Original Research

A special concern since the institution of hospital readmission penalties¹ is the transitions in care of a patient from one care setting to another, often at hospital discharge. Burke et al.² proposed a framework for an ideal transition in care (ITC) to study and improve transitions from the hospital to home. The features in the ITC were identified based upon their inclusion in the interventions that improved discharge outcomes.^3-5 Inspired by the ITC and other patient risk tools,⁶ we identified 10 domains of transitional care needs ([TCN] specified below), which we define as patient-centered risk factors that should be addressed to foster a safe and effective transition in care.⁷

One particularly important risk factor in patient self-management at transition points is health literacy, a patient’s ability to obtain, understand, and use basic health information and services. Low health literacy affects approximately 26% to 36% of adults in the United States.^8,9 Health literacy is associated with many factors that may affect successful navigation of care transitions, including doctor-patient communication,^10,11 understanding of the medication regimen,¹² and self-management.^13-15 Research has also demonstrated an association between low health literacy and poor outcomes after hospital discharge, including medication errors,¹⁶ 30-day hospital readmission,¹⁷ and mortality.¹⁸ Transitional care initiatives have begun to incorporate health literacy into patient risk assessments⁶ and provide specific attention to low health literacy in interventions to reduce adverse drug events and readmission.^4,19 Training programs for medical students and nurses advise teaching skills in health literacy as part of fostering effective transitions in care.^20,21

Although low health literacy is generally recognized as a barrier to patient education and self-management, little is known about whether patients with low health literacy are more likely to have other risk factors that could further increase their risk for poor transitions in care. A better understanding of associated risks would inform and improve patient care. We hypothesized that TCNs are more common among patients with low health literacy, as compared with those with adequate health literacy. We also aimed to describe the relationship between low health literacy and specific TCNs in order to guide clinical care and future interventions.

Setting

The present study is a cross-sectional analysis of data from a quality improvement (QI) intervention that was performed at Vanderbilt University Medical Center, a tertiary care facility in Nashville, Tennessee. The QI intervention, My Health Team (MHT), was funded by the Centers for Medicare and Medicaid Services Innovation Award program. The overall MHT program included outpatient care coordination for chronic disease management as well as a transitional care program that was designed to reduce hospital readmission. The latter included an inpatient needs assessment (which provided data for the present analysis), inpatient intervention, and postdischarge phone follow-up. The MHT initiative was reviewed by the institutional review board (IRB), which deemed it a QI program and granted a waiver of informed consent. The present secondary data analysis was reviewed and approved by the IRB.

Sample

Patients were identified for inclusion in the MHT transitions of care program if the presenting problem for hospital admission was pneumonia, chronic obstructive pulmonary disease (COPD) exacerbation, or decompensated heart failure, as determined by the review of clinical documentation by nurse transition care coordinators (TCCs). Adults over the age of 18 years were eligible, though priority was given to patients aged 65 years or older. This study includes the first inpatient encounter between June 2013 and December 31, 2014, for patients having a completed needs assessment and documentation of health literacy data in the medical record.

Data Collection

TCN assessment was developed from published patient risk tools and the ITC framework.^2,6,22 The assessment has 10 domains composed of 49 individual items as follows: (1) caregiver support (caregiver support not sufficient for patient needs), (2) transportation (relies on public or others for transportation and misses medical care because of transportation), (3) health care utilization (no primary care physician, unplanned hospitalization in the last year, emergency department [ED] visit in the last 6 months, or home health services in the last 60 days), (4) high-risk medical comorbidities (malnutrition or body mass index <18.5, renal failure, chronic pain, diabetes, heart failure, COPD, or stroke), (5) medication management provider or caregiver concern (cannot provide medication list, >10 preadmission medications, high-risk medications [eg, insulin, warfarin], poor medication understanding, or adherence issue identified), (6) medical devices (vascular access, urinary catheter, wounds, or home supplemental oxygen), (7) functional status (weakness of extremities, limited extremity range of motion, difficulty with mobility, falls at home, or activities of daily living challenges), (8) mental health comorbidities (over the past month has felt down, depressed, or hopeless or over the past month has felt little interest or pleasure in doing things, high-risk alcohol use, or high-risk substance use), (9) communication (limited English proficiency or at risk for limited health literacy), and (10) financial resources (no health insurance, skips or rations medicines because of cost, misses medical care because of cost, or misses medical care because of job).

The 49 items of the TCN assessment were documented as being present or absent by nurse TCCs at the time patients were enrolled in the transitional care program, based on patient and family interview and chart review, and the items were later extracted for analysis. Patients were determined to have a domain-level need if they reported a need on any individual item within that domain, resulting in a binary score (any need present, absent) for each of the 10 TCN domains.

Health literacy was assessed by using the Brief Health Literacy Screen (BHLS), which is administered routinely by nurses at hospital intake and documented in the medical record, with completion rates of approximately 90%.²³ The BHLS is a 3-question subjective health literacy assessment (scoring range 3-15) that has been validated against longer objective measures²⁴ and shown to predict disease control and mortality.^18,25 To improve the stability of scores (for patients who completed the BHLS more than once because of repeat hospitalizations) and to reduce missing values, we calculated the patient’s mean BHLS score for assessments obtained between January 1, 2013, and December 31, 2014. Patients were then categorized as having inadequate health literacy (BHLS ≤ 9) or adequate health literacy (BHLS > 9).^18,25 Demographic information was extracted from patient records and included age, sex (male/female), marital status (married/without a partner), race (white/nonwhite), and years of education. Income level and primary language were not available for analysis.

Statistical Analysis

Patient characteristics and TCNs were summarized by using the frequency and percentages for categorical variables and the mean and standard deviation (SD) for continuous variables. We compared patient characteristics (age, sex, marital status, race, and education) between health literacy groups (inadequate vs adequate) by using χ² or analysis of variance as appropriate. We assessed Pearson correlations among the 10 TCN domains, and we examined differences in reported needs for each of 10 TCN domains by the level of health literacy by using the χ² test. Because the TCN domain of communication included low health literacy as one of its items, we excluded this domain from subsequent analyses. We then compared differences in the number of TCNs documented (scoring range 0-9) by using an independent samples Student t test.

Multivariate logistic regression models were then constructed to examine the independent association of inadequate health literacy with 8 TCN domains while controlling for age, sex, marital status, race, and education. Patients with incomplete demographic data were excluded from these models. Additionally, these analyses excluded 2 TCN domains: the communication domain for reasons noted above and the high-risk medical comorbidity domain because it ended up being positive in 98.4% of patients. Statistical significance was set at an alpha of 0.05. All analyses were performed by using SPSS Statistics for Mac, version 23.0 (IBM Corp., Armonk, New York)

A structured patient risk factor assessment derived from literature was used to record TCNs in preparation for hospital discharge. On average, patients had needs in about half of the TCN domains (4.6 of 9). The most common areas identified were related to the presence of high-risk comorbidities (98.4%), frequent or prior healthcare utilization (76.6%), medication management (76.3%), functional status (54.9%), and transportation (48.7%). Many of the TCNs were significantly correlated with one another. The prevalence of these needs highlights the importance of using a structured assessment to identify patient concerns so that they may be addressed through discharge planning and follow-up. In addition, using a standardized TCN instrument based on a framework for ITC promotes further research in understanding patient needs and in developing personalized interventions to address them.

As hypothesized, we found that TCNs were more common in patients with inadequate health literacy. After adjustment for demographic factors, inadequate health literacy was significantly associated with transportation barriers and inadequate caregiver support. Analyses also suggested a relationship with needs related to medical devices, functional status, and mental health comorbidities. A review of the literature substantiates a link between inadequate health literacy and these needs and also suggests solutions to address these barriers.

The association with inadequate caregiver support is concerning because there is often a high degree of reliance on caregivers at transitions in care.^3-5 Caregivers are routinely called upon to provide assistance with activities that may be difficult for patients with low health literacy, including medication adherence, provider communication, and self-care activities.^26,27 Our finding that patients with inadequate health literacy are more likely to have inadequate caregiver support indicates additional vulnerability. This may be because of the absence of a caregiver, or in many cases, the presence of a caregiver who is underprepared to assist with care. Prior research has shown that when caregivers are present, up to 33% have low health literacy, even when they are paid nonfamilial caregivers.^26,28 Other studies have noted the inadequacy of information and patient training for caregivers.^29,30 Transitional care programs to improve caregiver understanding have been developed³¹ and have been demonstrated to lower rehospitalization and ED visits.³²

Patients with inadequate health literacy were also more likely to have transportation barriers. Lack of transportation has been recorded as a factor in early hospital readmission in patients with chronic disease,³³ and it has been shown to have a negative effect on a variety of health outcomes.³⁴ A likely link between readmission and lack of transportation is poor follow-up care. Wheeler et al.³⁵ found that 59% of patients expected difficulty keeping postdischarge appointments because of transportation needs. Instead of expecting patients to navigate their own transportation, the Agency for Healthcare Research and Quality recommends identifying community resources for patients with low health literacy.³⁶

In this sample, inadequate health literacy also had near significant associations with TCNs in the use of medical devices, lower functional status, and mental health comorbidities. The use of a medical device, such as home oxygen, is a risk factor for readmission,³⁷ and early reports suggest that interventions, including education related to home oxygen use, can dramatically reduce these readmissions.³⁸ Lower functional capacity and faster functional decline are associated with inadequate health literacy,³⁹ which may have to do with the inability to appropriately utilize health resources.⁴⁰ If so, structured discharge planning could alleviate the known connection between functional impairment and hospital readmissions.⁴¹ A relationship between low health literacy and depression has been demonstrated repeatedly,⁴² with worsened symptoms in those with addiction.⁴³ As has been shown in other domains where health literacy is a factor, literacy-focused interventions provide greater benefits to these depressed patients.⁴⁴

The TCN assessment worked well overall, but certain domains proved less valuable and could be removed in the future. First, it was not useful to separately identify communication barriers, because doing so did not add to information beyond the measurement of health literacy. Second, high-risk comorbidities were ubiquitous within the sample and therefore unhelpful for group comparisons. In hindsight, this is unsurprising because the sample was comprised primarily of elderly patients admitted to medical services. Still, in a younger population or a surgical setting, identifying patients with high-risk medical comorbidities may be more useful.

We acknowledge several limitations of this study. First, the study was performed at a single center, and the TCN assessments were conducted by a small number of registered nurses who received training. Therefore, the results may not generalize to the profile of patient needs at other settings, and the instrument may perform differently when scaled across an organization. Second, the needs assessment was developed for this QI initiative and did not undergo formal validation, although it was developed from published frameworks and similar assessments. Third, for the measure of health literacy, we relied on data collected by nurses as part of their normal workflow. As is often the case with data collected during routine care, the scores are imperfect,⁴⁵ but they have proven to be a valuable and valid indicator of health literacy in our previous research.^18,24,25,46 Fourth, we chose to declare a domain as positive if any item in that domain was positive and to perform a domain-level analysis (for greater clarity). We did not take into account the variable number of items within each domain or attempt to grade their severity, as this would be a subjective exercise and impractical in the discharge planning process. Finally, we were unable to address associations among socioeconomic status,⁴⁷ primary language,⁴⁸ and health literacy, because relevant data were not available for this analysis.

In this sample of hospitalized patients who were administered a structured needs assessment, patients commonly had needs that placed them at a higher risk of adverse outcomes, such as hospital readmission. Patients with low health literacy had more TCNs that extended beyond the areas that we normally associate with low health literacy, namely patient education and self-management. Healthcare professionals should be aware of the greater likelihood of transportation barriers and inadequate caregiver support among patients with low health literacy. Screening for health literacy and TCN at admission or as part of the discharge planning process will elevate such risks, better positioning clinicians and hospitals to address them as a part of the efforts to ensure a quality transition of care.

Disclosure 

This work was funded by the Centers for Medicare and Medicaid Services (1C1CMS330979) and in part by the National Center for Advancing Translational Sciences (2 UL1 TR000445-06). The content is solely the responsibility of the authors and does not necessarily represent official views of the funding agencies, which did not participate in the planning, collection, analysis, or interpretation of data or in the decision to submit for publication.

Dr. Dittus reports personal fees as a board member of the Robert Wood Johnson Foundation Medical Faculty Scholars Program National Advisory Committee; consultancy fees from the University of Virginia, Indiana University, University of Michigan, Northwestern University, Montana State University, and Purdue University; has grants/grants pending from NIH (research grants), PCORI (research grant), CME (innovation award), VA (training grant); payment for lectures including service on speakers bureaus from Corporate Parity (conference organizer) for the Global Hospital Management & Innovation Summit; and other from Medical Decision Making, Inc. (passive owner); all outside the submitted work. Dr. Kripalani has grants from NIH (research grant), PCORI (research grant), and CMS (QI grant); outside the submitted work. All other authors have nothing to disclose.

A special concern since the institution of hospital readmission penalties¹ is the transitions in care of a patient from one care setting to another, often at hospital discharge. Burke et al.² proposed a framework for an ideal transition in care (ITC) to study and improve transitions from the hospital to home. The features in the ITC were identified based upon their inclusion in the interventions that improved discharge outcomes.^3-5 Inspired by the ITC and other patient risk tools,⁶ we identified 10 domains of transitional care needs ([TCN] specified below), which we define as patient-centered risk factors that should be addressed to foster a safe and effective transition in care.⁷

One particularly important risk factor in patient self-management at transition points is health literacy, a patient’s ability to obtain, understand, and use basic health information and services. Low health literacy affects approximately 26% to 36% of adults in the United States.^8,9 Health literacy is associated with many factors that may affect successful navigation of care transitions, including doctor-patient communication,^10,11 understanding of the medication regimen,¹² and self-management.^13-15 Research has also demonstrated an association between low health literacy and poor outcomes after hospital discharge, including medication errors,¹⁶ 30-day hospital readmission,¹⁷ and mortality.¹⁸ Transitional care initiatives have begun to incorporate health literacy into patient risk assessments⁶ and provide specific attention to low health literacy in interventions to reduce adverse drug events and readmission.^4,19 Training programs for medical students and nurses advise teaching skills in health literacy as part of fostering effective transitions in care.^20,21

Although low health literacy is generally recognized as a barrier to patient education and self-management, little is known about whether patients with low health literacy are more likely to have other risk factors that could further increase their risk for poor transitions in care. A better understanding of associated risks would inform and improve patient care. We hypothesized that TCNs are more common among patients with low health literacy, as compared with those with adequate health literacy. We also aimed to describe the relationship between low health literacy and specific TCNs in order to guide clinical care and future interventions.

Setting

The present study is a cross-sectional analysis of data from a quality improvement (QI) intervention that was performed at Vanderbilt University Medical Center, a tertiary care facility in Nashville, Tennessee. The QI intervention, My Health Team (MHT), was funded by the Centers for Medicare and Medicaid Services Innovation Award program. The overall MHT program included outpatient care coordination for chronic disease management as well as a transitional care program that was designed to reduce hospital readmission. The latter included an inpatient needs assessment (which provided data for the present analysis), inpatient intervention, and postdischarge phone follow-up. The MHT initiative was reviewed by the institutional review board (IRB), which deemed it a QI program and granted a waiver of informed consent. The present secondary data analysis was reviewed and approved by the IRB.

Sample

Patients were identified for inclusion in the MHT transitions of care program if the presenting problem for hospital admission was pneumonia, chronic obstructive pulmonary disease (COPD) exacerbation, or decompensated heart failure, as determined by the review of clinical documentation by nurse transition care coordinators (TCCs). Adults over the age of 18 years were eligible, though priority was given to patients aged 65 years or older. This study includes the first inpatient encounter between June 2013 and December 31, 2014, for patients having a completed needs assessment and documentation of health literacy data in the medical record.

Data Collection

TCN assessment was developed from published patient risk tools and the ITC framework.^2,6,22 The assessment has 10 domains composed of 49 individual items as follows: (1) caregiver support (caregiver support not sufficient for patient needs), (2) transportation (relies on public or others for transportation and misses medical care because of transportation), (3) health care utilization (no primary care physician, unplanned hospitalization in the last year, emergency department [ED] visit in the last 6 months, or home health services in the last 60 days), (4) high-risk medical comorbidities (malnutrition or body mass index <18.5, renal failure, chronic pain, diabetes, heart failure, COPD, or stroke), (5) medication management provider or caregiver concern (cannot provide medication list, >10 preadmission medications, high-risk medications [eg, insulin, warfarin], poor medication understanding, or adherence issue identified), (6) medical devices (vascular access, urinary catheter, wounds, or home supplemental oxygen), (7) functional status (weakness of extremities, limited extremity range of motion, difficulty with mobility, falls at home, or activities of daily living challenges), (8) mental health comorbidities (over the past month has felt down, depressed, or hopeless or over the past month has felt little interest or pleasure in doing things, high-risk alcohol use, or high-risk substance use), (9) communication (limited English proficiency or at risk for limited health literacy), and (10) financial resources (no health insurance, skips or rations medicines because of cost, misses medical care because of cost, or misses medical care because of job).

The 49 items of the TCN assessment were documented as being present or absent by nurse TCCs at the time patients were enrolled in the transitional care program, based on patient and family interview and chart review, and the items were later extracted for analysis. Patients were determined to have a domain-level need if they reported a need on any individual item within that domain, resulting in a binary score (any need present, absent) for each of the 10 TCN domains.

Health literacy was assessed by using the Brief Health Literacy Screen (BHLS), which is administered routinely by nurses at hospital intake and documented in the medical record, with completion rates of approximately 90%.²³ The BHLS is a 3-question subjective health literacy assessment (scoring range 3-15) that has been validated against longer objective measures²⁴ and shown to predict disease control and mortality.^18,25 To improve the stability of scores (for patients who completed the BHLS more than once because of repeat hospitalizations) and to reduce missing values, we calculated the patient’s mean BHLS score for assessments obtained between January 1, 2013, and December 31, 2014. Patients were then categorized as having inadequate health literacy (BHLS ≤ 9) or adequate health literacy (BHLS > 9).^18,25 Demographic information was extracted from patient records and included age, sex (male/female), marital status (married/without a partner), race (white/nonwhite), and years of education. Income level and primary language were not available for analysis.

Statistical Analysis

Patient characteristics and TCNs were summarized by using the frequency and percentages for categorical variables and the mean and standard deviation (SD) for continuous variables. We compared patient characteristics (age, sex, marital status, race, and education) between health literacy groups (inadequate vs adequate) by using χ² or analysis of variance as appropriate. We assessed Pearson correlations among the 10 TCN domains, and we examined differences in reported needs for each of 10 TCN domains by the level of health literacy by using the χ² test. Because the TCN domain of communication included low health literacy as one of its items, we excluded this domain from subsequent analyses. We then compared differences in the number of TCNs documented (scoring range 0-9) by using an independent samples Student t test.

Multivariate logistic regression models were then constructed to examine the independent association of inadequate health literacy with 8 TCN domains while controlling for age, sex, marital status, race, and education. Patients with incomplete demographic data were excluded from these models. Additionally, these analyses excluded 2 TCN domains: the communication domain for reasons noted above and the high-risk medical comorbidity domain because it ended up being positive in 98.4% of patients. Statistical significance was set at an alpha of 0.05. All analyses were performed by using SPSS Statistics for Mac, version 23.0 (IBM Corp., Armonk, New York)

A structured patient risk factor assessment derived from literature was used to record TCNs in preparation for hospital discharge. On average, patients had needs in about half of the TCN domains (4.6 of 9). The most common areas identified were related to the presence of high-risk comorbidities (98.4%), frequent or prior healthcare utilization (76.6%), medication management (76.3%), functional status (54.9%), and transportation (48.7%). Many of the TCNs were significantly correlated with one another. The prevalence of these needs highlights the importance of using a structured assessment to identify patient concerns so that they may be addressed through discharge planning and follow-up. In addition, using a standardized TCN instrument based on a framework for ITC promotes further research in understanding patient needs and in developing personalized interventions to address them.

As hypothesized, we found that TCNs were more common in patients with inadequate health literacy. After adjustment for demographic factors, inadequate health literacy was significantly associated with transportation barriers and inadequate caregiver support. Analyses also suggested a relationship with needs related to medical devices, functional status, and mental health comorbidities. A review of the literature substantiates a link between inadequate health literacy and these needs and also suggests solutions to address these barriers.

The association with inadequate caregiver support is concerning because there is often a high degree of reliance on caregivers at transitions in care.^3-5 Caregivers are routinely called upon to provide assistance with activities that may be difficult for patients with low health literacy, including medication adherence, provider communication, and self-care activities.^26,27 Our finding that patients with inadequate health literacy are more likely to have inadequate caregiver support indicates additional vulnerability. This may be because of the absence of a caregiver, or in many cases, the presence of a caregiver who is underprepared to assist with care. Prior research has shown that when caregivers are present, up to 33% have low health literacy, even when they are paid nonfamilial caregivers.^26,28 Other studies have noted the inadequacy of information and patient training for caregivers.^29,30 Transitional care programs to improve caregiver understanding have been developed³¹ and have been demonstrated to lower rehospitalization and ED visits.³²

Patients with inadequate health literacy were also more likely to have transportation barriers. Lack of transportation has been recorded as a factor in early hospital readmission in patients with chronic disease,³³ and it has been shown to have a negative effect on a variety of health outcomes.³⁴ A likely link between readmission and lack of transportation is poor follow-up care. Wheeler et al.³⁵ found that 59% of patients expected difficulty keeping postdischarge appointments because of transportation needs. Instead of expecting patients to navigate their own transportation, the Agency for Healthcare Research and Quality recommends identifying community resources for patients with low health literacy.³⁶

In this sample, inadequate health literacy also had near significant associations with TCNs in the use of medical devices, lower functional status, and mental health comorbidities. The use of a medical device, such as home oxygen, is a risk factor for readmission,³⁷ and early reports suggest that interventions, including education related to home oxygen use, can dramatically reduce these readmissions.³⁸ Lower functional capacity and faster functional decline are associated with inadequate health literacy,³⁹ which may have to do with the inability to appropriately utilize health resources.⁴⁰ If so, structured discharge planning could alleviate the known connection between functional impairment and hospital readmissions.⁴¹ A relationship between low health literacy and depression has been demonstrated repeatedly,⁴² with worsened symptoms in those with addiction.⁴³ As has been shown in other domains where health literacy is a factor, literacy-focused interventions provide greater benefits to these depressed patients.⁴⁴

The TCN assessment worked well overall, but certain domains proved less valuable and could be removed in the future. First, it was not useful to separately identify communication barriers, because doing so did not add to information beyond the measurement of health literacy. Second, high-risk comorbidities were ubiquitous within the sample and therefore unhelpful for group comparisons. In hindsight, this is unsurprising because the sample was comprised primarily of elderly patients admitted to medical services. Still, in a younger population or a surgical setting, identifying patients with high-risk medical comorbidities may be more useful.

We acknowledge several limitations of this study. First, the study was performed at a single center, and the TCN assessments were conducted by a small number of registered nurses who received training. Therefore, the results may not generalize to the profile of patient needs at other settings, and the instrument may perform differently when scaled across an organization. Second, the needs assessment was developed for this QI initiative and did not undergo formal validation, although it was developed from published frameworks and similar assessments. Third, for the measure of health literacy, we relied on data collected by nurses as part of their normal workflow. As is often the case with data collected during routine care, the scores are imperfect,⁴⁵ but they have proven to be a valuable and valid indicator of health literacy in our previous research.^18,24,25,46 Fourth, we chose to declare a domain as positive if any item in that domain was positive and to perform a domain-level analysis (for greater clarity). We did not take into account the variable number of items within each domain or attempt to grade their severity, as this would be a subjective exercise and impractical in the discharge planning process. Finally, we were unable to address associations among socioeconomic status,⁴⁷ primary language,⁴⁸ and health literacy, because relevant data were not available for this analysis.

In this sample of hospitalized patients who were administered a structured needs assessment, patients commonly had needs that placed them at a higher risk of adverse outcomes, such as hospital readmission. Patients with low health literacy had more TCNs that extended beyond the areas that we normally associate with low health literacy, namely patient education and self-management. Healthcare professionals should be aware of the greater likelihood of transportation barriers and inadequate caregiver support among patients with low health literacy. Screening for health literacy and TCN at admission or as part of the discharge planning process will elevate such risks, better positioning clinicians and hospitals to address them as a part of the efforts to ensure a quality transition of care.

Disclosure 

This work was funded by the Centers for Medicare and Medicaid Services (1C1CMS330979) and in part by the National Center for Advancing Translational Sciences (2 UL1 TR000445-06). The content is solely the responsibility of the authors and does not necessarily represent official views of the funding agencies, which did not participate in the planning, collection, analysis, or interpretation of data or in the decision to submit for publication.

Dr. Dittus reports personal fees as a board member of the Robert Wood Johnson Foundation Medical Faculty Scholars Program National Advisory Committee; consultancy fees from the University of Virginia, Indiana University, University of Michigan, Northwestern University, Montana State University, and Purdue University; has grants/grants pending from NIH (research grants), PCORI (research grant), CME (innovation award), VA (training grant); payment for lectures including service on speakers bureaus from Corporate Parity (conference organizer) for the Global Hospital Management & Innovation Summit; and other from Medical Decision Making, Inc. (passive owner); all outside the submitted work. Dr. Kripalani has grants from NIH (research grant), PCORI (research grant), and CMS (QI grant); outside the submitted work. All other authors have nothing to disclose.

A special concern since the institution of hospital readmission penalties¹ is the transitions in care of a patient from one care setting to another, often at hospital discharge. Burke et al.² proposed a framework for an ideal transition in care (ITC) to study and improve transitions from the hospital to home. The features in the ITC were identified based upon their inclusion in the interventions that improved discharge outcomes.^3-5 Inspired by the ITC and other patient risk tools,⁶ we identified 10 domains of transitional care needs ([TCN] specified below), which we define as patient-centered risk factors that should be addressed to foster a safe and effective transition in care.⁷

One particularly important risk factor in patient self-management at transition points is health literacy, a patient’s ability to obtain, understand, and use basic health information and services. Low health literacy affects approximately 26% to 36% of adults in the United States.^8,9 Health literacy is associated with many factors that may affect successful navigation of care transitions, including doctor-patient communication,^10,11 understanding of the medication regimen,¹² and self-management.^13-15 Research has also demonstrated an association between low health literacy and poor outcomes after hospital discharge, including medication errors,¹⁶ 30-day hospital readmission,¹⁷ and mortality.¹⁸ Transitional care initiatives have begun to incorporate health literacy into patient risk assessments⁶ and provide specific attention to low health literacy in interventions to reduce adverse drug events and readmission.^4,19 Training programs for medical students and nurses advise teaching skills in health literacy as part of fostering effective transitions in care.^20,21

Although low health literacy is generally recognized as a barrier to patient education and self-management, little is known about whether patients with low health literacy are more likely to have other risk factors that could further increase their risk for poor transitions in care. A better understanding of associated risks would inform and improve patient care. We hypothesized that TCNs are more common among patients with low health literacy, as compared with those with adequate health literacy. We also aimed to describe the relationship between low health literacy and specific TCNs in order to guide clinical care and future interventions.

Setting

The present study is a cross-sectional analysis of data from a quality improvement (QI) intervention that was performed at Vanderbilt University Medical Center, a tertiary care facility in Nashville, Tennessee. The QI intervention, My Health Team (MHT), was funded by the Centers for Medicare and Medicaid Services Innovation Award program. The overall MHT program included outpatient care coordination for chronic disease management as well as a transitional care program that was designed to reduce hospital readmission. The latter included an inpatient needs assessment (which provided data for the present analysis), inpatient intervention, and postdischarge phone follow-up. The MHT initiative was reviewed by the institutional review board (IRB), which deemed it a QI program and granted a waiver of informed consent. The present secondary data analysis was reviewed and approved by the IRB.

Sample

Patients were identified for inclusion in the MHT transitions of care program if the presenting problem for hospital admission was pneumonia, chronic obstructive pulmonary disease (COPD) exacerbation, or decompensated heart failure, as determined by the review of clinical documentation by nurse transition care coordinators (TCCs). Adults over the age of 18 years were eligible, though priority was given to patients aged 65 years or older. This study includes the first inpatient encounter between June 2013 and December 31, 2014, for patients having a completed needs assessment and documentation of health literacy data in the medical record.

Data Collection

TCN assessment was developed from published patient risk tools and the ITC framework.^2,6,22 The assessment has 10 domains composed of 49 individual items as follows: (1) caregiver support (caregiver support not sufficient for patient needs), (2) transportation (relies on public or others for transportation and misses medical care because of transportation), (3) health care utilization (no primary care physician, unplanned hospitalization in the last year, emergency department [ED] visit in the last 6 months, or home health services in the last 60 days), (4) high-risk medical comorbidities (malnutrition or body mass index <18.5, renal failure, chronic pain, diabetes, heart failure, COPD, or stroke), (5) medication management provider or caregiver concern (cannot provide medication list, >10 preadmission medications, high-risk medications [eg, insulin, warfarin], poor medication understanding, or adherence issue identified), (6) medical devices (vascular access, urinary catheter, wounds, or home supplemental oxygen), (7) functional status (weakness of extremities, limited extremity range of motion, difficulty with mobility, falls at home, or activities of daily living challenges), (8) mental health comorbidities (over the past month has felt down, depressed, or hopeless or over the past month has felt little interest or pleasure in doing things, high-risk alcohol use, or high-risk substance use), (9) communication (limited English proficiency or at risk for limited health literacy), and (10) financial resources (no health insurance, skips or rations medicines because of cost, misses medical care because of cost, or misses medical care because of job).

The 49 items of the TCN assessment were documented as being present or absent by nurse TCCs at the time patients were enrolled in the transitional care program, based on patient and family interview and chart review, and the items were later extracted for analysis. Patients were determined to have a domain-level need if they reported a need on any individual item within that domain, resulting in a binary score (any need present, absent) for each of the 10 TCN domains.

Health literacy was assessed by using the Brief Health Literacy Screen (BHLS), which is administered routinely by nurses at hospital intake and documented in the medical record, with completion rates of approximately 90%.²³ The BHLS is a 3-question subjective health literacy assessment (scoring range 3-15) that has been validated against longer objective measures²⁴ and shown to predict disease control and mortality.^18,25 To improve the stability of scores (for patients who completed the BHLS more than once because of repeat hospitalizations) and to reduce missing values, we calculated the patient’s mean BHLS score for assessments obtained between January 1, 2013, and December 31, 2014. Patients were then categorized as having inadequate health literacy (BHLS ≤ 9) or adequate health literacy (BHLS > 9).^18,25 Demographic information was extracted from patient records and included age, sex (male/female), marital status (married/without a partner), race (white/nonwhite), and years of education. Income level and primary language were not available for analysis.

Statistical Analysis

Patient characteristics and TCNs were summarized by using the frequency and percentages for categorical variables and the mean and standard deviation (SD) for continuous variables. We compared patient characteristics (age, sex, marital status, race, and education) between health literacy groups (inadequate vs adequate) by using χ² or analysis of variance as appropriate. We assessed Pearson correlations among the 10 TCN domains, and we examined differences in reported needs for each of 10 TCN domains by the level of health literacy by using the χ² test. Because the TCN domain of communication included low health literacy as one of its items, we excluded this domain from subsequent analyses. We then compared differences in the number of TCNs documented (scoring range 0-9) by using an independent samples Student t test.

Multivariate logistic regression models were then constructed to examine the independent association of inadequate health literacy with 8 TCN domains while controlling for age, sex, marital status, race, and education. Patients with incomplete demographic data were excluded from these models. Additionally, these analyses excluded 2 TCN domains: the communication domain for reasons noted above and the high-risk medical comorbidity domain because it ended up being positive in 98.4% of patients. Statistical significance was set at an alpha of 0.05. All analyses were performed by using SPSS Statistics for Mac, version 23.0 (IBM Corp., Armonk, New York)

A structured patient risk factor assessment derived from literature was used to record TCNs in preparation for hospital discharge. On average, patients had needs in about half of the TCN domains (4.6 of 9). The most common areas identified were related to the presence of high-risk comorbidities (98.4%), frequent or prior healthcare utilization (76.6%), medication management (76.3%), functional status (54.9%), and transportation (48.7%). Many of the TCNs were significantly correlated with one another. The prevalence of these needs highlights the importance of using a structured assessment to identify patient concerns so that they may be addressed through discharge planning and follow-up. In addition, using a standardized TCN instrument based on a framework for ITC promotes further research in understanding patient needs and in developing personalized interventions to address them.

As hypothesized, we found that TCNs were more common in patients with inadequate health literacy. After adjustment for demographic factors, inadequate health literacy was significantly associated with transportation barriers and inadequate caregiver support. Analyses also suggested a relationship with needs related to medical devices, functional status, and mental health comorbidities. A review of the literature substantiates a link between inadequate health literacy and these needs and also suggests solutions to address these barriers.

The association with inadequate caregiver support is concerning because there is often a high degree of reliance on caregivers at transitions in care.^3-5 Caregivers are routinely called upon to provide assistance with activities that may be difficult for patients with low health literacy, including medication adherence, provider communication, and self-care activities.^26,27 Our finding that patients with inadequate health literacy are more likely to have inadequate caregiver support indicates additional vulnerability. This may be because of the absence of a caregiver, or in many cases, the presence of a caregiver who is underprepared to assist with care. Prior research has shown that when caregivers are present, up to 33% have low health literacy, even when they are paid nonfamilial caregivers.^26,28 Other studies have noted the inadequacy of information and patient training for caregivers.^29,30 Transitional care programs to improve caregiver understanding have been developed³¹ and have been demonstrated to lower rehospitalization and ED visits.³²

Patients with inadequate health literacy were also more likely to have transportation barriers. Lack of transportation has been recorded as a factor in early hospital readmission in patients with chronic disease,³³ and it has been shown to have a negative effect on a variety of health outcomes.³⁴ A likely link between readmission and lack of transportation is poor follow-up care. Wheeler et al.³⁵ found that 59% of patients expected difficulty keeping postdischarge appointments because of transportation needs. Instead of expecting patients to navigate their own transportation, the Agency for Healthcare Research and Quality recommends identifying community resources for patients with low health literacy.³⁶

In this sample, inadequate health literacy also had near significant associations with TCNs in the use of medical devices, lower functional status, and mental health comorbidities. The use of a medical device, such as home oxygen, is a risk factor for readmission,³⁷ and early reports suggest that interventions, including education related to home oxygen use, can dramatically reduce these readmissions.³⁸ Lower functional capacity and faster functional decline are associated with inadequate health literacy,³⁹ which may have to do with the inability to appropriately utilize health resources.⁴⁰ If so, structured discharge planning could alleviate the known connection between functional impairment and hospital readmissions.⁴¹ A relationship between low health literacy and depression has been demonstrated repeatedly,⁴² with worsened symptoms in those with addiction.⁴³ As has been shown in other domains where health literacy is a factor, literacy-focused interventions provide greater benefits to these depressed patients.⁴⁴

The TCN assessment worked well overall, but certain domains proved less valuable and could be removed in the future. First, it was not useful to separately identify communication barriers, because doing so did not add to information beyond the measurement of health literacy. Second, high-risk comorbidities were ubiquitous within the sample and therefore unhelpful for group comparisons. In hindsight, this is unsurprising because the sample was comprised primarily of elderly patients admitted to medical services. Still, in a younger population or a surgical setting, identifying patients with high-risk medical comorbidities may be more useful.

We acknowledge several limitations of this study. First, the study was performed at a single center, and the TCN assessments were conducted by a small number of registered nurses who received training. Therefore, the results may not generalize to the profile of patient needs at other settings, and the instrument may perform differently when scaled across an organization. Second, the needs assessment was developed for this QI initiative and did not undergo formal validation, although it was developed from published frameworks and similar assessments. Third, for the measure of health literacy, we relied on data collected by nurses as part of their normal workflow. As is often the case with data collected during routine care, the scores are imperfect,⁴⁵ but they have proven to be a valuable and valid indicator of health literacy in our previous research.^18,24,25,46 Fourth, we chose to declare a domain as positive if any item in that domain was positive and to perform a domain-level analysis (for greater clarity). We did not take into account the variable number of items within each domain or attempt to grade their severity, as this would be a subjective exercise and impractical in the discharge planning process. Finally, we were unable to address associations among socioeconomic status,⁴⁷ primary language,⁴⁸ and health literacy, because relevant data were not available for this analysis.

In this sample of hospitalized patients who were administered a structured needs assessment, patients commonly had needs that placed them at a higher risk of adverse outcomes, such as hospital readmission. Patients with low health literacy had more TCNs that extended beyond the areas that we normally associate with low health literacy, namely patient education and self-management. Healthcare professionals should be aware of the greater likelihood of transportation barriers and inadequate caregiver support among patients with low health literacy. Screening for health literacy and TCN at admission or as part of the discharge planning process will elevate such risks, better positioning clinicians and hospitals to address them as a part of the efforts to ensure a quality transition of care.

Disclosure 

This work was funded by the Centers for Medicare and Medicaid Services (1C1CMS330979) and in part by the National Center for Advancing Translational Sciences (2 UL1 TR000445-06). The content is solely the responsibility of the authors and does not necessarily represent official views of the funding agencies, which did not participate in the planning, collection, analysis, or interpretation of data or in the decision to submit for publication.

Dr. Dittus reports personal fees as a board member of the Robert Wood Johnson Foundation Medical Faculty Scholars Program National Advisory Committee; consultancy fees from the University of Virginia, Indiana University, University of Michigan, Northwestern University, Montana State University, and Purdue University; has grants/grants pending from NIH (research grants), PCORI (research grant), CME (innovation award), VA (training grant); payment for lectures including service on speakers bureaus from Corporate Parity (conference organizer) for the Global Hospital Management & Innovation Summit; and other from Medical Decision Making, Inc. (passive owner); all outside the submitted work. Dr. Kripalani has grants from NIH (research grant), PCORI (research grant), and CMS (QI grant); outside the submitted work. All other authors have nothing to disclose.

When seniors are discharged from the hospital, many will require additional support and therapy to regain their independence and return safely home.^1,2 Most seniors do not understand what their support needs will entail or the differences between therapy choices.³ To complicate the issue, seniors are often incapacitated and unable to make discharge selections for themselves.

Consequently, discharge planners and social workers often explain options to family members and loved ones, who frequently feel overwhelmed.^4,5 While often balancing jobs, loved ones are divided between wanting to stay with the senior in the hospital and driving to area skilled nursing facilities (SNFs) for consideration. Discharges are delayed waiting for families to make visits and choose an SNF. Longer lengths of stay are detrimental to seniors due to the increased risks of infection, functional loss, and cognitive decline.⁶

Although seniors comprised only 12% of the US population in 2003,⁷ they accounted for one-third of all hospitalizations, over 13.2 million hospital stays.⁸ Hospital stays for seniors resulted in hospital charges totaling nearly $329 billion, or 43.6% of national hospital bills in 2003.⁷ Seniors are also high consumers of postacute care services. By 2050, the number of individuals using long-term care services in any setting (eg, at home, assisted living, or SNFs) will be close to 27 million.^9-11 With the knowledge that many seniors will be hospitalized and subsequently require services thereafter, we sought to assist seniors in planning for their hospital discharge needs before they were hospitalized.

Our team developed PlanYourLifespan.org (PYL) to facilitate this planning for postdischarge needs and fill the knowledge gap in understanding postdischarge options. With funding from the Patient Centered Outcomes Research Institute, we aimed to test the effectiveness of PYL on improving knowledge of hospital discharge resources among seniors.

PlanYourLifespan.org

PlanYourLifespan.org (PYL) educates users on the health crises that often occur with age and connects them to posthospital and home-based resources available locally and nationally. PYL is personalized, dynamic, and adaptable in that all the information can be changed per the senior’s wishes or changing health needs.

Content of PYL

Previously, we conducted focus groups with seniors about current and perceived home needs and aging-in-place. Major themes of what advanced life events (ALEs) would impact aging-in-place were identified as follows: hospitalizations, falls, and Alzheimer’s.¹² We organized PYL around these health-related ALEs. Our multidisciplinary team of researchers, seniors, social workers, caregiver agencies, and Area Agencies on Aging representatives then determined what information and resources should be included.

Each section of PYL starts with a video of a senior discussing their real-life personal experiences, with subsections providing interactive information on what seniors can expect, types of resources available to support home needs, and choices to be made. Descriptions of types of settings for therapy, options available, and links to national/local resources (eg, quality indicators for SNFs) are also included. For example, by entering their zip code, users can identify their neighborhood SNFs, closest Area Agency on Aging, and what home caregiver agencies exist in their area.

Users can save their preferences and revisit their choices at any time. To support communication between seniors and their loved ones, a summary of their choices can be printed or e-mailed to relevant parties. For example, a senior uses PYL and can e-mail these choices to family members, which can stimulate a conversation about future posthospital care expectations.

As inadequate health literacy and cognitive impairment are prevalent among seniors, PYL presents information understandable at all levels of health literacy and sensitive to cognitive load.⁹ There is simplified, large-font, no mouse scrolling and audio available for the visually impaired.

Study Design and Randomization

To test PYL, a 2-armed (attention control [AC] and PYL intervention), parallel, randomized controlled trial was conducted. Participants were randomly assigned to 1 of the 2 conditions via a pregenerated central randomization list using equal (1:1) allocation and random permuted block design to ensure relatively equal allocation throughout the study. The AC condition exposed participants to the National Institute on Aging-sponsored website, Go4Life.nia.nih.gov, an educational website on physical activity for seniors. This website has comparable design and layout to PYL but does not include information about advanced planning. The AC condition controlled for the possibility that regular contact with the study team may improve outcomes in participants randomized to the intervention website.

The trial was conducted from October 2014 to September 2015 in Chicago, Illinois; Fort Wayne, Indiana; and Houston, Texas. Inclusion criteria were as follows: age 65 and older, English-speaking, scoring ≥4 questions correctly on the Brief Cognitive Screen,¹⁴ and current self-reported use of a computer or smartphone with internet. Participants were excluded if they had previously participated in the focus groups or beta testing of the PYL website. Community-based patient partners/stakeholders drove subject recruitment in their communities through word of mouth, e-mail bursts, newsletters, and flyers. At the Area Agency on Aging and community centers where services such as food vouchers and case management are provided, participants were recruited on-site and given study information. At the clinical sites, staff referred potential participants. Study materials such as flyers and information sheets were also located in the clinic waiting rooms. The Villages, nonprofit, grassroots, membership organizations that are redefining aging by being a key resource to community members wishing to age in place, heavily relied on electronic recruitment using their regular e-newsletters and e-mail lists to recruit potential participants. Potential subjects were also recruited by distributing flyers at local senior centers and senior housing buildings. Interested seniors contacted research staff who explained the study and assessed their eligibility. If eligible, subjects were scheduled for a face-to-face interview.

At the face-to-face encounter, all study subjects completed a written consent, answered baseline questions, and were randomized to either arm. Next, research staff introduced all study subjects to the website to which they were randomized and provided instructions on its use. Staff were present to assist with questions as needed on navigation but did not assist with decision making for either website. A minimum of 15 minutes and a maximum of 45 minutes was allotted for navigating either website. After navigating their website, participants were administered an immediate in-person posttest survey. One month and 3 months after the face-to-face encounter, research staff contacted all study participants over the phone to complete a follow-up survey. Staff attempted to reach participants up to 3 times by phone. Data were entered into Research Electronic Data Capture survey software.¹⁵ This study was approved by the Northwestern University Institutional Review Board.

Understanding of Posthospital Discharge and Home Services

As part of the larger trial, which included behavioural outcomes that will be reported elsewhere, we sought to explore the effects of PYL on participants’ knowledge and understanding of posthospital discharge and home services (UHS). Participants were asked to respond to 6 questions at baseline, immediate posttest, and at the 1- and 3-month follow-up time points. Knowledge items were developed by the study team in conjunction with the patient/partner stakeholders. UHS scores were calculated as the sum of the 6 questions (each scored 0 if incorrect and 1 if correct) with a possible range of 0-6.

Covariates

Demographic information, self-reported health, importance of religion, and existence of a power of attorney, living will, advanced directive (eg, Physician Orders for Life-Sustaining Treatment) were obtained via self-report. Participants were asked about their general and social self-efficacy using the validated Self-efficacy Scale¹⁶ and their social support using the Lubben Social Network Scale–6.¹⁷ Health literacy was assessed using the Rapid Estimate of Adult Literacy in Medicine–Short Form.¹⁸ To measure burden of disease, participant comorbidities were measured using a nonvalidated 9-item dichotomous response condition list, which included some items adapted from the Charlson Comorbidity Index and the Elixhauser Comorbidity Index.

Statistical Analysis

Data analysis included all available data in the intention-to-treat dataset. As UHS was collected at multiple time points up to 3 months postintervention, we employed linear- mixed modeling with random participant effect and fixed arm, time, and time-by-arm interaction terms. The time-by-arm interaction allows for comparison of UHS slopes (or trajectories) across arms. Analyses explored multiple potential covariates, including current utilization of services, physical function, comorbidities, social support, health literacy, self-efficacy, and sociodemographics. Those covariates found to have a significant association (P < 0.05) with outcome were considered for inclusion in the overall model selection process. Ultimately, we developed a final parsimonious, adjusted longitudinal model with primary predictors of time, arm, and their interaction, controlling for only significant baseline variables following a manual backward selection method. All analyses were conducted in SAS software (version 9.4, copyright 2012, The SAS Institute Inc., Cary, North Carolina).

The results of our study show that among seniors, PYL improved their understanding of home-based services and the services that may be required following a hospitalization. Educating seniors about what to expect regarding the transition home from a hospital before a hospitalization even occurs may enable seniors and their families to plan ahead instead of reacting to a hospitalization. PYL, a national, publicly available tool with links to local resources may potentially help in advancing transitional discharge care to prior to a hospitalization.

To our knowledge, this is one of the first websites and trials devoted to planning for seniors’ health trajectory as they age into their 70s, 80s, 90s, and 100s. Clinicians regularly discuss code status and powers of attorney during their end-of-life discussions with patients. We encourage clinicians to ask patients, “What about the 10 to 20 years before you die? Have you considered what you will do if you get sick or need help at home?” While not replacing a social worker, the ability of PYL to connect seniors to local resources makes it somewhat of a “virtual social worker.” With many physician practices unable to afford social workers, PYL provides a free-of-charge means of connecting seniors to area resources.

Acknowledgments

This work was supported through a Patient-Centered Outcomes Research Institute Award (IH-12-11-4259). Dr. Lindquist and Dr. Ciolino had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Research reported in this publication was also supported, in part, by the National Institutes of Health’s National Center for Advancing Translational Sciences, Grant Number UL1TR000150.

Disclaimer 

All statements in this manuscript, including its findings and conclusions, are solely those of the authors and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute, its Board of Governors or Methodology Committee, or the National Institutes of Health.

Disclosure: The authors have nothing to report.

When seniors are discharged from the hospital, many will require additional support and therapy to regain their independence and return safely home.^1,2 Most seniors do not understand what their support needs will entail or the differences between therapy choices.³ To complicate the issue, seniors are often incapacitated and unable to make discharge selections for themselves.

Consequently, discharge planners and social workers often explain options to family members and loved ones, who frequently feel overwhelmed.^4,5 While often balancing jobs, loved ones are divided between wanting to stay with the senior in the hospital and driving to area skilled nursing facilities (SNFs) for consideration. Discharges are delayed waiting for families to make visits and choose an SNF. Longer lengths of stay are detrimental to seniors due to the increased risks of infection, functional loss, and cognitive decline.⁶

Although seniors comprised only 12% of the US population in 2003,⁷ they accounted for one-third of all hospitalizations, over 13.2 million hospital stays.⁸ Hospital stays for seniors resulted in hospital charges totaling nearly $329 billion, or 43.6% of national hospital bills in 2003.⁷ Seniors are also high consumers of postacute care services. By 2050, the number of individuals using long-term care services in any setting (eg, at home, assisted living, or SNFs) will be close to 27 million.^9-11 With the knowledge that many seniors will be hospitalized and subsequently require services thereafter, we sought to assist seniors in planning for their hospital discharge needs before they were hospitalized.

Our team developed PlanYourLifespan.org (PYL) to facilitate this planning for postdischarge needs and fill the knowledge gap in understanding postdischarge options. With funding from the Patient Centered Outcomes Research Institute, we aimed to test the effectiveness of PYL on improving knowledge of hospital discharge resources among seniors.

PlanYourLifespan.org

PlanYourLifespan.org (PYL) educates users on the health crises that often occur with age and connects them to posthospital and home-based resources available locally and nationally. PYL is personalized, dynamic, and adaptable in that all the information can be changed per the senior’s wishes or changing health needs.

Content of PYL

Previously, we conducted focus groups with seniors about current and perceived home needs and aging-in-place. Major themes of what advanced life events (ALEs) would impact aging-in-place were identified as follows: hospitalizations, falls, and Alzheimer’s.¹² We organized PYL around these health-related ALEs. Our multidisciplinary team of researchers, seniors, social workers, caregiver agencies, and Area Agencies on Aging representatives then determined what information and resources should be included.

Each section of PYL starts with a video of a senior discussing their real-life personal experiences, with subsections providing interactive information on what seniors can expect, types of resources available to support home needs, and choices to be made. Descriptions of types of settings for therapy, options available, and links to national/local resources (eg, quality indicators for SNFs) are also included. For example, by entering their zip code, users can identify their neighborhood SNFs, closest Area Agency on Aging, and what home caregiver agencies exist in their area.

Users can save their preferences and revisit their choices at any time. To support communication between seniors and their loved ones, a summary of their choices can be printed or e-mailed to relevant parties. For example, a senior uses PYL and can e-mail these choices to family members, which can stimulate a conversation about future posthospital care expectations.

As inadequate health literacy and cognitive impairment are prevalent among seniors, PYL presents information understandable at all levels of health literacy and sensitive to cognitive load.⁹ There is simplified, large-font, no mouse scrolling and audio available for the visually impaired.

Study Design and Randomization

To test PYL, a 2-armed (attention control [AC] and PYL intervention), parallel, randomized controlled trial was conducted. Participants were randomly assigned to 1 of the 2 conditions via a pregenerated central randomization list using equal (1:1) allocation and random permuted block design to ensure relatively equal allocation throughout the study. The AC condition exposed participants to the National Institute on Aging-sponsored website, Go4Life.nia.nih.gov, an educational website on physical activity for seniors. This website has comparable design and layout to PYL but does not include information about advanced planning. The AC condition controlled for the possibility that regular contact with the study team may improve outcomes in participants randomized to the intervention website.

The trial was conducted from October 2014 to September 2015 in Chicago, Illinois; Fort Wayne, Indiana; and Houston, Texas. Inclusion criteria were as follows: age 65 and older, English-speaking, scoring ≥4 questions correctly on the Brief Cognitive Screen,¹⁴ and current self-reported use of a computer or smartphone with internet. Participants were excluded if they had previously participated in the focus groups or beta testing of the PYL website. Community-based patient partners/stakeholders drove subject recruitment in their communities through word of mouth, e-mail bursts, newsletters, and flyers. At the Area Agency on Aging and community centers where services such as food vouchers and case management are provided, participants were recruited on-site and given study information. At the clinical sites, staff referred potential participants. Study materials such as flyers and information sheets were also located in the clinic waiting rooms. The Villages, nonprofit, grassroots, membership organizations that are redefining aging by being a key resource to community members wishing to age in place, heavily relied on electronic recruitment using their regular e-newsletters and e-mail lists to recruit potential participants. Potential subjects were also recruited by distributing flyers at local senior centers and senior housing buildings. Interested seniors contacted research staff who explained the study and assessed their eligibility. If eligible, subjects were scheduled for a face-to-face interview.

At the face-to-face encounter, all study subjects completed a written consent, answered baseline questions, and were randomized to either arm. Next, research staff introduced all study subjects to the website to which they were randomized and provided instructions on its use. Staff were present to assist with questions as needed on navigation but did not assist with decision making for either website. A minimum of 15 minutes and a maximum of 45 minutes was allotted for navigating either website. After navigating their website, participants were administered an immediate in-person posttest survey. One month and 3 months after the face-to-face encounter, research staff contacted all study participants over the phone to complete a follow-up survey. Staff attempted to reach participants up to 3 times by phone. Data were entered into Research Electronic Data Capture survey software.¹⁵ This study was approved by the Northwestern University Institutional Review Board.

Understanding of Posthospital Discharge and Home Services

As part of the larger trial, which included behavioural outcomes that will be reported elsewhere, we sought to explore the effects of PYL on participants’ knowledge and understanding of posthospital discharge and home services (UHS). Participants were asked to respond to 6 questions at baseline, immediate posttest, and at the 1- and 3-month follow-up time points. Knowledge items were developed by the study team in conjunction with the patient/partner stakeholders. UHS scores were calculated as the sum of the 6 questions (each scored 0 if incorrect and 1 if correct) with a possible range of 0-6.

Covariates

Demographic information, self-reported health, importance of religion, and existence of a power of attorney, living will, advanced directive (eg, Physician Orders for Life-Sustaining Treatment) were obtained via self-report. Participants were asked about their general and social self-efficacy using the validated Self-efficacy Scale¹⁶ and their social support using the Lubben Social Network Scale–6.¹⁷ Health literacy was assessed using the Rapid Estimate of Adult Literacy in Medicine–Short Form.¹⁸ To measure burden of disease, participant comorbidities were measured using a nonvalidated 9-item dichotomous response condition list, which included some items adapted from the Charlson Comorbidity Index and the Elixhauser Comorbidity Index.

Statistical Analysis

Data analysis included all available data in the intention-to-treat dataset. As UHS was collected at multiple time points up to 3 months postintervention, we employed linear- mixed modeling with random participant effect and fixed arm, time, and time-by-arm interaction terms. The time-by-arm interaction allows for comparison of UHS slopes (or trajectories) across arms. Analyses explored multiple potential covariates, including current utilization of services, physical function, comorbidities, social support, health literacy, self-efficacy, and sociodemographics. Those covariates found to have a significant association (P < 0.05) with outcome were considered for inclusion in the overall model selection process. Ultimately, we developed a final parsimonious, adjusted longitudinal model with primary predictors of time, arm, and their interaction, controlling for only significant baseline variables following a manual backward selection method. All analyses were conducted in SAS software (version 9.4, copyright 2012, The SAS Institute Inc., Cary, North Carolina).

The results of our study show that among seniors, PYL improved their understanding of home-based services and the services that may be required following a hospitalization. Educating seniors about what to expect regarding the transition home from a hospital before a hospitalization even occurs may enable seniors and their families to plan ahead instead of reacting to a hospitalization. PYL, a national, publicly available tool with links to local resources may potentially help in advancing transitional discharge care to prior to a hospitalization.

To our knowledge, this is one of the first websites and trials devoted to planning for seniors’ health trajectory as they age into their 70s, 80s, 90s, and 100s. Clinicians regularly discuss code status and powers of attorney during their end-of-life discussions with patients. We encourage clinicians to ask patients, “What about the 10 to 20 years before you die? Have you considered what you will do if you get sick or need help at home?” While not replacing a social worker, the ability of PYL to connect seniors to local resources makes it somewhat of a “virtual social worker.” With many physician practices unable to afford social workers, PYL provides a free-of-charge means of connecting seniors to area resources.

Acknowledgments

This work was supported through a Patient-Centered Outcomes Research Institute Award (IH-12-11-4259). Dr. Lindquist and Dr. Ciolino had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Research reported in this publication was also supported, in part, by the National Institutes of Health’s National Center for Advancing Translational Sciences, Grant Number UL1TR000150.

Disclaimer 

All statements in this manuscript, including its findings and conclusions, are solely those of the authors and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute, its Board of Governors or Methodology Committee, or the National Institutes of Health.

Disclosure: The authors have nothing to report.

When seniors are discharged from the hospital, many will require additional support and therapy to regain their independence and return safely home.^1,2 Most seniors do not understand what their support needs will entail or the differences between therapy choices.³ To complicate the issue, seniors are often incapacitated and unable to make discharge selections for themselves.

Consequently, discharge planners and social workers often explain options to family members and loved ones, who frequently feel overwhelmed.^4,5 While often balancing jobs, loved ones are divided between wanting to stay with the senior in the hospital and driving to area skilled nursing facilities (SNFs) for consideration. Discharges are delayed waiting for families to make visits and choose an SNF. Longer lengths of stay are detrimental to seniors due to the increased risks of infection, functional loss, and cognitive decline.⁶

Although seniors comprised only 12% of the US population in 2003,⁷ they accounted for one-third of all hospitalizations, over 13.2 million hospital stays.⁸ Hospital stays for seniors resulted in hospital charges totaling nearly $329 billion, or 43.6% of national hospital bills in 2003.⁷ Seniors are also high consumers of postacute care services. By 2050, the number of individuals using long-term care services in any setting (eg, at home, assisted living, or SNFs) will be close to 27 million.^9-11 With the knowledge that many seniors will be hospitalized and subsequently require services thereafter, we sought to assist seniors in planning for their hospital discharge needs before they were hospitalized.

Our team developed PlanYourLifespan.org (PYL) to facilitate this planning for postdischarge needs and fill the knowledge gap in understanding postdischarge options. With funding from the Patient Centered Outcomes Research Institute, we aimed to test the effectiveness of PYL on improving knowledge of hospital discharge resources among seniors.

PlanYourLifespan.org

PlanYourLifespan.org (PYL) educates users on the health crises that often occur with age and connects them to posthospital and home-based resources available locally and nationally. PYL is personalized, dynamic, and adaptable in that all the information can be changed per the senior’s wishes or changing health needs.

Content of PYL

Previously, we conducted focus groups with seniors about current and perceived home needs and aging-in-place. Major themes of what advanced life events (ALEs) would impact aging-in-place were identified as follows: hospitalizations, falls, and Alzheimer’s.¹² We organized PYL around these health-related ALEs. Our multidisciplinary team of researchers, seniors, social workers, caregiver agencies, and Area Agencies on Aging representatives then determined what information and resources should be included.

Each section of PYL starts with a video of a senior discussing their real-life personal experiences, with subsections providing interactive information on what seniors can expect, types of resources available to support home needs, and choices to be made. Descriptions of types of settings for therapy, options available, and links to national/local resources (eg, quality indicators for SNFs) are also included. For example, by entering their zip code, users can identify their neighborhood SNFs, closest Area Agency on Aging, and what home caregiver agencies exist in their area.

Users can save their preferences and revisit their choices at any time. To support communication between seniors and their loved ones, a summary of their choices can be printed or e-mailed to relevant parties. For example, a senior uses PYL and can e-mail these choices to family members, which can stimulate a conversation about future posthospital care expectations.

As inadequate health literacy and cognitive impairment are prevalent among seniors, PYL presents information understandable at all levels of health literacy and sensitive to cognitive load.⁹ There is simplified, large-font, no mouse scrolling and audio available for the visually impaired.

Study Design and Randomization

To test PYL, a 2-armed (attention control [AC] and PYL intervention), parallel, randomized controlled trial was conducted. Participants were randomly assigned to 1 of the 2 conditions via a pregenerated central randomization list using equal (1:1) allocation and random permuted block design to ensure relatively equal allocation throughout the study. The AC condition exposed participants to the National Institute on Aging-sponsored website, Go4Life.nia.nih.gov, an educational website on physical activity for seniors. This website has comparable design and layout to PYL but does not include information about advanced planning. The AC condition controlled for the possibility that regular contact with the study team may improve outcomes in participants randomized to the intervention website.

The trial was conducted from October 2014 to September 2015 in Chicago, Illinois; Fort Wayne, Indiana; and Houston, Texas. Inclusion criteria were as follows: age 65 and older, English-speaking, scoring ≥4 questions correctly on the Brief Cognitive Screen,¹⁴ and current self-reported use of a computer or smartphone with internet. Participants were excluded if they had previously participated in the focus groups or beta testing of the PYL website. Community-based patient partners/stakeholders drove subject recruitment in their communities through word of mouth, e-mail bursts, newsletters, and flyers. At the Area Agency on Aging and community centers where services such as food vouchers and case management are provided, participants were recruited on-site and given study information. At the clinical sites, staff referred potential participants. Study materials such as flyers and information sheets were also located in the clinic waiting rooms. The Villages, nonprofit, grassroots, membership organizations that are redefining aging by being a key resource to community members wishing to age in place, heavily relied on electronic recruitment using their regular e-newsletters and e-mail lists to recruit potential participants. Potential subjects were also recruited by distributing flyers at local senior centers and senior housing buildings. Interested seniors contacted research staff who explained the study and assessed their eligibility. If eligible, subjects were scheduled for a face-to-face interview.

At the face-to-face encounter, all study subjects completed a written consent, answered baseline questions, and were randomized to either arm. Next, research staff introduced all study subjects to the website to which they were randomized and provided instructions on its use. Staff were present to assist with questions as needed on navigation but did not assist with decision making for either website. A minimum of 15 minutes and a maximum of 45 minutes was allotted for navigating either website. After navigating their website, participants were administered an immediate in-person posttest survey. One month and 3 months after the face-to-face encounter, research staff contacted all study participants over the phone to complete a follow-up survey. Staff attempted to reach participants up to 3 times by phone. Data were entered into Research Electronic Data Capture survey software.¹⁵ This study was approved by the Northwestern University Institutional Review Board.

Understanding of Posthospital Discharge and Home Services

As part of the larger trial, which included behavioural outcomes that will be reported elsewhere, we sought to explore the effects of PYL on participants’ knowledge and understanding of posthospital discharge and home services (UHS). Participants were asked to respond to 6 questions at baseline, immediate posttest, and at the 1- and 3-month follow-up time points. Knowledge items were developed by the study team in conjunction with the patient/partner stakeholders. UHS scores were calculated as the sum of the 6 questions (each scored 0 if incorrect and 1 if correct) with a possible range of 0-6.

Covariates

Demographic information, self-reported health, importance of religion, and existence of a power of attorney, living will, advanced directive (eg, Physician Orders for Life-Sustaining Treatment) were obtained via self-report. Participants were asked about their general and social self-efficacy using the validated Self-efficacy Scale¹⁶ and their social support using the Lubben Social Network Scale–6.¹⁷ Health literacy was assessed using the Rapid Estimate of Adult Literacy in Medicine–Short Form.¹⁸ To measure burden of disease, participant comorbidities were measured using a nonvalidated 9-item dichotomous response condition list, which included some items adapted from the Charlson Comorbidity Index and the Elixhauser Comorbidity Index.

Statistical Analysis

Data analysis included all available data in the intention-to-treat dataset. As UHS was collected at multiple time points up to 3 months postintervention, we employed linear- mixed modeling with random participant effect and fixed arm, time, and time-by-arm interaction terms. The time-by-arm interaction allows for comparison of UHS slopes (or trajectories) across arms. Analyses explored multiple potential covariates, including current utilization of services, physical function, comorbidities, social support, health literacy, self-efficacy, and sociodemographics. Those covariates found to have a significant association (P < 0.05) with outcome were considered for inclusion in the overall model selection process. Ultimately, we developed a final parsimonious, adjusted longitudinal model with primary predictors of time, arm, and their interaction, controlling for only significant baseline variables following a manual backward selection method. All analyses were conducted in SAS software (version 9.4, copyright 2012, The SAS Institute Inc., Cary, North Carolina).

The results of our study show that among seniors, PYL improved their understanding of home-based services and the services that may be required following a hospitalization. Educating seniors about what to expect regarding the transition home from a hospital before a hospitalization even occurs may enable seniors and their families to plan ahead instead of reacting to a hospitalization. PYL, a national, publicly available tool with links to local resources may potentially help in advancing transitional discharge care to prior to a hospitalization.

To our knowledge, this is one of the first websites and trials devoted to planning for seniors’ health trajectory as they age into their 70s, 80s, 90s, and 100s. Clinicians regularly discuss code status and powers of attorney during their end-of-life discussions with patients. We encourage clinicians to ask patients, “What about the 10 to 20 years before you die? Have you considered what you will do if you get sick or need help at home?” While not replacing a social worker, the ability of PYL to connect seniors to local resources makes it somewhat of a “virtual social worker.” With many physician practices unable to afford social workers, PYL provides a free-of-charge means of connecting seniors to area resources.

Acknowledgments

This work was supported through a Patient-Centered Outcomes Research Institute Award (IH-12-11-4259). Dr. Lindquist and Dr. Ciolino had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Research reported in this publication was also supported, in part, by the National Institutes of Health’s National Center for Advancing Translational Sciences, Grant Number UL1TR000150.

Disclaimer 

All statements in this manuscript, including its findings and conclusions, are solely those of the authors and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute, its Board of Governors or Methodology Committee, or the National Institutes of Health.

Disclosure: The authors have nothing to report.

Successful smoking cessation interventions result in substantial gains in health and life expectancy by reducing smoking-related illnesses and preventing premature deaths.^1,2 The Department of Health and Human Services recommends clinicians use hospitalization as “an opportunity to promote smoking cessation’’ and ‘‘to prescribe medications to alleviate withdrawal symptoms”³ because individual readiness to quit may be high during hospitalizations. A meta-analysis of 50 studies (21 from the United States) examining the efficacy of hospital-initiated smoking cessation interventions concluded that smoking cessation support programs that began in the hospital and continued for at least 1 month postdischarge significantly increase the likelihood of patients being smoke-free in the long term.⁴ The most efficacious strategies included counseling and pharmacotherapy rather than counseling alone.³ Most inpatient smoking cessation studies have focused on quit-rates or medical outcomes, while fewer studies have looked at healthcare utilization.

However, previous research has shown that smoking cessation for inpatients has relatively immediate economic and health benefits. Patients who quit smoking during hospitalizations for cardiovascular disease are less likely to be readmitted or to die during follow-up.^5,6 Patients with acute myocardial infarction (AMI), unstable angina, heart failure, and chronic obstructive pulmonary disease who received an inpatient smoking cessation intervention had reductions in inpatient readmission rates.⁷ A 1% reduction in overall smoking rates would lead to an annual reduction of 3,022 hospitalizations for stroke and 1,684 hospitalizations for AMI.⁸ One comprehensive program, the Ottawa Model for Smoking Cessation (OMSC), found that a hospital-initiated intervention increased long-term cessation rates by 15% in cardiac patients and by 11% in general hospital populations.^9,10 The applicability of this result to US healthcare systems is unknown. This paper adds to the existing literature by evaluating the impact of an inpatient smoking cessation program on healthcare utilization among patients hospitalized for any reason, rather than solely focused on those with cardiopulmonary diagnoses.

The current study focuses on an inpatient smoking cessation program at a teaching hospital in the Rocky Mountain region. The hospital implemented a smoking cessation treatment program on July 1, 2013, based on the OMSC. The goal was to identify and support inpatient adult smokers who wanted to make a quit attempt and help them remain smoke-free after discharge. The objective of the current study was to determine the effect of the program on 30-day readmission rates and length of stay (LOS) of the index hospitalization. Although the general cost effectiveness of properly structured smoking cessation programs are well established,^11-13 the healthcare utilization effects of inpatient smoking cessation programs are not well understood.

Data

The study population consists of patients over age 18 who were admitted to the hospital between July 1, 2012, and July 1, 2014. Baseline smoking status was assessed at hospital admission and recorded in Epic (Epic Systems Corporation, Verona, Wisconsin), the electronic medical records system, as a current smoker (every day and some days), former smoker, never smoker, and never assessed. To check the accuracy of recorded smoking status, a random sample of 819 inpatients was selected and contacted via telephone for verification; 93% of Epic-identified smokers confirmed that they were smokers at hospital admission.¹⁴

Intervention

The intervention, which launched July 13, 2014, modified the Epic system to automatically alert providers viewing a tobacco user’s medical record that the patient should receive standardized orders for a bedside consultation with a Tobacco Treatment Specialist (TTS) and a prescription for nicotine replacement therapy (NRT) while in the hospital.¹⁵ Previously, referrals for tobacco treatment were done on an ad-hoc basis by the physician, and NRT was not routinely available. This system-level intervention standardized and automated the referral process. For patients with a bedside consultation order, TTS used a patient-centered approach (motivational interviewing) to explore patients’ motivation to quit smoking and offered NRT to improve comfort and safety while in the hospital. Patients who chose to make a quit attempt received a free 2-week supply of NRT at discharge and 6 months of free follow-up counseling by interactive voice response (IVR) telephone technology that included (a) prerecorded advice keyed to individual patient needs, (b) a warm-transfer option to speak with a live TTS (later dropped), and (c) a collection of patient smoking and cessation treatment measures.¹⁵

Statistical Analysis

We used an intent-to-treat (ITT) framework for the analysis, which considers everyone eligible for the treatment to be in the treatment group. The approach ignores treatment nonacceptance, nonadherence, protocol deviations, withdrawal from treatment, and cessation outcomes, thus providing conservative estimates of outcomes.^16-18

Readmission rates and LOS were estimated by using a “difference-in-differences” model, comparing outcomes between smokers before versus after the introduction of the cessation treatment program with nonsmokers before versus after program introduction. The difference-in-differences method looks at the difference pre-and-post in the exposed group (smokers) and unexposed group (nonsmokers). Subtracting the difference between the 2 groups gives an estimate of the policy effect controlling for background trends.¹⁹ The smoking cessation treatment effect on readmission is measured by the coefficient on the interaction term between the smoking variable and an indicator that the program is operational. The coefficient is the “difference-in-differences.”

Other control variables include demographic factors (gender, age, race), hospitalization payer (Medicare, Medicaid, commercial), and the service line of the admission. We also included a severity of illness variable from the APR-DRG Grouper (3M, Maplewood, Minnesota)²⁰ and the number of days spent in the intensive care unit. For the readmission model, we included LOS as a control variable, because individuals with longer LOS had a better opportunity to access the intervention.

For readmissions, the model was estimated by using a probit model, predicting the effect of each of the intervention variables and the control variables on the marginal probability of a readmission. Because patients can appear in both the pre- and postyears, clustered standard errors were used, which correct for the lack of independence from multiple observations from the same individual.²¹ For LOS, a truncated negative binomial model was used. The negative binomial model is a specification for count models with a mass of observations plus a long right tail. The truncation is because zero and negative values for LOS are not possible. The dependent variable represents the number of days the individual was hospitalized. For both models, the reported coefficients represent the marginal effect of the independent variable on the dependent variable. This was calculated using the “margins” command in Stata version 13 (StataCorp LLC, College Station, Texas).

This study investigated the effect of an inpatient smoking cessation program, based on a successful Canadian model, on inpatient readmission rates and LOS. The program showed no effect on 30-day readmission rates or LOS. We see several potential explanations for the absence of a detectable impact.

First, the ITT approach reflected real-world implementation of smoking cessation services. The ITT approach adopts the hospital’s perspective because the hospital will assess overall effectiveness without regard to programmatic limitations. The intervention group for this analysis included individuals who were offered but declined treatment, individuals who accepted treatment but failed to quit smoking, and individuals who both accepted treatment and quit smoking. If the analysis had focused only on the latter group, an effect would have been more likely to be found. Further analysis of the subset of patients who accepted the intervention and quit smoking is warranted. Nevertheless, hospitals cannot expect all inpatient smokers, or even a majority, to embrace an offer of cessation treatment. This also emphasizes the challenges hospitals will face in offering tobacco cessation programs to smokers in a timely way. Reasons for patients not receiving orders varied but included issues with weekend admissions.

Second, the timeframe of the analysis is limited to the inpatient stay (for LOS) and 30 days (for readmission). A longer-term analysis might have found an effect. However, we examined this from the hospital perspective. For the hospital, LOS is a key cost driver; thus, reductions in LOS would create a strong financial incentive for hospitals to implement smoking cessation programs. Similarly, reducing readmissions is now a priority for hospitals because of new Medicare rules that penalize hospitals for readmissions. Thus, the 2 outcomes we examined are outcomes that are financially important to hospitals.

There are several limitations to our analysis. First, the difference-in-differences model assumes that in the absence of treatment, the average change in the dependent variables would have been the same for both the treatment and control groups, also known as the parallel trends assumption. Specification tests showed this assumption was met for the preperiod. Second, our study relies on electronic health record data to identify smokers. However, 93% of individuals who were identified as smokers confirmed their smoking status upon interview. Finally, we looked at all categories of inpatient admissions. Improvement in LOS and short-term readmission rates may be limited to patients admitted for specific conditions, such as cardiovascular and respiratory conditions.

There are a number of plausible reasons for our null finding. First, the “dose” of intervention may have been too weak; that is, the number of smokers who were offered the treatment, accepted the treatment, and adhered to the treatment may have been too low, leading to too few smokers quitting smoking and, thus, no effect of the intervention on our outcomes. This follows directly from the ITT design of the study.²³ This suggests that hospitals who wish to adopt smoking cessation programs need to focus on ensuring a timely offering of treatment and encouragement of uptake by smokers.

A second reason for the null finding may have been the short duration for the NRT, which was only offered for 2 weeks. Research suggests that use of NRT for less than 4 weeks is associated with a reduced likelihood of smoking cessation.²⁴ However, a review of the literature concludes that the duration of NRT is less important than the dosage and the combination of NRT with other forms of smoking cessation therapy.²⁵ It is important to note that this study used NRT; other treatments such as Chantix could have different effectiveness.^26,27 Further research on different treatment approaches, including longer duration of NRT, would be appropriate.

Disclosure

 The authors have no competing interests or conflicts to report. The study was supported by contract number 15FLA68717 from the Colorado Department of Public Health and Environment.

Successful smoking cessation interventions result in substantial gains in health and life expectancy by reducing smoking-related illnesses and preventing premature deaths.^1,2 The Department of Health and Human Services recommends clinicians use hospitalization as “an opportunity to promote smoking cessation’’ and ‘‘to prescribe medications to alleviate withdrawal symptoms”³ because individual readiness to quit may be high during hospitalizations. A meta-analysis of 50 studies (21 from the United States) examining the efficacy of hospital-initiated smoking cessation interventions concluded that smoking cessation support programs that began in the hospital and continued for at least 1 month postdischarge significantly increase the likelihood of patients being smoke-free in the long term.⁴ The most efficacious strategies included counseling and pharmacotherapy rather than counseling alone.³ Most inpatient smoking cessation studies have focused on quit-rates or medical outcomes, while fewer studies have looked at healthcare utilization.

However, previous research has shown that smoking cessation for inpatients has relatively immediate economic and health benefits. Patients who quit smoking during hospitalizations for cardiovascular disease are less likely to be readmitted or to die during follow-up.^5,6 Patients with acute myocardial infarction (AMI), unstable angina, heart failure, and chronic obstructive pulmonary disease who received an inpatient smoking cessation intervention had reductions in inpatient readmission rates.⁷ A 1% reduction in overall smoking rates would lead to an annual reduction of 3,022 hospitalizations for stroke and 1,684 hospitalizations for AMI.⁸ One comprehensive program, the Ottawa Model for Smoking Cessation (OMSC), found that a hospital-initiated intervention increased long-term cessation rates by 15% in cardiac patients and by 11% in general hospital populations.^9,10 The applicability of this result to US healthcare systems is unknown. This paper adds to the existing literature by evaluating the impact of an inpatient smoking cessation program on healthcare utilization among patients hospitalized for any reason, rather than solely focused on those with cardiopulmonary diagnoses.

The current study focuses on an inpatient smoking cessation program at a teaching hospital in the Rocky Mountain region. The hospital implemented a smoking cessation treatment program on July 1, 2013, based on the OMSC. The goal was to identify and support inpatient adult smokers who wanted to make a quit attempt and help them remain smoke-free after discharge. The objective of the current study was to determine the effect of the program on 30-day readmission rates and length of stay (LOS) of the index hospitalization. Although the general cost effectiveness of properly structured smoking cessation programs are well established,^11-13 the healthcare utilization effects of inpatient smoking cessation programs are not well understood.

Data

The study population consists of patients over age 18 who were admitted to the hospital between July 1, 2012, and July 1, 2014. Baseline smoking status was assessed at hospital admission and recorded in Epic (Epic Systems Corporation, Verona, Wisconsin), the electronic medical records system, as a current smoker (every day and some days), former smoker, never smoker, and never assessed. To check the accuracy of recorded smoking status, a random sample of 819 inpatients was selected and contacted via telephone for verification; 93% of Epic-identified smokers confirmed that they were smokers at hospital admission.¹⁴

Intervention

The intervention, which launched July 13, 2014, modified the Epic system to automatically alert providers viewing a tobacco user’s medical record that the patient should receive standardized orders for a bedside consultation with a Tobacco Treatment Specialist (TTS) and a prescription for nicotine replacement therapy (NRT) while in the hospital.¹⁵ Previously, referrals for tobacco treatment were done on an ad-hoc basis by the physician, and NRT was not routinely available. This system-level intervention standardized and automated the referral process. For patients with a bedside consultation order, TTS used a patient-centered approach (motivational interviewing) to explore patients’ motivation to quit smoking and offered NRT to improve comfort and safety while in the hospital. Patients who chose to make a quit attempt received a free 2-week supply of NRT at discharge and 6 months of free follow-up counseling by interactive voice response (IVR) telephone technology that included (a) prerecorded advice keyed to individual patient needs, (b) a warm-transfer option to speak with a live TTS (later dropped), and (c) a collection of patient smoking and cessation treatment measures.¹⁵

Statistical Analysis

We used an intent-to-treat (ITT) framework for the analysis, which considers everyone eligible for the treatment to be in the treatment group. The approach ignores treatment nonacceptance, nonadherence, protocol deviations, withdrawal from treatment, and cessation outcomes, thus providing conservative estimates of outcomes.^16-18

Readmission rates and LOS were estimated by using a “difference-in-differences” model, comparing outcomes between smokers before versus after the introduction of the cessation treatment program with nonsmokers before versus after program introduction. The difference-in-differences method looks at the difference pre-and-post in the exposed group (smokers) and unexposed group (nonsmokers). Subtracting the difference between the 2 groups gives an estimate of the policy effect controlling for background trends.¹⁹ The smoking cessation treatment effect on readmission is measured by the coefficient on the interaction term between the smoking variable and an indicator that the program is operational. The coefficient is the “difference-in-differences.”

Other control variables include demographic factors (gender, age, race), hospitalization payer (Medicare, Medicaid, commercial), and the service line of the admission. We also included a severity of illness variable from the APR-DRG Grouper (3M, Maplewood, Minnesota)²⁰ and the number of days spent in the intensive care unit. For the readmission model, we included LOS as a control variable, because individuals with longer LOS had a better opportunity to access the intervention.

For readmissions, the model was estimated by using a probit model, predicting the effect of each of the intervention variables and the control variables on the marginal probability of a readmission. Because patients can appear in both the pre- and postyears, clustered standard errors were used, which correct for the lack of independence from multiple observations from the same individual.²¹ For LOS, a truncated negative binomial model was used. The negative binomial model is a specification for count models with a mass of observations plus a long right tail. The truncation is because zero and negative values for LOS are not possible. The dependent variable represents the number of days the individual was hospitalized. For both models, the reported coefficients represent the marginal effect of the independent variable on the dependent variable. This was calculated using the “margins” command in Stata version 13 (StataCorp LLC, College Station, Texas).

This study investigated the effect of an inpatient smoking cessation program, based on a successful Canadian model, on inpatient readmission rates and LOS. The program showed no effect on 30-day readmission rates or LOS. We see several potential explanations for the absence of a detectable impact.

First, the ITT approach reflected real-world implementation of smoking cessation services. The ITT approach adopts the hospital’s perspective because the hospital will assess overall effectiveness without regard to programmatic limitations. The intervention group for this analysis included individuals who were offered but declined treatment, individuals who accepted treatment but failed to quit smoking, and individuals who both accepted treatment and quit smoking. If the analysis had focused only on the latter group, an effect would have been more likely to be found. Further analysis of the subset of patients who accepted the intervention and quit smoking is warranted. Nevertheless, hospitals cannot expect all inpatient smokers, or even a majority, to embrace an offer of cessation treatment. This also emphasizes the challenges hospitals will face in offering tobacco cessation programs to smokers in a timely way. Reasons for patients not receiving orders varied but included issues with weekend admissions.

Second, the timeframe of the analysis is limited to the inpatient stay (for LOS) and 30 days (for readmission). A longer-term analysis might have found an effect. However, we examined this from the hospital perspective. For the hospital, LOS is a key cost driver; thus, reductions in LOS would create a strong financial incentive for hospitals to implement smoking cessation programs. Similarly, reducing readmissions is now a priority for hospitals because of new Medicare rules that penalize hospitals for readmissions. Thus, the 2 outcomes we examined are outcomes that are financially important to hospitals.

There are several limitations to our analysis. First, the difference-in-differences model assumes that in the absence of treatment, the average change in the dependent variables would have been the same for both the treatment and control groups, also known as the parallel trends assumption. Specification tests showed this assumption was met for the preperiod. Second, our study relies on electronic health record data to identify smokers. However, 93% of individuals who were identified as smokers confirmed their smoking status upon interview. Finally, we looked at all categories of inpatient admissions. Improvement in LOS and short-term readmission rates may be limited to patients admitted for specific conditions, such as cardiovascular and respiratory conditions.

There are a number of plausible reasons for our null finding. First, the “dose” of intervention may have been too weak; that is, the number of smokers who were offered the treatment, accepted the treatment, and adhered to the treatment may have been too low, leading to too few smokers quitting smoking and, thus, no effect of the intervention on our outcomes. This follows directly from the ITT design of the study.²³ This suggests that hospitals who wish to adopt smoking cessation programs need to focus on ensuring a timely offering of treatment and encouragement of uptake by smokers.

A second reason for the null finding may have been the short duration for the NRT, which was only offered for 2 weeks. Research suggests that use of NRT for less than 4 weeks is associated with a reduced likelihood of smoking cessation.²⁴ However, a review of the literature concludes that the duration of NRT is less important than the dosage and the combination of NRT with other forms of smoking cessation therapy.²⁵ It is important to note that this study used NRT; other treatments such as Chantix could have different effectiveness.^26,27 Further research on different treatment approaches, including longer duration of NRT, would be appropriate.

Disclosure

 The authors have no competing interests or conflicts to report. The study was supported by contract number 15FLA68717 from the Colorado Department of Public Health and Environment.

Successful smoking cessation interventions result in substantial gains in health and life expectancy by reducing smoking-related illnesses and preventing premature deaths.^1,2 The Department of Health and Human Services recommends clinicians use hospitalization as “an opportunity to promote smoking cessation’’ and ‘‘to prescribe medications to alleviate withdrawal symptoms”³ because individual readiness to quit may be high during hospitalizations. A meta-analysis of 50 studies (21 from the United States) examining the efficacy of hospital-initiated smoking cessation interventions concluded that smoking cessation support programs that began in the hospital and continued for at least 1 month postdischarge significantly increase the likelihood of patients being smoke-free in the long term.⁴ The most efficacious strategies included counseling and pharmacotherapy rather than counseling alone.³ Most inpatient smoking cessation studies have focused on quit-rates or medical outcomes, while fewer studies have looked at healthcare utilization.

However, previous research has shown that smoking cessation for inpatients has relatively immediate economic and health benefits. Patients who quit smoking during hospitalizations for cardiovascular disease are less likely to be readmitted or to die during follow-up.^5,6 Patients with acute myocardial infarction (AMI), unstable angina, heart failure, and chronic obstructive pulmonary disease who received an inpatient smoking cessation intervention had reductions in inpatient readmission rates.⁷ A 1% reduction in overall smoking rates would lead to an annual reduction of 3,022 hospitalizations for stroke and 1,684 hospitalizations for AMI.⁸ One comprehensive program, the Ottawa Model for Smoking Cessation (OMSC), found that a hospital-initiated intervention increased long-term cessation rates by 15% in cardiac patients and by 11% in general hospital populations.^9,10 The applicability of this result to US healthcare systems is unknown. This paper adds to the existing literature by evaluating the impact of an inpatient smoking cessation program on healthcare utilization among patients hospitalized for any reason, rather than solely focused on those with cardiopulmonary diagnoses.

The current study focuses on an inpatient smoking cessation program at a teaching hospital in the Rocky Mountain region. The hospital implemented a smoking cessation treatment program on July 1, 2013, based on the OMSC. The goal was to identify and support inpatient adult smokers who wanted to make a quit attempt and help them remain smoke-free after discharge. The objective of the current study was to determine the effect of the program on 30-day readmission rates and length of stay (LOS) of the index hospitalization. Although the general cost effectiveness of properly structured smoking cessation programs are well established,^11-13 the healthcare utilization effects of inpatient smoking cessation programs are not well understood.

Data

The study population consists of patients over age 18 who were admitted to the hospital between July 1, 2012, and July 1, 2014. Baseline smoking status was assessed at hospital admission and recorded in Epic (Epic Systems Corporation, Verona, Wisconsin), the electronic medical records system, as a current smoker (every day and some days), former smoker, never smoker, and never assessed. To check the accuracy of recorded smoking status, a random sample of 819 inpatients was selected and contacted via telephone for verification; 93% of Epic-identified smokers confirmed that they were smokers at hospital admission.¹⁴

Intervention

The intervention, which launched July 13, 2014, modified the Epic system to automatically alert providers viewing a tobacco user’s medical record that the patient should receive standardized orders for a bedside consultation with a Tobacco Treatment Specialist (TTS) and a prescription for nicotine replacement therapy (NRT) while in the hospital.¹⁵ Previously, referrals for tobacco treatment were done on an ad-hoc basis by the physician, and NRT was not routinely available. This system-level intervention standardized and automated the referral process. For patients with a bedside consultation order, TTS used a patient-centered approach (motivational interviewing) to explore patients’ motivation to quit smoking and offered NRT to improve comfort and safety while in the hospital. Patients who chose to make a quit attempt received a free 2-week supply of NRT at discharge and 6 months of free follow-up counseling by interactive voice response (IVR) telephone technology that included (a) prerecorded advice keyed to individual patient needs, (b) a warm-transfer option to speak with a live TTS (later dropped), and (c) a collection of patient smoking and cessation treatment measures.¹⁵

Statistical Analysis

We used an intent-to-treat (ITT) framework for the analysis, which considers everyone eligible for the treatment to be in the treatment group. The approach ignores treatment nonacceptance, nonadherence, protocol deviations, withdrawal from treatment, and cessation outcomes, thus providing conservative estimates of outcomes.^16-18

Readmission rates and LOS were estimated by using a “difference-in-differences” model, comparing outcomes between smokers before versus after the introduction of the cessation treatment program with nonsmokers before versus after program introduction. The difference-in-differences method looks at the difference pre-and-post in the exposed group (smokers) and unexposed group (nonsmokers). Subtracting the difference between the 2 groups gives an estimate of the policy effect controlling for background trends.¹⁹ The smoking cessation treatment effect on readmission is measured by the coefficient on the interaction term between the smoking variable and an indicator that the program is operational. The coefficient is the “difference-in-differences.”

Other control variables include demographic factors (gender, age, race), hospitalization payer (Medicare, Medicaid, commercial), and the service line of the admission. We also included a severity of illness variable from the APR-DRG Grouper (3M, Maplewood, Minnesota)²⁰ and the number of days spent in the intensive care unit. For the readmission model, we included LOS as a control variable, because individuals with longer LOS had a better opportunity to access the intervention.

For readmissions, the model was estimated by using a probit model, predicting the effect of each of the intervention variables and the control variables on the marginal probability of a readmission. Because patients can appear in both the pre- and postyears, clustered standard errors were used, which correct for the lack of independence from multiple observations from the same individual.²¹ For LOS, a truncated negative binomial model was used. The negative binomial model is a specification for count models with a mass of observations plus a long right tail. The truncation is because zero and negative values for LOS are not possible. The dependent variable represents the number of days the individual was hospitalized. For both models, the reported coefficients represent the marginal effect of the independent variable on the dependent variable. This was calculated using the “margins” command in Stata version 13 (StataCorp LLC, College Station, Texas).

This study investigated the effect of an inpatient smoking cessation program, based on a successful Canadian model, on inpatient readmission rates and LOS. The program showed no effect on 30-day readmission rates or LOS. We see several potential explanations for the absence of a detectable impact.

First, the ITT approach reflected real-world implementation of smoking cessation services. The ITT approach adopts the hospital’s perspective because the hospital will assess overall effectiveness without regard to programmatic limitations. The intervention group for this analysis included individuals who were offered but declined treatment, individuals who accepted treatment but failed to quit smoking, and individuals who both accepted treatment and quit smoking. If the analysis had focused only on the latter group, an effect would have been more likely to be found. Further analysis of the subset of patients who accepted the intervention and quit smoking is warranted. Nevertheless, hospitals cannot expect all inpatient smokers, or even a majority, to embrace an offer of cessation treatment. This also emphasizes the challenges hospitals will face in offering tobacco cessation programs to smokers in a timely way. Reasons for patients not receiving orders varied but included issues with weekend admissions.

Second, the timeframe of the analysis is limited to the inpatient stay (for LOS) and 30 days (for readmission). A longer-term analysis might have found an effect. However, we examined this from the hospital perspective. For the hospital, LOS is a key cost driver; thus, reductions in LOS would create a strong financial incentive for hospitals to implement smoking cessation programs. Similarly, reducing readmissions is now a priority for hospitals because of new Medicare rules that penalize hospitals for readmissions. Thus, the 2 outcomes we examined are outcomes that are financially important to hospitals.

There are several limitations to our analysis. First, the difference-in-differences model assumes that in the absence of treatment, the average change in the dependent variables would have been the same for both the treatment and control groups, also known as the parallel trends assumption. Specification tests showed this assumption was met for the preperiod. Second, our study relies on electronic health record data to identify smokers. However, 93% of individuals who were identified as smokers confirmed their smoking status upon interview. Finally, we looked at all categories of inpatient admissions. Improvement in LOS and short-term readmission rates may be limited to patients admitted for specific conditions, such as cardiovascular and respiratory conditions.

There are a number of plausible reasons for our null finding. First, the “dose” of intervention may have been too weak; that is, the number of smokers who were offered the treatment, accepted the treatment, and adhered to the treatment may have been too low, leading to too few smokers quitting smoking and, thus, no effect of the intervention on our outcomes. This follows directly from the ITT design of the study.²³ This suggests that hospitals who wish to adopt smoking cessation programs need to focus on ensuring a timely offering of treatment and encouragement of uptake by smokers.

A second reason for the null finding may have been the short duration for the NRT, which was only offered for 2 weeks. Research suggests that use of NRT for less than 4 weeks is associated with a reduced likelihood of smoking cessation.²⁴ However, a review of the literature concludes that the duration of NRT is less important than the dosage and the combination of NRT with other forms of smoking cessation therapy.²⁵ It is important to note that this study used NRT; other treatments such as Chantix could have different effectiveness.^26,27 Further research on different treatment approaches, including longer duration of NRT, would be appropriate.

Disclosure

 The authors have no competing interests or conflicts to report. The study was supported by contract number 15FLA68717 from the Colorado Department of Public Health and Environment.

Bacterial pneumonia remains an important cause of morbidity and mortality in the United States, and is the 8^th leading cause of death with 55,227 deaths among adults annually.¹ In 2005, the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA) collaborated to update guidelines for hospital-acquired pneumonia (HAP), ventilator-associated pneumonia, and healthcare-associated pneumonia (HCAP).² This broad document outlines an evidence-based approach to diagnostic testing and antibiotic management based on the epidemiology and risk factors for these conditions. The guideline specifies the following criteria for HCAP: hospitalization in the past 90 days, residence in a skilled nursing facility (SNF), home infusion therapy, hemodialysis, home wound care, family members with multidrug resistant organisms (MDRO), and immunosuppressive diseases or medications, with the presumption that these patients are more likely to be harboring MDRO and should thus be treated empirically with broad-spectrum antibiotic therapy. Prior studies have shown that patients with HCAP have a more severe illness, are more likely to have MDRO, are more likely to be inadequately treated, and are at a higher risk for mortality than patients with community-acquired pneumonia (CAP).^3,4

These guidelines are controversial, especially in regard to the recommendations to empirically treat broadly with 2 antibiotics targeting Pseudomonas species, whether patients with HCAP merit broader spectrum coverage than patients with CAP, and whether the criteria for defining HCAP are adequate to predict which patients are harboring MDRO. It has subsequently been proposed that HCAP is more related to CAP than to HAP, and a recent update to the guideline removed recommendations for treatment of HCAP and will be placing HCAP into the guidelines for CAP instead.⁵ We sought to investigate the degree of uptake of the ATS and IDSA guideline recommendations by physicians over time, and whether this led to a change in outcomes among patients who met the criteria for HCAP.

Setting and Patients

We identified patients discharged between July 1, 2007, and November 30, 2011, from 488 US hospitals that participated in the Premier database (Premier Inc., Charlotte, North Carolina), an inpatient database developed for measuring quality and healthcare utilization. The database is frequently used for healthcare research and has been described previously.⁶ Member hospitals are in all regions of the US and are generally reflective of US hospitals. This database contains multiple data elements, including sociodemographic information, International Classification of Diseases, 9th Revision-Clinical Modification (ICD-9-CM) diagnosis and procedure codes, hospital and physician information, source of admission, and discharge status. It also includes a date-stamped log of all billed items and services, including diagnostic tests, medications, and other treatments. Because the data do not contain identifiable information, the institutional review board at our medical center determined that this study did not constitute human subjects research.

We included all patients aged ≥18 years with a principal diagnosis of pneumonia or with a secondary diagnosis of pneumonia paired with a principal diagnosis of respiratory failure, acute respiratory distress syndrome, respiratory arrest, sepsis, or influenza. Patients were excluded if they were transferred to or from another acute care institution, had a length of stay of 1 day or less, had cystic fibrosis, did not have a chest radiograph, or did not receive antibiotics within 48 hours of admission.

For each patient, we extracted age, gender, principal diagnosis, comorbidities, and the specialty of the attending physician. Comorbidities were identified from ICD-9-CM secondary diagnosis codes and Diagnosis Related Groups by using Healthcare Cost and Utilization Project Comorbidity Software, version 3.1, based on the work of Elixhauser (Agency for Healthcare Research and Quality, Rockville, Maryland).⁷ In order to ensure that patients had HCAP, we required the presence of ≥1 HCAP criteria, including hospitalization in the past 90 days, hemodialysis, admission from an SNF, or immune suppression (which was derived from either a secondary diagnosis for neutropenia, hematological malignancy, organ transplant, acquired immunodeficiency virus, or receiving immunosuppressant drugs or corticosteroids [equivalent to ≥20 mg/day of prednisone]).

Definitions of Guideline-Concordant and Discordant Antibiotic Therapy

The ATS and IDSA guidelines recommended the following antibiotic combinations for HCAP: an antipseudomonal cephalosporin or carbapenem or a beta-lactam/lactamase inhibitor, plus an antipseudomonal quinolone or aminoglycoside, plus an antibiotic with activity versus methicillin resistant Staphylococcus aureus (MRSA), such as vancomycin or linezolid. Based on these guidelines, we defined the receipt of fully guideline-concordant antibiotics as 2 recommended antibiotics for Pseudomonas species plus 1 for MRSA administered by the second day of admission. Partially guideline-concordant antibiotics were defined as 1 recommended antibiotic for Pseudomonas species plus 1 for MRSA by the second day of hospitalization. Guideline-discordant antibiotics were defined as all other combinations.

Statistical Analysis

Descriptive statistics on patient characteristics are presented as frequency, proportions for categorical factors, and median with interquartile range (IQR) for continuous variables for the full cohort and by treatment group, defined as fully or partially guideline-concordant antibiotic therapy or discordant therapy. Hospital rates of fully guideline-concordant treatment are presented overall and by hospital characteristics. The association of hospital characteristics with rates of fully guideline-concordant therapy were assessed by using 1-way analysis of variance tests.

To assess trends across hospitals for the association between the use of guideline-concordant therapy and mortality, progression to respiratory failure as measured by the late initiation of invasive mechanical ventilation (day 3 or later), and the length of stay among survivors, we divided the 4.5-year study period into 9 intervals of 6 months each; 292 hospitals that submitted data for all 9 time points were examined in this analysis. Based on the distribution of length of stay in the first time period, we created an indicator variable for extended length of stay with length of stay at or above the 75th percentile, defined as extended. For each hospital at each 6-month interval, we then computed risk-standardized guideline-concordant treatment (RS-treatment) rates and risk-standardized in-hospital outcome rates similar to methods used by the Centers for Medicare and Medicaid Services for public reporting.⁸ For each hospital at each time interval, we estimated a predicted rate of guideline-concordant treatment as the sum of predicted probabilities of guideline-concordant treatment from patient factors and the random intercept for the hospital in which they were admitted. We then calculated the expected rate of guideline-concordant treatment as the sum of expected probabilities of treatment received from patient factors only. RS-treatment was then calculated as the ratio of predicted to expected rates multiplied by the overall unadjusted mean treatment rate from all patients.⁹ We repeated the same modeling strategy to calculate risk-standardized outcome (RS-outcome) rates for each hospital across all time points. All models were adjusted for patient demographics and comorbidities. Similar models using administrative data have moderate discrimination for mortality.¹⁰

We then fit mixed-effects linear models with random hospital intercept and slope across time for the RS-treatment and outcome rates, respectively. From these models, we estimated the mean slope for RS-treatment and for RS-outcome over time. In addition, we estimated a slope or trend over time for each hospital for treatment and for outcome and evaluated the correlation between the treatment and outcome trends.

All analyses were performed using the Statistical Analysis System version 9.4 (SAS Institute Inc., Cary, NC) and STATA release 13 (StataCorp, LLC, College Station, Texas).

In this large, retrospective cohort study, we found that there was a substantial gap between the empiric antibiotics recommended by the ATS and IDSA guidelines and the empiric antibiotics that patients actually received. Over the study period, we saw an increased adherence to guidelines, in spite of growing evidence that HCAP risk factors do not adequately predict which patients are at risk for infection with an MDRO.¹¹ We used this change in antibiotic prescribing behavior over time to determine if there was a clinical impact on patient outcomes and found that at the hospital level, there were no improvements in mortality, excess length of stay, or progression to respiratory failure despite a doubling in guideline-concordant antibiotic use.

At least 2 other large studies have assessed the association between guideline-concordant therapy and outcomes in HCAP.^12,13 Both found that guideline-concordant therapy was associated with increased mortality, despite propensity matching. Both were conducted at the individual patient level by using administrative data, and results were likely affected by unmeasured clinical confounders, with sicker patients being more likely to receive guideline-concordant therapy. Our focus on the outcomes at the hospital level avoids this selection bias because the overall severity of illness of patients at any given hospital would not be expected to change over the study period, while physician uptake of antibiotic prescribing guidelines would be expected to increase over time. Determining the correlation between increases in guideline adherence and changes in patient outcome may offer a better assessment of the impact of guideline adherence. In this regard, our results are similar to those achieved by 1 quality improvement collaborative that was aimed at increasing guideline concordant therapy in ICUs. Despite an increase in guideline concordance from 33% to 47% of patients, they found no change in overall mortality.¹⁴

There were several limitations to our study. We did not have access to microbiologic data, so we were unable to determine which patients had MDRO infection or determine antibiotic-pathogen matching. However, the treating physicians in our study population presumably did not have access to this data at the time of treatment either because the time period we examined was within the first 48 hours of hospitalization, the interval during which cultures are incubating and the patients are being treated empirically. In addition, there may have been HCAP patients that we failed to identify, such as patients who were admitted in the past 90 days to a hospital that does not submit data to Premier. However, it is unlikely that prescribing for such patients should differ systematically from what we observed. While the database draws from 488 hospitals nationwide, it is possible that practices may be different at facilities that are not contained within the Premier database, such as Veterans Administration Hospitals. Similarly, we did not have readings for chest x-rays; hence, there could be some patients in the dataset who did not have pneumonia. However, we tried to overcome this by including only those patients with a principal diagnosis of pneumonia or sepsis with a secondary pneumonia diagnosis, a chest x-ray, and antibiotics administered within the first 48 hours of admission.

There are likely several reasons why so few HCAP patients in our study received guideline-concordant antibiotics. A lack of knowledge about the ATS and IDSA guidelines may have impacted the physicians in our study population. El-Solh et al.¹⁵ surveyed physicians about the ATS-IDSA guidelines 4 years after publication and found that only 45% were familiar with the document. We found that the rate of prescribing at least partially guideline-concordant antibiotics rose steadily over time, supporting the idea that the newness of the guidelines was 1 barrier. Additionally, prior studies have shown that many physicians may not agree with or choose to follow guidelines, with only 20% of physicians indicating that guidelines have a major impact on their clinical decision making,¹⁶ and the majority do not choose HCAP guideline-concordant antibiotics when tested.¹⁷ Alternatively, clinicians may not follow the guidelines because of a belief that the HCAP criteria do not adequately indicate patients who are at risk for MDRO. Previous studies have demonstrated the relative inability of HCAP risk factors to predict patients who harbor MDRO¹⁸ and suggest that better tools such as clinical scoring systems, which include not only the traditional HCAP risk factors but also prior exposure to antibiotics, prior culture data, and a cumulative assessment of both intrinsic and extrinsic factors, could more accurately predict MDRO and lead to a more judicious use of broad-spectrum antimicrobial agents.^19-25 Indeed, these collective findings have led the authors of the recently updated guidelines to remove HCAP as a clinical entity from the hospital-acquired or ventilator-associated pneumonia guidelines and place them instead in the upcoming updated guidelines on the management of CAP.⁵ Of these 3 explanations, the lack of familiarity fits best with our observation that guideline-concordant therapy increased steadily over time with no evidence of reaching a plateau. Ironically, as consensus was building that HCAP is a poor marker for MDROs, routine empiric treatment with vancomycin and piperacillin-tazobactam (“vanco and zosyn”) have become routine in many hospitals. Additional studies are needed to know if this trend has stabilized or reversed.

In conclusion, clinicians in our large, nationally representative sample treated the majority of HCAP patients as though they had CAP. Although there was an increase in the administration of guideline-concordant therapy over time, this increase was not associated with improved outcomes. This study supports the growing consensus that HCAP criteria do not accurately predict which patients benefit from broad-spectrum antibiotics for pneumonia, and most patients fare well with antibiotics targeting common community-acquired organisms.

Disclosure

 This work was supported by grant # R01HS018723 from the Agency for Healthcare Research and Quality. Dr. Lagu is also supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Dr. Lindenauer is supported by grant K24HL132008 from the National Heart, Lung, and Blood Institute. The funding agency had no role in the data acquisition, analysis, or manuscript preparation for this study. Drs. Haessler and Rothberg had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Haessler, Lagu, Lindenauer, Skiest, Zilberberg, Higgins, and Rothberg conceived of the study and analyzed and interpreted the data. Dr. Lindenauer acquired the data. Dr. Pekow and Ms. Priya carried out the statistical analyses. Dr. Haessler drafted the manuscript. All authors critically reviewed the manuscript for accuracy and integrity. All authors certify no potential conflicts of interest. Preliminary results from this study were presented in oral and poster format at IDWeek in 2012 and 2013.

Bacterial pneumonia remains an important cause of morbidity and mortality in the United States, and is the 8^th leading cause of death with 55,227 deaths among adults annually.¹ In 2005, the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA) collaborated to update guidelines for hospital-acquired pneumonia (HAP), ventilator-associated pneumonia, and healthcare-associated pneumonia (HCAP).² This broad document outlines an evidence-based approach to diagnostic testing and antibiotic management based on the epidemiology and risk factors for these conditions. The guideline specifies the following criteria for HCAP: hospitalization in the past 90 days, residence in a skilled nursing facility (SNF), home infusion therapy, hemodialysis, home wound care, family members with multidrug resistant organisms (MDRO), and immunosuppressive diseases or medications, with the presumption that these patients are more likely to be harboring MDRO and should thus be treated empirically with broad-spectrum antibiotic therapy. Prior studies have shown that patients with HCAP have a more severe illness, are more likely to have MDRO, are more likely to be inadequately treated, and are at a higher risk for mortality than patients with community-acquired pneumonia (CAP).^3,4

These guidelines are controversial, especially in regard to the recommendations to empirically treat broadly with 2 antibiotics targeting Pseudomonas species, whether patients with HCAP merit broader spectrum coverage than patients with CAP, and whether the criteria for defining HCAP are adequate to predict which patients are harboring MDRO. It has subsequently been proposed that HCAP is more related to CAP than to HAP, and a recent update to the guideline removed recommendations for treatment of HCAP and will be placing HCAP into the guidelines for CAP instead.⁵ We sought to investigate the degree of uptake of the ATS and IDSA guideline recommendations by physicians over time, and whether this led to a change in outcomes among patients who met the criteria for HCAP.

Setting and Patients

We identified patients discharged between July 1, 2007, and November 30, 2011, from 488 US hospitals that participated in the Premier database (Premier Inc., Charlotte, North Carolina), an inpatient database developed for measuring quality and healthcare utilization. The database is frequently used for healthcare research and has been described previously.⁶ Member hospitals are in all regions of the US and are generally reflective of US hospitals. This database contains multiple data elements, including sociodemographic information, International Classification of Diseases, 9th Revision-Clinical Modification (ICD-9-CM) diagnosis and procedure codes, hospital and physician information, source of admission, and discharge status. It also includes a date-stamped log of all billed items and services, including diagnostic tests, medications, and other treatments. Because the data do not contain identifiable information, the institutional review board at our medical center determined that this study did not constitute human subjects research.

We included all patients aged ≥18 years with a principal diagnosis of pneumonia or with a secondary diagnosis of pneumonia paired with a principal diagnosis of respiratory failure, acute respiratory distress syndrome, respiratory arrest, sepsis, or influenza. Patients were excluded if they were transferred to or from another acute care institution, had a length of stay of 1 day or less, had cystic fibrosis, did not have a chest radiograph, or did not receive antibiotics within 48 hours of admission.

For each patient, we extracted age, gender, principal diagnosis, comorbidities, and the specialty of the attending physician. Comorbidities were identified from ICD-9-CM secondary diagnosis codes and Diagnosis Related Groups by using Healthcare Cost and Utilization Project Comorbidity Software, version 3.1, based on the work of Elixhauser (Agency for Healthcare Research and Quality, Rockville, Maryland).⁷ In order to ensure that patients had HCAP, we required the presence of ≥1 HCAP criteria, including hospitalization in the past 90 days, hemodialysis, admission from an SNF, or immune suppression (which was derived from either a secondary diagnosis for neutropenia, hematological malignancy, organ transplant, acquired immunodeficiency virus, or receiving immunosuppressant drugs or corticosteroids [equivalent to ≥20 mg/day of prednisone]).

Definitions of Guideline-Concordant and Discordant Antibiotic Therapy

The ATS and IDSA guidelines recommended the following antibiotic combinations for HCAP: an antipseudomonal cephalosporin or carbapenem or a beta-lactam/lactamase inhibitor, plus an antipseudomonal quinolone or aminoglycoside, plus an antibiotic with activity versus methicillin resistant Staphylococcus aureus (MRSA), such as vancomycin or linezolid. Based on these guidelines, we defined the receipt of fully guideline-concordant antibiotics as 2 recommended antibiotics for Pseudomonas species plus 1 for MRSA administered by the second day of admission. Partially guideline-concordant antibiotics were defined as 1 recommended antibiotic for Pseudomonas species plus 1 for MRSA by the second day of hospitalization. Guideline-discordant antibiotics were defined as all other combinations.

Statistical Analysis

Descriptive statistics on patient characteristics are presented as frequency, proportions for categorical factors, and median with interquartile range (IQR) for continuous variables for the full cohort and by treatment group, defined as fully or partially guideline-concordant antibiotic therapy or discordant therapy. Hospital rates of fully guideline-concordant treatment are presented overall and by hospital characteristics. The association of hospital characteristics with rates of fully guideline-concordant therapy were assessed by using 1-way analysis of variance tests.

To assess trends across hospitals for the association between the use of guideline-concordant therapy and mortality, progression to respiratory failure as measured by the late initiation of invasive mechanical ventilation (day 3 or later), and the length of stay among survivors, we divided the 4.5-year study period into 9 intervals of 6 months each; 292 hospitals that submitted data for all 9 time points were examined in this analysis. Based on the distribution of length of stay in the first time period, we created an indicator variable for extended length of stay with length of stay at or above the 75th percentile, defined as extended. For each hospital at each 6-month interval, we then computed risk-standardized guideline-concordant treatment (RS-treatment) rates and risk-standardized in-hospital outcome rates similar to methods used by the Centers for Medicare and Medicaid Services for public reporting.⁸ For each hospital at each time interval, we estimated a predicted rate of guideline-concordant treatment as the sum of predicted probabilities of guideline-concordant treatment from patient factors and the random intercept for the hospital in which they were admitted. We then calculated the expected rate of guideline-concordant treatment as the sum of expected probabilities of treatment received from patient factors only. RS-treatment was then calculated as the ratio of predicted to expected rates multiplied by the overall unadjusted mean treatment rate from all patients.⁹ We repeated the same modeling strategy to calculate risk-standardized outcome (RS-outcome) rates for each hospital across all time points. All models were adjusted for patient demographics and comorbidities. Similar models using administrative data have moderate discrimination for mortality.¹⁰

We then fit mixed-effects linear models with random hospital intercept and slope across time for the RS-treatment and outcome rates, respectively. From these models, we estimated the mean slope for RS-treatment and for RS-outcome over time. In addition, we estimated a slope or trend over time for each hospital for treatment and for outcome and evaluated the correlation between the treatment and outcome trends.

All analyses were performed using the Statistical Analysis System version 9.4 (SAS Institute Inc., Cary, NC) and STATA release 13 (StataCorp, LLC, College Station, Texas).

In this large, retrospective cohort study, we found that there was a substantial gap between the empiric antibiotics recommended by the ATS and IDSA guidelines and the empiric antibiotics that patients actually received. Over the study period, we saw an increased adherence to guidelines, in spite of growing evidence that HCAP risk factors do not adequately predict which patients are at risk for infection with an MDRO.¹¹ We used this change in antibiotic prescribing behavior over time to determine if there was a clinical impact on patient outcomes and found that at the hospital level, there were no improvements in mortality, excess length of stay, or progression to respiratory failure despite a doubling in guideline-concordant antibiotic use.

At least 2 other large studies have assessed the association between guideline-concordant therapy and outcomes in HCAP.^12,13 Both found that guideline-concordant therapy was associated with increased mortality, despite propensity matching. Both were conducted at the individual patient level by using administrative data, and results were likely affected by unmeasured clinical confounders, with sicker patients being more likely to receive guideline-concordant therapy. Our focus on the outcomes at the hospital level avoids this selection bias because the overall severity of illness of patients at any given hospital would not be expected to change over the study period, while physician uptake of antibiotic prescribing guidelines would be expected to increase over time. Determining the correlation between increases in guideline adherence and changes in patient outcome may offer a better assessment of the impact of guideline adherence. In this regard, our results are similar to those achieved by 1 quality improvement collaborative that was aimed at increasing guideline concordant therapy in ICUs. Despite an increase in guideline concordance from 33% to 47% of patients, they found no change in overall mortality.¹⁴

There were several limitations to our study. We did not have access to microbiologic data, so we were unable to determine which patients had MDRO infection or determine antibiotic-pathogen matching. However, the treating physicians in our study population presumably did not have access to this data at the time of treatment either because the time period we examined was within the first 48 hours of hospitalization, the interval during which cultures are incubating and the patients are being treated empirically. In addition, there may have been HCAP patients that we failed to identify, such as patients who were admitted in the past 90 days to a hospital that does not submit data to Premier. However, it is unlikely that prescribing for such patients should differ systematically from what we observed. While the database draws from 488 hospitals nationwide, it is possible that practices may be different at facilities that are not contained within the Premier database, such as Veterans Administration Hospitals. Similarly, we did not have readings for chest x-rays; hence, there could be some patients in the dataset who did not have pneumonia. However, we tried to overcome this by including only those patients with a principal diagnosis of pneumonia or sepsis with a secondary pneumonia diagnosis, a chest x-ray, and antibiotics administered within the first 48 hours of admission.

There are likely several reasons why so few HCAP patients in our study received guideline-concordant antibiotics. A lack of knowledge about the ATS and IDSA guidelines may have impacted the physicians in our study population. El-Solh et al.¹⁵ surveyed physicians about the ATS-IDSA guidelines 4 years after publication and found that only 45% were familiar with the document. We found that the rate of prescribing at least partially guideline-concordant antibiotics rose steadily over time, supporting the idea that the newness of the guidelines was 1 barrier. Additionally, prior studies have shown that many physicians may not agree with or choose to follow guidelines, with only 20% of physicians indicating that guidelines have a major impact on their clinical decision making,¹⁶ and the majority do not choose HCAP guideline-concordant antibiotics when tested.¹⁷ Alternatively, clinicians may not follow the guidelines because of a belief that the HCAP criteria do not adequately indicate patients who are at risk for MDRO. Previous studies have demonstrated the relative inability of HCAP risk factors to predict patients who harbor MDRO¹⁸ and suggest that better tools such as clinical scoring systems, which include not only the traditional HCAP risk factors but also prior exposure to antibiotics, prior culture data, and a cumulative assessment of both intrinsic and extrinsic factors, could more accurately predict MDRO and lead to a more judicious use of broad-spectrum antimicrobial agents.^19-25 Indeed, these collective findings have led the authors of the recently updated guidelines to remove HCAP as a clinical entity from the hospital-acquired or ventilator-associated pneumonia guidelines and place them instead in the upcoming updated guidelines on the management of CAP.⁵ Of these 3 explanations, the lack of familiarity fits best with our observation that guideline-concordant therapy increased steadily over time with no evidence of reaching a plateau. Ironically, as consensus was building that HCAP is a poor marker for MDROs, routine empiric treatment with vancomycin and piperacillin-tazobactam (“vanco and zosyn”) have become routine in many hospitals. Additional studies are needed to know if this trend has stabilized or reversed.

In conclusion, clinicians in our large, nationally representative sample treated the majority of HCAP patients as though they had CAP. Although there was an increase in the administration of guideline-concordant therapy over time, this increase was not associated with improved outcomes. This study supports the growing consensus that HCAP criteria do not accurately predict which patients benefit from broad-spectrum antibiotics for pneumonia, and most patients fare well with antibiotics targeting common community-acquired organisms.

Disclosure

 This work was supported by grant # R01HS018723 from the Agency for Healthcare Research and Quality. Dr. Lagu is also supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Dr. Lindenauer is supported by grant K24HL132008 from the National Heart, Lung, and Blood Institute. The funding agency had no role in the data acquisition, analysis, or manuscript preparation for this study. Drs. Haessler and Rothberg had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Haessler, Lagu, Lindenauer, Skiest, Zilberberg, Higgins, and Rothberg conceived of the study and analyzed and interpreted the data. Dr. Lindenauer acquired the data. Dr. Pekow and Ms. Priya carried out the statistical analyses. Dr. Haessler drafted the manuscript. All authors critically reviewed the manuscript for accuracy and integrity. All authors certify no potential conflicts of interest. Preliminary results from this study were presented in oral and poster format at IDWeek in 2012 and 2013.

Bacterial pneumonia remains an important cause of morbidity and mortality in the United States, and is the 8^th leading cause of death with 55,227 deaths among adults annually.¹ In 2005, the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA) collaborated to update guidelines for hospital-acquired pneumonia (HAP), ventilator-associated pneumonia, and healthcare-associated pneumonia (HCAP).² This broad document outlines an evidence-based approach to diagnostic testing and antibiotic management based on the epidemiology and risk factors for these conditions. The guideline specifies the following criteria for HCAP: hospitalization in the past 90 days, residence in a skilled nursing facility (SNF), home infusion therapy, hemodialysis, home wound care, family members with multidrug resistant organisms (MDRO), and immunosuppressive diseases or medications, with the presumption that these patients are more likely to be harboring MDRO and should thus be treated empirically with broad-spectrum antibiotic therapy. Prior studies have shown that patients with HCAP have a more severe illness, are more likely to have MDRO, are more likely to be inadequately treated, and are at a higher risk for mortality than patients with community-acquired pneumonia (CAP).^3,4

These guidelines are controversial, especially in regard to the recommendations to empirically treat broadly with 2 antibiotics targeting Pseudomonas species, whether patients with HCAP merit broader spectrum coverage than patients with CAP, and whether the criteria for defining HCAP are adequate to predict which patients are harboring MDRO. It has subsequently been proposed that HCAP is more related to CAP than to HAP, and a recent update to the guideline removed recommendations for treatment of HCAP and will be placing HCAP into the guidelines for CAP instead.⁵ We sought to investigate the degree of uptake of the ATS and IDSA guideline recommendations by physicians over time, and whether this led to a change in outcomes among patients who met the criteria for HCAP.

Setting and Patients

We identified patients discharged between July 1, 2007, and November 30, 2011, from 488 US hospitals that participated in the Premier database (Premier Inc., Charlotte, North Carolina), an inpatient database developed for measuring quality and healthcare utilization. The database is frequently used for healthcare research and has been described previously.⁶ Member hospitals are in all regions of the US and are generally reflective of US hospitals. This database contains multiple data elements, including sociodemographic information, International Classification of Diseases, 9th Revision-Clinical Modification (ICD-9-CM) diagnosis and procedure codes, hospital and physician information, source of admission, and discharge status. It also includes a date-stamped log of all billed items and services, including diagnostic tests, medications, and other treatments. Because the data do not contain identifiable information, the institutional review board at our medical center determined that this study did not constitute human subjects research.

We included all patients aged ≥18 years with a principal diagnosis of pneumonia or with a secondary diagnosis of pneumonia paired with a principal diagnosis of respiratory failure, acute respiratory distress syndrome, respiratory arrest, sepsis, or influenza. Patients were excluded if they were transferred to or from another acute care institution, had a length of stay of 1 day or less, had cystic fibrosis, did not have a chest radiograph, or did not receive antibiotics within 48 hours of admission.

For each patient, we extracted age, gender, principal diagnosis, comorbidities, and the specialty of the attending physician. Comorbidities were identified from ICD-9-CM secondary diagnosis codes and Diagnosis Related Groups by using Healthcare Cost and Utilization Project Comorbidity Software, version 3.1, based on the work of Elixhauser (Agency for Healthcare Research and Quality, Rockville, Maryland).⁷ In order to ensure that patients had HCAP, we required the presence of ≥1 HCAP criteria, including hospitalization in the past 90 days, hemodialysis, admission from an SNF, or immune suppression (which was derived from either a secondary diagnosis for neutropenia, hematological malignancy, organ transplant, acquired immunodeficiency virus, or receiving immunosuppressant drugs or corticosteroids [equivalent to ≥20 mg/day of prednisone]).

Definitions of Guideline-Concordant and Discordant Antibiotic Therapy

The ATS and IDSA guidelines recommended the following antibiotic combinations for HCAP: an antipseudomonal cephalosporin or carbapenem or a beta-lactam/lactamase inhibitor, plus an antipseudomonal quinolone or aminoglycoside, plus an antibiotic with activity versus methicillin resistant Staphylococcus aureus (MRSA), such as vancomycin or linezolid. Based on these guidelines, we defined the receipt of fully guideline-concordant antibiotics as 2 recommended antibiotics for Pseudomonas species plus 1 for MRSA administered by the second day of admission. Partially guideline-concordant antibiotics were defined as 1 recommended antibiotic for Pseudomonas species plus 1 for MRSA by the second day of hospitalization. Guideline-discordant antibiotics were defined as all other combinations.

Statistical Analysis

Descriptive statistics on patient characteristics are presented as frequency, proportions for categorical factors, and median with interquartile range (IQR) for continuous variables for the full cohort and by treatment group, defined as fully or partially guideline-concordant antibiotic therapy or discordant therapy. Hospital rates of fully guideline-concordant treatment are presented overall and by hospital characteristics. The association of hospital characteristics with rates of fully guideline-concordant therapy were assessed by using 1-way analysis of variance tests.

To assess trends across hospitals for the association between the use of guideline-concordant therapy and mortality, progression to respiratory failure as measured by the late initiation of invasive mechanical ventilation (day 3 or later), and the length of stay among survivors, we divided the 4.5-year study period into 9 intervals of 6 months each; 292 hospitals that submitted data for all 9 time points were examined in this analysis. Based on the distribution of length of stay in the first time period, we created an indicator variable for extended length of stay with length of stay at or above the 75th percentile, defined as extended. For each hospital at each 6-month interval, we then computed risk-standardized guideline-concordant treatment (RS-treatment) rates and risk-standardized in-hospital outcome rates similar to methods used by the Centers for Medicare and Medicaid Services for public reporting.⁸ For each hospital at each time interval, we estimated a predicted rate of guideline-concordant treatment as the sum of predicted probabilities of guideline-concordant treatment from patient factors and the random intercept for the hospital in which they were admitted. We then calculated the expected rate of guideline-concordant treatment as the sum of expected probabilities of treatment received from patient factors only. RS-treatment was then calculated as the ratio of predicted to expected rates multiplied by the overall unadjusted mean treatment rate from all patients.⁹ We repeated the same modeling strategy to calculate risk-standardized outcome (RS-outcome) rates for each hospital across all time points. All models were adjusted for patient demographics and comorbidities. Similar models using administrative data have moderate discrimination for mortality.¹⁰

We then fit mixed-effects linear models with random hospital intercept and slope across time for the RS-treatment and outcome rates, respectively. From these models, we estimated the mean slope for RS-treatment and for RS-outcome over time. In addition, we estimated a slope or trend over time for each hospital for treatment and for outcome and evaluated the correlation between the treatment and outcome trends.

All analyses were performed using the Statistical Analysis System version 9.4 (SAS Institute Inc., Cary, NC) and STATA release 13 (StataCorp, LLC, College Station, Texas).

In this large, retrospective cohort study, we found that there was a substantial gap between the empiric antibiotics recommended by the ATS and IDSA guidelines and the empiric antibiotics that patients actually received. Over the study period, we saw an increased adherence to guidelines, in spite of growing evidence that HCAP risk factors do not adequately predict which patients are at risk for infection with an MDRO.¹¹ We used this change in antibiotic prescribing behavior over time to determine if there was a clinical impact on patient outcomes and found that at the hospital level, there were no improvements in mortality, excess length of stay, or progression to respiratory failure despite a doubling in guideline-concordant antibiotic use.

At least 2 other large studies have assessed the association between guideline-concordant therapy and outcomes in HCAP.^12,13 Both found that guideline-concordant therapy was associated with increased mortality, despite propensity matching. Both were conducted at the individual patient level by using administrative data, and results were likely affected by unmeasured clinical confounders, with sicker patients being more likely to receive guideline-concordant therapy. Our focus on the outcomes at the hospital level avoids this selection bias because the overall severity of illness of patients at any given hospital would not be expected to change over the study period, while physician uptake of antibiotic prescribing guidelines would be expected to increase over time. Determining the correlation between increases in guideline adherence and changes in patient outcome may offer a better assessment of the impact of guideline adherence. In this regard, our results are similar to those achieved by 1 quality improvement collaborative that was aimed at increasing guideline concordant therapy in ICUs. Despite an increase in guideline concordance from 33% to 47% of patients, they found no change in overall mortality.¹⁴

There were several limitations to our study. We did not have access to microbiologic data, so we were unable to determine which patients had MDRO infection or determine antibiotic-pathogen matching. However, the treating physicians in our study population presumably did not have access to this data at the time of treatment either because the time period we examined was within the first 48 hours of hospitalization, the interval during which cultures are incubating and the patients are being treated empirically. In addition, there may have been HCAP patients that we failed to identify, such as patients who were admitted in the past 90 days to a hospital that does not submit data to Premier. However, it is unlikely that prescribing for such patients should differ systematically from what we observed. While the database draws from 488 hospitals nationwide, it is possible that practices may be different at facilities that are not contained within the Premier database, such as Veterans Administration Hospitals. Similarly, we did not have readings for chest x-rays; hence, there could be some patients in the dataset who did not have pneumonia. However, we tried to overcome this by including only those patients with a principal diagnosis of pneumonia or sepsis with a secondary pneumonia diagnosis, a chest x-ray, and antibiotics administered within the first 48 hours of admission.

There are likely several reasons why so few HCAP patients in our study received guideline-concordant antibiotics. A lack of knowledge about the ATS and IDSA guidelines may have impacted the physicians in our study population. El-Solh et al.¹⁵ surveyed physicians about the ATS-IDSA guidelines 4 years after publication and found that only 45% were familiar with the document. We found that the rate of prescribing at least partially guideline-concordant antibiotics rose steadily over time, supporting the idea that the newness of the guidelines was 1 barrier. Additionally, prior studies have shown that many physicians may not agree with or choose to follow guidelines, with only 20% of physicians indicating that guidelines have a major impact on their clinical decision making,¹⁶ and the majority do not choose HCAP guideline-concordant antibiotics when tested.¹⁷ Alternatively, clinicians may not follow the guidelines because of a belief that the HCAP criteria do not adequately indicate patients who are at risk for MDRO. Previous studies have demonstrated the relative inability of HCAP risk factors to predict patients who harbor MDRO¹⁸ and suggest that better tools such as clinical scoring systems, which include not only the traditional HCAP risk factors but also prior exposure to antibiotics, prior culture data, and a cumulative assessment of both intrinsic and extrinsic factors, could more accurately predict MDRO and lead to a more judicious use of broad-spectrum antimicrobial agents.^19-25 Indeed, these collective findings have led the authors of the recently updated guidelines to remove HCAP as a clinical entity from the hospital-acquired or ventilator-associated pneumonia guidelines and place them instead in the upcoming updated guidelines on the management of CAP.⁵ Of these 3 explanations, the lack of familiarity fits best with our observation that guideline-concordant therapy increased steadily over time with no evidence of reaching a plateau. Ironically, as consensus was building that HCAP is a poor marker for MDROs, routine empiric treatment with vancomycin and piperacillin-tazobactam (“vanco and zosyn”) have become routine in many hospitals. Additional studies are needed to know if this trend has stabilized or reversed.

In conclusion, clinicians in our large, nationally representative sample treated the majority of HCAP patients as though they had CAP. Although there was an increase in the administration of guideline-concordant therapy over time, this increase was not associated with improved outcomes. This study supports the growing consensus that HCAP criteria do not accurately predict which patients benefit from broad-spectrum antibiotics for pneumonia, and most patients fare well with antibiotics targeting common community-acquired organisms.

Disclosure

 This work was supported by grant # R01HS018723 from the Agency for Healthcare Research and Quality. Dr. Lagu is also supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Dr. Lindenauer is supported by grant K24HL132008 from the National Heart, Lung, and Blood Institute. The funding agency had no role in the data acquisition, analysis, or manuscript preparation for this study. Drs. Haessler and Rothberg had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Haessler, Lagu, Lindenauer, Skiest, Zilberberg, Higgins, and Rothberg conceived of the study and analyzed and interpreted the data. Dr. Lindenauer acquired the data. Dr. Pekow and Ms. Priya carried out the statistical analyses. Dr. Haessler drafted the manuscript. All authors critically reviewed the manuscript for accuracy and integrity. All authors certify no potential conflicts of interest. Preliminary results from this study were presented in oral and poster format at IDWeek in 2012 and 2013.

Peripheral intravenous catheter (PIV) insertion is the fastest, simplest, and most cost-effective method to gain vascular access, and it is used for short-term intravenous (IV) fluids, medications, blood products, and contrast media.¹ It is the most common invasive device in hospitalized patients,² with up to 70% of hospital patients receiving a PIV.³ Unacceptable PIV failure rates have been reported as high as 69%.^4-7 Failure is most frequently due to phlebitis (vein wall irritation/inflammation), occlusion (blockage), infiltration or extravasation (IV fluids/vesicant therapy entering surrounding tissue), partial dislodgement or accidental removal, leakage, and infection.^4,6,8 These failures have important implications for patients, who endure the discomfort of PIV complications and catheter replacements, and healthcare staff and budgets.

To reduce the incidence of catheter failure and avoid preventable PIV replacements, a clear understanding of why catheters fail is required. Previous research has identified that catheter gauge,^9-11 insertion site,^12-14 and inserter skill^10,15 have an impact on PIV failure. Limitations of existing research are small study sizes,^16-18 retrospective design,¹⁹ or secondary analysis of an existing data set; all potentially introduce sampling bias.^10,20

To overcome these potential biases, we developed a data collection instrument based on the catheter-associated risk factors described in the literature,^9-11,13 and other potential insertion and maintenance risks for PIV failure (eg, multiple insertion attempts, medications administered), with data collected prospectively. The study aim was to improve patient outcomes by identifying PIV insertion and maintenance risk factors amenable to modification through education or alternative clinical interventions, such as catheter gauge selection or insertion site.

Study Design and Participants

We conducted this prospective cohort study in a large tertiary hospital in Queensland, Australia. Ethics committee approval was obtained from the hospital (HREC/14/QRBW/76) and Griffith University (NRS/26/14/HREC). The study was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12615000738527). Patients in medical and surgical wards were screened Monday, Wednesday, and Friday between October 2014 and December 2015. Patients over 18 years with a PIV (BD Insyte^TM Autoguard^TM BC; Becton Dickinson, Franklin Lakes, NJ) inserted within 24 hours, and who were able to provide written informed consent, were eligible and recruited sequentially. Patients classified as palliative by the treating clinical team were excluded.

Sample Size Calculation

The “10 events per variable” rule was used to determine the sample size required to study 50 potential risk factors.^21,22 This determined that 1000 patients, with an average of 1.5 PIVs each and an expected PIV failure of 30% (500 events), were required.

Data Collection

At recruitment, baseline patient information was collected by a research nurse (ReNs) (demographics, admitting diagnosis, comorbidities, skin type,²³ and vein condition) and entered into an electronic data platform supported by Research Electronic Data Capture (REDCap).²⁴ Baseline data also included catheter variables (eg, gauge, insertion site, catheterized vein) and insertion details (eg, department of insertion, inserting clinician, number of insertion attempts). We included every PIV the participant had during their admission until hospital discharge or insertion of a central venous access device. PIV sites were reviewed Monday, Wednesday, and Friday by ReNs for site complications (eg, redness, pain, swelling, palpable cord). Potential risk factors for failure were also recorded (eg, infusates and additives, antibiotic type and dosage, flushing regimen, number of times the PIV was accessed each day for administration of IV medications or fluids, dressing type and condition, securement method for the catheter and tubing, presence of extension tubing or 3-way taps, patient mobility status, and delirium). A project manager trained and supervised ReNs for protocol compliance and audited study data quality. We considered PIV failure to have occurred if the catheter had complications at removal identified by the ReNs assessment, from medical charts, or by speaking to the patient and beside nurse. We grouped the failures in 1 of 3 types: (1) occlusion or infiltration, defined as blockage, IV fluids moving into surrounding tissue, induration, or swelling greater than 1 cm from the insertion site at or within 24 hours of removal; (2) phlebitis, defined as per clinicians’ definitions or one or more of the following signs and symptoms: pain or tenderness scored at 2 or more on a 1 to 10 increasing severity pain scale, or redness or a palpable cord (either extending greater than 1 cm from the insertion site) at or within 24 hours of PIV removal; and (3) dislodgement (partial or complete). If multiple complications were present, all were recorded.

Statistical Analysis

Data were downloaded from REDcap to Stata 14.2 (StataCorp., College Station, TX) for data management and analysis. Missing data were not imputed. Nominal data observations were collapsed into a single observation per device. Patient and device variables were described as frequencies and proportions, means and standard deviations, or medians and interquartile ranges. Failure incidence rates were calculated, and a Kaplan-Meier survival curve was plotted. In general, Cox proportional hazards models were fitted (Efron method) to handle tied failures (clustering by patient). Variables significant at P < 0.20 on univariable analyses were subjected to multivariable regression. Generally, the largest category was set as referent. Correlations between variables were checked (Spearman’s rank for binary variables, R-squared value of linear regressions for continuous/categorical or continuous/continuous variables). Correlations were considered significant if r > 0.5 and the lower bound of the 95% confidence interval (CI) was >0.5 (where calculated). Covariate interactions were explored, and effects at P < 0.05 noted. The 4 steps of multivariable model building were (1) baseline covariates only with manual stepwise removal of covariates at P ≥ 0.05, (2) treatment covariates only with manual stepwise removal of covariates at P ≥ 0.05, (3) a combination of the derived models from (1) and (2) and manual stepwise removal of covariates at P ≥ 0.05, and (4) manual stepwise addition and removal (at P ≥ 0.05) of variables dropped during the previous steps and interaction testing. Final models were checked as follows: global proportional-hazards assumption test, concordance probability (that predictions and outcomes were in agreement), and Nelson-Aalen cumulative hazard function plotted against the Cox-Snell residuals.

Patient Characteristics

In total, 1000 patients with 1578 PIVs were recruited. The average age was 54 years and the majority were surgical patients (673; 67%). Almost half of patients (455; 46%) had 2 or more comorbidities, and 334 (33%) were obese (body mass index greater than 30). Sample characteristics are shown by the type of catheter failure in Table 1.

PIV Characteristics

All 1578 PIVs were followed until removal, with only 7 PIVs (0.44%) having missing data for the 3 outcomes of interest (these were coded as nonfailures for analysis). Sixty percent of participants had more than 1 PIV followed in the study. Doctors and physicians inserted 1278 (83%) catheters. A total of 550 (35%) were placed in the ward, with 428 (28%) inserted in the emergency department or ambulance. A third of the catheters (540; 34%) were 18-gauge or larger in diameter, and 1000 (64%) were located in the cubital fossa or hand. Multiple insertion attempts were required to place 315 (23%) PIVs. No PIVs were inserted with ultrasound, as this is rarely used in this hospital. The flushing policy was for the administration of 9% sodium chloride every 8 hours if no IV medications or fluids were ordered. Table 2 contains further details of device-related characteristics. Although the hospital policy was for catheter removal by 72 hours, dwell time ranged from <1 to 14 days, with an average of 2.4 days.

PIV Complications

Catheter failure (any cause) occurred in 512 (32%) catheters, which is a failure rate of 136 per 1000 catheter days (95% CI, 125-148). A total of 346 patients out of 1000 (35%) had at least 1 failed PIV during the study. Failures were 267 phlebitis (17%), 228 occlusion/infiltration (14%), and/or 154 dislodgement (10%; Figure), with some PIVs exhibiting multiple concurrent complications (Table 2).

Multivariable AnalysisOcclusion/Infiltration

The multivariable analysis (Table 3) showed occlusion or infiltration was statistically significantly associated with female patients (hazard ratio [HR], 1.48; 95% CI, 1.10-2.00), with a 22-gauge catheter (HR, 1.43; 95% CI, 1.02-2.00), IV flucloxacillin (HR, 1.98; 95% CI, 1.19-3.31), and with frequent PIV access (HR, 1.12; 95% CI, 1.04-1.21; ie, with each increase of 1 in the mean medications/fluids administrations per day, relative PIV failure increased 112%). Less occlusion and infiltration were statistically significantly associated with securement by using additional nonsterile tape (HR, 0.46; 95% CI, 0.33-0.63), elasticized tubular bandages (HR, 0.49; 95% CI, 0.35-0.70 ), or other types of additional securement for the PIV (HR, 0.35; 95% CI, 0.26-0.47).

Phlebitis

Phlebitis was statistically significantly associated with female patients (HR, 1.81; 95% CI, 1.40-2.35), bruising at the insertion site (HR, 2.16; 95% CI, 1.26-3.71), insertion in patients’ dominant side (HR, 1.39; 95% CI, 1.09-1.77), IV flucloxicillin (HR, 2.01; 95% CI, 1.26-3.21), or with frequent PIV access (HR, 1.14; 95% CI, 1.08-1.21). Older age, (HR, 0.99; 95% CI, 0.98-0.99; ie, each year older was associated with 1% less phlebitis), securement with additional nonsterile tape (HR, 0.63; 95% CI, 0.48-0.82) or with any other additional securement (HR, 0.53; 95% CI, 0.39-0.70), or the administration of IV cephazolin (HR, 0.63; 95% CI, 0.44-0.89) were associated with lower phlebitis risk.

Dislodgement

Statistically significant predictors associated with an increased risk of PIV dislodgement included paramedic insertion (HR, 1.78; 95% CI, 1.03-3.06) and frequent PIV access (HR, 1.11; 95% CI, 1.03-1.20). A decreased risk was associated with the additional securement of the PIV, including nonsterile tape (HR, 0.44; 95% CI, 0.31-0.63) or other forms of additional securement (HR, 0.32; 95% CI, 0.22-0.46).

One in 3 PIVs failed in this study, with phlebitis as the most common cause of PIV failure. The 17% phlebitis rate reflected clinician-reported phlebitis or phlebitis observed by research staff using a 1-criteria definition because any sign or symptom can trigger PIV removal (eg, pain), even if other signs or symptoms are not present. Reported phlebitis rates are lower if definitions require 2 signs or symptoms.^4,6 With over 71 different phlebitis assessment scales in use, and none well validated, the best method for diagnosing phlebitis remains unclear and explains the variation in reported rates.²⁵ Occlusion/infiltration and dislodgement were also highly prevalent forms of PIV failure at 14% and 10%, respectively. Occlusion and infiltration were combined because clinical staff use these terms interchangeably, and differential diagnostic tools are not used in practice. Both result in the same outcome (therapy interruption and PIV removal), and this combination of outcomes has been used previously.²³ No PIV-associated bloodstream infections occurred, despite the heightened awareness of these infections in the literature.³

Females had significantly more occlusion/infiltration and phlebitis than males, in keeping with previous studies.^7,9,10 This could be because of females’ smaller vein caliber, although the effect remained after adjustment for PIV gauge.^7,26 The effect of aging on vascular endothelium and structural integrity may explain the observed decrease in phlebitis of 1% with each older year of age.²⁷ However, gender and age effects could be explained by psychosocial factors (eg, older people may be less likely to admit pain, or we may question them less sympathetically), but, regardless, women and younger patients should be monitored more closely.

We found 22-gauge catheters were more likely to fail from occlusion/infiltration than other sizes. This confirms similar findings from Abolfotouh et al.⁹ PIV gauge selection for this study was made at the inserter’s discretion and may be confounded by smaller vein size, which was not measured. In addition, risk may be because of smaller gauge alone or also more influenced by the shorter length of the studied 22-gauge (25 mm) than the <20-gauge catheters (30 mm). These results question international guidelines, which currently recommend the smallest gauge peripheral catheter possible,^28,29 and randomized trials are needed. Although practice varies between inserters, some preferentially cannulate the nondominant limb. We are not aware of previous studies on this practice; however, our results support this approach.

Flucloxacillin was associated with a 2-fold increase in occlusion/infiltration and phlebitis. Although multiple studies have reported IV medications^9,11 and IV antibiotics^10,30,31 as risk factors for PIV failure, none have identified flucloxacillin as an independent risk factor. IV flucloxacillin is recommended for reconstitution as 1 g in 15 mL to 20 mL of sterile water, and injection over 3 to 4 minutes, although this may not be adhered to in practice. Alternative administration regimes or improved adherence to current policy may be needed. An exception to the relationship between IV antibiotics and catheter failure was IV cephazolin, associated with 40% relatively less phlebitis. This may be a spurious finding because the administration, pH, and osmolality of cephazolin are similar to other IV antibiotics.

The more PIVs that were accessed per day, whether for infusions or medications, the more failure occurred from occlusion/infiltration, phlebitis, and dislodgement. This suggests that peripheral veins are easily damaged and/or inflamed by the influx of fluids or medications. Lower injection pressures or the timely transfer to oral medications may limit this problem. Flushing regimens may also assist because practice varies greatly, and questions on whether slow continuous flush infusion or intermittent manual flushing are more vein-protective, and the optimal flush volume, frequency, and technique (eg, pulsatile) remain.^32,33 Manual handling for frequent access may loosen dressings and securement, thus explaining the observed association between frequent access and catheter dislodgement. Finally, the association between use and failure may indicate that many of these patients were not suitable for a PIV, and different approaches (eg, ultrasound-guided insertion) or a midline may have been a superior option. There is growing emphasis on the need for better preinsertion assessment and selection of the most appropriate device for the patient and the IV treatment required.³⁴

Suboptimal dressings or securements are not unusual in hospitals.³⁵ Despite our policy of PIV securement with bordered transparent dressings, we found 4 dressing types in use. In addition, we found almost 50% of PIVs had an additional (secondary) securement, and this was associated with significantly less PIV failure of all 3 types. This suggests that 1 or more of nonsterile tape, elasticized tubular bandages, or other securement (eg, bandage or second transparent dressing) can reduce PIV failure, although a randomized trial is lacking.³⁶ Whether the dressing was failing and required reinforcement or hospital staff lacked confidence in the dressing and placed additional securement preventatively is unclear. Both PIV failure and PIV dressing failure are common, and further research into superior PIV products and practices is urgently needed. Paramedic insertions had a higher risk of dislodgement, suggesting that the increased emphasis on securement should start in the prehospital setting.

While multiple or difficult insertion attempts were not associated with PIV failure, insertions were not directly observed, and clinicians may have underreported attempts. In contrast, insertion-related bruising (a surrogate for difficult insertion) was associated with more than double the incidence of phlebitis. The long-term implications of multiple insertion attempts on patient’s vasculature are unclear, but we believe first time PIV insertion is important to patients and of interest to clinicians. A recent systematic review of strategies associated with first attempt PIV insertion success in an emergency department found little evidence for effective strategies and recommended further research.³⁷

The overall PIV failure rate in our study was 32%, lower than the 35% to 40% failure observed in our previous randomized controlled trials, which had more stringent inclusion and exclusion criteria (eg, longer predicted duration of therapy).^6,38 The implications for patients and costs to the organization of frequent catheter replacement demonstrate urgent need for further research in this area of practice.³⁹ A strength of this study is that all PIVs, regardless of the expected length of dwell time or reason for insertion, were eligible for inclusion, providing more generalizable results. The PIV failure rate of 32% is concerning because these failures trigger treatment delays and replacement insertions, with significant increased labor and equipment costs. The mean cost of PIV replacement has been costed at AUD $69.30 or US $51.92 (as per 2010 $ value) per episode of IV treatment.⁴⁰ For our hospital, which uses 200,000 PIVs per year, the current level of PIV failure suggests almost AU $5.5 (US $4.1) million in waste annually at this site alone.

The additional strengths of this study include the extensive information collected prospectively about PIV insertion and maintenance, including information on who inserted the PIV, IV medications administered, and PIV dressings used. Limitations were the population of surgical and medical patients in 1 tertiary hospital, which may not be generalizable to other settings.

Our study confirms the high rate of catheter failure in acute care hospitals, validates existing evidence related to PIV failure, and identifies new, potentially modifiable risk factors to improve PIV insertion and management. Implications for future research were also identified.

Acknowledgments

The researchers acknowledge and thank the nurses and patients involved in this study. The authors would also like to acknowledge Becton Dickinson for partly funding this study in the form of an unrestricted grant-in-aid paid to Griffith University. Becton Dickinson did not design the study protocol, collect or analyze data, and did not prepare or review the manuscript.

Disclosure

 On behalf of NM and CMR, Griffith University has received unrestricted educational and research grants and consultancy payment for lectures from 3M and Becton Dickinson. On behalf of NM, MC, and CMR, Griffith University has received unrestricted investigator-initiated research grants from Centurion Medical Products and Entrotech Lifesciences (manufacturers of PIV dressings) and Becton Dickinson (manufacturer of PIVs). On behalf of MC, Griffith University has received a consultancy payment to develop education material from Baxter. On behalf of CMR, Griffith University has received unrestricted donations or investigator initiated research grants unrelated to this research from Adhezion, Angiodynamics, Baxter, Carefusion, Cook Medical, Hospira, Mayo, Smiths Medical, and Vygon. On behalf of CMR, Griffith University has received consultancy payments for educational lectures or professional opinion from B. Braun, Bard, Carefusion, Mayo, ResQDevices, and Smiths Medical. On behalf of EL, Griffith University has received consultancy payments for educational lecture from 3M. On behalf of MC, Griffith University has received a consultancy payment to develop education material from Baxter. As this was an observational study, no products were trialed in this study. JW and GM have no conflicts of interest.

Peripheral intravenous catheter (PIV) insertion is the fastest, simplest, and most cost-effective method to gain vascular access, and it is used for short-term intravenous (IV) fluids, medications, blood products, and contrast media.¹ It is the most common invasive device in hospitalized patients,² with up to 70% of hospital patients receiving a PIV.³ Unacceptable PIV failure rates have been reported as high as 69%.^4-7 Failure is most frequently due to phlebitis (vein wall irritation/inflammation), occlusion (blockage), infiltration or extravasation (IV fluids/vesicant therapy entering surrounding tissue), partial dislodgement or accidental removal, leakage, and infection.^4,6,8 These failures have important implications for patients, who endure the discomfort of PIV complications and catheter replacements, and healthcare staff and budgets.

To reduce the incidence of catheter failure and avoid preventable PIV replacements, a clear understanding of why catheters fail is required. Previous research has identified that catheter gauge,^9-11 insertion site,^12-14 and inserter skill^10,15 have an impact on PIV failure. Limitations of existing research are small study sizes,^16-18 retrospective design,¹⁹ or secondary analysis of an existing data set; all potentially introduce sampling bias.^10,20

To overcome these potential biases, we developed a data collection instrument based on the catheter-associated risk factors described in the literature,^9-11,13 and other potential insertion and maintenance risks for PIV failure (eg, multiple insertion attempts, medications administered), with data collected prospectively. The study aim was to improve patient outcomes by identifying PIV insertion and maintenance risk factors amenable to modification through education or alternative clinical interventions, such as catheter gauge selection or insertion site.

Study Design and Participants

We conducted this prospective cohort study in a large tertiary hospital in Queensland, Australia. Ethics committee approval was obtained from the hospital (HREC/14/QRBW/76) and Griffith University (NRS/26/14/HREC). The study was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12615000738527). Patients in medical and surgical wards were screened Monday, Wednesday, and Friday between October 2014 and December 2015. Patients over 18 years with a PIV (BD Insyte^TM Autoguard^TM BC; Becton Dickinson, Franklin Lakes, NJ) inserted within 24 hours, and who were able to provide written informed consent, were eligible and recruited sequentially. Patients classified as palliative by the treating clinical team were excluded.

Sample Size Calculation

The “10 events per variable” rule was used to determine the sample size required to study 50 potential risk factors.^21,22 This determined that 1000 patients, with an average of 1.5 PIVs each and an expected PIV failure of 30% (500 events), were required.

Data Collection

At recruitment, baseline patient information was collected by a research nurse (ReNs) (demographics, admitting diagnosis, comorbidities, skin type,²³ and vein condition) and entered into an electronic data platform supported by Research Electronic Data Capture (REDCap).²⁴ Baseline data also included catheter variables (eg, gauge, insertion site, catheterized vein) and insertion details (eg, department of insertion, inserting clinician, number of insertion attempts). We included every PIV the participant had during their admission until hospital discharge or insertion of a central venous access device. PIV sites were reviewed Monday, Wednesday, and Friday by ReNs for site complications (eg, redness, pain, swelling, palpable cord). Potential risk factors for failure were also recorded (eg, infusates and additives, antibiotic type and dosage, flushing regimen, number of times the PIV was accessed each day for administration of IV medications or fluids, dressing type and condition, securement method for the catheter and tubing, presence of extension tubing or 3-way taps, patient mobility status, and delirium). A project manager trained and supervised ReNs for protocol compliance and audited study data quality. We considered PIV failure to have occurred if the catheter had complications at removal identified by the ReNs assessment, from medical charts, or by speaking to the patient and beside nurse. We grouped the failures in 1 of 3 types: (1) occlusion or infiltration, defined as blockage, IV fluids moving into surrounding tissue, induration, or swelling greater than 1 cm from the insertion site at or within 24 hours of removal; (2) phlebitis, defined as per clinicians’ definitions or one or more of the following signs and symptoms: pain or tenderness scored at 2 or more on a 1 to 10 increasing severity pain scale, or redness or a palpable cord (either extending greater than 1 cm from the insertion site) at or within 24 hours of PIV removal; and (3) dislodgement (partial or complete). If multiple complications were present, all were recorded.

Statistical Analysis

Data were downloaded from REDcap to Stata 14.2 (StataCorp., College Station, TX) for data management and analysis. Missing data were not imputed. Nominal data observations were collapsed into a single observation per device. Patient and device variables were described as frequencies and proportions, means and standard deviations, or medians and interquartile ranges. Failure incidence rates were calculated, and a Kaplan-Meier survival curve was plotted. In general, Cox proportional hazards models were fitted (Efron method) to handle tied failures (clustering by patient). Variables significant at P < 0.20 on univariable analyses were subjected to multivariable regression. Generally, the largest category was set as referent. Correlations between variables were checked (Spearman’s rank for binary variables, R-squared value of linear regressions for continuous/categorical or continuous/continuous variables). Correlations were considered significant if r > 0.5 and the lower bound of the 95% confidence interval (CI) was >0.5 (where calculated). Covariate interactions were explored, and effects at P < 0.05 noted. The 4 steps of multivariable model building were (1) baseline covariates only with manual stepwise removal of covariates at P ≥ 0.05, (2) treatment covariates only with manual stepwise removal of covariates at P ≥ 0.05, (3) a combination of the derived models from (1) and (2) and manual stepwise removal of covariates at P ≥ 0.05, and (4) manual stepwise addition and removal (at P ≥ 0.05) of variables dropped during the previous steps and interaction testing. Final models were checked as follows: global proportional-hazards assumption test, concordance probability (that predictions and outcomes were in agreement), and Nelson-Aalen cumulative hazard function plotted against the Cox-Snell residuals.

Patient Characteristics

In total, 1000 patients with 1578 PIVs were recruited. The average age was 54 years and the majority were surgical patients (673; 67%). Almost half of patients (455; 46%) had 2 or more comorbidities, and 334 (33%) were obese (body mass index greater than 30). Sample characteristics are shown by the type of catheter failure in Table 1.

PIV Characteristics

All 1578 PIVs were followed until removal, with only 7 PIVs (0.44%) having missing data for the 3 outcomes of interest (these were coded as nonfailures for analysis). Sixty percent of participants had more than 1 PIV followed in the study. Doctors and physicians inserted 1278 (83%) catheters. A total of 550 (35%) were placed in the ward, with 428 (28%) inserted in the emergency department or ambulance. A third of the catheters (540; 34%) were 18-gauge or larger in diameter, and 1000 (64%) were located in the cubital fossa or hand. Multiple insertion attempts were required to place 315 (23%) PIVs. No PIVs were inserted with ultrasound, as this is rarely used in this hospital. The flushing policy was for the administration of 9% sodium chloride every 8 hours if no IV medications or fluids were ordered. Table 2 contains further details of device-related characteristics. Although the hospital policy was for catheter removal by 72 hours, dwell time ranged from <1 to 14 days, with an average of 2.4 days.

PIV Complications

Catheter failure (any cause) occurred in 512 (32%) catheters, which is a failure rate of 136 per 1000 catheter days (95% CI, 125-148). A total of 346 patients out of 1000 (35%) had at least 1 failed PIV during the study. Failures were 267 phlebitis (17%), 228 occlusion/infiltration (14%), and/or 154 dislodgement (10%; Figure), with some PIVs exhibiting multiple concurrent complications (Table 2).

Multivariable AnalysisOcclusion/Infiltration

The multivariable analysis (Table 3) showed occlusion or infiltration was statistically significantly associated with female patients (hazard ratio [HR], 1.48; 95% CI, 1.10-2.00), with a 22-gauge catheter (HR, 1.43; 95% CI, 1.02-2.00), IV flucloxacillin (HR, 1.98; 95% CI, 1.19-3.31), and with frequent PIV access (HR, 1.12; 95% CI, 1.04-1.21; ie, with each increase of 1 in the mean medications/fluids administrations per day, relative PIV failure increased 112%). Less occlusion and infiltration were statistically significantly associated with securement by using additional nonsterile tape (HR, 0.46; 95% CI, 0.33-0.63), elasticized tubular bandages (HR, 0.49; 95% CI, 0.35-0.70 ), or other types of additional securement for the PIV (HR, 0.35; 95% CI, 0.26-0.47).

Phlebitis

Phlebitis was statistically significantly associated with female patients (HR, 1.81; 95% CI, 1.40-2.35), bruising at the insertion site (HR, 2.16; 95% CI, 1.26-3.71), insertion in patients’ dominant side (HR, 1.39; 95% CI, 1.09-1.77), IV flucloxicillin (HR, 2.01; 95% CI, 1.26-3.21), or with frequent PIV access (HR, 1.14; 95% CI, 1.08-1.21). Older age, (HR, 0.99; 95% CI, 0.98-0.99; ie, each year older was associated with 1% less phlebitis), securement with additional nonsterile tape (HR, 0.63; 95% CI, 0.48-0.82) or with any other additional securement (HR, 0.53; 95% CI, 0.39-0.70), or the administration of IV cephazolin (HR, 0.63; 95% CI, 0.44-0.89) were associated with lower phlebitis risk.

Dislodgement

Statistically significant predictors associated with an increased risk of PIV dislodgement included paramedic insertion (HR, 1.78; 95% CI, 1.03-3.06) and frequent PIV access (HR, 1.11; 95% CI, 1.03-1.20). A decreased risk was associated with the additional securement of the PIV, including nonsterile tape (HR, 0.44; 95% CI, 0.31-0.63) or other forms of additional securement (HR, 0.32; 95% CI, 0.22-0.46).

One in 3 PIVs failed in this study, with phlebitis as the most common cause of PIV failure. The 17% phlebitis rate reflected clinician-reported phlebitis or phlebitis observed by research staff using a 1-criteria definition because any sign or symptom can trigger PIV removal (eg, pain), even if other signs or symptoms are not present. Reported phlebitis rates are lower if definitions require 2 signs or symptoms.^4,6 With over 71 different phlebitis assessment scales in use, and none well validated, the best method for diagnosing phlebitis remains unclear and explains the variation in reported rates.²⁵ Occlusion/infiltration and dislodgement were also highly prevalent forms of PIV failure at 14% and 10%, respectively. Occlusion and infiltration were combined because clinical staff use these terms interchangeably, and differential diagnostic tools are not used in practice. Both result in the same outcome (therapy interruption and PIV removal), and this combination of outcomes has been used previously.²³ No PIV-associated bloodstream infections occurred, despite the heightened awareness of these infections in the literature.³

Females had significantly more occlusion/infiltration and phlebitis than males, in keeping with previous studies.^7,9,10 This could be because of females’ smaller vein caliber, although the effect remained after adjustment for PIV gauge.^7,26 The effect of aging on vascular endothelium and structural integrity may explain the observed decrease in phlebitis of 1% with each older year of age.²⁷ However, gender and age effects could be explained by psychosocial factors (eg, older people may be less likely to admit pain, or we may question them less sympathetically), but, regardless, women and younger patients should be monitored more closely.

We found 22-gauge catheters were more likely to fail from occlusion/infiltration than other sizes. This confirms similar findings from Abolfotouh et al.⁹ PIV gauge selection for this study was made at the inserter’s discretion and may be confounded by smaller vein size, which was not measured. In addition, risk may be because of smaller gauge alone or also more influenced by the shorter length of the studied 22-gauge (25 mm) than the <20-gauge catheters (30 mm). These results question international guidelines, which currently recommend the smallest gauge peripheral catheter possible,^28,29 and randomized trials are needed. Although practice varies between inserters, some preferentially cannulate the nondominant limb. We are not aware of previous studies on this practice; however, our results support this approach.

Flucloxacillin was associated with a 2-fold increase in occlusion/infiltration and phlebitis. Although multiple studies have reported IV medications^9,11 and IV antibiotics^10,30,31 as risk factors for PIV failure, none have identified flucloxacillin as an independent risk factor. IV flucloxacillin is recommended for reconstitution as 1 g in 15 mL to 20 mL of sterile water, and injection over 3 to 4 minutes, although this may not be adhered to in practice. Alternative administration regimes or improved adherence to current policy may be needed. An exception to the relationship between IV antibiotics and catheter failure was IV cephazolin, associated with 40% relatively less phlebitis. This may be a spurious finding because the administration, pH, and osmolality of cephazolin are similar to other IV antibiotics.

The more PIVs that were accessed per day, whether for infusions or medications, the more failure occurred from occlusion/infiltration, phlebitis, and dislodgement. This suggests that peripheral veins are easily damaged and/or inflamed by the influx of fluids or medications. Lower injection pressures or the timely transfer to oral medications may limit this problem. Flushing regimens may also assist because practice varies greatly, and questions on whether slow continuous flush infusion or intermittent manual flushing are more vein-protective, and the optimal flush volume, frequency, and technique (eg, pulsatile) remain.^32,33 Manual handling for frequent access may loosen dressings and securement, thus explaining the observed association between frequent access and catheter dislodgement. Finally, the association between use and failure may indicate that many of these patients were not suitable for a PIV, and different approaches (eg, ultrasound-guided insertion) or a midline may have been a superior option. There is growing emphasis on the need for better preinsertion assessment and selection of the most appropriate device for the patient and the IV treatment required.³⁴

Suboptimal dressings or securements are not unusual in hospitals.³⁵ Despite our policy of PIV securement with bordered transparent dressings, we found 4 dressing types in use. In addition, we found almost 50% of PIVs had an additional (secondary) securement, and this was associated with significantly less PIV failure of all 3 types. This suggests that 1 or more of nonsterile tape, elasticized tubular bandages, or other securement (eg, bandage or second transparent dressing) can reduce PIV failure, although a randomized trial is lacking.³⁶ Whether the dressing was failing and required reinforcement or hospital staff lacked confidence in the dressing and placed additional securement preventatively is unclear. Both PIV failure and PIV dressing failure are common, and further research into superior PIV products and practices is urgently needed. Paramedic insertions had a higher risk of dislodgement, suggesting that the increased emphasis on securement should start in the prehospital setting.

While multiple or difficult insertion attempts were not associated with PIV failure, insertions were not directly observed, and clinicians may have underreported attempts. In contrast, insertion-related bruising (a surrogate for difficult insertion) was associated with more than double the incidence of phlebitis. The long-term implications of multiple insertion attempts on patient’s vasculature are unclear, but we believe first time PIV insertion is important to patients and of interest to clinicians. A recent systematic review of strategies associated with first attempt PIV insertion success in an emergency department found little evidence for effective strategies and recommended further research.³⁷

The overall PIV failure rate in our study was 32%, lower than the 35% to 40% failure observed in our previous randomized controlled trials, which had more stringent inclusion and exclusion criteria (eg, longer predicted duration of therapy).^6,38 The implications for patients and costs to the organization of frequent catheter replacement demonstrate urgent need for further research in this area of practice.³⁹ A strength of this study is that all PIVs, regardless of the expected length of dwell time or reason for insertion, were eligible for inclusion, providing more generalizable results. The PIV failure rate of 32% is concerning because these failures trigger treatment delays and replacement insertions, with significant increased labor and equipment costs. The mean cost of PIV replacement has been costed at AUD $69.30 or US $51.92 (as per 2010 $ value) per episode of IV treatment.⁴⁰ For our hospital, which uses 200,000 PIVs per year, the current level of PIV failure suggests almost AU $5.5 (US $4.1) million in waste annually at this site alone.

The additional strengths of this study include the extensive information collected prospectively about PIV insertion and maintenance, including information on who inserted the PIV, IV medications administered, and PIV dressings used. Limitations were the population of surgical and medical patients in 1 tertiary hospital, which may not be generalizable to other settings.

Our study confirms the high rate of catheter failure in acute care hospitals, validates existing evidence related to PIV failure, and identifies new, potentially modifiable risk factors to improve PIV insertion and management. Implications for future research were also identified.

Acknowledgments

The researchers acknowledge and thank the nurses and patients involved in this study. The authors would also like to acknowledge Becton Dickinson for partly funding this study in the form of an unrestricted grant-in-aid paid to Griffith University. Becton Dickinson did not design the study protocol, collect or analyze data, and did not prepare or review the manuscript.

Disclosure

 On behalf of NM and CMR, Griffith University has received unrestricted educational and research grants and consultancy payment for lectures from 3M and Becton Dickinson. On behalf of NM, MC, and CMR, Griffith University has received unrestricted investigator-initiated research grants from Centurion Medical Products and Entrotech Lifesciences (manufacturers of PIV dressings) and Becton Dickinson (manufacturer of PIVs). On behalf of MC, Griffith University has received a consultancy payment to develop education material from Baxter. On behalf of CMR, Griffith University has received unrestricted donations or investigator initiated research grants unrelated to this research from Adhezion, Angiodynamics, Baxter, Carefusion, Cook Medical, Hospira, Mayo, Smiths Medical, and Vygon. On behalf of CMR, Griffith University has received consultancy payments for educational lectures or professional opinion from B. Braun, Bard, Carefusion, Mayo, ResQDevices, and Smiths Medical. On behalf of EL, Griffith University has received consultancy payments for educational lecture from 3M. On behalf of MC, Griffith University has received a consultancy payment to develop education material from Baxter. As this was an observational study, no products were trialed in this study. JW and GM have no conflicts of interest.

Peripheral intravenous catheter (PIV) insertion is the fastest, simplest, and most cost-effective method to gain vascular access, and it is used for short-term intravenous (IV) fluids, medications, blood products, and contrast media.¹ It is the most common invasive device in hospitalized patients,² with up to 70% of hospital patients receiving a PIV.³ Unacceptable PIV failure rates have been reported as high as 69%.^4-7 Failure is most frequently due to phlebitis (vein wall irritation/inflammation), occlusion (blockage), infiltration or extravasation (IV fluids/vesicant therapy entering surrounding tissue), partial dislodgement or accidental removal, leakage, and infection.^4,6,8 These failures have important implications for patients, who endure the discomfort of PIV complications and catheter replacements, and healthcare staff and budgets.

To reduce the incidence of catheter failure and avoid preventable PIV replacements, a clear understanding of why catheters fail is required. Previous research has identified that catheter gauge,^9-11 insertion site,^12-14 and inserter skill^10,15 have an impact on PIV failure. Limitations of existing research are small study sizes,^16-18 retrospective design,¹⁹ or secondary analysis of an existing data set; all potentially introduce sampling bias.^10,20

To overcome these potential biases, we developed a data collection instrument based on the catheter-associated risk factors described in the literature,^9-11,13 and other potential insertion and maintenance risks for PIV failure (eg, multiple insertion attempts, medications administered), with data collected prospectively. The study aim was to improve patient outcomes by identifying PIV insertion and maintenance risk factors amenable to modification through education or alternative clinical interventions, such as catheter gauge selection or insertion site.

Study Design and Participants

We conducted this prospective cohort study in a large tertiary hospital in Queensland, Australia. Ethics committee approval was obtained from the hospital (HREC/14/QRBW/76) and Griffith University (NRS/26/14/HREC). The study was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12615000738527). Patients in medical and surgical wards were screened Monday, Wednesday, and Friday between October 2014 and December 2015. Patients over 18 years with a PIV (BD Insyte^TM Autoguard^TM BC; Becton Dickinson, Franklin Lakes, NJ) inserted within 24 hours, and who were able to provide written informed consent, were eligible and recruited sequentially. Patients classified as palliative by the treating clinical team were excluded.

Sample Size Calculation

The “10 events per variable” rule was used to determine the sample size required to study 50 potential risk factors.^21,22 This determined that 1000 patients, with an average of 1.5 PIVs each and an expected PIV failure of 30% (500 events), were required.

Data Collection

At recruitment, baseline patient information was collected by a research nurse (ReNs) (demographics, admitting diagnosis, comorbidities, skin type,²³ and vein condition) and entered into an electronic data platform supported by Research Electronic Data Capture (REDCap).²⁴ Baseline data also included catheter variables (eg, gauge, insertion site, catheterized vein) and insertion details (eg, department of insertion, inserting clinician, number of insertion attempts). We included every PIV the participant had during their admission until hospital discharge or insertion of a central venous access device. PIV sites were reviewed Monday, Wednesday, and Friday by ReNs for site complications (eg, redness, pain, swelling, palpable cord). Potential risk factors for failure were also recorded (eg, infusates and additives, antibiotic type and dosage, flushing regimen, number of times the PIV was accessed each day for administration of IV medications or fluids, dressing type and condition, securement method for the catheter and tubing, presence of extension tubing or 3-way taps, patient mobility status, and delirium). A project manager trained and supervised ReNs for protocol compliance and audited study data quality. We considered PIV failure to have occurred if the catheter had complications at removal identified by the ReNs assessment, from medical charts, or by speaking to the patient and beside nurse. We grouped the failures in 1 of 3 types: (1) occlusion or infiltration, defined as blockage, IV fluids moving into surrounding tissue, induration, or swelling greater than 1 cm from the insertion site at or within 24 hours of removal; (2) phlebitis, defined as per clinicians’ definitions or one or more of the following signs and symptoms: pain or tenderness scored at 2 or more on a 1 to 10 increasing severity pain scale, or redness or a palpable cord (either extending greater than 1 cm from the insertion site) at or within 24 hours of PIV removal; and (3) dislodgement (partial or complete). If multiple complications were present, all were recorded.

Statistical Analysis

Data were downloaded from REDcap to Stata 14.2 (StataCorp., College Station, TX) for data management and analysis. Missing data were not imputed. Nominal data observations were collapsed into a single observation per device. Patient and device variables were described as frequencies and proportions, means and standard deviations, or medians and interquartile ranges. Failure incidence rates were calculated, and a Kaplan-Meier survival curve was plotted. In general, Cox proportional hazards models were fitted (Efron method) to handle tied failures (clustering by patient). Variables significant at P < 0.20 on univariable analyses were subjected to multivariable regression. Generally, the largest category was set as referent. Correlations between variables were checked (Spearman’s rank for binary variables, R-squared value of linear regressions for continuous/categorical or continuous/continuous variables). Correlations were considered significant if r > 0.5 and the lower bound of the 95% confidence interval (CI) was >0.5 (where calculated). Covariate interactions were explored, and effects at P < 0.05 noted. The 4 steps of multivariable model building were (1) baseline covariates only with manual stepwise removal of covariates at P ≥ 0.05, (2) treatment covariates only with manual stepwise removal of covariates at P ≥ 0.05, (3) a combination of the derived models from (1) and (2) and manual stepwise removal of covariates at P ≥ 0.05, and (4) manual stepwise addition and removal (at P ≥ 0.05) of variables dropped during the previous steps and interaction testing. Final models were checked as follows: global proportional-hazards assumption test, concordance probability (that predictions and outcomes were in agreement), and Nelson-Aalen cumulative hazard function plotted against the Cox-Snell residuals.

Patient Characteristics

In total, 1000 patients with 1578 PIVs were recruited. The average age was 54 years and the majority were surgical patients (673; 67%). Almost half of patients (455; 46%) had 2 or more comorbidities, and 334 (33%) were obese (body mass index greater than 30). Sample characteristics are shown by the type of catheter failure in Table 1.

PIV Characteristics

All 1578 PIVs were followed until removal, with only 7 PIVs (0.44%) having missing data for the 3 outcomes of interest (these were coded as nonfailures for analysis). Sixty percent of participants had more than 1 PIV followed in the study. Doctors and physicians inserted 1278 (83%) catheters. A total of 550 (35%) were placed in the ward, with 428 (28%) inserted in the emergency department or ambulance. A third of the catheters (540; 34%) were 18-gauge or larger in diameter, and 1000 (64%) were located in the cubital fossa or hand. Multiple insertion attempts were required to place 315 (23%) PIVs. No PIVs were inserted with ultrasound, as this is rarely used in this hospital. The flushing policy was for the administration of 9% sodium chloride every 8 hours if no IV medications or fluids were ordered. Table 2 contains further details of device-related characteristics. Although the hospital policy was for catheter removal by 72 hours, dwell time ranged from <1 to 14 days, with an average of 2.4 days.

PIV Complications

Catheter failure (any cause) occurred in 512 (32%) catheters, which is a failure rate of 136 per 1000 catheter days (95% CI, 125-148). A total of 346 patients out of 1000 (35%) had at least 1 failed PIV during the study. Failures were 267 phlebitis (17%), 228 occlusion/infiltration (14%), and/or 154 dislodgement (10%; Figure), with some PIVs exhibiting multiple concurrent complications (Table 2).

Multivariable AnalysisOcclusion/Infiltration

The multivariable analysis (Table 3) showed occlusion or infiltration was statistically significantly associated with female patients (hazard ratio [HR], 1.48; 95% CI, 1.10-2.00), with a 22-gauge catheter (HR, 1.43; 95% CI, 1.02-2.00), IV flucloxacillin (HR, 1.98; 95% CI, 1.19-3.31), and with frequent PIV access (HR, 1.12; 95% CI, 1.04-1.21; ie, with each increase of 1 in the mean medications/fluids administrations per day, relative PIV failure increased 112%). Less occlusion and infiltration were statistically significantly associated with securement by using additional nonsterile tape (HR, 0.46; 95% CI, 0.33-0.63), elasticized tubular bandages (HR, 0.49; 95% CI, 0.35-0.70 ), or other types of additional securement for the PIV (HR, 0.35; 95% CI, 0.26-0.47).

Phlebitis

Phlebitis was statistically significantly associated with female patients (HR, 1.81; 95% CI, 1.40-2.35), bruising at the insertion site (HR, 2.16; 95% CI, 1.26-3.71), insertion in patients’ dominant side (HR, 1.39; 95% CI, 1.09-1.77), IV flucloxicillin (HR, 2.01; 95% CI, 1.26-3.21), or with frequent PIV access (HR, 1.14; 95% CI, 1.08-1.21). Older age, (HR, 0.99; 95% CI, 0.98-0.99; ie, each year older was associated with 1% less phlebitis), securement with additional nonsterile tape (HR, 0.63; 95% CI, 0.48-0.82) or with any other additional securement (HR, 0.53; 95% CI, 0.39-0.70), or the administration of IV cephazolin (HR, 0.63; 95% CI, 0.44-0.89) were associated with lower phlebitis risk.

Dislodgement

Statistically significant predictors associated with an increased risk of PIV dislodgement included paramedic insertion (HR, 1.78; 95% CI, 1.03-3.06) and frequent PIV access (HR, 1.11; 95% CI, 1.03-1.20). A decreased risk was associated with the additional securement of the PIV, including nonsterile tape (HR, 0.44; 95% CI, 0.31-0.63) or other forms of additional securement (HR, 0.32; 95% CI, 0.22-0.46).

One in 3 PIVs failed in this study, with phlebitis as the most common cause of PIV failure. The 17% phlebitis rate reflected clinician-reported phlebitis or phlebitis observed by research staff using a 1-criteria definition because any sign or symptom can trigger PIV removal (eg, pain), even if other signs or symptoms are not present. Reported phlebitis rates are lower if definitions require 2 signs or symptoms.^4,6 With over 71 different phlebitis assessment scales in use, and none well validated, the best method for diagnosing phlebitis remains unclear and explains the variation in reported rates.²⁵ Occlusion/infiltration and dislodgement were also highly prevalent forms of PIV failure at 14% and 10%, respectively. Occlusion and infiltration were combined because clinical staff use these terms interchangeably, and differential diagnostic tools are not used in practice. Both result in the same outcome (therapy interruption and PIV removal), and this combination of outcomes has been used previously.²³ No PIV-associated bloodstream infections occurred, despite the heightened awareness of these infections in the literature.³

Females had significantly more occlusion/infiltration and phlebitis than males, in keeping with previous studies.^7,9,10 This could be because of females’ smaller vein caliber, although the effect remained after adjustment for PIV gauge.^7,26 The effect of aging on vascular endothelium and structural integrity may explain the observed decrease in phlebitis of 1% with each older year of age.²⁷ However, gender and age effects could be explained by psychosocial factors (eg, older people may be less likely to admit pain, or we may question them less sympathetically), but, regardless, women and younger patients should be monitored more closely.

We found 22-gauge catheters were more likely to fail from occlusion/infiltration than other sizes. This confirms similar findings from Abolfotouh et al.⁹ PIV gauge selection for this study was made at the inserter’s discretion and may be confounded by smaller vein size, which was not measured. In addition, risk may be because of smaller gauge alone or also more influenced by the shorter length of the studied 22-gauge (25 mm) than the <20-gauge catheters (30 mm). These results question international guidelines, which currently recommend the smallest gauge peripheral catheter possible,^28,29 and randomized trials are needed. Although practice varies between inserters, some preferentially cannulate the nondominant limb. We are not aware of previous studies on this practice; however, our results support this approach.

Flucloxacillin was associated with a 2-fold increase in occlusion/infiltration and phlebitis. Although multiple studies have reported IV medications^9,11 and IV antibiotics^10,30,31 as risk factors for PIV failure, none have identified flucloxacillin as an independent risk factor. IV flucloxacillin is recommended for reconstitution as 1 g in 15 mL to 20 mL of sterile water, and injection over 3 to 4 minutes, although this may not be adhered to in practice. Alternative administration regimes or improved adherence to current policy may be needed. An exception to the relationship between IV antibiotics and catheter failure was IV cephazolin, associated with 40% relatively less phlebitis. This may be a spurious finding because the administration, pH, and osmolality of cephazolin are similar to other IV antibiotics.

The more PIVs that were accessed per day, whether for infusions or medications, the more failure occurred from occlusion/infiltration, phlebitis, and dislodgement. This suggests that peripheral veins are easily damaged and/or inflamed by the influx of fluids or medications. Lower injection pressures or the timely transfer to oral medications may limit this problem. Flushing regimens may also assist because practice varies greatly, and questions on whether slow continuous flush infusion or intermittent manual flushing are more vein-protective, and the optimal flush volume, frequency, and technique (eg, pulsatile) remain.^32,33 Manual handling for frequent access may loosen dressings and securement, thus explaining the observed association between frequent access and catheter dislodgement. Finally, the association between use and failure may indicate that many of these patients were not suitable for a PIV, and different approaches (eg, ultrasound-guided insertion) or a midline may have been a superior option. There is growing emphasis on the need for better preinsertion assessment and selection of the most appropriate device for the patient and the IV treatment required.³⁴

Suboptimal dressings or securements are not unusual in hospitals.³⁵ Despite our policy of PIV securement with bordered transparent dressings, we found 4 dressing types in use. In addition, we found almost 50% of PIVs had an additional (secondary) securement, and this was associated with significantly less PIV failure of all 3 types. This suggests that 1 or more of nonsterile tape, elasticized tubular bandages, or other securement (eg, bandage or second transparent dressing) can reduce PIV failure, although a randomized trial is lacking.³⁶ Whether the dressing was failing and required reinforcement or hospital staff lacked confidence in the dressing and placed additional securement preventatively is unclear. Both PIV failure and PIV dressing failure are common, and further research into superior PIV products and practices is urgently needed. Paramedic insertions had a higher risk of dislodgement, suggesting that the increased emphasis on securement should start in the prehospital setting.

While multiple or difficult insertion attempts were not associated with PIV failure, insertions were not directly observed, and clinicians may have underreported attempts. In contrast, insertion-related bruising (a surrogate for difficult insertion) was associated with more than double the incidence of phlebitis. The long-term implications of multiple insertion attempts on patient’s vasculature are unclear, but we believe first time PIV insertion is important to patients and of interest to clinicians. A recent systematic review of strategies associated with first attempt PIV insertion success in an emergency department found little evidence for effective strategies and recommended further research.³⁷

The overall PIV failure rate in our study was 32%, lower than the 35% to 40% failure observed in our previous randomized controlled trials, which had more stringent inclusion and exclusion criteria (eg, longer predicted duration of therapy).^6,38 The implications for patients and costs to the organization of frequent catheter replacement demonstrate urgent need for further research in this area of practice.³⁹ A strength of this study is that all PIVs, regardless of the expected length of dwell time or reason for insertion, were eligible for inclusion, providing more generalizable results. The PIV failure rate of 32% is concerning because these failures trigger treatment delays and replacement insertions, with significant increased labor and equipment costs. The mean cost of PIV replacement has been costed at AUD $69.30 or US $51.92 (as per 2010 $ value) per episode of IV treatment.⁴⁰ For our hospital, which uses 200,000 PIVs per year, the current level of PIV failure suggests almost AU $5.5 (US $4.1) million in waste annually at this site alone.

The additional strengths of this study include the extensive information collected prospectively about PIV insertion and maintenance, including information on who inserted the PIV, IV medications administered, and PIV dressings used. Limitations were the population of surgical and medical patients in 1 tertiary hospital, which may not be generalizable to other settings.

Our study confirms the high rate of catheter failure in acute care hospitals, validates existing evidence related to PIV failure, and identifies new, potentially modifiable risk factors to improve PIV insertion and management. Implications for future research were also identified.

Acknowledgments

The researchers acknowledge and thank the nurses and patients involved in this study. The authors would also like to acknowledge Becton Dickinson for partly funding this study in the form of an unrestricted grant-in-aid paid to Griffith University. Becton Dickinson did not design the study protocol, collect or analyze data, and did not prepare or review the manuscript.

Disclosure

 On behalf of NM and CMR, Griffith University has received unrestricted educational and research grants and consultancy payment for lectures from 3M and Becton Dickinson. On behalf of NM, MC, and CMR, Griffith University has received unrestricted investigator-initiated research grants from Centurion Medical Products and Entrotech Lifesciences (manufacturers of PIV dressings) and Becton Dickinson (manufacturer of PIVs). On behalf of MC, Griffith University has received a consultancy payment to develop education material from Baxter. On behalf of CMR, Griffith University has received unrestricted donations or investigator initiated research grants unrelated to this research from Adhezion, Angiodynamics, Baxter, Carefusion, Cook Medical, Hospira, Mayo, Smiths Medical, and Vygon. On behalf of CMR, Griffith University has received consultancy payments for educational lectures or professional opinion from B. Braun, Bard, Carefusion, Mayo, ResQDevices, and Smiths Medical. On behalf of EL, Griffith University has received consultancy payments for educational lecture from 3M. On behalf of MC, Griffith University has received a consultancy payment to develop education material from Baxter. As this was an observational study, no products were trialed in this study. JW and GM have no conflicts of interest.

Transthoracic echocardiography (TTE) is one of the most commonly ordered diagnostic tests in healthcare. Studies of Medicare beneficiaries, for example, have shown that each year, approximately 20% undergo at least 1 TTE, including 4% who have 2 or more.¹ TTE utilization rates increased dramatically in the 1990s and early 2000s. Between 1999 and 2008, for example, the rate of use of TTE per Medicare beneficiary nearly doubled.² In 2014, echocardiography accounted for 10% of all Medicare spending for imaging services, or approximately $930 million.³ In response to concerns about the possible unnecessary use of TTE, the American Heart Association and American Society of Echocardiography developed Appropriate Use Criteria (AUC) in 2007 and 2011, which describe appropriate versus inappropriate indications for TTE.⁴ Subsequent studies have shown that rather than rooting out inappropriate studies, the vast majority of ordered studies appear to be appropriate according to the AUC criteria.⁵ The AUC criteria have also been criticized for being based on expert opinion rather than clinical evidence.⁶ Repeat TTE, defined as TTE done within 1 year of a prior TTE, represents 24% to 42% of all studies,^7-9 and 31% of all Medicare beneficiaries who have a TTE get a repeat TTE within 1 year.¹⁰ In the present study, we reviewed all inpatient TTE performed over 1 year and described the group that have had a prior TTE within the past year (“repeat TTE”). We then derived a clinical prediction model to predict unchanged repeat TTE, with the goal of defining a subset of studies that are potentially unnecessary.

The West Haven Connecticut Veteran’s Administration Hospital (WHVA), located outside New Haven, Connecticut, is a 228-bed tertiary care center affiliated with Yale University School of Medicine. Potential subjects were identified from review of the electronic medical records of all inpatients who had an inpatient echocardiogram between October 1, 2013, and September 30, 2014. Patient’s records were reviewed by using a standardized data extraction form for demographics, comorbidity, cardiovascular risk factors, service ordering the TTE, intensive care unit (ICU) location, prior TTE abnormalities, TTE indication, AUC category, time between TTEs, technical quality of TTE, electrocardiogram (ECG) abnormalities, history of intervening acute coronary syndrome, cardiac surgery, and revascularization. Candidate predictors included any variables suspected by the authors as being potentially associated with the primary outcome of changed repeat TTE. All patients who had an inpatient TTE and a prior TTE within the Veterans Affairs (VA) system within the past year were included in the study. Repeat studies from the same admission were only counted as 1 TTE and patients had to have had a prior TTE from a different admission or a prior outpatient TTE to be included. Patients who did not have a prior TTE within the past year or who had only a transesophageal echocardiogram or stress echocardiography were excluded. Suboptimal studies were included but noted as limited quality. The study was approved by the WHVA Institutional Review Board. The Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement was used in planning and reporting this study.¹¹

TTEs were classified as normal, mildly abnormal, or with a major abnormality based on previously published definitions.^12-14 Any abnormality was defined as any left ventricle (LV) dysfunction (left ventricular ejection fraction [LVEF] <55%), any aortic or mitral valve stenosis, any regional wall motion abnormality, any right ventricular dysfunction, any pulmonary hypertension, mild or greater valvular regurgitation, any diastolic dysfunction, moderate or greater pericardial effusion, any ventricular hypertrophy, or any other significant abnormality including thrombus, vegetation, or tamponade. Major abnormality was defined as moderate or greater LV dysfunction (LVEF <45%), moderate or greater valvular regurgitation, moderate or greater valvular stenosis (aortic or mitral valve area <1.5 cm²), any regional wall motion abnormality, right ventricular dysfunction, moderate or greater pulmonary hypertension, moderate or greater diastolic dysfunction, moderate or greater pericardial effusion, or any other major abnormality including thrombus, vegetation, tumor, or tamponade. Repeat TTEs were classified as changed or unchanged. Changed TTEs were divided into any new abnormality or improvement or a new major abnormality or improvement. Any new abnormality or improvement was defined as any new TTE abnormality that had not previously been described or in which there was a change of at least 1 severity grade from a prior TTE, including improvement by 1 grade. A new major TTE abnormality or improvement was defined as any new major TTE abnormality that had previously been normal, or if there had been a prior abnormality, a change in at least 1 severity grade for LVEF or 2 severity grades for abnormal valvular, pericardial, or prior pulmonary hypertension, including improvement by 2 severity grades. A change from mild to moderate mitral regurgitation therefore was classified as a nonmajor change, whereas a change from mild to severe was classified as major. All TTE classifications were based on the electronic TTE reports and were reviewed by 2 independent investigators (CG and JC) blinded to the patients’ other clinical characteristics. For TTE studies in which the investigators agreed, that determination was the final classification. Disagreements were reviewed and the final classification was determined by consensus.

In an analogous manner, ECGs were classified as normal, mildly abnormal, or with a major abnormality based on previous definitions in the literature.¹⁵ Major abnormality was defined as atrial fibrillation or flutter, high-degree atrioventricular blocks, left bundle-branch block, right bundle-branch block, indeterminate conduction delay, q-wave myocardial infarction, isolated ischemic abnormalities, left ventricular hypertrophy with ST-T abnormalities, other arrhythmias including supraventricular tachycardia (SVT) or ventricular tachycardia (VT), low voltage (peak-to-peak QRS amplitude of <5 mm in the limb leads and/or <10 mm in the precordial leads), paced rhythm, sinus tachycardia (heart rate [HR] >100) or bradycardia (HR <50). Mild ECG abnormality was defined as low-grade atrioventricular blocks, borderline prolonged ventricular excitation, prolonged ventricular repolarization, isolated minor Q and ST-T abnormalities, left ventricular hypertrophy without ST-T abnormalities, left atrial enlargement, atrial or ventricular premature beats, or fascicular blocks. New major ECG abnormalities were any of the listed major ECG abnormalities that were not present on ECGs prior to the admission during which the repeat TTE was performed.

Other study definitions included intervening acute myocardial infarction (AMI), which was defined by any intervening history of elevated troponins, regardless of symptoms or ECG changes and including demand ischemia. Chronic kidney disease (CKD) was defined as an abnormal serum creatinine on 2 or more occasions 3 months apart. Active cancer was defined as receiving chemotherapy or palliative care for advanced cancer. Valvular heart disease was defined as prior moderate or severe valvular stenosis or regurgitation.

For analysis, we first compared patients with repeat TTE with major changes with those without major changes. For comparison of dichotomous variables, χ² or Fisher exact tests were used. For continuous variables, Student t test or the Mann-Whitney U test were performed. Because many of the frequencies of individual AUC criteria were small, related AUC criteria were grouped for analysis as grouped by the tables of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography, American Heart Association, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance (ACCF/ASE/AHA) Guideline.⁴ Criteria groupings that were significantly less likely to have major TTE changes on analysis were classified as low risk and criteria that were significantly more likely were classified as high risk. Criteria groupings that were not significantly associated with TTE change were classified as average risk. All variables with P values less than 0.05 on bivariate analysis were then entered into a multivariate logistic regression analysis with major TTE change as the dependent variable, using backward stepwise variable selection with entry and exit criteria of P < 0.05 and P > 0.10, respectively. Scores were derived by converting the regression coefficients of independently predictive variables in the logistic regression model into corresponding integers. A total score was calculated for each patient by summing up the points for each independently significant variable. Model performance was described by calculating a C statistic by creation of a receiver operating characteristic curve to assess discrimination, and by performing the Hosmer and Lemeshow test to assess calibration. Internal validation was assessed by calculating the C statistic using the statistical method of bootstrapping in which the data were resampled multiple times (n = 200) and the average resultant C statistic reported. The bootstrap analysis was performed using R version 3.1 (R Foundation for Statistical Computing, Vienna, Austria). All other analyses were performed using SPSS version 21.0 (IBM, Armonk, New York). P values <0.05 were considered significant.

During the 1-year study period, there were 3944 medical/surgical admissions for 3266 patients and 845 inpatient TTEs obtained on 601 patients. Of all patients who were admitted, 601/3266 (18.4%) had at least 1 inpatient TTE. Of these 601 TTEs, 211 (35%) had a TTE within the VA system during the prior year. Of the 211 repeat TTEs, 67 (32%) were unchanged, 66 (31%) had minor changes, and 78 (37%) had major changes. The kappa statistic for agreement between extractors for “major TTE change” was 0.91, P < 0.001. The 10 most common AUC indications for TTE, which accounted for 72% of all studies, are listed in Table 1. The initial AUCs assigned by reviewers were the same in 187 of 211 TTEs (kappa 0.86, P < 0.001). Most indications were not associated with TTE outcome, although studies ordered for AUC indications 1 and 2 were less likely be associated with major changes and AUC indications 22 and 47 were more likely to be associated with major changes. Table 2 shows the comparison of the 78 patients that had repeat TTE with major changes compared with the 133 patients that did not. Nine variables were significantly different between the 2 groups; repeat TTEs with major changes were more likely to have dementia, be ordered by the surgery service, be located in an ICU, have major new ECG changes, have had prior valvular heart disease, have had an intervening AMI or cardiac surgery, or be in a high-risk AUC category. Patients with CKD were less likely to have major changes. Table 3 shows the results of the multivariate analysis; CKD, intervening AMI, prior valvular heart disease, major new ECG changes, and intervening cardiac surgery all independently predicted major changes on repeat TTE. Based on the β-coefficient for each variable, a point system was assigned to each variable and a total score calculated for each patient. Most variables had β-coefficients close to 1 and were therefore assigned a score of 1. CKD was associated with a lower risk of major TTE abnormality and was assigned a negative score. Intervening AMI was associated with a β-coefficient of 2.2 and was assigned a score of 2. Based on the points assigned to each variable and its presence or absence for each patient, a total score, which we named the CAVES score, was calculated. The acronym CAVES stands for CKD, AMI, valvular disease, ECG changes, and surgery (cardiac). Table 4 shows the frequencies of each score for each patient, ranging from patients with CKD and no other risk factors who scored −1 to patients without CKD who had all 4 of the other variables who scored 5. The prevalence of major TTE change for the full cohort was 37%. For the group with a CAVES score of −1, the probability was only 5.6%; for the group with a score of 0, the probability was 17.7%; and for the group with a score ≥1, the probability was 55.3%.

In this retrospective study, we found that approximately 18% of all patients admitted to the hospital had an inpatient TTE performed, and that approximately 35% of this group had a prior TTE within the past year. Of the group with prior TTEs within the past year, 37% had a major new change and 63% had either minor or no changes. Prior studies have reported similar high rates of repeat TTE^7-9 and of major changes on repeat TTE.^8,14,16 On multivariate analysis, we found that 5 variables were independent predictors of new changes on TTE—absence of CKD, intervening AMI, intervening cardiac surgery, history of valvular heart disease, and major new ECG changes. We developed and internally validated a risk score based on these 5 variables, which was found to have good overall accuracy as measured by the bootstrap corrected C statistic. The simplified version of the score divides patients into low, intermediate, and high risk for major changes on TTE. The low-risk group, defined as the group with no risk factors, had an approximately 6% risk of a major TTE change; the intermediate risk group, defined as a score of 0, had an 18% risk of major TTE change; and the high-risk group, defined as a score of 1 or greater, had a 55% chance of major TTE change. We believe that this risk score, if further validated, will potentially allow hospital-based clinicians to estimate the chance of a major change on TTE prior to ordering the study. For the low-risk group, this may indicate that the study is unnecessary. Conversely, for patients at high risk, this may offer further evidence that it will be useful to obtain a repeat TTE.

Disclosure 

The authors indicated no conflicts of interest.

Transthoracic echocardiography (TTE) is one of the most commonly ordered diagnostic tests in healthcare. Studies of Medicare beneficiaries, for example, have shown that each year, approximately 20% undergo at least 1 TTE, including 4% who have 2 or more.¹ TTE utilization rates increased dramatically in the 1990s and early 2000s. Between 1999 and 2008, for example, the rate of use of TTE per Medicare beneficiary nearly doubled.² In 2014, echocardiography accounted for 10% of all Medicare spending for imaging services, or approximately $930 million.³ In response to concerns about the possible unnecessary use of TTE, the American Heart Association and American Society of Echocardiography developed Appropriate Use Criteria (AUC) in 2007 and 2011, which describe appropriate versus inappropriate indications for TTE.⁴ Subsequent studies have shown that rather than rooting out inappropriate studies, the vast majority of ordered studies appear to be appropriate according to the AUC criteria.⁵ The AUC criteria have also been criticized for being based on expert opinion rather than clinical evidence.⁶ Repeat TTE, defined as TTE done within 1 year of a prior TTE, represents 24% to 42% of all studies,^7-9 and 31% of all Medicare beneficiaries who have a TTE get a repeat TTE within 1 year.¹⁰ In the present study, we reviewed all inpatient TTE performed over 1 year and described the group that have had a prior TTE within the past year (“repeat TTE”). We then derived a clinical prediction model to predict unchanged repeat TTE, with the goal of defining a subset of studies that are potentially unnecessary.

The West Haven Connecticut Veteran’s Administration Hospital (WHVA), located outside New Haven, Connecticut, is a 228-bed tertiary care center affiliated with Yale University School of Medicine. Potential subjects were identified from review of the electronic medical records of all inpatients who had an inpatient echocardiogram between October 1, 2013, and September 30, 2014. Patient’s records were reviewed by using a standardized data extraction form for demographics, comorbidity, cardiovascular risk factors, service ordering the TTE, intensive care unit (ICU) location, prior TTE abnormalities, TTE indication, AUC category, time between TTEs, technical quality of TTE, electrocardiogram (ECG) abnormalities, history of intervening acute coronary syndrome, cardiac surgery, and revascularization. Candidate predictors included any variables suspected by the authors as being potentially associated with the primary outcome of changed repeat TTE. All patients who had an inpatient TTE and a prior TTE within the Veterans Affairs (VA) system within the past year were included in the study. Repeat studies from the same admission were only counted as 1 TTE and patients had to have had a prior TTE from a different admission or a prior outpatient TTE to be included. Patients who did not have a prior TTE within the past year or who had only a transesophageal echocardiogram or stress echocardiography were excluded. Suboptimal studies were included but noted as limited quality. The study was approved by the WHVA Institutional Review Board. The Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement was used in planning and reporting this study.¹¹

TTEs were classified as normal, mildly abnormal, or with a major abnormality based on previously published definitions.^12-14 Any abnormality was defined as any left ventricle (LV) dysfunction (left ventricular ejection fraction [LVEF] <55%), any aortic or mitral valve stenosis, any regional wall motion abnormality, any right ventricular dysfunction, any pulmonary hypertension, mild or greater valvular regurgitation, any diastolic dysfunction, moderate or greater pericardial effusion, any ventricular hypertrophy, or any other significant abnormality including thrombus, vegetation, or tamponade. Major abnormality was defined as moderate or greater LV dysfunction (LVEF <45%), moderate or greater valvular regurgitation, moderate or greater valvular stenosis (aortic or mitral valve area <1.5 cm²), any regional wall motion abnormality, right ventricular dysfunction, moderate or greater pulmonary hypertension, moderate or greater diastolic dysfunction, moderate or greater pericardial effusion, or any other major abnormality including thrombus, vegetation, tumor, or tamponade. Repeat TTEs were classified as changed or unchanged. Changed TTEs were divided into any new abnormality or improvement or a new major abnormality or improvement. Any new abnormality or improvement was defined as any new TTE abnormality that had not previously been described or in which there was a change of at least 1 severity grade from a prior TTE, including improvement by 1 grade. A new major TTE abnormality or improvement was defined as any new major TTE abnormality that had previously been normal, or if there had been a prior abnormality, a change in at least 1 severity grade for LVEF or 2 severity grades for abnormal valvular, pericardial, or prior pulmonary hypertension, including improvement by 2 severity grades. A change from mild to moderate mitral regurgitation therefore was classified as a nonmajor change, whereas a change from mild to severe was classified as major. All TTE classifications were based on the electronic TTE reports and were reviewed by 2 independent investigators (CG and JC) blinded to the patients’ other clinical characteristics. For TTE studies in which the investigators agreed, that determination was the final classification. Disagreements were reviewed and the final classification was determined by consensus.

In an analogous manner, ECGs were classified as normal, mildly abnormal, or with a major abnormality based on previous definitions in the literature.¹⁵ Major abnormality was defined as atrial fibrillation or flutter, high-degree atrioventricular blocks, left bundle-branch block, right bundle-branch block, indeterminate conduction delay, q-wave myocardial infarction, isolated ischemic abnormalities, left ventricular hypertrophy with ST-T abnormalities, other arrhythmias including supraventricular tachycardia (SVT) or ventricular tachycardia (VT), low voltage (peak-to-peak QRS amplitude of <5 mm in the limb leads and/or <10 mm in the precordial leads), paced rhythm, sinus tachycardia (heart rate [HR] >100) or bradycardia (HR <50). Mild ECG abnormality was defined as low-grade atrioventricular blocks, borderline prolonged ventricular excitation, prolonged ventricular repolarization, isolated minor Q and ST-T abnormalities, left ventricular hypertrophy without ST-T abnormalities, left atrial enlargement, atrial or ventricular premature beats, or fascicular blocks. New major ECG abnormalities were any of the listed major ECG abnormalities that were not present on ECGs prior to the admission during which the repeat TTE was performed.

Other study definitions included intervening acute myocardial infarction (AMI), which was defined by any intervening history of elevated troponins, regardless of symptoms or ECG changes and including demand ischemia. Chronic kidney disease (CKD) was defined as an abnormal serum creatinine on 2 or more occasions 3 months apart. Active cancer was defined as receiving chemotherapy or palliative care for advanced cancer. Valvular heart disease was defined as prior moderate or severe valvular stenosis or regurgitation.

For analysis, we first compared patients with repeat TTE with major changes with those without major changes. For comparison of dichotomous variables, χ² or Fisher exact tests were used. For continuous variables, Student t test or the Mann-Whitney U test were performed. Because many of the frequencies of individual AUC criteria were small, related AUC criteria were grouped for analysis as grouped by the tables of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography, American Heart Association, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance (ACCF/ASE/AHA) Guideline.⁴ Criteria groupings that were significantly less likely to have major TTE changes on analysis were classified as low risk and criteria that were significantly more likely were classified as high risk. Criteria groupings that were not significantly associated with TTE change were classified as average risk. All variables with P values less than 0.05 on bivariate analysis were then entered into a multivariate logistic regression analysis with major TTE change as the dependent variable, using backward stepwise variable selection with entry and exit criteria of P < 0.05 and P > 0.10, respectively. Scores were derived by converting the regression coefficients of independently predictive variables in the logistic regression model into corresponding integers. A total score was calculated for each patient by summing up the points for each independently significant variable. Model performance was described by calculating a C statistic by creation of a receiver operating characteristic curve to assess discrimination, and by performing the Hosmer and Lemeshow test to assess calibration. Internal validation was assessed by calculating the C statistic using the statistical method of bootstrapping in which the data were resampled multiple times (n = 200) and the average resultant C statistic reported. The bootstrap analysis was performed using R version 3.1 (R Foundation for Statistical Computing, Vienna, Austria). All other analyses were performed using SPSS version 21.0 (IBM, Armonk, New York). P values <0.05 were considered significant.

During the 1-year study period, there were 3944 medical/surgical admissions for 3266 patients and 845 inpatient TTEs obtained on 601 patients. Of all patients who were admitted, 601/3266 (18.4%) had at least 1 inpatient TTE. Of these 601 TTEs, 211 (35%) had a TTE within the VA system during the prior year. Of the 211 repeat TTEs, 67 (32%) were unchanged, 66 (31%) had minor changes, and 78 (37%) had major changes. The kappa statistic for agreement between extractors for “major TTE change” was 0.91, P < 0.001. The 10 most common AUC indications for TTE, which accounted for 72% of all studies, are listed in Table 1. The initial AUCs assigned by reviewers were the same in 187 of 211 TTEs (kappa 0.86, P < 0.001). Most indications were not associated with TTE outcome, although studies ordered for AUC indications 1 and 2 were less likely be associated with major changes and AUC indications 22 and 47 were more likely to be associated with major changes. Table 2 shows the comparison of the 78 patients that had repeat TTE with major changes compared with the 133 patients that did not. Nine variables were significantly different between the 2 groups; repeat TTEs with major changes were more likely to have dementia, be ordered by the surgery service, be located in an ICU, have major new ECG changes, have had prior valvular heart disease, have had an intervening AMI or cardiac surgery, or be in a high-risk AUC category. Patients with CKD were less likely to have major changes. Table 3 shows the results of the multivariate analysis; CKD, intervening AMI, prior valvular heart disease, major new ECG changes, and intervening cardiac surgery all independently predicted major changes on repeat TTE. Based on the β-coefficient for each variable, a point system was assigned to each variable and a total score calculated for each patient. Most variables had β-coefficients close to 1 and were therefore assigned a score of 1. CKD was associated with a lower risk of major TTE abnormality and was assigned a negative score. Intervening AMI was associated with a β-coefficient of 2.2 and was assigned a score of 2. Based on the points assigned to each variable and its presence or absence for each patient, a total score, which we named the CAVES score, was calculated. The acronym CAVES stands for CKD, AMI, valvular disease, ECG changes, and surgery (cardiac). Table 4 shows the frequencies of each score for each patient, ranging from patients with CKD and no other risk factors who scored −1 to patients without CKD who had all 4 of the other variables who scored 5. The prevalence of major TTE change for the full cohort was 37%. For the group with a CAVES score of −1, the probability was only 5.6%; for the group with a score of 0, the probability was 17.7%; and for the group with a score ≥1, the probability was 55.3%.

In this retrospective study, we found that approximately 18% of all patients admitted to the hospital had an inpatient TTE performed, and that approximately 35% of this group had a prior TTE within the past year. Of the group with prior TTEs within the past year, 37% had a major new change and 63% had either minor or no changes. Prior studies have reported similar high rates of repeat TTE^7-9 and of major changes on repeat TTE.^8,14,16 On multivariate analysis, we found that 5 variables were independent predictors of new changes on TTE—absence of CKD, intervening AMI, intervening cardiac surgery, history of valvular heart disease, and major new ECG changes. We developed and internally validated a risk score based on these 5 variables, which was found to have good overall accuracy as measured by the bootstrap corrected C statistic. The simplified version of the score divides patients into low, intermediate, and high risk for major changes on TTE. The low-risk group, defined as the group with no risk factors, had an approximately 6% risk of a major TTE change; the intermediate risk group, defined as a score of 0, had an 18% risk of major TTE change; and the high-risk group, defined as a score of 1 or greater, had a 55% chance of major TTE change. We believe that this risk score, if further validated, will potentially allow hospital-based clinicians to estimate the chance of a major change on TTE prior to ordering the study. For the low-risk group, this may indicate that the study is unnecessary. Conversely, for patients at high risk, this may offer further evidence that it will be useful to obtain a repeat TTE.

Disclosure 

The authors indicated no conflicts of interest.

Transthoracic echocardiography (TTE) is one of the most commonly ordered diagnostic tests in healthcare. Studies of Medicare beneficiaries, for example, have shown that each year, approximately 20% undergo at least 1 TTE, including 4% who have 2 or more.¹ TTE utilization rates increased dramatically in the 1990s and early 2000s. Between 1999 and 2008, for example, the rate of use of TTE per Medicare beneficiary nearly doubled.² In 2014, echocardiography accounted for 10% of all Medicare spending for imaging services, or approximately $930 million.³ In response to concerns about the possible unnecessary use of TTE, the American Heart Association and American Society of Echocardiography developed Appropriate Use Criteria (AUC) in 2007 and 2011, which describe appropriate versus inappropriate indications for TTE.⁴ Subsequent studies have shown that rather than rooting out inappropriate studies, the vast majority of ordered studies appear to be appropriate according to the AUC criteria.⁵ The AUC criteria have also been criticized for being based on expert opinion rather than clinical evidence.⁶ Repeat TTE, defined as TTE done within 1 year of a prior TTE, represents 24% to 42% of all studies,^7-9 and 31% of all Medicare beneficiaries who have a TTE get a repeat TTE within 1 year.¹⁰ In the present study, we reviewed all inpatient TTE performed over 1 year and described the group that have had a prior TTE within the past year (“repeat TTE”). We then derived a clinical prediction model to predict unchanged repeat TTE, with the goal of defining a subset of studies that are potentially unnecessary.

The West Haven Connecticut Veteran’s Administration Hospital (WHVA), located outside New Haven, Connecticut, is a 228-bed tertiary care center affiliated with Yale University School of Medicine. Potential subjects were identified from review of the electronic medical records of all inpatients who had an inpatient echocardiogram between October 1, 2013, and September 30, 2014. Patient’s records were reviewed by using a standardized data extraction form for demographics, comorbidity, cardiovascular risk factors, service ordering the TTE, intensive care unit (ICU) location, prior TTE abnormalities, TTE indication, AUC category, time between TTEs, technical quality of TTE, electrocardiogram (ECG) abnormalities, history of intervening acute coronary syndrome, cardiac surgery, and revascularization. Candidate predictors included any variables suspected by the authors as being potentially associated with the primary outcome of changed repeat TTE. All patients who had an inpatient TTE and a prior TTE within the Veterans Affairs (VA) system within the past year were included in the study. Repeat studies from the same admission were only counted as 1 TTE and patients had to have had a prior TTE from a different admission or a prior outpatient TTE to be included. Patients who did not have a prior TTE within the past year or who had only a transesophageal echocardiogram or stress echocardiography were excluded. Suboptimal studies were included but noted as limited quality. The study was approved by the WHVA Institutional Review Board. The Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement was used in planning and reporting this study.¹¹

TTEs were classified as normal, mildly abnormal, or with a major abnormality based on previously published definitions.^12-14 Any abnormality was defined as any left ventricle (LV) dysfunction (left ventricular ejection fraction [LVEF] <55%), any aortic or mitral valve stenosis, any regional wall motion abnormality, any right ventricular dysfunction, any pulmonary hypertension, mild or greater valvular regurgitation, any diastolic dysfunction, moderate or greater pericardial effusion, any ventricular hypertrophy, or any other significant abnormality including thrombus, vegetation, or tamponade. Major abnormality was defined as moderate or greater LV dysfunction (LVEF <45%), moderate or greater valvular regurgitation, moderate or greater valvular stenosis (aortic or mitral valve area <1.5 cm²), any regional wall motion abnormality, right ventricular dysfunction, moderate or greater pulmonary hypertension, moderate or greater diastolic dysfunction, moderate or greater pericardial effusion, or any other major abnormality including thrombus, vegetation, tumor, or tamponade. Repeat TTEs were classified as changed or unchanged. Changed TTEs were divided into any new abnormality or improvement or a new major abnormality or improvement. Any new abnormality or improvement was defined as any new TTE abnormality that had not previously been described or in which there was a change of at least 1 severity grade from a prior TTE, including improvement by 1 grade. A new major TTE abnormality or improvement was defined as any new major TTE abnormality that had previously been normal, or if there had been a prior abnormality, a change in at least 1 severity grade for LVEF or 2 severity grades for abnormal valvular, pericardial, or prior pulmonary hypertension, including improvement by 2 severity grades. A change from mild to moderate mitral regurgitation therefore was classified as a nonmajor change, whereas a change from mild to severe was classified as major. All TTE classifications were based on the electronic TTE reports and were reviewed by 2 independent investigators (CG and JC) blinded to the patients’ other clinical characteristics. For TTE studies in which the investigators agreed, that determination was the final classification. Disagreements were reviewed and the final classification was determined by consensus.

In an analogous manner, ECGs were classified as normal, mildly abnormal, or with a major abnormality based on previous definitions in the literature.¹⁵ Major abnormality was defined as atrial fibrillation or flutter, high-degree atrioventricular blocks, left bundle-branch block, right bundle-branch block, indeterminate conduction delay, q-wave myocardial infarction, isolated ischemic abnormalities, left ventricular hypertrophy with ST-T abnormalities, other arrhythmias including supraventricular tachycardia (SVT) or ventricular tachycardia (VT), low voltage (peak-to-peak QRS amplitude of <5 mm in the limb leads and/or <10 mm in the precordial leads), paced rhythm, sinus tachycardia (heart rate [HR] >100) or bradycardia (HR <50). Mild ECG abnormality was defined as low-grade atrioventricular blocks, borderline prolonged ventricular excitation, prolonged ventricular repolarization, isolated minor Q and ST-T abnormalities, left ventricular hypertrophy without ST-T abnormalities, left atrial enlargement, atrial or ventricular premature beats, or fascicular blocks. New major ECG abnormalities were any of the listed major ECG abnormalities that were not present on ECGs prior to the admission during which the repeat TTE was performed.

Other study definitions included intervening acute myocardial infarction (AMI), which was defined by any intervening history of elevated troponins, regardless of symptoms or ECG changes and including demand ischemia. Chronic kidney disease (CKD) was defined as an abnormal serum creatinine on 2 or more occasions 3 months apart. Active cancer was defined as receiving chemotherapy or palliative care for advanced cancer. Valvular heart disease was defined as prior moderate or severe valvular stenosis or regurgitation.

For analysis, we first compared patients with repeat TTE with major changes with those without major changes. For comparison of dichotomous variables, χ² or Fisher exact tests were used. For continuous variables, Student t test or the Mann-Whitney U test were performed. Because many of the frequencies of individual AUC criteria were small, related AUC criteria were grouped for analysis as grouped by the tables of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography, American Heart Association, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance (ACCF/ASE/AHA) Guideline.⁴ Criteria groupings that were significantly less likely to have major TTE changes on analysis were classified as low risk and criteria that were significantly more likely were classified as high risk. Criteria groupings that were not significantly associated with TTE change were classified as average risk. All variables with P values less than 0.05 on bivariate analysis were then entered into a multivariate logistic regression analysis with major TTE change as the dependent variable, using backward stepwise variable selection with entry and exit criteria of P < 0.05 and P > 0.10, respectively. Scores were derived by converting the regression coefficients of independently predictive variables in the logistic regression model into corresponding integers. A total score was calculated for each patient by summing up the points for each independently significant variable. Model performance was described by calculating a C statistic by creation of a receiver operating characteristic curve to assess discrimination, and by performing the Hosmer and Lemeshow test to assess calibration. Internal validation was assessed by calculating the C statistic using the statistical method of bootstrapping in which the data were resampled multiple times (n = 200) and the average resultant C statistic reported. The bootstrap analysis was performed using R version 3.1 (R Foundation for Statistical Computing, Vienna, Austria). All other analyses were performed using SPSS version 21.0 (IBM, Armonk, New York). P values <0.05 were considered significant.

During the 1-year study period, there were 3944 medical/surgical admissions for 3266 patients and 845 inpatient TTEs obtained on 601 patients. Of all patients who were admitted, 601/3266 (18.4%) had at least 1 inpatient TTE. Of these 601 TTEs, 211 (35%) had a TTE within the VA system during the prior year. Of the 211 repeat TTEs, 67 (32%) were unchanged, 66 (31%) had minor changes, and 78 (37%) had major changes. The kappa statistic for agreement between extractors for “major TTE change” was 0.91, P < 0.001. The 10 most common AUC indications for TTE, which accounted for 72% of all studies, are listed in Table 1. The initial AUCs assigned by reviewers were the same in 187 of 211 TTEs (kappa 0.86, P < 0.001). Most indications were not associated with TTE outcome, although studies ordered for AUC indications 1 and 2 were less likely be associated with major changes and AUC indications 22 and 47 were more likely to be associated with major changes. Table 2 shows the comparison of the 78 patients that had repeat TTE with major changes compared with the 133 patients that did not. Nine variables were significantly different between the 2 groups; repeat TTEs with major changes were more likely to have dementia, be ordered by the surgery service, be located in an ICU, have major new ECG changes, have had prior valvular heart disease, have had an intervening AMI or cardiac surgery, or be in a high-risk AUC category. Patients with CKD were less likely to have major changes. Table 3 shows the results of the multivariate analysis; CKD, intervening AMI, prior valvular heart disease, major new ECG changes, and intervening cardiac surgery all independently predicted major changes on repeat TTE. Based on the β-coefficient for each variable, a point system was assigned to each variable and a total score calculated for each patient. Most variables had β-coefficients close to 1 and were therefore assigned a score of 1. CKD was associated with a lower risk of major TTE abnormality and was assigned a negative score. Intervening AMI was associated with a β-coefficient of 2.2 and was assigned a score of 2. Based on the points assigned to each variable and its presence or absence for each patient, a total score, which we named the CAVES score, was calculated. The acronym CAVES stands for CKD, AMI, valvular disease, ECG changes, and surgery (cardiac). Table 4 shows the frequencies of each score for each patient, ranging from patients with CKD and no other risk factors who scored −1 to patients without CKD who had all 4 of the other variables who scored 5. The prevalence of major TTE change for the full cohort was 37%. For the group with a CAVES score of −1, the probability was only 5.6%; for the group with a score of 0, the probability was 17.7%; and for the group with a score ≥1, the probability was 55.3%.

In this retrospective study, we found that approximately 18% of all patients admitted to the hospital had an inpatient TTE performed, and that approximately 35% of this group had a prior TTE within the past year. Of the group with prior TTEs within the past year, 37% had a major new change and 63% had either minor or no changes. Prior studies have reported similar high rates of repeat TTE^7-9 and of major changes on repeat TTE.^8,14,16 On multivariate analysis, we found that 5 variables were independent predictors of new changes on TTE—absence of CKD, intervening AMI, intervening cardiac surgery, history of valvular heart disease, and major new ECG changes. We developed and internally validated a risk score based on these 5 variables, which was found to have good overall accuracy as measured by the bootstrap corrected C statistic. The simplified version of the score divides patients into low, intermediate, and high risk for major changes on TTE. The low-risk group, defined as the group with no risk factors, had an approximately 6% risk of a major TTE change; the intermediate risk group, defined as a score of 0, had an 18% risk of major TTE change; and the high-risk group, defined as a score of 1 or greater, had a 55% chance of major TTE change. We believe that this risk score, if further validated, will potentially allow hospital-based clinicians to estimate the chance of a major change on TTE prior to ordering the study. For the low-risk group, this may indicate that the study is unnecessary. Conversely, for patients at high risk, this may offer further evidence that it will be useful to obtain a repeat TTE.

Disclosure 

The authors indicated no conflicts of interest.

Take-Home Points

• The Internet is a popular resource for orthopedic fellowship applicants.
• 86% of OTF websites are accessible from Google and FREIDA.
• Accessible websites feature only 40% of fellowship applicant content.
• Accessibility and content of OTF websites are highly variable and largely deficient.
• Improvement of the accessibility and content of website information should be a future focus of OTF programs.

The Orthopaedic Trauma Fellowship Match facilitates the matching process for orthopedic residency graduates pursuing a career as orthopedic traumatologists. This match is supported by the Orthopaedic Trauma Association (OTA) and the San Francisco Matching Program (SFMP). Orthopedic trauma fellowship (OTF) programs are accredited by the OTA and may receive oversight by the American Council for Graduate Medical Education (ACGME), which defines uniform standards for fellowship training.¹

Studies have found that the internet is an important and popular resource for applicants researching residency and fellowship programs.^2-5 For many applicants, the internet is their initial and main source of information.⁵ Unfortunately, training programs do not have standardized website accessibility and content.

Few studies have addressed online content on orthopedic fellowship programs,^4,6,7 and to our knowledge no one has studied online content on OTF programs. We conducted a study to assess the accessibility and ease of navigation of OTF websites and to evaluate the content on these sites. We wanted to identify content that applicants may reliably expect on OTF sites. Any deficits identified may be useful to fellowship programs and program directors interested in improving website quality. We hypothesized that the accessibility and content of online OTF content would be highly variable and largely deficient.

Methods

This study was conducted at New York University Hospital for Joint Diseases. On February 5, 2015, both the OTA database⁸ and the Fellowship and Residency Electronic Interactive Database (FREIDA)⁹ were accessed in order to create a comprehensive list of OTF programs. FREIDA, a catalog of all ACGME-accredited graduate medical education programs in the United States, is supported by the American Medical Association and provides cursory program information, including training program duration and number of positions per year.

The databases were reviewed for links to OTF program websites. An independent Google search for program websites was also initiated on February 5, 2015. The Google search was performed in the format “program name + orthopaedic trauma fellowship” to assess how accessible the program sites are from outside the 2 databases (OTA, FREIDA). Google was used because it is the most commonly used search engine.¹⁰ The first 25 search results were reviewed for links to OTF websites. Programs without accessible links to OTF websites—from the OTA database, from FREIDA, or from the Google search—were excluded from content assessment.

Accessible websites were electronically captured to ensure consistency of content during assessment. OTF site content was evaluated using methods described in similar investigations.^4,5,11,12 In our dichotomous assessment of fellow education content, we awarded 1 point per content item on the website. The 10 education content items evaluated were call responsibilities, didactic instruction, journal club, research requirements, evaluation criteria, rotation schedule, operative experience, office/clinic experience, meetings attended, and courses attended. We also performed a dichotomous assessment of fellow recruitment content. The 10 recruitment content items evaluated were program description, application requirements, selection criteria, OTA link, SFMP link, location description, program contact information, fellow listing, faculty listing, and salary. Content items were chosen for evaluation on the basis of published OTF applicant experience.¹³ Percentages of education content, recruitment content, and total content were compared by program location, number of fellows, ACGME accreditation status,¹⁴ affiliation with a top 20 orthopedic hospital,¹⁵ and affiliation with a top 20 medical school,¹⁶ as in similar studies.^7,17

Chi-square tests were used to compare content by fellowship location, number of fellows, ACGME accreditation status, affiliation with a top 20 orthopedic hospital, and affiliation with a top 20 medical school. For all tests, the significance level was set at P < .05.

Results

Of the 49 OTF programs identified with database queries, 9 appeared in both the OTA database and FREIDA, 39 appeared only in the OTA database, and 1 appeared only in FREIDA. There were 48 programs total in the OTA database and 10 total in FREIDA.

The OTA database had no OTF website links. Of the 10 OTF links in FREIDA, 3 (6%) were nonfunctioning, 6 (12%) had multiple steps for accessing program information, and 1 (2%) connected directly to program information. Therefore, FREIDA had a total of 7 accessible OTF links (14%). The independent Google search yielded website links for 42 (86%) of the 49 OTF programs. Five links (10%, 5/49) had multiple steps for accessing program information, and 37 links (76%, 37/49) connected directly to program information. The 7 OTF links accessible through FREIDA were accessible through Google as well. Table 1 summarizes the accessibility data.

All 42 accessible OTF websites were assessed for content. On average, these sites had 40% (range, 0%-75%) of the total assessed content. Mean (SD) education content score was 3.6 (2.2) out of 10. Operative experience (88%) and research requirements (81%) were the most consistently presented education items. Didactic learning (45%) and description of common office/clinic cases (43%) were next. Less than 5% of the sites had content on the training courses (eg, sponsored fracture courses) attended by fellows. Figure 1 summarizes the education items on the OTF websites.

Mean (SD) recruitment content score was 4.4 (2.2) out of 10. Program description (93%) and program contact information (88%) were the most consistently presented recruitment items. Clinical faculty (52%) and current and/or prior fellows (36%) were next. Fellow selection criteria appeared least often (12%). Figure 2 summarizes the recruitment items on the OTF websites.

Thirty-six percent of OTF programs with accessible websites were in the southern United States. However, there were no significant differences in online content between OTF program locations. Websites of programs with >1 fellow had significantly more education content (48% vs 33%; P = .043) and total content (46% vs 37%; P = .01) than websites of programs with 1 fellow. ACGME accreditation status, affiliation with a top 20 orthopedic hospital, and affiliation with a top 20 medical school did not have a significant effect on OTF website content. Table 2 summarizes OTF website content by location, number of fellows, top 20 orthopedic hospital affiliation, and top 20 medical school affiliation.

Discussion

We conducted this study to assess the accessibility of OTF program websites and to evaluate the content of the sites. Our hypothesis, that the accessibility and content of online OTF content would be highly variable and largely deficient, was supported by our findings. We found that the OTA database had no OTF website links and that FREIDA links connected directly to only 2% of OTF sites. The majority of OTF sites were accessed from the Google search, which had direct links to 76% of the OTF programs.

Other studies have had similar findings regarding the accessibility of fellowship websites. Mulcahey and colleagues⁶ evaluated sports medicine fellowship websites for accessibility and content, and found that the website of the American Orthopaedic Society for Sports Medicine directly linked to fellowship information for only 3% of programs; a Google search yielded direct links to 71% of program websites. Davidson and colleagues⁴ examined the quality and accessibility of online information on pediatric orthopedic fellowships and found no program links on the website of the Pediatric Orthopaedic Society of North America; a Google search yielded direct links to 68% of programs. Silvestre and colleagues⁷ assessed spine fellowship information on the Internet. The North American Spine Society website had working links to only 3% of fellowship sites, and FREIDA connected to only 6% of sites.

Content scores in our study were highly variable. Mean education and recruitment content scores were 3.6 (range, 0-9) and 4.4 (range, 0-10), respectively. Operative experience (88%) and program description (93%) were the most frequently presented education and recruitment items, respectively. Consistency in presenting program descriptions on OTF websites was slightly poorer than that in other orthopedic specialties. Sports medicine, pediatric orthopedic, and spine fellowship websites provided program descriptions for fellowship recruitment.^4,6,7 Nevertheless, overall content scores in our study and in the aforementioned studies were similarly poor.

In our study, OTF websites showed no significant differences in content scores for program location, ACGME accreditation status, affiliation with a top 20 orthopedic hospital, or affiliation with a top 20 medical school. Lack of a significant effect of medical school or orthopedic hospital affiliation suggests academic prestige does not play a large role in attempts by OTF websites to attract applicants. However, programs with >1 fellow had significantly more education and total content than programs with 1 fellow. Results from a comparable study support this finding. Silvestre and colleagues¹⁸ assessed the accessibility of online plastic surgery residency content. Programs with 3 or 4 residents had significantly more online education content than programs with 1 resident. This finding may relate to the cost efficiency of developing low-cost websites to attract applicants to multiple positions.⁷

Despite lacking links to OTF websites, the OTA database had a large amount of content on 98% (48/49) of OTFs. In addition to presenting the content that we assessed in this study, the OTA database provided the number of inpatient beds at the primary teaching hospital, the annual number of emergency department visits, the annual number of trauma admissions, and the annual number of orthopedic trauma procedures. This standardized information may be very helpful to fellowship applicants and may be an important adjunct to fellowship websites.

FREIDA provided similar content, but accessible links were found for only 14% of the assessed programs. Although the deficiency in accessible OTF links in the OTA database and FREIDA is not well understood, it is important. The results of our study and of similar studies suggest that the listing of active fellowship program links on society websites would benefit orthopedic fellowship applicants, likely fostering a better understanding and a more efficient review of available programs. In addition, links on society websites afford fellowship directors the means to efficiently publicize their programs to large numbers of potential applicants, who likely use society websites as an initial informational resource.

Our study had limitations. First, its findings are subject to the dynamism of the internet, and OTF information may have been updated after this investigation was conducted. Second, our study did not rank-order accessible links, which may have provided more information on the efficiency of using Internet search engines in a review of OTF programs. In addition, our study involved dichotomous assessment of OTF content. Multichotomous evaluation may have further elucidated the quality of website information. Last, our study evaluated websites only for US-based OTF programs. Inclusion of international OTF programs, though outside the scope of this study, may have yielded different findings.

Conclusion

Our results highlight the difficulties that OTF applicants may experience in gathering fellowship information online. OTF website accessibility and content were found to be highly variable and largely deficient. Comparing our findings with those of similar studies revealed that fellowship websites generally provided little information that orthopedic specialty applicants could use. OTF programs should focus on improving their website accessibility and content.

Take-Home Points

• The Internet is a popular resource for orthopedic fellowship applicants.
• 86% of OTF websites are accessible from Google and FREIDA.
• Accessible websites feature only 40% of fellowship applicant content.
• Accessibility and content of OTF websites are highly variable and largely deficient.
• Improvement of the accessibility and content of website information should be a future focus of OTF programs.

The Orthopaedic Trauma Fellowship Match facilitates the matching process for orthopedic residency graduates pursuing a career as orthopedic traumatologists. This match is supported by the Orthopaedic Trauma Association (OTA) and the San Francisco Matching Program (SFMP). Orthopedic trauma fellowship (OTF) programs are accredited by the OTA and may receive oversight by the American Council for Graduate Medical Education (ACGME), which defines uniform standards for fellowship training.¹

Studies have found that the internet is an important and popular resource for applicants researching residency and fellowship programs.^2-5 For many applicants, the internet is their initial and main source of information.⁵ Unfortunately, training programs do not have standardized website accessibility and content.

Few studies have addressed online content on orthopedic fellowship programs,^4,6,7 and to our knowledge no one has studied online content on OTF programs. We conducted a study to assess the accessibility and ease of navigation of OTF websites and to evaluate the content on these sites. We wanted to identify content that applicants may reliably expect on OTF sites. Any deficits identified may be useful to fellowship programs and program directors interested in improving website quality. We hypothesized that the accessibility and content of online OTF content would be highly variable and largely deficient.

Methods

This study was conducted at New York University Hospital for Joint Diseases. On February 5, 2015, both the OTA database⁸ and the Fellowship and Residency Electronic Interactive Database (FREIDA)⁹ were accessed in order to create a comprehensive list of OTF programs. FREIDA, a catalog of all ACGME-accredited graduate medical education programs in the United States, is supported by the American Medical Association and provides cursory program information, including training program duration and number of positions per year.

The databases were reviewed for links to OTF program websites. An independent Google search for program websites was also initiated on February 5, 2015. The Google search was performed in the format “program name + orthopaedic trauma fellowship” to assess how accessible the program sites are from outside the 2 databases (OTA, FREIDA). Google was used because it is the most commonly used search engine.¹⁰ The first 25 search results were reviewed for links to OTF websites. Programs without accessible links to OTF websites—from the OTA database, from FREIDA, or from the Google search—were excluded from content assessment.

Accessible websites were electronically captured to ensure consistency of content during assessment. OTF site content was evaluated using methods described in similar investigations.^4,5,11,12 In our dichotomous assessment of fellow education content, we awarded 1 point per content item on the website. The 10 education content items evaluated were call responsibilities, didactic instruction, journal club, research requirements, evaluation criteria, rotation schedule, operative experience, office/clinic experience, meetings attended, and courses attended. We also performed a dichotomous assessment of fellow recruitment content. The 10 recruitment content items evaluated were program description, application requirements, selection criteria, OTA link, SFMP link, location description, program contact information, fellow listing, faculty listing, and salary. Content items were chosen for evaluation on the basis of published OTF applicant experience.¹³ Percentages of education content, recruitment content, and total content were compared by program location, number of fellows, ACGME accreditation status,¹⁴ affiliation with a top 20 orthopedic hospital,¹⁵ and affiliation with a top 20 medical school,¹⁶ as in similar studies.^7,17

Chi-square tests were used to compare content by fellowship location, number of fellows, ACGME accreditation status, affiliation with a top 20 orthopedic hospital, and affiliation with a top 20 medical school. For all tests, the significance level was set at P < .05.

Results

Of the 49 OTF programs identified with database queries, 9 appeared in both the OTA database and FREIDA, 39 appeared only in the OTA database, and 1 appeared only in FREIDA. There were 48 programs total in the OTA database and 10 total in FREIDA.

The OTA database had no OTF website links. Of the 10 OTF links in FREIDA, 3 (6%) were nonfunctioning, 6 (12%) had multiple steps for accessing program information, and 1 (2%) connected directly to program information. Therefore, FREIDA had a total of 7 accessible OTF links (14%). The independent Google search yielded website links for 42 (86%) of the 49 OTF programs. Five links (10%, 5/49) had multiple steps for accessing program information, and 37 links (76%, 37/49) connected directly to program information. The 7 OTF links accessible through FREIDA were accessible through Google as well. Table 1 summarizes the accessibility data.

All 42 accessible OTF websites were assessed for content. On average, these sites had 40% (range, 0%-75%) of the total assessed content. Mean (SD) education content score was 3.6 (2.2) out of 10. Operative experience (88%) and research requirements (81%) were the most consistently presented education items. Didactic learning (45%) and description of common office/clinic cases (43%) were next. Less than 5% of the sites had content on the training courses (eg, sponsored fracture courses) attended by fellows. Figure 1 summarizes the education items on the OTF websites.

Mean (SD) recruitment content score was 4.4 (2.2) out of 10. Program description (93%) and program contact information (88%) were the most consistently presented recruitment items. Clinical faculty (52%) and current and/or prior fellows (36%) were next. Fellow selection criteria appeared least often (12%). Figure 2 summarizes the recruitment items on the OTF websites.

Thirty-six percent of OTF programs with accessible websites were in the southern United States. However, there were no significant differences in online content between OTF program locations. Websites of programs with >1 fellow had significantly more education content (48% vs 33%; P = .043) and total content (46% vs 37%; P = .01) than websites of programs with 1 fellow. ACGME accreditation status, affiliation with a top 20 orthopedic hospital, and affiliation with a top 20 medical school did not have a significant effect on OTF website content. Table 2 summarizes OTF website content by location, number of fellows, top 20 orthopedic hospital affiliation, and top 20 medical school affiliation.

Discussion

We conducted this study to assess the accessibility of OTF program websites and to evaluate the content of the sites. Our hypothesis, that the accessibility and content of online OTF content would be highly variable and largely deficient, was supported by our findings. We found that the OTA database had no OTF website links and that FREIDA links connected directly to only 2% of OTF sites. The majority of OTF sites were accessed from the Google search, which had direct links to 76% of the OTF programs.

Other studies have had similar findings regarding the accessibility of fellowship websites. Mulcahey and colleagues⁶ evaluated sports medicine fellowship websites for accessibility and content, and found that the website of the American Orthopaedic Society for Sports Medicine directly linked to fellowship information for only 3% of programs; a Google search yielded direct links to 71% of program websites. Davidson and colleagues⁴ examined the quality and accessibility of online information on pediatric orthopedic fellowships and found no program links on the website of the Pediatric Orthopaedic Society of North America; a Google search yielded direct links to 68% of programs. Silvestre and colleagues⁷ assessed spine fellowship information on the Internet. The North American Spine Society website had working links to only 3% of fellowship sites, and FREIDA connected to only 6% of sites.

Content scores in our study were highly variable. Mean education and recruitment content scores were 3.6 (range, 0-9) and 4.4 (range, 0-10), respectively. Operative experience (88%) and program description (93%) were the most frequently presented education and recruitment items, respectively. Consistency in presenting program descriptions on OTF websites was slightly poorer than that in other orthopedic specialties. Sports medicine, pediatric orthopedic, and spine fellowship websites provided program descriptions for fellowship recruitment.^4,6,7 Nevertheless, overall content scores in our study and in the aforementioned studies were similarly poor.

In our study, OTF websites showed no significant differences in content scores for program location, ACGME accreditation status, affiliation with a top 20 orthopedic hospital, or affiliation with a top 20 medical school. Lack of a significant effect of medical school or orthopedic hospital affiliation suggests academic prestige does not play a large role in attempts by OTF websites to attract applicants. However, programs with >1 fellow had significantly more education and total content than programs with 1 fellow. Results from a comparable study support this finding. Silvestre and colleagues¹⁸ assessed the accessibility of online plastic surgery residency content. Programs with 3 or 4 residents had significantly more online education content than programs with 1 resident. This finding may relate to the cost efficiency of developing low-cost websites to attract applicants to multiple positions.⁷

Despite lacking links to OTF websites, the OTA database had a large amount of content on 98% (48/49) of OTFs. In addition to presenting the content that we assessed in this study, the OTA database provided the number of inpatient beds at the primary teaching hospital, the annual number of emergency department visits, the annual number of trauma admissions, and the annual number of orthopedic trauma procedures. This standardized information may be very helpful to fellowship applicants and may be an important adjunct to fellowship websites.

FREIDA provided similar content, but accessible links were found for only 14% of the assessed programs. Although the deficiency in accessible OTF links in the OTA database and FREIDA is not well understood, it is important. The results of our study and of similar studies suggest that the listing of active fellowship program links on society websites would benefit orthopedic fellowship applicants, likely fostering a better understanding and a more efficient review of available programs. In addition, links on society websites afford fellowship directors the means to efficiently publicize their programs to large numbers of potential applicants, who likely use society websites as an initial informational resource.

Our study had limitations. First, its findings are subject to the dynamism of the internet, and OTF information may have been updated after this investigation was conducted. Second, our study did not rank-order accessible links, which may have provided more information on the efficiency of using Internet search engines in a review of OTF programs. In addition, our study involved dichotomous assessment of OTF content. Multichotomous evaluation may have further elucidated the quality of website information. Last, our study evaluated websites only for US-based OTF programs. Inclusion of international OTF programs, though outside the scope of this study, may have yielded different findings.

Conclusion

Our results highlight the difficulties that OTF applicants may experience in gathering fellowship information online. OTF website accessibility and content were found to be highly variable and largely deficient. Comparing our findings with those of similar studies revealed that fellowship websites generally provided little information that orthopedic specialty applicants could use. OTF programs should focus on improving their website accessibility and content.

Take-Home Points

• The Internet is a popular resource for orthopedic fellowship applicants.
• 86% of OTF websites are accessible from Google and FREIDA.
• Accessible websites feature only 40% of fellowship applicant content.
• Accessibility and content of OTF websites are highly variable and largely deficient.
• Improvement of the accessibility and content of website information should be a future focus of OTF programs.

The Orthopaedic Trauma Fellowship Match facilitates the matching process for orthopedic residency graduates pursuing a career as orthopedic traumatologists. This match is supported by the Orthopaedic Trauma Association (OTA) and the San Francisco Matching Program (SFMP). Orthopedic trauma fellowship (OTF) programs are accredited by the OTA and may receive oversight by the American Council for Graduate Medical Education (ACGME), which defines uniform standards for fellowship training.¹

Studies have found that the internet is an important and popular resource for applicants researching residency and fellowship programs.^2-5 For many applicants, the internet is their initial and main source of information.⁵ Unfortunately, training programs do not have standardized website accessibility and content.

Few studies have addressed online content on orthopedic fellowship programs,^4,6,7 and to our knowledge no one has studied online content on OTF programs. We conducted a study to assess the accessibility and ease of navigation of OTF websites and to evaluate the content on these sites. We wanted to identify content that applicants may reliably expect on OTF sites. Any deficits identified may be useful to fellowship programs and program directors interested in improving website quality. We hypothesized that the accessibility and content of online OTF content would be highly variable and largely deficient.

Methods

This study was conducted at New York University Hospital for Joint Diseases. On February 5, 2015, both the OTA database⁸ and the Fellowship and Residency Electronic Interactive Database (FREIDA)⁹ were accessed in order to create a comprehensive list of OTF programs. FREIDA, a catalog of all ACGME-accredited graduate medical education programs in the United States, is supported by the American Medical Association and provides cursory program information, including training program duration and number of positions per year.

The databases were reviewed for links to OTF program websites. An independent Google search for program websites was also initiated on February 5, 2015. The Google search was performed in the format “program name + orthopaedic trauma fellowship” to assess how accessible the program sites are from outside the 2 databases (OTA, FREIDA). Google was used because it is the most commonly used search engine.¹⁰ The first 25 search results were reviewed for links to OTF websites. Programs without accessible links to OTF websites—from the OTA database, from FREIDA, or from the Google search—were excluded from content assessment.

Accessible websites were electronically captured to ensure consistency of content during assessment. OTF site content was evaluated using methods described in similar investigations.^4,5,11,12 In our dichotomous assessment of fellow education content, we awarded 1 point per content item on the website. The 10 education content items evaluated were call responsibilities, didactic instruction, journal club, research requirements, evaluation criteria, rotation schedule, operative experience, office/clinic experience, meetings attended, and courses attended. We also performed a dichotomous assessment of fellow recruitment content. The 10 recruitment content items evaluated were program description, application requirements, selection criteria, OTA link, SFMP link, location description, program contact information, fellow listing, faculty listing, and salary. Content items were chosen for evaluation on the basis of published OTF applicant experience.¹³ Percentages of education content, recruitment content, and total content were compared by program location, number of fellows, ACGME accreditation status,¹⁴ affiliation with a top 20 orthopedic hospital,¹⁵ and affiliation with a top 20 medical school,¹⁶ as in similar studies.^7,17

Chi-square tests were used to compare content by fellowship location, number of fellows, ACGME accreditation status, affiliation with a top 20 orthopedic hospital, and affiliation with a top 20 medical school. For all tests, the significance level was set at P < .05.

Results

Of the 49 OTF programs identified with database queries, 9 appeared in both the OTA database and FREIDA, 39 appeared only in the OTA database, and 1 appeared only in FREIDA. There were 48 programs total in the OTA database and 10 total in FREIDA.

The OTA database had no OTF website links. Of the 10 OTF links in FREIDA, 3 (6%) were nonfunctioning, 6 (12%) had multiple steps for accessing program information, and 1 (2%) connected directly to program information. Therefore, FREIDA had a total of 7 accessible OTF links (14%). The independent Google search yielded website links for 42 (86%) of the 49 OTF programs. Five links (10%, 5/49) had multiple steps for accessing program information, and 37 links (76%, 37/49) connected directly to program information. The 7 OTF links accessible through FREIDA were accessible through Google as well. Table 1 summarizes the accessibility data.

All 42 accessible OTF websites were assessed for content. On average, these sites had 40% (range, 0%-75%) of the total assessed content. Mean (SD) education content score was 3.6 (2.2) out of 10. Operative experience (88%) and research requirements (81%) were the most consistently presented education items. Didactic learning (45%) and description of common office/clinic cases (43%) were next. Less than 5% of the sites had content on the training courses (eg, sponsored fracture courses) attended by fellows. Figure 1 summarizes the education items on the OTF websites.

Mean (SD) recruitment content score was 4.4 (2.2) out of 10. Program description (93%) and program contact information (88%) were the most consistently presented recruitment items. Clinical faculty (52%) and current and/or prior fellows (36%) were next. Fellow selection criteria appeared least often (12%). Figure 2 summarizes the recruitment items on the OTF websites.

Thirty-six percent of OTF programs with accessible websites were in the southern United States. However, there were no significant differences in online content between OTF program locations. Websites of programs with >1 fellow had significantly more education content (48% vs 33%; P = .043) and total content (46% vs 37%; P = .01) than websites of programs with 1 fellow. ACGME accreditation status, affiliation with a top 20 orthopedic hospital, and affiliation with a top 20 medical school did not have a significant effect on OTF website content. Table 2 summarizes OTF website content by location, number of fellows, top 20 orthopedic hospital affiliation, and top 20 medical school affiliation.

Discussion

We conducted this study to assess the accessibility of OTF program websites and to evaluate the content of the sites. Our hypothesis, that the accessibility and content of online OTF content would be highly variable and largely deficient, was supported by our findings. We found that the OTA database had no OTF website links and that FREIDA links connected directly to only 2% of OTF sites. The majority of OTF sites were accessed from the Google search, which had direct links to 76% of the OTF programs.

Other studies have had similar findings regarding the accessibility of fellowship websites. Mulcahey and colleagues⁶ evaluated sports medicine fellowship websites for accessibility and content, and found that the website of the American Orthopaedic Society for Sports Medicine directly linked to fellowship information for only 3% of programs; a Google search yielded direct links to 71% of program websites. Davidson and colleagues⁴ examined the quality and accessibility of online information on pediatric orthopedic fellowships and found no program links on the website of the Pediatric Orthopaedic Society of North America; a Google search yielded direct links to 68% of programs. Silvestre and colleagues⁷ assessed spine fellowship information on the Internet. The North American Spine Society website had working links to only 3% of fellowship sites, and FREIDA connected to only 6% of sites.

Content scores in our study were highly variable. Mean education and recruitment content scores were 3.6 (range, 0-9) and 4.4 (range, 0-10), respectively. Operative experience (88%) and program description (93%) were the most frequently presented education and recruitment items, respectively. Consistency in presenting program descriptions on OTF websites was slightly poorer than that in other orthopedic specialties. Sports medicine, pediatric orthopedic, and spine fellowship websites provided program descriptions for fellowship recruitment.^4,6,7 Nevertheless, overall content scores in our study and in the aforementioned studies were similarly poor.

In our study, OTF websites showed no significant differences in content scores for program location, ACGME accreditation status, affiliation with a top 20 orthopedic hospital, or affiliation with a top 20 medical school. Lack of a significant effect of medical school or orthopedic hospital affiliation suggests academic prestige does not play a large role in attempts by OTF websites to attract applicants. However, programs with >1 fellow had significantly more education and total content than programs with 1 fellow. Results from a comparable study support this finding. Silvestre and colleagues¹⁸ assessed the accessibility of online plastic surgery residency content. Programs with 3 or 4 residents had significantly more online education content than programs with 1 resident. This finding may relate to the cost efficiency of developing low-cost websites to attract applicants to multiple positions.⁷

Despite lacking links to OTF websites, the OTA database had a large amount of content on 98% (48/49) of OTFs. In addition to presenting the content that we assessed in this study, the OTA database provided the number of inpatient beds at the primary teaching hospital, the annual number of emergency department visits, the annual number of trauma admissions, and the annual number of orthopedic trauma procedures. This standardized information may be very helpful to fellowship applicants and may be an important adjunct to fellowship websites.

FREIDA provided similar content, but accessible links were found for only 14% of the assessed programs. Although the deficiency in accessible OTF links in the OTA database and FREIDA is not well understood, it is important. The results of our study and of similar studies suggest that the listing of active fellowship program links on society websites would benefit orthopedic fellowship applicants, likely fostering a better understanding and a more efficient review of available programs. In addition, links on society websites afford fellowship directors the means to efficiently publicize their programs to large numbers of potential applicants, who likely use society websites as an initial informational resource.

Our study had limitations. First, its findings are subject to the dynamism of the internet, and OTF information may have been updated after this investigation was conducted. Second, our study did not rank-order accessible links, which may have provided more information on the efficiency of using Internet search engines in a review of OTF programs. In addition, our study involved dichotomous assessment of OTF content. Multichotomous evaluation may have further elucidated the quality of website information. Last, our study evaluated websites only for US-based OTF programs. Inclusion of international OTF programs, though outside the scope of this study, may have yielded different findings.

Conclusion

Our results highlight the difficulties that OTF applicants may experience in gathering fellowship information online. OTF website accessibility and content were found to be highly variable and largely deficient. Comparing our findings with those of similar studies revealed that fellowship websites generally provided little information that orthopedic specialty applicants could use. OTF programs should focus on improving their website accessibility and content.

Take-Home Points

• IV-TXA significantly reduces intraoperative blood loss following TJA.
• Early mobilization correlates with reduced incidence of postoperative complications.
• IV-TXA minimizes postoperative anemia, facilitating improved early ambulation following TJA.
• IV-TXA significantly reduces the need for postoperative transfusions.
• IV-TXA is safe to use with no adverse events noted.

By the year 2020, use of primary total knee arthroplasty (TKA) in the United States will increase an estimated 110%, to 1.375 million procedures annually, and use of primary total hip arthroplasty (THA) will increase an estimated 75%, to more than 500,000 procedures.¹ Minimizing perioperative blood loss and improving early postoperative ambulation both correlate with reduced postoperative morbidity, allowing patients to return to their daily lives expeditiously. 

Tranexamic acid (TXA), a fibrinolytic inhibitor, competitively blocks lysine receptor binding sites of plasminogen, sustaining and stabilizing the fibrin architecture.² TXA must be present to occupy binding sites before plasminogen binds to fibrin, validating the need for preoperative administration so the drug is available early in the fibrinolytic cascade.³ Intravenous (IV) TXA diffuses rapidly into joint fluid and the synovial membrane.⁴ Drug concentration and elimination half-life in joint fluid are equivalent to those in serum. Elimination of TXA occurs by glomerular filtration, with about 30% of a 10-mg/kg dose removed in 1 hour, 55% over the first 3 hours, and 90% within 24 hours of IV administration.⁵

The efficacy of IV-TXA in minimizing total joint arthroplasty (TJA) perioperative blood loss has been proved in small studies and meta-analyses.^6-9 TXA-induced blood conservation decreases or eliminates the need for postoperative transfusion, which can impede valuable, early ambulation.10 In addition, the positive clinical safety profile of TXA supports routine use of TXA in TJA.^6,11-15

The benefits of early ambulation after TJA are well established. Getting patients to walk on the day of surgery is a key part of effective and rapid postoperative rehabilitation. Early mobilization correlates with reduced incidence of venous thrombosis and postoperative complications.¹⁶ In contrast to bed rest, sitting and standing promotes oxygen saturation, which improves tissue healing and minimizes adverse pulmonary events. Oxygen saturation also preserves muscle strength and blood flow, reducing the risk of venous thromboembolism and ulcers. Muscle strength must be maintained so normal gait can be regained.¹⁷ Compared with rehabilitation initiated 48 to 72 hours after TKA, rehabilitation initiated within 24 hours reduced the number of sessions needed to achieve independence and normal gait; in addition, early mobilization improved patient reports of pain after surgery.¹⁸ An evaluation of Denmark registry data revealed that mobilization to walking and use of crutches or canes was achieved earlier when ambulation was initiated on day of surgery.¹⁹ Finally, mobilization on day of surgery and during the immediate postoperative period improved long-term quality of life after TJA.²⁰

We conducted a retrospective cohort study to determine if use of IV-TXA improves early ambulation and reduces blood loss after TKA and anterior and posterior THA. We hypothesized that IV-TXA use would reduce postoperative anemia and improve early ambulation and outcomes without producing adverse events during the immediate postoperative period. TXA reduces bleeding, and reduced incidence of hemarthrosis, wound swelling, and anemia could facilitate ambulation, reduce complications, and shorten recovery in patients who undergo TJA.

Patients and Methods

In February 2014, this retrospective cohort study received Institutional Review Board approval to compare the safety and efficacy of IV-TXA (vs no TXA) in patients who underwent TKA, anterior THA, and posterior THA.

In March 2012, multidisciplinary protocols were standardized to ensure a uniform hospital course for patients at our institution. All patients underwent preoperative testing and evaluation by a nurse practitioner and an anesthesiologist. In March 2013, IV-TXA became our standard of care. TXA use was contraindicated in patients with thromboembolic disease or with hypersensitivity to TXA. Patients without a contraindication were given two 10-mg/kg IV-TXA doses, each administered over 15 to 30 minutes; the first dose was administered before incision, and the second was infused at case close and/or at least 60 minutes after the first dose. Most TKA patients received regional (femoral) anesthesia and analgesia, and most THA patients received spinal or epidural anesthesia and analgesia. In a small percentage of cases, IV analgesia was patient-controlled, as determined by the pain service. There were no significant differences in anesthesia/analgesia modality between the 2 study groups—patients who received TXA and those who did not. Patients were then transitioned to oral opioids for pain management, unless otherwise contraindicated, and were ambulated 4 hours after end of surgery, unless medically unstable. Hematology and chemistry laboratory values were monitored daily during admission.

Patients underwent physical therapy (PT) after surgery and until hospital discharge. Physical therapists blinded to patients’ intraoperative use or no use of TXA measured ambulation. After initial evaluation on postoperative day 0 (POD-0), patients were ambulated twice daily. The daily ambulation distance used for the study was the larger of the 2 daily PT distances (occasionally, patients were unable to participate fully in both sessions). Patients received either enoxaparin or rivaroxaban for postoperative thromboprophylaxis (the anticoagulant used was based on surgeon preference). Enoxaparin was subcutaneously administered at 30 mg every 12 hours for TKA, 40 mg once daily for THA, 30 mg once daily for calculated creatinine clearance under 30 mL/min, or 40 mg every 12 hours for body mass index (BMI) 40 or above. With enoxaparin, therapy duration was 14 days. Oral rivaroxaban was administered at 10 mg once daily for 12 days for TKA and 35 days for THA unless contraindicated.

The primary outcome variables were ambulation measured on POD-1 and POD-2 and intraoperative blood loss. In addition, hemoglobin and hematocrit were measured on POD-0, POD-1, and POD-2. Ambulation was defined as number of feet walked during postoperative hospitalization. To calculate intraoperative blood loss, the anesthesiologist subtracted any saline irrigation volume from the total volume in the suction canister. Also noted were postoperative transfusions and any diagnosis of postoperative venous thromboembolism—specifically, deep vein thrombosis (DVT) or pulmonary embolism (PE).

Demographic and clinical characteristics of the TXA and no-TXA groups were compared using either 2-sample t test (for continuous variables) or χ2 test (for categorical variables).

The ambulation outcome was log-transformed to meet standard assumptions of Gaussian residuals and equality of variance. Means and 95% confidence intervals (CIs) were calculated on the log scale and were anti-logged so the results could be presented in their original units. 

A linear mixed model was used to model intraoperative blood loss as a function of group (TXA, no TXA), procedure (TKA, anterior THA, posterior THA), and potential confounders (age, sex, BMI, operative time).

Linear mixed models for repeated measures were used to compare outcomes (hemoglobin, hematocrit) between groups (TXA, no TXA) and procedures (TKA, anterior THA, posterior THA) and to compare changes in outcomes over time. Group, procedure, and operative time interactions were explored. Potential confounders (age, sex, BMI, operative time) were included in the model as well.

A χ2 test was used to compare the groups (TXA, no TXA) on postoperative blood transfusion (yes, no). Given the smaller number of events, a more complex model accounting for clustered data and potential confounders was not used. Need for transfusion was clinically assessed case by case. Symptomatic anemia (dyspnea on exertion, headaches, tachycardia) was used as the primary indication for transfusion once hemoglobin fell below 8 g/dL or hematocrit below 24%. Number of patients with a postoperative thrombus formation was minimal. Therefore, this outcome was described with summary statistics and was not formally analyzed.

Results

Of the 477 patients who underwent TJAs (275 TKAs, 98 anterior THAs, 104 posterior THAs; all unilateral), 111 did not receive TXA (June 2012-February 2013), and 366 received TXA (March 2013-January 2014). Other than for the addition of IV-TXA, the same standardized protocols instituted in March 2012 continued throughout the study period. The difference in sample size between the TXA and no-TXA groups was not statistically significant and did not influence the outcome measures.

Ambulation

There was a significant (P = .0066) 3-way interaction of TXA, procedure, and operative time after adjusting for age (P < .0001), sex (P < .0001), BMI (P < .0001), and operative time (P = .8308). Regarding TKA, mean ambulation was higher for the TXA group than for the no-TXA group at POD-1 (8.36 vs 3.40 feet; P < .0001) and POD-2 (25.81 vs 18.75 feet; P = .0054). The same was true for anterior THA at POD-1 (10.86 vs 3.33 feet; P < .0001) and POD-2 (27.24 vs 13.19 feet; P < .0001) and posterior THA at POD-1 (10.64 vs 3.37 feet; P < .0001) and POD-2 (24.68 vs 12.93 feet; P = .0002). See Table 3.

Intraoperative Blood Loss

There was a significant 3-way interaction of TXA, procedure (P < .0053), and operative time (P < .0001) after adjusting for age (P < .6136), sex (P = .1147), and BMI (P = .6180). Regarding TKA, mean intraoperative blood loss was significantly lower for the TXA group than for the no-TXA group (241.58 vs 287.81 mL; P = .0004). The same was true for anterior THA (352.91 vs 533.79 mL; P < .0001). Regarding posterior THA, there was no significant difference between the TXA and no-TXA groups (326.00 vs 350.16 mL; P = .3246). See Table 4. 

Hemoglobin

There was a significant (P = .0008) 3-way interaction of TXA, procedure, and operative time after adjusting for age (P = .0174), sex (P < .0001), BMI (P = .0007), and operative time (P = .0002). Regarding TKA, postoperative hemoglobin levels were higher for the TXA group than for the no-TXA group at POD-0 (12.10 vs 11.68 g/dL; P = .0135), POD-1 (11.62 vs 10.67 g/dL; P < .0001), and POD-2 (11.02 vs 10.11 g/dL; P < .0001). The same was true for anterior THA at POD-1 (11.03 vs 10.19 g/dL; P = .0034) and POD-2 (10.57 vs 9.64 g/dL; P = .0009) and posterior THA at POD-2 (11.04 vs 10.16 g/dL; P = .0003). See Table 5.

Hematocrit

There was a significant (P < .0006) 3-way interaction of TXA, procedure, and operative time after adjusting for age (P = .1597), sex (P < .0001), BMI (P < .0001), and operative time (P = .0003). Regarding TKA, postoperative hematocrit levels were higher for the TXA group than for the no-TXA group at POD-0 (36.52% vs 34.65%; P < .0001), POD-1 (34.62% vs 31.83%; P < .0001), and POD-2 (33.01% vs 30.20%; P < .0001). The same was true for anterior THA at POD-1 (32.82% vs 30.59%; P = .0037) and POD-2 (31.58% vs 28.61%; P = .0004) and posterior THA at POD-2 (32.93% vs 30.17%; P < .0001). See Table 6.

Postoperative Transfusions 

Of the 477 patients, 25 (5.24%) required a postoperative transfusion. Postoperative transfusions were less likely (P < .0001) required in the TXA group (1.64%, 6/366) than in the no-TXA group (17.12%, 19/111). Given the smaller number of events, a more complex model accounting for clustered data and potential confounders was not used, and the different procedures were not evaluated separately.

Deep Vein Thrombosis and Pulmonary Embolism

Of the 477 patients, 2 developed a DVT, and 5 developed a PE. Both DVTs occurred in the TXA group (2/366, 0.55%; 95% CI, 0.07%-1.96%). Of the 5 PEs, 4 occurred in the TXA group (4/366, 1.09%; 95% CI, 0.30%-2.77%), and 1 occurred in the no-TXA group (1/111, 0.90%; 95% CI, 0.02%-4.92%). Given the exceedingly small number of events, no statistical significance was noted between groups.

Discussion

Orthopedic surgeons carefully balance patient expectations, societal needs, and regulatory mandates while providing excellent care and working under payers’ financial restrictions. The Centers for Medicare & Medicaid Services announced that, starting in 2016, TJAs will be reimbursed in total as a single bundled payment, adding to the need to provide optimal care in a fiscally responsible manner.²¹ Standardized protocols implementing multimodal therapies are pivotal in achieving favorable postoperative outcomes.

Our study results showed that IV-TXA use minimized hemoglobin and hematocrit reductions after TKA, anterior THA, and posterior THA. Postoperative anemia correlates with decreased ambulation ability and performance during the early postoperative period. In general, higher postoperative hemoglobin and hematocrit levels result in improved motor performance and shorter recovery.²² In addition, early ambulation is a validated predictor of favorable TJA outcomes. In our study, for TKA, anterior THA, and posterior THA, ambulation on POD-1 and POD-2 was significantly better for patients who received TXA than for patients who did not.

Transfusion rates were markedly lower for our TXA group than for our no-TXA group (1.64% vs 17.12%), confirming the findings of numerous other studies on outcomes of TJA with TXA.^{2,3,6-12,14,15} Transfusions impede physical therapy and affect hospitalization costs.

Although potential thrombosis-related adverse events remain an endpoint in studies involving TXA, we found a comparably low incidence of postoperative venous thrombosis in our TXA and no-TXA groups (1.09% and 0.90%, respectively). In addition, no patient in either group developed a postoperative arterial thrombosis.

This is the largest single-center study of TXA use in TKA, anterior THA, and posterior THA. The effect of TXA use on postoperative ambulation was not previously found with TJA.

This study had its limitations. First, it was not prospective, randomized, or double-blinded. However, the physical therapists who mobilized patients and recorded ambulation data were blinded to the study and its hypothesis and followed a standardized protocol for all patients. In addition, intraoperative blood loss was recorded by an anesthesiologist using a standardized protocol, and patients received TXA per orthopedic protocol and surgeon preference, without selection bias. Another limitation was that ambulation data were captured only for POD-1 and POD-2 (most patients were discharged by POD-3). However, a goal of the study was to capture immediate postoperative data in order to determine the efficacy of intraoperative TXA. Subsequent studies can determine if this early benefit leads to long-term clinical outcome improvements.

In reducing blood loss and transfusion rates, intra-articular TXA is as efficacious as IV-TXA.^23-25 We anticipate that the improved clinical outcomes found with IV-TXA in our study will be similar with intra-articular TXA, but more study is needed to confirm this hypothesis.

Conclusion

This retrospective cohort study found that use of IV-TXA in TJA improved early ambulation and clinical outcomes (reduced anemia, fewer transfusions) in the initial postoperative period, without producing adverse events.

Take-Home Points

• IV-TXA significantly reduces intraoperative blood loss following TJA.
• Early mobilization correlates with reduced incidence of postoperative complications.
• IV-TXA minimizes postoperative anemia, facilitating improved early ambulation following TJA.
• IV-TXA significantly reduces the need for postoperative transfusions.
• IV-TXA is safe to use with no adverse events noted.

By the year 2020, use of primary total knee arthroplasty (TKA) in the United States will increase an estimated 110%, to 1.375 million procedures annually, and use of primary total hip arthroplasty (THA) will increase an estimated 75%, to more than 500,000 procedures.¹ Minimizing perioperative blood loss and improving early postoperative ambulation both correlate with reduced postoperative morbidity, allowing patients to return to their daily lives expeditiously. 

Tranexamic acid (TXA), a fibrinolytic inhibitor, competitively blocks lysine receptor binding sites of plasminogen, sustaining and stabilizing the fibrin architecture.² TXA must be present to occupy binding sites before plasminogen binds to fibrin, validating the need for preoperative administration so the drug is available early in the fibrinolytic cascade.³ Intravenous (IV) TXA diffuses rapidly into joint fluid and the synovial membrane.⁴ Drug concentration and elimination half-life in joint fluid are equivalent to those in serum. Elimination of TXA occurs by glomerular filtration, with about 30% of a 10-mg/kg dose removed in 1 hour, 55% over the first 3 hours, and 90% within 24 hours of IV administration.⁵

The efficacy of IV-TXA in minimizing total joint arthroplasty (TJA) perioperative blood loss has been proved in small studies and meta-analyses.^6-9 TXA-induced blood conservation decreases or eliminates the need for postoperative transfusion, which can impede valuable, early ambulation.10 In addition, the positive clinical safety profile of TXA supports routine use of TXA in TJA.^6,11-15

The benefits of early ambulation after TJA are well established. Getting patients to walk on the day of surgery is a key part of effective and rapid postoperative rehabilitation. Early mobilization correlates with reduced incidence of venous thrombosis and postoperative complications.¹⁶ In contrast to bed rest, sitting and standing promotes oxygen saturation, which improves tissue healing and minimizes adverse pulmonary events. Oxygen saturation also preserves muscle strength and blood flow, reducing the risk of venous thromboembolism and ulcers. Muscle strength must be maintained so normal gait can be regained.¹⁷ Compared with rehabilitation initiated 48 to 72 hours after TKA, rehabilitation initiated within 24 hours reduced the number of sessions needed to achieve independence and normal gait; in addition, early mobilization improved patient reports of pain after surgery.¹⁸ An evaluation of Denmark registry data revealed that mobilization to walking and use of crutches or canes was achieved earlier when ambulation was initiated on day of surgery.¹⁹ Finally, mobilization on day of surgery and during the immediate postoperative period improved long-term quality of life after TJA.²⁰

We conducted a retrospective cohort study to determine if use of IV-TXA improves early ambulation and reduces blood loss after TKA and anterior and posterior THA. We hypothesized that IV-TXA use would reduce postoperative anemia and improve early ambulation and outcomes without producing adverse events during the immediate postoperative period. TXA reduces bleeding, and reduced incidence of hemarthrosis, wound swelling, and anemia could facilitate ambulation, reduce complications, and shorten recovery in patients who undergo TJA.

Patients and Methods

In February 2014, this retrospective cohort study received Institutional Review Board approval to compare the safety and efficacy of IV-TXA (vs no TXA) in patients who underwent TKA, anterior THA, and posterior THA.

In March 2012, multidisciplinary protocols were standardized to ensure a uniform hospital course for patients at our institution. All patients underwent preoperative testing and evaluation by a nurse practitioner and an anesthesiologist. In March 2013, IV-TXA became our standard of care. TXA use was contraindicated in patients with thromboembolic disease or with hypersensitivity to TXA. Patients without a contraindication were given two 10-mg/kg IV-TXA doses, each administered over 15 to 30 minutes; the first dose was administered before incision, and the second was infused at case close and/or at least 60 minutes after the first dose. Most TKA patients received regional (femoral) anesthesia and analgesia, and most THA patients received spinal or epidural anesthesia and analgesia. In a small percentage of cases, IV analgesia was patient-controlled, as determined by the pain service. There were no significant differences in anesthesia/analgesia modality between the 2 study groups—patients who received TXA and those who did not. Patients were then transitioned to oral opioids for pain management, unless otherwise contraindicated, and were ambulated 4 hours after end of surgery, unless medically unstable. Hematology and chemistry laboratory values were monitored daily during admission.

Patients underwent physical therapy (PT) after surgery and until hospital discharge. Physical therapists blinded to patients’ intraoperative use or no use of TXA measured ambulation. After initial evaluation on postoperative day 0 (POD-0), patients were ambulated twice daily. The daily ambulation distance used for the study was the larger of the 2 daily PT distances (occasionally, patients were unable to participate fully in both sessions). Patients received either enoxaparin or rivaroxaban for postoperative thromboprophylaxis (the anticoagulant used was based on surgeon preference). Enoxaparin was subcutaneously administered at 30 mg every 12 hours for TKA, 40 mg once daily for THA, 30 mg once daily for calculated creatinine clearance under 30 mL/min, or 40 mg every 12 hours for body mass index (BMI) 40 or above. With enoxaparin, therapy duration was 14 days. Oral rivaroxaban was administered at 10 mg once daily for 12 days for TKA and 35 days for THA unless contraindicated.

The primary outcome variables were ambulation measured on POD-1 and POD-2 and intraoperative blood loss. In addition, hemoglobin and hematocrit were measured on POD-0, POD-1, and POD-2. Ambulation was defined as number of feet walked during postoperative hospitalization. To calculate intraoperative blood loss, the anesthesiologist subtracted any saline irrigation volume from the total volume in the suction canister. Also noted were postoperative transfusions and any diagnosis of postoperative venous thromboembolism—specifically, deep vein thrombosis (DVT) or pulmonary embolism (PE).

Demographic and clinical characteristics of the TXA and no-TXA groups were compared using either 2-sample t test (for continuous variables) or χ2 test (for categorical variables).

The ambulation outcome was log-transformed to meet standard assumptions of Gaussian residuals and equality of variance. Means and 95% confidence intervals (CIs) were calculated on the log scale and were anti-logged so the results could be presented in their original units. 

A linear mixed model was used to model intraoperative blood loss as a function of group (TXA, no TXA), procedure (TKA, anterior THA, posterior THA), and potential confounders (age, sex, BMI, operative time).

Linear mixed models for repeated measures were used to compare outcomes (hemoglobin, hematocrit) between groups (TXA, no TXA) and procedures (TKA, anterior THA, posterior THA) and to compare changes in outcomes over time. Group, procedure, and operative time interactions were explored. Potential confounders (age, sex, BMI, operative time) were included in the model as well.

A χ2 test was used to compare the groups (TXA, no TXA) on postoperative blood transfusion (yes, no). Given the smaller number of events, a more complex model accounting for clustered data and potential confounders was not used. Need for transfusion was clinically assessed case by case. Symptomatic anemia (dyspnea on exertion, headaches, tachycardia) was used as the primary indication for transfusion once hemoglobin fell below 8 g/dL or hematocrit below 24%. Number of patients with a postoperative thrombus formation was minimal. Therefore, this outcome was described with summary statistics and was not formally analyzed.

Results

Of the 477 patients who underwent TJAs (275 TKAs, 98 anterior THAs, 104 posterior THAs; all unilateral), 111 did not receive TXA (June 2012-February 2013), and 366 received TXA (March 2013-January 2014). Other than for the addition of IV-TXA, the same standardized protocols instituted in March 2012 continued throughout the study period. The difference in sample size between the TXA and no-TXA groups was not statistically significant and did not influence the outcome measures.

Ambulation

There was a significant (P = .0066) 3-way interaction of TXA, procedure, and operative time after adjusting for age (P < .0001), sex (P < .0001), BMI (P < .0001), and operative time (P = .8308). Regarding TKA, mean ambulation was higher for the TXA group than for the no-TXA group at POD-1 (8.36 vs 3.40 feet; P < .0001) and POD-2 (25.81 vs 18.75 feet; P = .0054). The same was true for anterior THA at POD-1 (10.86 vs 3.33 feet; P < .0001) and POD-2 (27.24 vs 13.19 feet; P < .0001) and posterior THA at POD-1 (10.64 vs 3.37 feet; P < .0001) and POD-2 (24.68 vs 12.93 feet; P = .0002). See Table 3.

Intraoperative Blood Loss

There was a significant 3-way interaction of TXA, procedure (P < .0053), and operative time (P < .0001) after adjusting for age (P < .6136), sex (P = .1147), and BMI (P = .6180). Regarding TKA, mean intraoperative blood loss was significantly lower for the TXA group than for the no-TXA group (241.58 vs 287.81 mL; P = .0004). The same was true for anterior THA (352.91 vs 533.79 mL; P < .0001). Regarding posterior THA, there was no significant difference between the TXA and no-TXA groups (326.00 vs 350.16 mL; P = .3246). See Table 4. 

Hemoglobin

There was a significant (P = .0008) 3-way interaction of TXA, procedure, and operative time after adjusting for age (P = .0174), sex (P < .0001), BMI (P = .0007), and operative time (P = .0002). Regarding TKA, postoperative hemoglobin levels were higher for the TXA group than for the no-TXA group at POD-0 (12.10 vs 11.68 g/dL; P = .0135), POD-1 (11.62 vs 10.67 g/dL; P < .0001), and POD-2 (11.02 vs 10.11 g/dL; P < .0001). The same was true for anterior THA at POD-1 (11.03 vs 10.19 g/dL; P = .0034) and POD-2 (10.57 vs 9.64 g/dL; P = .0009) and posterior THA at POD-2 (11.04 vs 10.16 g/dL; P = .0003). See Table 5.

Hematocrit

There was a significant (P < .0006) 3-way interaction of TXA, procedure, and operative time after adjusting for age (P = .1597), sex (P < .0001), BMI (P < .0001), and operative time (P = .0003). Regarding TKA, postoperative hematocrit levels were higher for the TXA group than for the no-TXA group at POD-0 (36.52% vs 34.65%; P < .0001), POD-1 (34.62% vs 31.83%; P < .0001), and POD-2 (33.01% vs 30.20%; P < .0001). The same was true for anterior THA at POD-1 (32.82% vs 30.59%; P = .0037) and POD-2 (31.58% vs 28.61%; P = .0004) and posterior THA at POD-2 (32.93% vs 30.17%; P < .0001). See Table 6.

Postoperative Transfusions 

Of the 477 patients, 25 (5.24%) required a postoperative transfusion. Postoperative transfusions were less likely (P < .0001) required in the TXA group (1.64%, 6/366) than in the no-TXA group (17.12%, 19/111). Given the smaller number of events, a more complex model accounting for clustered data and potential confounders was not used, and the different procedures were not evaluated separately.

Deep Vein Thrombosis and Pulmonary Embolism

Of the 477 patients, 2 developed a DVT, and 5 developed a PE. Both DVTs occurred in the TXA group (2/366, 0.55%; 95% CI, 0.07%-1.96%). Of the 5 PEs, 4 occurred in the TXA group (4/366, 1.09%; 95% CI, 0.30%-2.77%), and 1 occurred in the no-TXA group (1/111, 0.90%; 95% CI, 0.02%-4.92%). Given the exceedingly small number of events, no statistical significance was noted between groups.

Discussion

Orthopedic surgeons carefully balance patient expectations, societal needs, and regulatory mandates while providing excellent care and working under payers’ financial restrictions. The Centers for Medicare & Medicaid Services announced that, starting in 2016, TJAs will be reimbursed in total as a single bundled payment, adding to the need to provide optimal care in a fiscally responsible manner.²¹ Standardized protocols implementing multimodal therapies are pivotal in achieving favorable postoperative outcomes.

Our study results showed that IV-TXA use minimized hemoglobin and hematocrit reductions after TKA, anterior THA, and posterior THA. Postoperative anemia correlates with decreased ambulation ability and performance during the early postoperative period. In general, higher postoperative hemoglobin and hematocrit levels result in improved motor performance and shorter recovery.²² In addition, early ambulation is a validated predictor of favorable TJA outcomes. In our study, for TKA, anterior THA, and posterior THA, ambulation on POD-1 and POD-2 was significantly better for patients who received TXA than for patients who did not.

Transfusion rates were markedly lower for our TXA group than for our no-TXA group (1.64% vs 17.12%), confirming the findings of numerous other studies on outcomes of TJA with TXA.^{2,3,6-12,14,15} Transfusions impede physical therapy and affect hospitalization costs.

Although potential thrombosis-related adverse events remain an endpoint in studies involving TXA, we found a comparably low incidence of postoperative venous thrombosis in our TXA and no-TXA groups (1.09% and 0.90%, respectively). In addition, no patient in either group developed a postoperative arterial thrombosis.

This is the largest single-center study of TXA use in TKA, anterior THA, and posterior THA. The effect of TXA use on postoperative ambulation was not previously found with TJA.

This study had its limitations. First, it was not prospective, randomized, or double-blinded. However, the physical therapists who mobilized patients and recorded ambulation data were blinded to the study and its hypothesis and followed a standardized protocol for all patients. In addition, intraoperative blood loss was recorded by an anesthesiologist using a standardized protocol, and patients received TXA per orthopedic protocol and surgeon preference, without selection bias. Another limitation was that ambulation data were captured only for POD-1 and POD-2 (most patients were discharged by POD-3). However, a goal of the study was to capture immediate postoperative data in order to determine the efficacy of intraoperative TXA. Subsequent studies can determine if this early benefit leads to long-term clinical outcome improvements.

In reducing blood loss and transfusion rates, intra-articular TXA is as efficacious as IV-TXA.^23-25 We anticipate that the improved clinical outcomes found with IV-TXA in our study will be similar with intra-articular TXA, but more study is needed to confirm this hypothesis.

Conclusion

This retrospective cohort study found that use of IV-TXA in TJA improved early ambulation and clinical outcomes (reduced anemia, fewer transfusions) in the initial postoperative period, without producing adverse events.

Take-Home Points

• IV-TXA significantly reduces intraoperative blood loss following TJA.
• Early mobilization correlates with reduced incidence of postoperative complications.
• IV-TXA minimizes postoperative anemia, facilitating improved early ambulation following TJA.
• IV-TXA significantly reduces the need for postoperative transfusions.
• IV-TXA is safe to use with no adverse events noted.

By the year 2020, use of primary total knee arthroplasty (TKA) in the United States will increase an estimated 110%, to 1.375 million procedures annually, and use of primary total hip arthroplasty (THA) will increase an estimated 75%, to more than 500,000 procedures.¹ Minimizing perioperative blood loss and improving early postoperative ambulation both correlate with reduced postoperative morbidity, allowing patients to return to their daily lives expeditiously. 

Tranexamic acid (TXA), a fibrinolytic inhibitor, competitively blocks lysine receptor binding sites of plasminogen, sustaining and stabilizing the fibrin architecture.² TXA must be present to occupy binding sites before plasminogen binds to fibrin, validating the need for preoperative administration so the drug is available early in the fibrinolytic cascade.³ Intravenous (IV) TXA diffuses rapidly into joint fluid and the synovial membrane.⁴ Drug concentration and elimination half-life in joint fluid are equivalent to those in serum. Elimination of TXA occurs by glomerular filtration, with about 30% of a 10-mg/kg dose removed in 1 hour, 55% over the first 3 hours, and 90% within 24 hours of IV administration.⁵

The efficacy of IV-TXA in minimizing total joint arthroplasty (TJA) perioperative blood loss has been proved in small studies and meta-analyses.^6-9 TXA-induced blood conservation decreases or eliminates the need for postoperative transfusion, which can impede valuable, early ambulation.10 In addition, the positive clinical safety profile of TXA supports routine use of TXA in TJA.^6,11-15

The benefits of early ambulation after TJA are well established. Getting patients to walk on the day of surgery is a key part of effective and rapid postoperative rehabilitation. Early mobilization correlates with reduced incidence of venous thrombosis and postoperative complications.¹⁶ In contrast to bed rest, sitting and standing promotes oxygen saturation, which improves tissue healing and minimizes adverse pulmonary events. Oxygen saturation also preserves muscle strength and blood flow, reducing the risk of venous thromboembolism and ulcers. Muscle strength must be maintained so normal gait can be regained.¹⁷ Compared with rehabilitation initiated 48 to 72 hours after TKA, rehabilitation initiated within 24 hours reduced the number of sessions needed to achieve independence and normal gait; in addition, early mobilization improved patient reports of pain after surgery.¹⁸ An evaluation of Denmark registry data revealed that mobilization to walking and use of crutches or canes was achieved earlier when ambulation was initiated on day of surgery.¹⁹ Finally, mobilization on day of surgery and during the immediate postoperative period improved long-term quality of life after TJA.²⁰

We conducted a retrospective cohort study to determine if use of IV-TXA improves early ambulation and reduces blood loss after TKA and anterior and posterior THA. We hypothesized that IV-TXA use would reduce postoperative anemia and improve early ambulation and outcomes without producing adverse events during the immediate postoperative period. TXA reduces bleeding, and reduced incidence of hemarthrosis, wound swelling, and anemia could facilitate ambulation, reduce complications, and shorten recovery in patients who undergo TJA.

Patients and Methods

In February 2014, this retrospective cohort study received Institutional Review Board approval to compare the safety and efficacy of IV-TXA (vs no TXA) in patients who underwent TKA, anterior THA, and posterior THA.

In March 2012, multidisciplinary protocols were standardized to ensure a uniform hospital course for patients at our institution. All patients underwent preoperative testing and evaluation by a nurse practitioner and an anesthesiologist. In March 2013, IV-TXA became our standard of care. TXA use was contraindicated in patients with thromboembolic disease or with hypersensitivity to TXA. Patients without a contraindication were given two 10-mg/kg IV-TXA doses, each administered over 15 to 30 minutes; the first dose was administered before incision, and the second was infused at case close and/or at least 60 minutes after the first dose. Most TKA patients received regional (femoral) anesthesia and analgesia, and most THA patients received spinal or epidural anesthesia and analgesia. In a small percentage of cases, IV analgesia was patient-controlled, as determined by the pain service. There were no significant differences in anesthesia/analgesia modality between the 2 study groups—patients who received TXA and those who did not. Patients were then transitioned to oral opioids for pain management, unless otherwise contraindicated, and were ambulated 4 hours after end of surgery, unless medically unstable. Hematology and chemistry laboratory values were monitored daily during admission.

Patients underwent physical therapy (PT) after surgery and until hospital discharge. Physical therapists blinded to patients’ intraoperative use or no use of TXA measured ambulation. After initial evaluation on postoperative day 0 (POD-0), patients were ambulated twice daily. The daily ambulation distance used for the study was the larger of the 2 daily PT distances (occasionally, patients were unable to participate fully in both sessions). Patients received either enoxaparin or rivaroxaban for postoperative thromboprophylaxis (the anticoagulant used was based on surgeon preference). Enoxaparin was subcutaneously administered at 30 mg every 12 hours for TKA, 40 mg once daily for THA, 30 mg once daily for calculated creatinine clearance under 30 mL/min, or 40 mg every 12 hours for body mass index (BMI) 40 or above. With enoxaparin, therapy duration was 14 days. Oral rivaroxaban was administered at 10 mg once daily for 12 days for TKA and 35 days for THA unless contraindicated.

The primary outcome variables were ambulation measured on POD-1 and POD-2 and intraoperative blood loss. In addition, hemoglobin and hematocrit were measured on POD-0, POD-1, and POD-2. Ambulation was defined as number of feet walked during postoperative hospitalization. To calculate intraoperative blood loss, the anesthesiologist subtracted any saline irrigation volume from the total volume in the suction canister. Also noted were postoperative transfusions and any diagnosis of postoperative venous thromboembolism—specifically, deep vein thrombosis (DVT) or pulmonary embolism (PE).

Demographic and clinical characteristics of the TXA and no-TXA groups were compared using either 2-sample t test (for continuous variables) or χ2 test (for categorical variables).

The ambulation outcome was log-transformed to meet standard assumptions of Gaussian residuals and equality of variance. Means and 95% confidence intervals (CIs) were calculated on the log scale and were anti-logged so the results could be presented in their original units. 

A linear mixed model was used to model intraoperative blood loss as a function of group (TXA, no TXA), procedure (TKA, anterior THA, posterior THA), and potential confounders (age, sex, BMI, operative time).

Linear mixed models for repeated measures were used to compare outcomes (hemoglobin, hematocrit) between groups (TXA, no TXA) and procedures (TKA, anterior THA, posterior THA) and to compare changes in outcomes over time. Group, procedure, and operative time interactions were explored. Potential confounders (age, sex, BMI, operative time) were included in the model as well.

A χ2 test was used to compare the groups (TXA, no TXA) on postoperative blood transfusion (yes, no). Given the smaller number of events, a more complex model accounting for clustered data and potential confounders was not used. Need for transfusion was clinically assessed case by case. Symptomatic anemia (dyspnea on exertion, headaches, tachycardia) was used as the primary indication for transfusion once hemoglobin fell below 8 g/dL or hematocrit below 24%. Number of patients with a postoperative thrombus formation was minimal. Therefore, this outcome was described with summary statistics and was not formally analyzed.

Results

Of the 477 patients who underwent TJAs (275 TKAs, 98 anterior THAs, 104 posterior THAs; all unilateral), 111 did not receive TXA (June 2012-February 2013), and 366 received TXA (March 2013-January 2014). Other than for the addition of IV-TXA, the same standardized protocols instituted in March 2012 continued throughout the study period. The difference in sample size between the TXA and no-TXA groups was not statistically significant and did not influence the outcome measures.

Ambulation

There was a significant (P = .0066) 3-way interaction of TXA, procedure, and operative time after adjusting for age (P < .0001), sex (P < .0001), BMI (P < .0001), and operative time (P = .8308). Regarding TKA, mean ambulation was higher for the TXA group than for the no-TXA group at POD-1 (8.36 vs 3.40 feet; P < .0001) and POD-2 (25.81 vs 18.75 feet; P = .0054). The same was true for anterior THA at POD-1 (10.86 vs 3.33 feet; P < .0001) and POD-2 (27.24 vs 13.19 feet; P < .0001) and posterior THA at POD-1 (10.64 vs 3.37 feet; P < .0001) and POD-2 (24.68 vs 12.93 feet; P = .0002). See Table 3.

Intraoperative Blood Loss

There was a significant 3-way interaction of TXA, procedure (P < .0053), and operative time (P < .0001) after adjusting for age (P < .6136), sex (P = .1147), and BMI (P = .6180). Regarding TKA, mean intraoperative blood loss was significantly lower for the TXA group than for the no-TXA group (241.58 vs 287.81 mL; P = .0004). The same was true for anterior THA (352.91 vs 533.79 mL; P < .0001). Regarding posterior THA, there was no significant difference between the TXA and no-TXA groups (326.00 vs 350.16 mL; P = .3246). See Table 4. 

Hemoglobin

There was a significant (P = .0008) 3-way interaction of TXA, procedure, and operative time after adjusting for age (P = .0174), sex (P < .0001), BMI (P = .0007), and operative time (P = .0002). Regarding TKA, postoperative hemoglobin levels were higher for the TXA group than for the no-TXA group at POD-0 (12.10 vs 11.68 g/dL; P = .0135), POD-1 (11.62 vs 10.67 g/dL; P < .0001), and POD-2 (11.02 vs 10.11 g/dL; P < .0001). The same was true for anterior THA at POD-1 (11.03 vs 10.19 g/dL; P = .0034) and POD-2 (10.57 vs 9.64 g/dL; P = .0009) and posterior THA at POD-2 (11.04 vs 10.16 g/dL; P = .0003). See Table 5.

Hematocrit

There was a significant (P < .0006) 3-way interaction of TXA, procedure, and operative time after adjusting for age (P = .1597), sex (P < .0001), BMI (P < .0001), and operative time (P = .0003). Regarding TKA, postoperative hematocrit levels were higher for the TXA group than for the no-TXA group at POD-0 (36.52% vs 34.65%; P < .0001), POD-1 (34.62% vs 31.83%; P < .0001), and POD-2 (33.01% vs 30.20%; P < .0001). The same was true for anterior THA at POD-1 (32.82% vs 30.59%; P = .0037) and POD-2 (31.58% vs 28.61%; P = .0004) and posterior THA at POD-2 (32.93% vs 30.17%; P < .0001). See Table 6.

Postoperative Transfusions 

Of the 477 patients, 25 (5.24%) required a postoperative transfusion. Postoperative transfusions were less likely (P < .0001) required in the TXA group (1.64%, 6/366) than in the no-TXA group (17.12%, 19/111). Given the smaller number of events, a more complex model accounting for clustered data and potential confounders was not used, and the different procedures were not evaluated separately.

Deep Vein Thrombosis and Pulmonary Embolism

Of the 477 patients, 2 developed a DVT, and 5 developed a PE. Both DVTs occurred in the TXA group (2/366, 0.55%; 95% CI, 0.07%-1.96%). Of the 5 PEs, 4 occurred in the TXA group (4/366, 1.09%; 95% CI, 0.30%-2.77%), and 1 occurred in the no-TXA group (1/111, 0.90%; 95% CI, 0.02%-4.92%). Given the exceedingly small number of events, no statistical significance was noted between groups.

Discussion

Orthopedic surgeons carefully balance patient expectations, societal needs, and regulatory mandates while providing excellent care and working under payers’ financial restrictions. The Centers for Medicare & Medicaid Services announced that, starting in 2016, TJAs will be reimbursed in total as a single bundled payment, adding to the need to provide optimal care in a fiscally responsible manner.²¹ Standardized protocols implementing multimodal therapies are pivotal in achieving favorable postoperative outcomes.

Our study results showed that IV-TXA use minimized hemoglobin and hematocrit reductions after TKA, anterior THA, and posterior THA. Postoperative anemia correlates with decreased ambulation ability and performance during the early postoperative period. In general, higher postoperative hemoglobin and hematocrit levels result in improved motor performance and shorter recovery.²² In addition, early ambulation is a validated predictor of favorable TJA outcomes. In our study, for TKA, anterior THA, and posterior THA, ambulation on POD-1 and POD-2 was significantly better for patients who received TXA than for patients who did not.

Transfusion rates were markedly lower for our TXA group than for our no-TXA group (1.64% vs 17.12%), confirming the findings of numerous other studies on outcomes of TJA with TXA.^{2,3,6-12,14,15} Transfusions impede physical therapy and affect hospitalization costs.

Although potential thrombosis-related adverse events remain an endpoint in studies involving TXA, we found a comparably low incidence of postoperative venous thrombosis in our TXA and no-TXA groups (1.09% and 0.90%, respectively). In addition, no patient in either group developed a postoperative arterial thrombosis.

This is the largest single-center study of TXA use in TKA, anterior THA, and posterior THA. The effect of TXA use on postoperative ambulation was not previously found with TJA.

This study had its limitations. First, it was not prospective, randomized, or double-blinded. However, the physical therapists who mobilized patients and recorded ambulation data were blinded to the study and its hypothesis and followed a standardized protocol for all patients. In addition, intraoperative blood loss was recorded by an anesthesiologist using a standardized protocol, and patients received TXA per orthopedic protocol and surgeon preference, without selection bias. Another limitation was that ambulation data were captured only for POD-1 and POD-2 (most patients were discharged by POD-3). However, a goal of the study was to capture immediate postoperative data in order to determine the efficacy of intraoperative TXA. Subsequent studies can determine if this early benefit leads to long-term clinical outcome improvements.

In reducing blood loss and transfusion rates, intra-articular TXA is as efficacious as IV-TXA.^23-25 We anticipate that the improved clinical outcomes found with IV-TXA in our study will be similar with intra-articular TXA, but more study is needed to confirm this hypothesis.

Conclusion

This retrospective cohort study found that use of IV-TXA in TJA improved early ambulation and clinical outcomes (reduced anemia, fewer transfusions) in the initial postoperative period, without producing adverse events.

The VA operates the largest integrated health care system in the country, consisting of 144 hospitals and 1,221 outpatient clinics. This system provides medical care for about 22 million veterans. In 2015, women accounted for nearly 10% of the veteran population and are expected to increase to about 16% by 2040.¹ With an expected population increase of 18,000 per year over the next 10 years, women are the fastest growing group of veterans.

The VA acknowledges that women are an integral part of the veteran community and that a paradigm shift must occur to meet their unique health needs. Although clinical services specific to women veterans’ health needs have been introduced within the VA, gynecologic surgical services must be addressed in order to improve access and provide comprehensive women’s health care within the VA system.

About 600,000 hysterectomies are performed annually in the U.S., making this procedure one of the most commonly performed in women.² Over the past 30 years, technologic advances have allowed surgeons to perform more hysterectomies via minimally invasive methods. Both the American Congress of Obstetricians and Gynecologists and American Association of Gynecologic Laparoscopists have published consensus statements that minimally invasive hysterectomy should be the standard of care.^3,4 Studies in non-VA facilities have shown that practice patterns in the route of hysterectomy have evolved with the advancement of surgical equipment and techniques.

It is uncertain, however, whether these changes in practice patterns exist in the VA, because there are limited published data. Given the frequency of hysterectomies in the U.S., the rate and route of this procedure are easily identifiable measures that can be evaluated and utilized as a comparison model for health care received within the VA vs the civilian sector.

The aim of this study was to assess the changes in rate and surgical approach to benign hysterectomy for women veterans at VAMCs and referrals to non-VA facilities over a 10-year period. The authors’ hypothesis was that a minimally invasive approach would be more common in recent years. This study also compares published national data to evaluate whether the VA is offering comparable surgical services to the civilian sector.

Methods

The institutional review boards of Indiana University and the Richard L. Roudebush VAMC in Indianapolis, Indiana, approved this retrospective cross-sectional study. The VHA Support Service Center (VSSC) authorized access to VA database information.

All women veterans who underwent hysterectomy for benign indications from fiscal years (FY) 2005 to 2014 were included. In order to identify this group, the authors queried the VA Corporate Data Warehouse (CDW) and the Non-VA Care Cube for all hysterectomy current procedural terminology (CPT) codes typically performed for benign indications, including 58150, 58152, 58180, 58260, 58262, 58263, 58267, 58270, 58290, 58291, 58292, 58293, 58294, 58541, 58542, 58543, 58544, 58550, 58552, 58553, 58554, 58570, 58571, 58572, and 58573. For each patient identified, the following variables were collected: date of the procedure, facility location, primary CPT code, primary ICD-9 code, and patient age. Patients whose primary ICD-9 code was for a malignancy of gynecologic origin were excluded from the study.

The CDW is a national database collected by the VA Office of Information and Technology to provide clinical data for VA analytical purposes. The Non-VA Care Cube identifies services purchased for veterans with non-VA care dollars and, therefore, captures women veterans who were referred outside the VA for a hysterectomy. Additional data collected include age, gender, hospital complexity, place of care, payment location, primary CPT, primary ICD-9, and several other parameters. The annual number of women veterans accessing VA health care was extracted from the VSSC Unique Patients Cube.

Laparoscopic hysterectomy was defined as total laparoscopic hysterectomy, laparoscopic-assisted vaginal hysterectomy, laparoscopic-supracervical hysterectomy, and robotic-assisted laparoscopic hysterectomy. Minimally invasive hysterectomy was defined as all laparoscopic and vaginal hysterectomies.

Frequency distributions between categoric variables were compared using chi-squared tests. The population-adjusted hysterectomy rates were estimated by dividing the total number of hysterectomies by the number of women veterans accessing VA medical care. Hysterectomy rates are reported as rate per 1,000 women per year. A time trend analysis was performed with linear regression to evaluate the slopes of trends for each route of hysterectomy, using Microsoft Excel 2010 (Redmond, WA). The authors analyzed the relationship between route of hysterectomy and fiscal year, using a multivariable logistic regression that was adjusted for age, district, and surgical diagnosis. The adjusted relative risk (RR) for each type of hysterectomy was reported with 95% confidence intervals (CI). All statistical analyses were performed using SPSS 12.0 (Chicago, IL) with P < .05 defined as being statistically significant.To ensure the accuracy of the CDW data, the documented CPT and ICD-9 codes were compared between the CDW and the VA electronic medical records (EMR) for 400 charts selected at random. This cohort represents about 5% of the total charts and was felt to be an adequate measure of the entire sample since the CPT and ICD-9 codes were verified and matched 100% of the time. Demographic and descriptive data regarding body mass index, level of education, race, smoking status, medical comorbidities, and surgical history were excluded from the study because it was either not available or not consistently reported within the CDW.

Results

A retrospective query of the CDW identified 8,327 hysterectomies performed at the VA for benign indications from fiscal year (FY) 2005 to FY 2014. The total number of annual hysterectomies at the VA increased 30.7% from 710 in FY 2004 to 1,025 in FY 2014. The annual number of women veterans who accessed VA health care increased 30.8% from 412,271 to 596,011 during the same time frame. Thus, the population adjusted hysterectomy rate remained stable at 1.72 (Figure 1).

The authors also analyzed the VA data by district and decided to highlight the most recent data trends, as this is most applicable to how the VA currently operates. During FY 2014, the VA hysterectomy rates were as follows: district 1 (North Atlantic) 1.52; district 2 (Southeast) 2.21; district 3 (Midwest) 1.47; district 4 (Continental) 1.43; and district 5 (Pacific) 1.64 (Figure 2)

During the study period, calculated hysterectomy rates based on route at the VA showed that the laparoscopic hysterectomy rate increased from 0.11 to 0.53, the vaginal hysterectomy rate remained relatively stable at 0.34 to 0.37, and the abdominal hysterectomy rate declined from 1.28 to 0.8 (Figure 3).

Discussion

Although the total hysterectomy rate within the VA remained stable during the study period, the minimally invasive hysterectomy rate increased significantly. In FY 2014, the majority of hysterectomies at the VA were performed via a minimally invasive approach. Minimally invasive hysterectomy has many recognized advantages over abdominal hysterectomy as it offers a significant reduction in postoperative pain, narcotic use, length of stay, intraoperative blood loss, fever, deep venous thrombosis, and a faster recovery with return to baseline functioning thus improving overall quality of life.^5-7 Previous literature of VA hysterectomy data from 1991 to 1997 reported an abdominal hysterectomy percentage of 74%, vaginal hysterectomy percentage of 22%, and laparoscopic assisted vaginal hysterectomy percentage of 4%.⁸

Additionally, previous literature of the civilian sector reported a national laparoscopic hysterectomy percentage of 32.4% in 2012, which is comparable to the laparoscopic hysterectomy percentage found in this study.^9,10 These data highlight the growth of laparoscopic hysterectomy at the VA, which is comparable to that of the civilian sector.The Nationwide Inpatient Sample reported an abdominal hysterectomy percentage of 66.1% in 2003 and 52.8% in 2012.^9,10 The authors observed a similar decline in the abdominal hysterectomy rate at the VA over the period studied. Although many factors may have contributed to this decline, the growth of laparoscopic hysterectomy was a possible contributing factor since the vaginal hysterectomy rate remained stable over the study period. Future studies are needed to evaluate surgical complications and readmission rates in order to more accurately assess the quality of gynecologic surgical care provided by the VA compared with the civilian sector.

Strengths and Limitations

This study has several important strengths. First, the large sample size from VA nationwide databases included information from all VAMC performing hysterectomies. Second, this study included 10 years of data, with the latest data from 2014, allowing for depiction of both long-term and recent trends.

Potential issues with large databases such as the CDW and the Non-VA Care Cube included inaccurate coding of procedures and diagnoses as well as missing data. This possible limitation was addressed by randomly selecting 400 patients in the database to verify the database information against the patient’s EMR, which matched 100% of the time. In addition, the authors calculated the hysterectomy rates using a denominator based on all women veterans accessing VA health care, which included women who had previously had a hysterectomy. Therefore, the true hysterectomy rate may have been underestimated.

Conclusion

The VA operates the largest health care system in the U.S. with more than 500,000 women veterans currently utilizing VA health care.¹¹ The VA provides services to women veterans living in urban, suburban, and rural areas. The breadth of geographic locations, the declining number of VA facilities offering gynecologic surgical services, and the growing population of female veterans present unique challenges to providing accessible and comparable health care to these female patients.

VA district 4 (Continental) has the lowest population density as well as the lowest VA hysterectomy rate in FY 2014, which may be attributable to the aforementioned challenges. As a result of these challenges, an increasing number of gynecologic surgical referrals to non-VA facilities was observed during the study period. The VA has made considerable progress in supporting and promoting health care for women by strategically enhancing services and access for women veterans. Although the number of hysterectomies has increased across VA facilities offering gynecologic surgical services, about 1 in 3 women veterans are referred to non-VA facilities for their gynecologic surgical needs. The VA has a challenging opportunity to expand gynecologic surgical services and improve access for the growing population of women veterans. To accommodate this growth, the VA may consider strategically increasing the number of facilities providing gynecologic surgical services or expanding established gynecologic surgical departments.

The VA operates the largest integrated health care system in the country, consisting of 144 hospitals and 1,221 outpatient clinics. This system provides medical care for about 22 million veterans. In 2015, women accounted for nearly 10% of the veteran population and are expected to increase to about 16% by 2040.¹ With an expected population increase of 18,000 per year over the next 10 years, women are the fastest growing group of veterans.

The VA acknowledges that women are an integral part of the veteran community and that a paradigm shift must occur to meet their unique health needs. Although clinical services specific to women veterans’ health needs have been introduced within the VA, gynecologic surgical services must be addressed in order to improve access and provide comprehensive women’s health care within the VA system.

About 600,000 hysterectomies are performed annually in the U.S., making this procedure one of the most commonly performed in women.² Over the past 30 years, technologic advances have allowed surgeons to perform more hysterectomies via minimally invasive methods. Both the American Congress of Obstetricians and Gynecologists and American Association of Gynecologic Laparoscopists have published consensus statements that minimally invasive hysterectomy should be the standard of care.^3,4 Studies in non-VA facilities have shown that practice patterns in the route of hysterectomy have evolved with the advancement of surgical equipment and techniques.

It is uncertain, however, whether these changes in practice patterns exist in the VA, because there are limited published data. Given the frequency of hysterectomies in the U.S., the rate and route of this procedure are easily identifiable measures that can be evaluated and utilized as a comparison model for health care received within the VA vs the civilian sector.

The aim of this study was to assess the changes in rate and surgical approach to benign hysterectomy for women veterans at VAMCs and referrals to non-VA facilities over a 10-year period. The authors’ hypothesis was that a minimally invasive approach would be more common in recent years. This study also compares published national data to evaluate whether the VA is offering comparable surgical services to the civilian sector.

Methods

The institutional review boards of Indiana University and the Richard L. Roudebush VAMC in Indianapolis, Indiana, approved this retrospective cross-sectional study. The VHA Support Service Center (VSSC) authorized access to VA database information.

All women veterans who underwent hysterectomy for benign indications from fiscal years (FY) 2005 to 2014 were included. In order to identify this group, the authors queried the VA Corporate Data Warehouse (CDW) and the Non-VA Care Cube for all hysterectomy current procedural terminology (CPT) codes typically performed for benign indications, including 58150, 58152, 58180, 58260, 58262, 58263, 58267, 58270, 58290, 58291, 58292, 58293, 58294, 58541, 58542, 58543, 58544, 58550, 58552, 58553, 58554, 58570, 58571, 58572, and 58573. For each patient identified, the following variables were collected: date of the procedure, facility location, primary CPT code, primary ICD-9 code, and patient age. Patients whose primary ICD-9 code was for a malignancy of gynecologic origin were excluded from the study.

The CDW is a national database collected by the VA Office of Information and Technology to provide clinical data for VA analytical purposes. The Non-VA Care Cube identifies services purchased for veterans with non-VA care dollars and, therefore, captures women veterans who were referred outside the VA for a hysterectomy. Additional data collected include age, gender, hospital complexity, place of care, payment location, primary CPT, primary ICD-9, and several other parameters. The annual number of women veterans accessing VA health care was extracted from the VSSC Unique Patients Cube.

Laparoscopic hysterectomy was defined as total laparoscopic hysterectomy, laparoscopic-assisted vaginal hysterectomy, laparoscopic-supracervical hysterectomy, and robotic-assisted laparoscopic hysterectomy. Minimally invasive hysterectomy was defined as all laparoscopic and vaginal hysterectomies.

Frequency distributions between categoric variables were compared using chi-squared tests. The population-adjusted hysterectomy rates were estimated by dividing the total number of hysterectomies by the number of women veterans accessing VA medical care. Hysterectomy rates are reported as rate per 1,000 women per year. A time trend analysis was performed with linear regression to evaluate the slopes of trends for each route of hysterectomy, using Microsoft Excel 2010 (Redmond, WA). The authors analyzed the relationship between route of hysterectomy and fiscal year, using a multivariable logistic regression that was adjusted for age, district, and surgical diagnosis. The adjusted relative risk (RR) for each type of hysterectomy was reported with 95% confidence intervals (CI). All statistical analyses were performed using SPSS 12.0 (Chicago, IL) with P < .05 defined as being statistically significant.To ensure the accuracy of the CDW data, the documented CPT and ICD-9 codes were compared between the CDW and the VA electronic medical records (EMR) for 400 charts selected at random. This cohort represents about 5% of the total charts and was felt to be an adequate measure of the entire sample since the CPT and ICD-9 codes were verified and matched 100% of the time. Demographic and descriptive data regarding body mass index, level of education, race, smoking status, medical comorbidities, and surgical history were excluded from the study because it was either not available or not consistently reported within the CDW.

Results

A retrospective query of the CDW identified 8,327 hysterectomies performed at the VA for benign indications from fiscal year (FY) 2005 to FY 2014. The total number of annual hysterectomies at the VA increased 30.7% from 710 in FY 2004 to 1,025 in FY 2014. The annual number of women veterans who accessed VA health care increased 30.8% from 412,271 to 596,011 during the same time frame. Thus, the population adjusted hysterectomy rate remained stable at 1.72 (Figure 1).

The authors also analyzed the VA data by district and decided to highlight the most recent data trends, as this is most applicable to how the VA currently operates. During FY 2014, the VA hysterectomy rates were as follows: district 1 (North Atlantic) 1.52; district 2 (Southeast) 2.21; district 3 (Midwest) 1.47; district 4 (Continental) 1.43; and district 5 (Pacific) 1.64 (Figure 2)

During the study period, calculated hysterectomy rates based on route at the VA showed that the laparoscopic hysterectomy rate increased from 0.11 to 0.53, the vaginal hysterectomy rate remained relatively stable at 0.34 to 0.37, and the abdominal hysterectomy rate declined from 1.28 to 0.8 (Figure 3).

Discussion

Although the total hysterectomy rate within the VA remained stable during the study period, the minimally invasive hysterectomy rate increased significantly. In FY 2014, the majority of hysterectomies at the VA were performed via a minimally invasive approach. Minimally invasive hysterectomy has many recognized advantages over abdominal hysterectomy as it offers a significant reduction in postoperative pain, narcotic use, length of stay, intraoperative blood loss, fever, deep venous thrombosis, and a faster recovery with return to baseline functioning thus improving overall quality of life.^5-7 Previous literature of VA hysterectomy data from 1991 to 1997 reported an abdominal hysterectomy percentage of 74%, vaginal hysterectomy percentage of 22%, and laparoscopic assisted vaginal hysterectomy percentage of 4%.⁸

Additionally, previous literature of the civilian sector reported a national laparoscopic hysterectomy percentage of 32.4% in 2012, which is comparable to the laparoscopic hysterectomy percentage found in this study.^9,10 These data highlight the growth of laparoscopic hysterectomy at the VA, which is comparable to that of the civilian sector.The Nationwide Inpatient Sample reported an abdominal hysterectomy percentage of 66.1% in 2003 and 52.8% in 2012.^9,10 The authors observed a similar decline in the abdominal hysterectomy rate at the VA over the period studied. Although many factors may have contributed to this decline, the growth of laparoscopic hysterectomy was a possible contributing factor since the vaginal hysterectomy rate remained stable over the study period. Future studies are needed to evaluate surgical complications and readmission rates in order to more accurately assess the quality of gynecologic surgical care provided by the VA compared with the civilian sector.

Strengths and Limitations

This study has several important strengths. First, the large sample size from VA nationwide databases included information from all VAMC performing hysterectomies. Second, this study included 10 years of data, with the latest data from 2014, allowing for depiction of both long-term and recent trends.

Potential issues with large databases such as the CDW and the Non-VA Care Cube included inaccurate coding of procedures and diagnoses as well as missing data. This possible limitation was addressed by randomly selecting 400 patients in the database to verify the database information against the patient’s EMR, which matched 100% of the time. In addition, the authors calculated the hysterectomy rates using a denominator based on all women veterans accessing VA health care, which included women who had previously had a hysterectomy. Therefore, the true hysterectomy rate may have been underestimated.

Conclusion

The VA operates the largest health care system in the U.S. with more than 500,000 women veterans currently utilizing VA health care.¹¹ The VA provides services to women veterans living in urban, suburban, and rural areas. The breadth of geographic locations, the declining number of VA facilities offering gynecologic surgical services, and the growing population of female veterans present unique challenges to providing accessible and comparable health care to these female patients.

VA district 4 (Continental) has the lowest population density as well as the lowest VA hysterectomy rate in FY 2014, which may be attributable to the aforementioned challenges. As a result of these challenges, an increasing number of gynecologic surgical referrals to non-VA facilities was observed during the study period. The VA has made considerable progress in supporting and promoting health care for women by strategically enhancing services and access for women veterans. Although the number of hysterectomies has increased across VA facilities offering gynecologic surgical services, about 1 in 3 women veterans are referred to non-VA facilities for their gynecologic surgical needs. The VA has a challenging opportunity to expand gynecologic surgical services and improve access for the growing population of women veterans. To accommodate this growth, the VA may consider strategically increasing the number of facilities providing gynecologic surgical services or expanding established gynecologic surgical departments.

The VA operates the largest integrated health care system in the country, consisting of 144 hospitals and 1,221 outpatient clinics. This system provides medical care for about 22 million veterans. In 2015, women accounted for nearly 10% of the veteran population and are expected to increase to about 16% by 2040.¹ With an expected population increase of 18,000 per year over the next 10 years, women are the fastest growing group of veterans.

The VA acknowledges that women are an integral part of the veteran community and that a paradigm shift must occur to meet their unique health needs. Although clinical services specific to women veterans’ health needs have been introduced within the VA, gynecologic surgical services must be addressed in order to improve access and provide comprehensive women’s health care within the VA system.

About 600,000 hysterectomies are performed annually in the U.S., making this procedure one of the most commonly performed in women.² Over the past 30 years, technologic advances have allowed surgeons to perform more hysterectomies via minimally invasive methods. Both the American Congress of Obstetricians and Gynecologists and American Association of Gynecologic Laparoscopists have published consensus statements that minimally invasive hysterectomy should be the standard of care.^3,4 Studies in non-VA facilities have shown that practice patterns in the route of hysterectomy have evolved with the advancement of surgical equipment and techniques.

It is uncertain, however, whether these changes in practice patterns exist in the VA, because there are limited published data. Given the frequency of hysterectomies in the U.S., the rate and route of this procedure are easily identifiable measures that can be evaluated and utilized as a comparison model for health care received within the VA vs the civilian sector.

The aim of this study was to assess the changes in rate and surgical approach to benign hysterectomy for women veterans at VAMCs and referrals to non-VA facilities over a 10-year period. The authors’ hypothesis was that a minimally invasive approach would be more common in recent years. This study also compares published national data to evaluate whether the VA is offering comparable surgical services to the civilian sector.

Methods

The institutional review boards of Indiana University and the Richard L. Roudebush VAMC in Indianapolis, Indiana, approved this retrospective cross-sectional study. The VHA Support Service Center (VSSC) authorized access to VA database information.

All women veterans who underwent hysterectomy for benign indications from fiscal years (FY) 2005 to 2014 were included. In order to identify this group, the authors queried the VA Corporate Data Warehouse (CDW) and the Non-VA Care Cube for all hysterectomy current procedural terminology (CPT) codes typically performed for benign indications, including 58150, 58152, 58180, 58260, 58262, 58263, 58267, 58270, 58290, 58291, 58292, 58293, 58294, 58541, 58542, 58543, 58544, 58550, 58552, 58553, 58554, 58570, 58571, 58572, and 58573. For each patient identified, the following variables were collected: date of the procedure, facility location, primary CPT code, primary ICD-9 code, and patient age. Patients whose primary ICD-9 code was for a malignancy of gynecologic origin were excluded from the study.

The CDW is a national database collected by the VA Office of Information and Technology to provide clinical data for VA analytical purposes. The Non-VA Care Cube identifies services purchased for veterans with non-VA care dollars and, therefore, captures women veterans who were referred outside the VA for a hysterectomy. Additional data collected include age, gender, hospital complexity, place of care, payment location, primary CPT, primary ICD-9, and several other parameters. The annual number of women veterans accessing VA health care was extracted from the VSSC Unique Patients Cube.

Laparoscopic hysterectomy was defined as total laparoscopic hysterectomy, laparoscopic-assisted vaginal hysterectomy, laparoscopic-supracervical hysterectomy, and robotic-assisted laparoscopic hysterectomy. Minimally invasive hysterectomy was defined as all laparoscopic and vaginal hysterectomies.

Frequency distributions between categoric variables were compared using chi-squared tests. The population-adjusted hysterectomy rates were estimated by dividing the total number of hysterectomies by the number of women veterans accessing VA medical care. Hysterectomy rates are reported as rate per 1,000 women per year. A time trend analysis was performed with linear regression to evaluate the slopes of trends for each route of hysterectomy, using Microsoft Excel 2010 (Redmond, WA). The authors analyzed the relationship between route of hysterectomy and fiscal year, using a multivariable logistic regression that was adjusted for age, district, and surgical diagnosis. The adjusted relative risk (RR) for each type of hysterectomy was reported with 95% confidence intervals (CI). All statistical analyses were performed using SPSS 12.0 (Chicago, IL) with P < .05 defined as being statistically significant.To ensure the accuracy of the CDW data, the documented CPT and ICD-9 codes were compared between the CDW and the VA electronic medical records (EMR) for 400 charts selected at random. This cohort represents about 5% of the total charts and was felt to be an adequate measure of the entire sample since the CPT and ICD-9 codes were verified and matched 100% of the time. Demographic and descriptive data regarding body mass index, level of education, race, smoking status, medical comorbidities, and surgical history were excluded from the study because it was either not available or not consistently reported within the CDW.

Results

A retrospective query of the CDW identified 8,327 hysterectomies performed at the VA for benign indications from fiscal year (FY) 2005 to FY 2014. The total number of annual hysterectomies at the VA increased 30.7% from 710 in FY 2004 to 1,025 in FY 2014. The annual number of women veterans who accessed VA health care increased 30.8% from 412,271 to 596,011 during the same time frame. Thus, the population adjusted hysterectomy rate remained stable at 1.72 (Figure 1).

The authors also analyzed the VA data by district and decided to highlight the most recent data trends, as this is most applicable to how the VA currently operates. During FY 2014, the VA hysterectomy rates were as follows: district 1 (North Atlantic) 1.52; district 2 (Southeast) 2.21; district 3 (Midwest) 1.47; district 4 (Continental) 1.43; and district 5 (Pacific) 1.64 (Figure 2)

During the study period, calculated hysterectomy rates based on route at the VA showed that the laparoscopic hysterectomy rate increased from 0.11 to 0.53, the vaginal hysterectomy rate remained relatively stable at 0.34 to 0.37, and the abdominal hysterectomy rate declined from 1.28 to 0.8 (Figure 3).

Discussion

Although the total hysterectomy rate within the VA remained stable during the study period, the minimally invasive hysterectomy rate increased significantly. In FY 2014, the majority of hysterectomies at the VA were performed via a minimally invasive approach. Minimally invasive hysterectomy has many recognized advantages over abdominal hysterectomy as it offers a significant reduction in postoperative pain, narcotic use, length of stay, intraoperative blood loss, fever, deep venous thrombosis, and a faster recovery with return to baseline functioning thus improving overall quality of life.^5-7 Previous literature of VA hysterectomy data from 1991 to 1997 reported an abdominal hysterectomy percentage of 74%, vaginal hysterectomy percentage of 22%, and laparoscopic assisted vaginal hysterectomy percentage of 4%.⁸

Additionally, previous literature of the civilian sector reported a national laparoscopic hysterectomy percentage of 32.4% in 2012, which is comparable to the laparoscopic hysterectomy percentage found in this study.^9,10 These data highlight the growth of laparoscopic hysterectomy at the VA, which is comparable to that of the civilian sector.The Nationwide Inpatient Sample reported an abdominal hysterectomy percentage of 66.1% in 2003 and 52.8% in 2012.^9,10 The authors observed a similar decline in the abdominal hysterectomy rate at the VA over the period studied. Although many factors may have contributed to this decline, the growth of laparoscopic hysterectomy was a possible contributing factor since the vaginal hysterectomy rate remained stable over the study period. Future studies are needed to evaluate surgical complications and readmission rates in order to more accurately assess the quality of gynecologic surgical care provided by the VA compared with the civilian sector.

Strengths and Limitations

This study has several important strengths. First, the large sample size from VA nationwide databases included information from all VAMC performing hysterectomies. Second, this study included 10 years of data, with the latest data from 2014, allowing for depiction of both long-term and recent trends.

Potential issues with large databases such as the CDW and the Non-VA Care Cube included inaccurate coding of procedures and diagnoses as well as missing data. This possible limitation was addressed by randomly selecting 400 patients in the database to verify the database information against the patient’s EMR, which matched 100% of the time. In addition, the authors calculated the hysterectomy rates using a denominator based on all women veterans accessing VA health care, which included women who had previously had a hysterectomy. Therefore, the true hysterectomy rate may have been underestimated.

Conclusion

The VA operates the largest health care system in the U.S. with more than 500,000 women veterans currently utilizing VA health care.¹¹ The VA provides services to women veterans living in urban, suburban, and rural areas. The breadth of geographic locations, the declining number of VA facilities offering gynecologic surgical services, and the growing population of female veterans present unique challenges to providing accessible and comparable health care to these female patients.

VA district 4 (Continental) has the lowest population density as well as the lowest VA hysterectomy rate in FY 2014, which may be attributable to the aforementioned challenges. As a result of these challenges, an increasing number of gynecologic surgical referrals to non-VA facilities was observed during the study period. The VA has made considerable progress in supporting and promoting health care for women by strategically enhancing services and access for women veterans. Although the number of hysterectomies has increased across VA facilities offering gynecologic surgical services, about 1 in 3 women veterans are referred to non-VA facilities for their gynecologic surgical needs. The VA has a challenging opportunity to expand gynecologic surgical services and improve access for the growing population of women veterans. To accommodate this growth, the VA may consider strategically increasing the number of facilities providing gynecologic surgical services or expanding established gynecologic surgical departments.

Onychomycosis is a fungal nail infection primarily caused by dermatophytes.¹ If left untreated, the infection can cause nail destruction and deformities,¹ resulting in pain and discomfort,² impaired foot mobility,³ and an overall reduced quality of life.¹ Onychomycosis is a chronic condition that requires long treatment periods due to the slow growth rates of toenails.¹ To successfully cure the condition, fungal eradication must be achieved.

Prior to the US Food and Drug Administration (FDA) approval of tavaborole and efinaconazole, ciclopirox was the only approved topical treatment for onychomycosis.⁴ The recent approval of tavaborole and efinaconazole has increased treatment options available to patients and has started to pave the way for future topical treatments. This article discusses the 3 approved topical treatments for onychomycosis and focuses on the design of the phase 3 clinical trials that led to their approval.

Topical Agents Used to Treat Onychomycosis

Tavaborole, efinaconazole, and ciclopirox have undergone extensive clinical investigation to receive FDA approval. Results from pivotal phase 3 studies establishing the efficacy and safety of each agent formed the basis for regulatory submission. Although it may seem intuitive to compare the relative performance of these agents based on their respective phase 3 clinical trial data, there are important differences in study methodology, conduct, and populations that prevent direct comparisons. The FDA provides limited guidance to the pharmaceutical industry on how to conduct clinical trials for potential onychomycosis treatments. Comparative efficacy and safety claims are limited based on cross-study comparisons. The details of the phase 3 trial designs are summarized in the Table.

Tavaborole
Tavaborole is a boron-based treatment with a novel mechanism of action.⁵ Tavaborole binds to the editing domain of leucyl–transfer ribonucleic acid synthetase via an integrated boron atom and inhibits fungal protein synthesis.⁶ Two identical randomized, double-blind, vehicle-controlled, parallel-group, phase 3 clinical trials evaluating tavaborole were performed.⁵ The first study (registered at www.clinicaltrials.gov with the identifier NCT01270971) included 594 participants from27 sites in the United States and Mexico and was conducted between December 2010 and November 2012. The second study (NCT01302119) included 604 participants from 32 sites in the United States and Canada and was conducted between February 2011 and January 2013.

Eligible participants 18 years and older had distal subungual onychomycosis (DSO) of the toenails affecting 20% to 60% of 1 or more target great toenails (TGTs), tested positive for fungus using potassium hydroxide (KOH) wet mounts and positive for Trichophyton rubrum and Trichophyton mentagrophytes on fungal culture diagnostic tests, had distal TGT thickness of 3 mm or less, and had 3 mm or more of clear nail between the proximal nail fold and the most proximal visible mycotic border.⁵ Those with active tinea pedis requiring treatment or with a history of chronic moccasin-type tinea pedis were excluded. Participants were randomized to receive either tavaborole or vehicle (2:1). Treatments were applied once daily to all infected toenails for a total of 48 weeks, and nail debridement (defined as partial or complete removal of the toenail) was not permitted. Notably, controlled trimming of the nail was allowed to 1 mm of the leading nail edge. Regular assessments of each toenail for disease involvement, onycholysis, and subungual hyperkeratosis were made at screening, baseline, week 2, week 6, and every 6 weeks thereafter until week 52. Subungual TGT samples were taken at screening and every 12 weeks during the study for examination at a mycology laboratory, which performed KOH and fungal culture tests. A follow-up assessment was made at week 52.⁵

The primary end point was complete cure of the TGT at week 52, with secondary end points of completely or almost clear TGT nail (≤10% dystrophic nail), completely or almost clear TGT nail (≤10% dystrophic nail) plus negative mycology, and negative mycology of TGT.⁵ Examples of TGTs in participants who achieved complete cure and almost clear nails with negative mycology before and after treatment with tavaborole are shown in Figure 1. An example of a patient considered to have treatment failure is shown in Figure 2. This patient showed marked improvement in nail appearance and had a negative culture result but had a positive KOH test, which demonstrates the stringency in which topical agents are judged in onychomycosis trials.⁵

Efinaconazole
Efinaconazole is a topical triazole antifungal specifically indicated to treat onychomycosis. Two identical randomized, vehicle-controlled, double-blind, multicenter trials were performed to assess the safety and efficacy of efinaconazole solution 10%^.7 The first study (NCT01008033) involved 870 participants and was conducted at a total of 74 sites in Japan (33 sites), Canada (7 sites), and the United States (34 sites) between December 2009 and September 2011. The second study (NCT01007708) had 785 participants and was conducted at 44 sites in Canada (8 sites) and the United States (36 sites) between December 2009 and October 2011.

Participants aged 18 to 70 years with a clinical diagnosis of DSO affecting 1 or more TGT were eligible to participate.⁷ Other eligibility criteria included an uninfected toenail length 3 mm or more from the proximal nail fold, a maximum toenail thickness of 3 mm, positive KOH wet mounts, and positive dermatophyte or mixed dermatophyte/candida cultures. Dermatophytes included T rubrum and T mentagrophytes. Those with severe moccasin-type tinea pedis were excluded. Participants were randomized to receive efinaconazole or vehicle (3:1). Once-daily treatments were self-applied to nails for 48 weeks. Clinical assessments were made at baseline and every 12 weeks until week 48, with a follow-up assessment at week 52. No nail trimming protocol was provided.⁷

The primary end point of the efinaconazole phase 3 trials was complete cure at week 52, with secondary end points including mycologic cure, treatment success (≤5% mycotic nail), and complete or almost complete cure (negative culture and KOH, ≤5% mycotic nail). An example of a complete cure from baseline to week 52 is shown in Figure 3.⁷

Ciclopirox
Ciclopirox was the first topical therapy to be approved for the treatment of onychomycosis. Ciclopirox is a broad-spectrum antifungal agent that inhibits metal-dependent enzymes, which are responsible for the degradation of toxic peroxides in fungal cells. The safety and efficacy of ciclopirox nail lacquer topical solution 8% also was investigated in 2 identical phase 3 clinical trials.⁸ The first study was conducted at 9 sites in the United States between June 1994 and June 1996 and included 223 participants. The second study was conducted at 9 sites in the United States between July 1994 and April 1996 and included 237 participants.

Eligible participants were required to have DSO in at least one TGT, positive KOH wet mount with positive dermatophyte culture, and 20% to 65% nail involvement.⁸ Those with tinea pedis were not excluded. Participants were randomized to receive once-daily treatment with ciclopirox or vehicle (1:1)(applied to all toenails and affected fingernails) for 48 weeks. The product was to be removed by the patient with alcohol on a weekly basis. Trimming was allowed as necessary, and mechanical debridement by the physician could be performed monthly. Assessments were made every 4 weeks, and mycologic examinations were performed every 12 weeks. Participants who were clinically cured were assessed further in a 12- to 24-week posttreatment follow-up period.⁸

The primary end point of complete cure and secondary end points of treatment success (negative culture and KOH, ≤10% mycotic nail), mycologic cure, and negative mycologic culture were assessed at week 48.⁸

Phase 3 Clinical Trial Similarities and Differences

The phase 3 clinical trials used to investigate the safety and efficacy of tavaborole,⁵ efinaconazole,⁷ and ciclopirox⁸ were similar in their overall design. All trials were randomized, double-blind, vehicle-controlled studies in patients with DSO. Each agent was assessed using a once-daily application for a treatment period of 48 weeks.

Primary differences among study designs included the age range of participants, the range of mycotic nail involvement, the presence/absence of tinea pedis, and the nail trimming/debridement protocols used. Differences were observed in the patient eligibility criteria of these trials. Both mycotic area and participant age range were inconsistent for each agent (eTable). Participants with larger mycotic areas usually have a poorer prognosis, as they tend to have a greater fungal load.⁹ A baseline mycotic area of 20% to 60%,⁵ 20% to 50%,⁷ and 20% to 65%⁸ at baseline was required for the tavaborole, efinaconazole, and ciclopirox trials, respectively. Variations in mycotic area between trials can affect treatment efficacy, as clinical cures can be reached quicker by patients with smaller areas of infection. Of note, the average mycotic area of involvement was not reported in the tavaborole studies but was 36% and 40% for the efinaconazole and ciclopirox studies, respectively.^5,8 It also is more difficult to achieve complete cure in older patients, as they have poor circulation and reduced nail growth rates.^1,10 The participant age range was 18 to 88 years in the tavaborole trials, with 8% of the participants older than 70 years,⁵ compared to 18 to 71 years in both the efinaconazole and ciclopirox trials.^7,8 The average age of participants in each study was approximately 54, 51, and 50 years for tavaborole, efinaconazole, and ciclopirox, respectively. Because factors impacting treatment failure can increase with age, efficacy results can be confounded by differing age distributions across different studies.

Another important feature that differed between the clinical trials was the approach to nail trimming—defined as shortening of the free edge of the nail distal to the hyponychium—which varies from debridement in that the nail plate is removed or reduced in thickness proximal to the hyponychium. In the tavaborole trials, trimming was controlled to within 1 mm of the free edge of the nail,⁵ whereas the protocol used for the ciclopirox trials allowed nail trimming as necessary as well as moderate debridement before treatment application and on a monthly basis.⁸ Debridement is an important component in all ciclopirox trials, as it is used to reduce fungal load.¹¹ No trimming control was provided during the efinaconazole trials; however, debridement was prohibited.⁷ These differences can dramatically affect the study results, as residual fungal elements and portions of infected nails are removed during the trimming process in an uncontrolled manner, which can affect mycologic testing results as well as the clinical efficacy results determined through investigator evaluation. Discrepancies regarding nail trimming approach inevitably makes the trial results difficult to compare, as mycologic cure is not translatable between studies.

Furthermore, somewhat unusually, complete cure rate variations were observed between different study centers in the efinaconazole trials. Japanese centers in the first efinaconazole study (NCT01008033) had higher complete cure rates in both the efinaconazole and vehicle treatment arms, which is notable because approximately 29% of participants in this study were Asian, mostly hailing from 33 Japanese centers. The reason for these confounding results is unknown and requires further analysis.

Lastly, the presence or absence of tinea pedis can affect the response to onychomycosis treatment. In the tavaborole trials, patients with active interdigital tinea pedis or exclusively plantar tinea pedis or chronic moccasin-type tinea pedis requiring treatment were excluded from the studies.⁵ In contrast, only patients with severe moccasin-type tinea pedis were excluded in efinaconazole trials.⁷ The ciclopirox studies had no exclusions based on presence of tinea pedis.⁸ These differences are noteworthy, as tinea pedis can serve as a reservoir for fungal infection if not treated and can lead to recurrence of onychomycosis.¹²

Conclusion

In recent years, disappointing efficacy has resulted in the failure of several topical agents for onychomycosis during their development; however, there are several aspects to consider when examining efficacy data in onychomycosis studies. Obtaining a complete cure in onychomycosis is difficult. Because patients applying treatments at home are unlikely to undergo mycologic testing to confirm complete cure, visual inspections are helpful to determine treatment efficacy.

Despite similar overall designs, notable differences in the study designs of the phase 3 clinical trials investigating tavaborole, efinaconazole, and ciclopirox are likely to have had an effect on the reported results, making the efficacy of the agents difficult to compare. It is particularly tempting to compare the primary end point results of each trial, especially considering tavaborole and efinaconazole had primary end points with the same parameters; however, there are several other factors (eg, age range of study population, extent of infection, nail trimming, patient demographics) that may have affected the outcomes of the studies and precluded a direct comparison of any end points. Without head-to-head investigations, there is room for prescribing clinicians to interpret results differently.

Acknowledgment

Writing and editorial assistance was provided by ApotheCom Associates, LLC, Yardley, Pennsylvania, and was supported by Sandoz, a Novartis division.

Onychomycosis is a fungal nail infection primarily caused by dermatophytes.¹ If left untreated, the infection can cause nail destruction and deformities,¹ resulting in pain and discomfort,² impaired foot mobility,³ and an overall reduced quality of life.¹ Onychomycosis is a chronic condition that requires long treatment periods due to the slow growth rates of toenails.¹ To successfully cure the condition, fungal eradication must be achieved.

Prior to the US Food and Drug Administration (FDA) approval of tavaborole and efinaconazole, ciclopirox was the only approved topical treatment for onychomycosis.⁴ The recent approval of tavaborole and efinaconazole has increased treatment options available to patients and has started to pave the way for future topical treatments. This article discusses the 3 approved topical treatments for onychomycosis and focuses on the design of the phase 3 clinical trials that led to their approval.

Topical Agents Used to Treat Onychomycosis

Tavaborole, efinaconazole, and ciclopirox have undergone extensive clinical investigation to receive FDA approval. Results from pivotal phase 3 studies establishing the efficacy and safety of each agent formed the basis for regulatory submission. Although it may seem intuitive to compare the relative performance of these agents based on their respective phase 3 clinical trial data, there are important differences in study methodology, conduct, and populations that prevent direct comparisons. The FDA provides limited guidance to the pharmaceutical industry on how to conduct clinical trials for potential onychomycosis treatments. Comparative efficacy and safety claims are limited based on cross-study comparisons. The details of the phase 3 trial designs are summarized in the Table.

Tavaborole
Tavaborole is a boron-based treatment with a novel mechanism of action.⁵ Tavaborole binds to the editing domain of leucyl–transfer ribonucleic acid synthetase via an integrated boron atom and inhibits fungal protein synthesis.⁶ Two identical randomized, double-blind, vehicle-controlled, parallel-group, phase 3 clinical trials evaluating tavaborole were performed.⁵ The first study (registered at www.clinicaltrials.gov with the identifier NCT01270971) included 594 participants from27 sites in the United States and Mexico and was conducted between December 2010 and November 2012. The second study (NCT01302119) included 604 participants from 32 sites in the United States and Canada and was conducted between February 2011 and January 2013.

Eligible participants 18 years and older had distal subungual onychomycosis (DSO) of the toenails affecting 20% to 60% of 1 or more target great toenails (TGTs), tested positive for fungus using potassium hydroxide (KOH) wet mounts and positive for Trichophyton rubrum and Trichophyton mentagrophytes on fungal culture diagnostic tests, had distal TGT thickness of 3 mm or less, and had 3 mm or more of clear nail between the proximal nail fold and the most proximal visible mycotic border.⁵ Those with active tinea pedis requiring treatment or with a history of chronic moccasin-type tinea pedis were excluded. Participants were randomized to receive either tavaborole or vehicle (2:1). Treatments were applied once daily to all infected toenails for a total of 48 weeks, and nail debridement (defined as partial or complete removal of the toenail) was not permitted. Notably, controlled trimming of the nail was allowed to 1 mm of the leading nail edge. Regular assessments of each toenail for disease involvement, onycholysis, and subungual hyperkeratosis were made at screening, baseline, week 2, week 6, and every 6 weeks thereafter until week 52. Subungual TGT samples were taken at screening and every 12 weeks during the study for examination at a mycology laboratory, which performed KOH and fungal culture tests. A follow-up assessment was made at week 52.⁵

The primary end point was complete cure of the TGT at week 52, with secondary end points of completely or almost clear TGT nail (≤10% dystrophic nail), completely or almost clear TGT nail (≤10% dystrophic nail) plus negative mycology, and negative mycology of TGT.⁵ Examples of TGTs in participants who achieved complete cure and almost clear nails with negative mycology before and after treatment with tavaborole are shown in Figure 1. An example of a patient considered to have treatment failure is shown in Figure 2. This patient showed marked improvement in nail appearance and had a negative culture result but had a positive KOH test, which demonstrates the stringency in which topical agents are judged in onychomycosis trials.⁵

Efinaconazole
Efinaconazole is a topical triazole antifungal specifically indicated to treat onychomycosis. Two identical randomized, vehicle-controlled, double-blind, multicenter trials were performed to assess the safety and efficacy of efinaconazole solution 10%^.7 The first study (NCT01008033) involved 870 participants and was conducted at a total of 74 sites in Japan (33 sites), Canada (7 sites), and the United States (34 sites) between December 2009 and September 2011. The second study (NCT01007708) had 785 participants and was conducted at 44 sites in Canada (8 sites) and the United States (36 sites) between December 2009 and October 2011.

Participants aged 18 to 70 years with a clinical diagnosis of DSO affecting 1 or more TGT were eligible to participate.⁷ Other eligibility criteria included an uninfected toenail length 3 mm or more from the proximal nail fold, a maximum toenail thickness of 3 mm, positive KOH wet mounts, and positive dermatophyte or mixed dermatophyte/candida cultures. Dermatophytes included T rubrum and T mentagrophytes. Those with severe moccasin-type tinea pedis were excluded. Participants were randomized to receive efinaconazole or vehicle (3:1). Once-daily treatments were self-applied to nails for 48 weeks. Clinical assessments were made at baseline and every 12 weeks until week 48, with a follow-up assessment at week 52. No nail trimming protocol was provided.⁷

The primary end point of the efinaconazole phase 3 trials was complete cure at week 52, with secondary end points including mycologic cure, treatment success (≤5% mycotic nail), and complete or almost complete cure (negative culture and KOH, ≤5% mycotic nail). An example of a complete cure from baseline to week 52 is shown in Figure 3.⁷

Ciclopirox
Ciclopirox was the first topical therapy to be approved for the treatment of onychomycosis. Ciclopirox is a broad-spectrum antifungal agent that inhibits metal-dependent enzymes, which are responsible for the degradation of toxic peroxides in fungal cells. The safety and efficacy of ciclopirox nail lacquer topical solution 8% also was investigated in 2 identical phase 3 clinical trials.⁸ The first study was conducted at 9 sites in the United States between June 1994 and June 1996 and included 223 participants. The second study was conducted at 9 sites in the United States between July 1994 and April 1996 and included 237 participants.

Eligible participants were required to have DSO in at least one TGT, positive KOH wet mount with positive dermatophyte culture, and 20% to 65% nail involvement.⁸ Those with tinea pedis were not excluded. Participants were randomized to receive once-daily treatment with ciclopirox or vehicle (1:1)(applied to all toenails and affected fingernails) for 48 weeks. The product was to be removed by the patient with alcohol on a weekly basis. Trimming was allowed as necessary, and mechanical debridement by the physician could be performed monthly. Assessments were made every 4 weeks, and mycologic examinations were performed every 12 weeks. Participants who were clinically cured were assessed further in a 12- to 24-week posttreatment follow-up period.⁸

The primary end point of complete cure and secondary end points of treatment success (negative culture and KOH, ≤10% mycotic nail), mycologic cure, and negative mycologic culture were assessed at week 48.⁸

Phase 3 Clinical Trial Similarities and Differences

The phase 3 clinical trials used to investigate the safety and efficacy of tavaborole,⁵ efinaconazole,⁷ and ciclopirox⁸ were similar in their overall design. All trials were randomized, double-blind, vehicle-controlled studies in patients with DSO. Each agent was assessed using a once-daily application for a treatment period of 48 weeks.

Primary differences among study designs included the age range of participants, the range of mycotic nail involvement, the presence/absence of tinea pedis, and the nail trimming/debridement protocols used. Differences were observed in the patient eligibility criteria of these trials. Both mycotic area and participant age range were inconsistent for each agent (eTable). Participants with larger mycotic areas usually have a poorer prognosis, as they tend to have a greater fungal load.⁹ A baseline mycotic area of 20% to 60%,⁵ 20% to 50%,⁷ and 20% to 65%⁸ at baseline was required for the tavaborole, efinaconazole, and ciclopirox trials, respectively. Variations in mycotic area between trials can affect treatment efficacy, as clinical cures can be reached quicker by patients with smaller areas of infection. Of note, the average mycotic area of involvement was not reported in the tavaborole studies but was 36% and 40% for the efinaconazole and ciclopirox studies, respectively.^5,8 It also is more difficult to achieve complete cure in older patients, as they have poor circulation and reduced nail growth rates.^1,10 The participant age range was 18 to 88 years in the tavaborole trials, with 8% of the participants older than 70 years,⁵ compared to 18 to 71 years in both the efinaconazole and ciclopirox trials.^7,8 The average age of participants in each study was approximately 54, 51, and 50 years for tavaborole, efinaconazole, and ciclopirox, respectively. Because factors impacting treatment failure can increase with age, efficacy results can be confounded by differing age distributions across different studies.

Another important feature that differed between the clinical trials was the approach to nail trimming—defined as shortening of the free edge of the nail distal to the hyponychium—which varies from debridement in that the nail plate is removed or reduced in thickness proximal to the hyponychium. In the tavaborole trials, trimming was controlled to within 1 mm of the free edge of the nail,⁵ whereas the protocol used for the ciclopirox trials allowed nail trimming as necessary as well as moderate debridement before treatment application and on a monthly basis.⁸ Debridement is an important component in all ciclopirox trials, as it is used to reduce fungal load.¹¹ No trimming control was provided during the efinaconazole trials; however, debridement was prohibited.⁷ These differences can dramatically affect the study results, as residual fungal elements and portions of infected nails are removed during the trimming process in an uncontrolled manner, which can affect mycologic testing results as well as the clinical efficacy results determined through investigator evaluation. Discrepancies regarding nail trimming approach inevitably makes the trial results difficult to compare, as mycologic cure is not translatable between studies.

Furthermore, somewhat unusually, complete cure rate variations were observed between different study centers in the efinaconazole trials. Japanese centers in the first efinaconazole study (NCT01008033) had higher complete cure rates in both the efinaconazole and vehicle treatment arms, which is notable because approximately 29% of participants in this study were Asian, mostly hailing from 33 Japanese centers. The reason for these confounding results is unknown and requires further analysis.

Lastly, the presence or absence of tinea pedis can affect the response to onychomycosis treatment. In the tavaborole trials, patients with active interdigital tinea pedis or exclusively plantar tinea pedis or chronic moccasin-type tinea pedis requiring treatment were excluded from the studies.⁵ In contrast, only patients with severe moccasin-type tinea pedis were excluded in efinaconazole trials.⁷ The ciclopirox studies had no exclusions based on presence of tinea pedis.⁸ These differences are noteworthy, as tinea pedis can serve as a reservoir for fungal infection if not treated and can lead to recurrence of onychomycosis.¹²

Conclusion

In recent years, disappointing efficacy has resulted in the failure of several topical agents for onychomycosis during their development; however, there are several aspects to consider when examining efficacy data in onychomycosis studies. Obtaining a complete cure in onychomycosis is difficult. Because patients applying treatments at home are unlikely to undergo mycologic testing to confirm complete cure, visual inspections are helpful to determine treatment efficacy.

Despite similar overall designs, notable differences in the study designs of the phase 3 clinical trials investigating tavaborole, efinaconazole, and ciclopirox are likely to have had an effect on the reported results, making the efficacy of the agents difficult to compare. It is particularly tempting to compare the primary end point results of each trial, especially considering tavaborole and efinaconazole had primary end points with the same parameters; however, there are several other factors (eg, age range of study population, extent of infection, nail trimming, patient demographics) that may have affected the outcomes of the studies and precluded a direct comparison of any end points. Without head-to-head investigations, there is room for prescribing clinicians to interpret results differently.

Acknowledgment

Writing and editorial assistance was provided by ApotheCom Associates, LLC, Yardley, Pennsylvania, and was supported by Sandoz, a Novartis division.

Onychomycosis is a fungal nail infection primarily caused by dermatophytes.¹ If left untreated, the infection can cause nail destruction and deformities,¹ resulting in pain and discomfort,² impaired foot mobility,³ and an overall reduced quality of life.¹ Onychomycosis is a chronic condition that requires long treatment periods due to the slow growth rates of toenails.¹ To successfully cure the condition, fungal eradication must be achieved.

Prior to the US Food and Drug Administration (FDA) approval of tavaborole and efinaconazole, ciclopirox was the only approved topical treatment for onychomycosis.⁴ The recent approval of tavaborole and efinaconazole has increased treatment options available to patients and has started to pave the way for future topical treatments. This article discusses the 3 approved topical treatments for onychomycosis and focuses on the design of the phase 3 clinical trials that led to their approval.

Topical Agents Used to Treat Onychomycosis

Tavaborole, efinaconazole, and ciclopirox have undergone extensive clinical investigation to receive FDA approval. Results from pivotal phase 3 studies establishing the efficacy and safety of each agent formed the basis for regulatory submission. Although it may seem intuitive to compare the relative performance of these agents based on their respective phase 3 clinical trial data, there are important differences in study methodology, conduct, and populations that prevent direct comparisons. The FDA provides limited guidance to the pharmaceutical industry on how to conduct clinical trials for potential onychomycosis treatments. Comparative efficacy and safety claims are limited based on cross-study comparisons. The details of the phase 3 trial designs are summarized in the Table.

Tavaborole
Tavaborole is a boron-based treatment with a novel mechanism of action.⁵ Tavaborole binds to the editing domain of leucyl–transfer ribonucleic acid synthetase via an integrated boron atom and inhibits fungal protein synthesis.⁶ Two identical randomized, double-blind, vehicle-controlled, parallel-group, phase 3 clinical trials evaluating tavaborole were performed.⁵ The first study (registered at www.clinicaltrials.gov with the identifier NCT01270971) included 594 participants from27 sites in the United States and Mexico and was conducted between December 2010 and November 2012. The second study (NCT01302119) included 604 participants from 32 sites in the United States and Canada and was conducted between February 2011 and January 2013.

Eligible participants 18 years and older had distal subungual onychomycosis (DSO) of the toenails affecting 20% to 60% of 1 or more target great toenails (TGTs), tested positive for fungus using potassium hydroxide (KOH) wet mounts and positive for Trichophyton rubrum and Trichophyton mentagrophytes on fungal culture diagnostic tests, had distal TGT thickness of 3 mm or less, and had 3 mm or more of clear nail between the proximal nail fold and the most proximal visible mycotic border.⁵ Those with active tinea pedis requiring treatment or with a history of chronic moccasin-type tinea pedis were excluded. Participants were randomized to receive either tavaborole or vehicle (2:1). Treatments were applied once daily to all infected toenails for a total of 48 weeks, and nail debridement (defined as partial or complete removal of the toenail) was not permitted. Notably, controlled trimming of the nail was allowed to 1 mm of the leading nail edge. Regular assessments of each toenail for disease involvement, onycholysis, and subungual hyperkeratosis were made at screening, baseline, week 2, week 6, and every 6 weeks thereafter until week 52. Subungual TGT samples were taken at screening and every 12 weeks during the study for examination at a mycology laboratory, which performed KOH and fungal culture tests. A follow-up assessment was made at week 52.⁵

The primary end point was complete cure of the TGT at week 52, with secondary end points of completely or almost clear TGT nail (≤10% dystrophic nail), completely or almost clear TGT nail (≤10% dystrophic nail) plus negative mycology, and negative mycology of TGT.⁵ Examples of TGTs in participants who achieved complete cure and almost clear nails with negative mycology before and after treatment with tavaborole are shown in Figure 1. An example of a patient considered to have treatment failure is shown in Figure 2. This patient showed marked improvement in nail appearance and had a negative culture result but had a positive KOH test, which demonstrates the stringency in which topical agents are judged in onychomycosis trials.⁵

Efinaconazole
Efinaconazole is a topical triazole antifungal specifically indicated to treat onychomycosis. Two identical randomized, vehicle-controlled, double-blind, multicenter trials were performed to assess the safety and efficacy of efinaconazole solution 10%^.7 The first study (NCT01008033) involved 870 participants and was conducted at a total of 74 sites in Japan (33 sites), Canada (7 sites), and the United States (34 sites) between December 2009 and September 2011. The second study (NCT01007708) had 785 participants and was conducted at 44 sites in Canada (8 sites) and the United States (36 sites) between December 2009 and October 2011.

Participants aged 18 to 70 years with a clinical diagnosis of DSO affecting 1 or more TGT were eligible to participate.⁷ Other eligibility criteria included an uninfected toenail length 3 mm or more from the proximal nail fold, a maximum toenail thickness of 3 mm, positive KOH wet mounts, and positive dermatophyte or mixed dermatophyte/candida cultures. Dermatophytes included T rubrum and T mentagrophytes. Those with severe moccasin-type tinea pedis were excluded. Participants were randomized to receive efinaconazole or vehicle (3:1). Once-daily treatments were self-applied to nails for 48 weeks. Clinical assessments were made at baseline and every 12 weeks until week 48, with a follow-up assessment at week 52. No nail trimming protocol was provided.⁷

The primary end point of the efinaconazole phase 3 trials was complete cure at week 52, with secondary end points including mycologic cure, treatment success (≤5% mycotic nail), and complete or almost complete cure (negative culture and KOH, ≤5% mycotic nail). An example of a complete cure from baseline to week 52 is shown in Figure 3.⁷

Ciclopirox
Ciclopirox was the first topical therapy to be approved for the treatment of onychomycosis. Ciclopirox is a broad-spectrum antifungal agent that inhibits metal-dependent enzymes, which are responsible for the degradation of toxic peroxides in fungal cells. The safety and efficacy of ciclopirox nail lacquer topical solution 8% also was investigated in 2 identical phase 3 clinical trials.⁸ The first study was conducted at 9 sites in the United States between June 1994 and June 1996 and included 223 participants. The second study was conducted at 9 sites in the United States between July 1994 and April 1996 and included 237 participants.

Eligible participants were required to have DSO in at least one TGT, positive KOH wet mount with positive dermatophyte culture, and 20% to 65% nail involvement.⁸ Those with tinea pedis were not excluded. Participants were randomized to receive once-daily treatment with ciclopirox or vehicle (1:1)(applied to all toenails and affected fingernails) for 48 weeks. The product was to be removed by the patient with alcohol on a weekly basis. Trimming was allowed as necessary, and mechanical debridement by the physician could be performed monthly. Assessments were made every 4 weeks, and mycologic examinations were performed every 12 weeks. Participants who were clinically cured were assessed further in a 12- to 24-week posttreatment follow-up period.⁸

The primary end point of complete cure and secondary end points of treatment success (negative culture and KOH, ≤10% mycotic nail), mycologic cure, and negative mycologic culture were assessed at week 48.⁸

Phase 3 Clinical Trial Similarities and Differences

The phase 3 clinical trials used to investigate the safety and efficacy of tavaborole,⁵ efinaconazole,⁷ and ciclopirox⁸ were similar in their overall design. All trials were randomized, double-blind, vehicle-controlled studies in patients with DSO. Each agent was assessed using a once-daily application for a treatment period of 48 weeks.

Primary differences among study designs included the age range of participants, the range of mycotic nail involvement, the presence/absence of tinea pedis, and the nail trimming/debridement protocols used. Differences were observed in the patient eligibility criteria of these trials. Both mycotic area and participant age range were inconsistent for each agent (eTable). Participants with larger mycotic areas usually have a poorer prognosis, as they tend to have a greater fungal load.⁹ A baseline mycotic area of 20% to 60%,⁵ 20% to 50%,⁷ and 20% to 65%⁸ at baseline was required for the tavaborole, efinaconazole, and ciclopirox trials, respectively. Variations in mycotic area between trials can affect treatment efficacy, as clinical cures can be reached quicker by patients with smaller areas of infection. Of note, the average mycotic area of involvement was not reported in the tavaborole studies but was 36% and 40% for the efinaconazole and ciclopirox studies, respectively.^5,8 It also is more difficult to achieve complete cure in older patients, as they have poor circulation and reduced nail growth rates.^1,10 The participant age range was 18 to 88 years in the tavaborole trials, with 8% of the participants older than 70 years,⁵ compared to 18 to 71 years in both the efinaconazole and ciclopirox trials.^7,8 The average age of participants in each study was approximately 54, 51, and 50 years for tavaborole, efinaconazole, and ciclopirox, respectively. Because factors impacting treatment failure can increase with age, efficacy results can be confounded by differing age distributions across different studies.

Another important feature that differed between the clinical trials was the approach to nail trimming—defined as shortening of the free edge of the nail distal to the hyponychium—which varies from debridement in that the nail plate is removed or reduced in thickness proximal to the hyponychium. In the tavaborole trials, trimming was controlled to within 1 mm of the free edge of the nail,⁵ whereas the protocol used for the ciclopirox trials allowed nail trimming as necessary as well as moderate debridement before treatment application and on a monthly basis.⁸ Debridement is an important component in all ciclopirox trials, as it is used to reduce fungal load.¹¹ No trimming control was provided during the efinaconazole trials; however, debridement was prohibited.⁷ These differences can dramatically affect the study results, as residual fungal elements and portions of infected nails are removed during the trimming process in an uncontrolled manner, which can affect mycologic testing results as well as the clinical efficacy results determined through investigator evaluation. Discrepancies regarding nail trimming approach inevitably makes the trial results difficult to compare, as mycologic cure is not translatable between studies.

Furthermore, somewhat unusually, complete cure rate variations were observed between different study centers in the efinaconazole trials. Japanese centers in the first efinaconazole study (NCT01008033) had higher complete cure rates in both the efinaconazole and vehicle treatment arms, which is notable because approximately 29% of participants in this study were Asian, mostly hailing from 33 Japanese centers. The reason for these confounding results is unknown and requires further analysis.

Lastly, the presence or absence of tinea pedis can affect the response to onychomycosis treatment. In the tavaborole trials, patients with active interdigital tinea pedis or exclusively plantar tinea pedis or chronic moccasin-type tinea pedis requiring treatment were excluded from the studies.⁵ In contrast, only patients with severe moccasin-type tinea pedis were excluded in efinaconazole trials.⁷ The ciclopirox studies had no exclusions based on presence of tinea pedis.⁸ These differences are noteworthy, as tinea pedis can serve as a reservoir for fungal infection if not treated and can lead to recurrence of onychomycosis.¹²

Conclusion

In recent years, disappointing efficacy has resulted in the failure of several topical agents for onychomycosis during their development; however, there are several aspects to consider when examining efficacy data in onychomycosis studies. Obtaining a complete cure in onychomycosis is difficult. Because patients applying treatments at home are unlikely to undergo mycologic testing to confirm complete cure, visual inspections are helpful to determine treatment efficacy.

Despite similar overall designs, notable differences in the study designs of the phase 3 clinical trials investigating tavaborole, efinaconazole, and ciclopirox are likely to have had an effect on the reported results, making the efficacy of the agents difficult to compare. It is particularly tempting to compare the primary end point results of each trial, especially considering tavaborole and efinaconazole had primary end points with the same parameters; however, there are several other factors (eg, age range of study population, extent of infection, nail trimming, patient demographics) that may have affected the outcomes of the studies and precluded a direct comparison of any end points. Without head-to-head investigations, there is room for prescribing clinicians to interpret results differently.

Acknowledgment

Writing and editorial assistance was provided by ApotheCom Associates, LLC, Yardley, Pennsylvania, and was supported by Sandoz, a Novartis division.