, about 15% work in large multistate management companies, and the remaining 25% are equally split between multispecialty practices and local hospitalist groups. The diversity extends to internists, pediatricians, family practitioners, nurse practitioners, physician assistants, specialists—the list goes on.

All of us at SHM appreciate that diversity and routinely try to nurture it. Our board of directors includes physicians from all the aforementioned practice settings and includes dedicated seats for such key constituencies as pediatrics. We have more than 25 committees and task-force groups representing all the key factions of our membership. These groups address issues of relevance to every type of hospitalist and hospitalist group. Our annual meeting has evolved to meet the needs of this diverse membership by addressing an enormous volume of topics and incorporating a variety of tracks that cater to general hospitalists, quality experts, academics, and pediatricians.

One notable area in which we lack diversity: age. We are a young specialty; the average hospitalist is 40 years old.

SHM’s organizational diversity creates challenges; new issues surface every year. One key issue is the balance between academic hospitalists and community hospitalists. Academic hospitalists have wanted SHM to more aggressively support their interests. Community hospitalists want SHM to advocate for their interests, as well as develop programs and projects to meet their needs.

With my election as president and the recent election of another academic hospitalist to serve as SHM president in 2010-2011, there might be some concern that community hospitalists could get lost in an academic agenda. Interestingly, academic hospitalists might have raised similar concerns several years ago following the election of a second consecutive community hospitalist as society president. We have been fortunate to have leaders who can see the whole HM picture, regardless of their professional backgrounds.

We have been fortunate to have leaders who can see the whole HM picture, regardless of their professional backgrounds.

One Tent, Many Spikes in the Ground

The issues are more complex than simply the differences between academic and community hospitalists. Appropriately, each of our members wants their groups’ issues discussed and addressed. Although workforce might be an issue for private-practice hospitalists, academic hospitalists share these same issues—just in a different environment. Pediatricians see SHM develop core competencies for adult medicine, then want their own pediatric core competencies; SHM needs to look for a way to make this happen. Nurse practitioners (NPs), physician assistants (PAs), and administrators have looked to SHM to represent not just physicians in HM, but also their interests.

As a result, SHM has developed committees and approaches to engage the professional societies representing PAs and NPs, along with the Medical Group Management Association, to design specific projects and programs. At any point in time, there might be a group of members who see a need for SHM to pay attention to “their” issue or perceive that a current approach, while relevant to one group, falls short of the needs of another. As our diversity grows, the frequency of these situations will increase.

So, is this worrisome? Quite the contrary. I believe it is healthy.

 

 

Having an established organization with members of differing opinions and backgrounds helps challenge our assumptions. It refines our approach to complex problems, highlights issues or concerns we did not anticipate, and, most importantly, guards against “groupthink”—the tendency to agree with one another all the time. SHM’s board of directors is committed to this type of inclusive leadership.

We do need to be cautious and think quite a bit about this issue in the coming years. The big tent is filling up quickly. It’s becoming more diverse by the week. The concern is that in trying to work at a level that keeps all our constituents happy, we might please no one. If all our activities have to be justified as being relevant to every distinct group that makes up SHM, then we might dilute our effectiveness.

Alternatively, we do not currently have the bandwidth as an organization to initiate in-depth projects in areas relevant to all our members. So far, our approach has been to focus on areas core to every hospitalist: quality and safety, process improvement, leadership, practice management, care transitions, networking, and education.

As unique problems or issues arise that are relevant to only a subset of members, we will weigh the importance. In many cases, we have created task-force groups to clarify and tackle the problem. We provide the support, but the members of the group create the solution. It has worked well so far.

One Voice, One Goal

But can we stick to this strategy as the diversity of membership expands and the number of relevant issues grows? I don’t know. What I do know is that there is strength in numbers, and even though we all have different issues we deem more important, there are times when it helps to come together and speak as one very big, very loud voice.

Older specialties like endocrinology, allergy, and others have split into a variety of organizations and potentially diluted their message. SHM needs to look for creative ways to be relevant to many constituencies within the specialty. In the meantime, we must pay close attention to the big-tent issues. An academic hospitalist in leadership needs to listen to the voices of hospitalists in the community, work to understand them, and support efforts to address problems relevant to them.

In the past, SHM leadership from the community hospitalist setting has worked to help address and solve issues relevant to academic hospitalists. We need to understand and respect the diversity within SHM’s tent, and we need to work to keep us all together. I firmly believe that is the way forward, and I assure you that is the goal of SHM’s leadership.

As President Kennedy said, “If we cannot end now our differences, at least we can help make the world safe for diversity.” I pledge to keep SHM your organization, regardless of how you were trained or where you practice HM. I can’t hope to know all of your important issues, but I can commit to stand ready to hear your concerns and do what SHM has always done—give your request a thoughtful response and all of our energy.

SHM is your organization. Let me know the direction you think SHM should go. Send me an e-mail at [email protected]. TH

Dr. Flanders is president of SHM.

SHM prides itself on being a “big tent” organization—inclusive of care providers with different training backgrounds, from varied clinical settings, and representing a multitude of hospital roles. SHM’s diversity expands beyond care providers to include other key stakeholders, such as administrators of hospitalist programs or departments. The diversity was highlighted in the society’s 2007-2008 “Bi-annual Survey on the State of the Hospital Medicine Movement,” which shows that 40% of our members are hospital-employed, 20% are from academic settings, about 15% work in large multistate management companies, and the remaining 25% are equally split between multispecialty practices and local hospitalist groups. The diversity extends to internists, pediatricians, family practitioners, nurse practitioners, physician assistants, specialists—the list goes on.

All of us at SHM appreciate that diversity and routinely try to nurture it. Our board of directors includes physicians from all the aforementioned practice settings and includes dedicated seats for such key constituencies as pediatrics. We have more than 25 committees and task-force groups representing all the key factions of our membership. These groups address issues of relevance to every type of hospitalist and hospitalist group. Our annual meeting has evolved to meet the needs of this diverse membership by addressing an enormous volume of topics and incorporating a variety of tracks that cater to general hospitalists, quality experts, academics, and pediatricians.

One notable area in which we lack diversity: age. We are a young specialty; the average hospitalist is 40 years old.

SHM’s organizational diversity creates challenges; new issues surface every year. One key issue is the balance between academic hospitalists and community hospitalists. Academic hospitalists have wanted SHM to more aggressively support their interests. Community hospitalists want SHM to advocate for their interests, as well as develop programs and projects to meet their needs.

With my election as president and the recent election of another academic hospitalist to serve as SHM president in 2010-2011, there might be some concern that community hospitalists could get lost in an academic agenda. Interestingly, academic hospitalists might have raised similar concerns several years ago following the election of a second consecutive community hospitalist as society president. We have been fortunate to have leaders who can see the whole HM picture, regardless of their professional backgrounds.

We have been fortunate to have leaders who can see the whole HM picture, regardless of their professional backgrounds.

One Tent, Many Spikes in the Ground

The issues are more complex than simply the differences between academic and community hospitalists. Appropriately, each of our members wants their groups’ issues discussed and addressed. Although workforce might be an issue for private-practice hospitalists, academic hospitalists share these same issues—just in a different environment. Pediatricians see SHM develop core competencies for adult medicine, then want their own pediatric core competencies; SHM needs to look for a way to make this happen. Nurse practitioners (NPs), physician assistants (PAs), and administrators have looked to SHM to represent not just physicians in HM, but also their interests.

As a result, SHM has developed committees and approaches to engage the professional societies representing PAs and NPs, along with the Medical Group Management Association, to design specific projects and programs. At any point in time, there might be a group of members who see a need for SHM to pay attention to “their” issue or perceive that a current approach, while relevant to one group, falls short of the needs of another. As our diversity grows, the frequency of these situations will increase.

So, is this worrisome? Quite the contrary. I believe it is healthy.

 

 

Having an established organization with members of differing opinions and backgrounds helps challenge our assumptions. It refines our approach to complex problems, highlights issues or concerns we did not anticipate, and, most importantly, guards against “groupthink”—the tendency to agree with one another all the time. SHM’s board of directors is committed to this type of inclusive leadership.

We do need to be cautious and think quite a bit about this issue in the coming years. The big tent is filling up quickly. It’s becoming more diverse by the week. The concern is that in trying to work at a level that keeps all our constituents happy, we might please no one. If all our activities have to be justified as being relevant to every distinct group that makes up SHM, then we might dilute our effectiveness.

Alternatively, we do not currently have the bandwidth as an organization to initiate in-depth projects in areas relevant to all our members. So far, our approach has been to focus on areas core to every hospitalist: quality and safety, process improvement, leadership, practice management, care transitions, networking, and education.

As unique problems or issues arise that are relevant to only a subset of members, we will weigh the importance. In many cases, we have created task-force groups to clarify and tackle the problem. We provide the support, but the members of the group create the solution. It has worked well so far.

One Voice, One Goal

But can we stick to this strategy as the diversity of membership expands and the number of relevant issues grows? I don’t know. What I do know is that there is strength in numbers, and even though we all have different issues we deem more important, there are times when it helps to come together and speak as one very big, very loud voice.

Older specialties like endocrinology, allergy, and others have split into a variety of organizations and potentially diluted their message. SHM needs to look for creative ways to be relevant to many constituencies within the specialty. In the meantime, we must pay close attention to the big-tent issues. An academic hospitalist in leadership needs to listen to the voices of hospitalists in the community, work to understand them, and support efforts to address problems relevant to them.

In the past, SHM leadership from the community hospitalist setting has worked to help address and solve issues relevant to academic hospitalists. We need to understand and respect the diversity within SHM’s tent, and we need to work to keep us all together. I firmly believe that is the way forward, and I assure you that is the goal of SHM’s leadership.

As President Kennedy said, “If we cannot end now our differences, at least we can help make the world safe for diversity.” I pledge to keep SHM your organization, regardless of how you were trained or where you practice HM. I can’t hope to know all of your important issues, but I can commit to stand ready to hear your concerns and do what SHM has always done—give your request a thoughtful response and all of our energy.

SHM is your organization. Let me know the direction you think SHM should go. Send me an e-mail at [email protected]. TH

Dr. Flanders is president of SHM.

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