Hospital Medicine (HM) is medicine’s fastest growing specialty.¹ Rapid expansion of the field has been met with rising interest by young physicians, many of whom are first-time job seekers and may desire information on best practices for applying and interviewing in HM.^2-4 However, no prior work has examined HM-specific candidate qualifications and qualities that may be most valued in the hiring process.

As members of the Society of Hospital Medicine (SHM) Physicians in Training Committee, a group charged with “prepar[ing] trainees and early career hospitalists in their transition into hospital medicine,” we aimed to fill this knowledge gap around the HM-specific hiring process.

Survey Instrument

The authors developed the survey based on expertise as HM interviewers (JAD, AH, CD, EE, BK, DS, and SM) and local and national interview workshop leaders (JAD, CD, BK, SM). The questionnaire focused on objective applicant qualifications, qualities and attributes displayed during interviews (Appendix 1). Content, length, and reliability of physician understanding were assessed via feedback from local HM group leaders.

Respondents were asked to provide nonidentifying demographics and their role in their HM group’s hiring process. If they reported no role, the survey was terminated. Subsequent standardized HM group demographic questions were adapted from the Society of Hospital Medicine (SHM) State of Hospital Medicine Report.⁵

Survey questions were multiple choice, ranking and free-response aimed at understanding how respondents assess HM candidate attributes, skills, and behavior. For ranking questions, answer choice order was randomized to reduce answer order-based bias. One free-response question asked the respondent to provide a unique interview question they use that “reveals the most about a hospitalist candidate.” Responses were then individually inserted into the list of choices for a subsequent ranking question regarding the most important qualities a candidate must demonstrate.

Respondents were asked four open-ended questions designed to understand the approach to candidate assessment: (1) use of unique interview questions (as above); (2) identification of “red flags” during interviews; (3) distinctions between assessment of long-term (LT) career hospitalist candidates versus short-term (ST) candidates (eg, those seeking positions prior to fellowship); and (4) key qualifications of ST candidates.

Survey Administration

Survey recipients were identified via SHM administrative rosters. Surveys were distributed electronically via SHM to all current nontrainee physician members who reported a United States mailing address. The survey was determined to not constitute human subjects research by the Beth Israel Deaconess Medical Center Committee on Clinical Investigations.

Data Analysis

Multiple-choice responses were analyzed descriptively. For ranking-type questions, answers were weighted based on ranking order.

Responses to all open-ended survey questions were analyzed using thematic analysis. We used an iterative process to develop and refine codes identifying key concepts that emerged from the data. Three authors independently coded survey responses. As a group, research team members established the coding framework and resolved discrepancies via discussion to achieve consensus.

Survey links were sent to 8,398 e-mail addresses, of which 7,306 were undeliverable or unopened, leaving 1,092 total eligible respondents. Of these, 347 (31.8%) responded.

A total of 236 respondents reported having a formal role in HM hiring. Of these roles, 79.0% were one-on-one interviewers, 49.6% group interviewers, 45.5% telephone/videoconference interviewers, 41.5% participated on a selection committee, and 32.1% identified as the ultimate decision-maker. Regarding graduate medical education teaching status, 42.0% of respondents identified their primary workplace as a community/affiliated teaching hospital, 33.05% as a university-based teaching hospital, and 23.0% as a nonteaching hospital. Additional characteristics are reported in Appendix 2.

Quantitative Analysis

Respondents ranked the top five qualifications of HM candidates and the top five qualities a candidate should demonstrate on the interview day to be considered for hiring (Table 1).

When asked to rate agreement with the statement “I evaluate and consider all hospital medicine candidates similarly, regardless of whether they articulate an interest in hospital medicine as a long-term career or as a short-term position before fellowship,” 99 (57.23%) respondents disagreed.

Qualitative Analysis

Thematic analysis of responses to open-ended survey questions identified several “red flag” themes (Table 2). Negative interactions with current providers or staff were commonly noted. Additional red flags were a lack of knowledge or interest in the specific HM group, an inability to articulate career goals, or abnormalities in employment history or application materials. Respondents identified an overly strong focus on lifestyle or salary as factors that might limit a candidate’s chance of advancing in the hiring process.

Responses to free-text questions additionally highlighted preferred questioning techniques and approaches to HM candidate assessment (Appendix 3). Many interview questions addressed candidate interest in a particular HM program and candidate responses to challenging scenarios they had encountered. Other questions explored career development. Respondents wanted LT candidates to have specific HM career goals, while they expected ST candidates to demonstrate commitment to and appreciation of HM as a discipline.

Some respondents described their approach to candidate assessment in terms of investment and risk. LT candidates were often viewed as investments in stability and performance; they were evaluated on current abilities and future potential as related to group-specific goals. Some respondents viewed hiring ST candidates as more risky given concerns that they might be less engaged or integrated with the group. Others viewed the hiring of LT candidates as comparably more risky, relating the longer time commitment to the potential for higher impact on the group and patient care. Accordingly, these respondents viewed ST candidate hiring as less risky, estimating their shorter time commitment as having less of a positive or negative impact, with the benefit of addressing urgent staffing issues or unfilled less desirable positions. One respondent summarized: “If they plan to be a career candidate, I care more about them as people and future coworkers. Short term folks are great if we are in a pinch and can deal with personality issues for a short period of time.”

Respondents also described how valued candidate qualities could help mitigate the risk inherent in hiring, especially for ST hires. Strong interpersonal and teamwork skills were highlighted, as well as a demonstrated record of clinical excellence, evidenced by strong training backgrounds and superlative references. A key factor aiding in ST hiring decisions was prior knowledge of the candidate, such as residents or moonlighters previously working in the respondent’s institution. This allowed for familiarity with the candidate’s clinical acumen as well as perceived ease of onboarding and knowledge of the system.

We present the results of a national survey of hospitalists identifying candidate attributes, skills, and behaviors viewed most favorably by those involved in the HM hiring process. To our knowledge, this is the first research to be published on the topic of evaluating HM candidates.

Survey respondents identified demonstrable HM candidate clinical skills and experience as highly important, consistent with prior research identifying clinical skills as being among those that hospitalists most value.⁶ Based on these responses, job seekers should be prepared to discuss objective measures of clinical experience when appropriate, such as number of cases seen or procedures performed. HM groups may accordingly consider the use of hiring rubrics or scoring systems to standardize these measures and reduce bias.

Respondents also highly valued more subjective assessments of HM applicants’ candidacy. The most highly ranked action item was a candidate’s ability to meaningfully respond to a respondent’s customized interview question. There was also a preference for candidates who were knowledgeable about and interested in the specifics of a particular HM group. The high value placed on these elements may suggest the need for formalized coaching or interview preparation for HM candidates. Similarly, interviewer emphasis on customized questions may also highlight an opportunity for HM groups to internally standardize how to best approach subjective components of the interview.

Our heterogeneous findings on the distinctions between ST and LT candidate hiring practices support the need for additional research on the ST HM job market. Until then, our findings reinforce the importance of applicant transparency about ST versus LT career goals. Although many programs may prefer LT candidates over ST candidates, our results suggest ST candidates may benefit from targeting groups with ST needs and using the application process as an opportunity to highlight certain mitigating strengths.

Our study has limitations. While our population included diverse national representation, the response rate and demographics of our respondents may limit generalizability beyond our study population. Respondents represented multiple perspectives within the HM hiring process and were not limited to those making the final hiring decisions. For questions with prespecified multiple-choice answers, answer choices may have influenced participant responses. Our conclusions are based on the reported preferences of those involved in the HM hiring process and not actual hiring behavior. Future research should attempt to identify factors (eg, region, graduate medical education status, practice setting type) that may be responsible for some of the heterogeneous themes we observed in our analysis.

Our research represents introductory work into the previously unpublished topic of HM-specific hiring practices. These findings may provide relevant insight for trainees considering careers in HM, hospitalists reentering the job market, and those involved in career advising, professional development and the HM hiring process.

Acknowledgments

The authors would like to acknowledge current and former members of SHM’s Physicians in Training Committee whose feedback and leadership helped to inspire this project, as well as those students, residents, and hospitalists who have participated in our Hospital Medicine Annual Meeting interview workshop.

Disclosures

The authors have no conflicts of interest to disclose.

Hospital Medicine (HM) is medicine’s fastest growing specialty.¹ Rapid expansion of the field has been met with rising interest by young physicians, many of whom are first-time job seekers and may desire information on best practices for applying and interviewing in HM.^2-4 However, no prior work has examined HM-specific candidate qualifications and qualities that may be most valued in the hiring process.

As members of the Society of Hospital Medicine (SHM) Physicians in Training Committee, a group charged with “prepar[ing] trainees and early career hospitalists in their transition into hospital medicine,” we aimed to fill this knowledge gap around the HM-specific hiring process.

Survey Instrument

The authors developed the survey based on expertise as HM interviewers (JAD, AH, CD, EE, BK, DS, and SM) and local and national interview workshop leaders (JAD, CD, BK, SM). The questionnaire focused on objective applicant qualifications, qualities and attributes displayed during interviews (Appendix 1). Content, length, and reliability of physician understanding were assessed via feedback from local HM group leaders.

Respondents were asked to provide nonidentifying demographics and their role in their HM group’s hiring process. If they reported no role, the survey was terminated. Subsequent standardized HM group demographic questions were adapted from the Society of Hospital Medicine (SHM) State of Hospital Medicine Report.⁵

Survey questions were multiple choice, ranking and free-response aimed at understanding how respondents assess HM candidate attributes, skills, and behavior. For ranking questions, answer choice order was randomized to reduce answer order-based bias. One free-response question asked the respondent to provide a unique interview question they use that “reveals the most about a hospitalist candidate.” Responses were then individually inserted into the list of choices for a subsequent ranking question regarding the most important qualities a candidate must demonstrate.

Respondents were asked four open-ended questions designed to understand the approach to candidate assessment: (1) use of unique interview questions (as above); (2) identification of “red flags” during interviews; (3) distinctions between assessment of long-term (LT) career hospitalist candidates versus short-term (ST) candidates (eg, those seeking positions prior to fellowship); and (4) key qualifications of ST candidates.

Survey Administration

Survey recipients were identified via SHM administrative rosters. Surveys were distributed electronically via SHM to all current nontrainee physician members who reported a United States mailing address. The survey was determined to not constitute human subjects research by the Beth Israel Deaconess Medical Center Committee on Clinical Investigations.

Data Analysis

Multiple-choice responses were analyzed descriptively. For ranking-type questions, answers were weighted based on ranking order.

Responses to all open-ended survey questions were analyzed using thematic analysis. We used an iterative process to develop and refine codes identifying key concepts that emerged from the data. Three authors independently coded survey responses. As a group, research team members established the coding framework and resolved discrepancies via discussion to achieve consensus.

Survey links were sent to 8,398 e-mail addresses, of which 7,306 were undeliverable or unopened, leaving 1,092 total eligible respondents. Of these, 347 (31.8%) responded.

A total of 236 respondents reported having a formal role in HM hiring. Of these roles, 79.0% were one-on-one interviewers, 49.6% group interviewers, 45.5% telephone/videoconference interviewers, 41.5% participated on a selection committee, and 32.1% identified as the ultimate decision-maker. Regarding graduate medical education teaching status, 42.0% of respondents identified their primary workplace as a community/affiliated teaching hospital, 33.05% as a university-based teaching hospital, and 23.0% as a nonteaching hospital. Additional characteristics are reported in Appendix 2.

Quantitative Analysis

Respondents ranked the top five qualifications of HM candidates and the top five qualities a candidate should demonstrate on the interview day to be considered for hiring (Table 1).

When asked to rate agreement with the statement “I evaluate and consider all hospital medicine candidates similarly, regardless of whether they articulate an interest in hospital medicine as a long-term career or as a short-term position before fellowship,” 99 (57.23%) respondents disagreed.

Qualitative Analysis

Thematic analysis of responses to open-ended survey questions identified several “red flag” themes (Table 2). Negative interactions with current providers or staff were commonly noted. Additional red flags were a lack of knowledge or interest in the specific HM group, an inability to articulate career goals, or abnormalities in employment history or application materials. Respondents identified an overly strong focus on lifestyle or salary as factors that might limit a candidate’s chance of advancing in the hiring process.

Responses to free-text questions additionally highlighted preferred questioning techniques and approaches to HM candidate assessment (Appendix 3). Many interview questions addressed candidate interest in a particular HM program and candidate responses to challenging scenarios they had encountered. Other questions explored career development. Respondents wanted LT candidates to have specific HM career goals, while they expected ST candidates to demonstrate commitment to and appreciation of HM as a discipline.

Some respondents described their approach to candidate assessment in terms of investment and risk. LT candidates were often viewed as investments in stability and performance; they were evaluated on current abilities and future potential as related to group-specific goals. Some respondents viewed hiring ST candidates as more risky given concerns that they might be less engaged or integrated with the group. Others viewed the hiring of LT candidates as comparably more risky, relating the longer time commitment to the potential for higher impact on the group and patient care. Accordingly, these respondents viewed ST candidate hiring as less risky, estimating their shorter time commitment as having less of a positive or negative impact, with the benefit of addressing urgent staffing issues or unfilled less desirable positions. One respondent summarized: “If they plan to be a career candidate, I care more about them as people and future coworkers. Short term folks are great if we are in a pinch and can deal with personality issues for a short period of time.”

Respondents also described how valued candidate qualities could help mitigate the risk inherent in hiring, especially for ST hires. Strong interpersonal and teamwork skills were highlighted, as well as a demonstrated record of clinical excellence, evidenced by strong training backgrounds and superlative references. A key factor aiding in ST hiring decisions was prior knowledge of the candidate, such as residents or moonlighters previously working in the respondent’s institution. This allowed for familiarity with the candidate’s clinical acumen as well as perceived ease of onboarding and knowledge of the system.

We present the results of a national survey of hospitalists identifying candidate attributes, skills, and behaviors viewed most favorably by those involved in the HM hiring process. To our knowledge, this is the first research to be published on the topic of evaluating HM candidates.

Survey respondents identified demonstrable HM candidate clinical skills and experience as highly important, consistent with prior research identifying clinical skills as being among those that hospitalists most value.⁶ Based on these responses, job seekers should be prepared to discuss objective measures of clinical experience when appropriate, such as number of cases seen or procedures performed. HM groups may accordingly consider the use of hiring rubrics or scoring systems to standardize these measures and reduce bias.

Respondents also highly valued more subjective assessments of HM applicants’ candidacy. The most highly ranked action item was a candidate’s ability to meaningfully respond to a respondent’s customized interview question. There was also a preference for candidates who were knowledgeable about and interested in the specifics of a particular HM group. The high value placed on these elements may suggest the need for formalized coaching or interview preparation for HM candidates. Similarly, interviewer emphasis on customized questions may also highlight an opportunity for HM groups to internally standardize how to best approach subjective components of the interview.

Our heterogeneous findings on the distinctions between ST and LT candidate hiring practices support the need for additional research on the ST HM job market. Until then, our findings reinforce the importance of applicant transparency about ST versus LT career goals. Although many programs may prefer LT candidates over ST candidates, our results suggest ST candidates may benefit from targeting groups with ST needs and using the application process as an opportunity to highlight certain mitigating strengths.

Our study has limitations. While our population included diverse national representation, the response rate and demographics of our respondents may limit generalizability beyond our study population. Respondents represented multiple perspectives within the HM hiring process and were not limited to those making the final hiring decisions. For questions with prespecified multiple-choice answers, answer choices may have influenced participant responses. Our conclusions are based on the reported preferences of those involved in the HM hiring process and not actual hiring behavior. Future research should attempt to identify factors (eg, region, graduate medical education status, practice setting type) that may be responsible for some of the heterogeneous themes we observed in our analysis.

Our research represents introductory work into the previously unpublished topic of HM-specific hiring practices. These findings may provide relevant insight for trainees considering careers in HM, hospitalists reentering the job market, and those involved in career advising, professional development and the HM hiring process.

Acknowledgments

The authors would like to acknowledge current and former members of SHM’s Physicians in Training Committee whose feedback and leadership helped to inspire this project, as well as those students, residents, and hospitalists who have participated in our Hospital Medicine Annual Meeting interview workshop.

Disclosures

The authors have no conflicts of interest to disclose.

Hospital Medicine (HM) is medicine’s fastest growing specialty.¹ Rapid expansion of the field has been met with rising interest by young physicians, many of whom are first-time job seekers and may desire information on best practices for applying and interviewing in HM.^2-4 However, no prior work has examined HM-specific candidate qualifications and qualities that may be most valued in the hiring process.

As members of the Society of Hospital Medicine (SHM) Physicians in Training Committee, a group charged with “prepar[ing] trainees and early career hospitalists in their transition into hospital medicine,” we aimed to fill this knowledge gap around the HM-specific hiring process.

Survey Instrument

The authors developed the survey based on expertise as HM interviewers (JAD, AH, CD, EE, BK, DS, and SM) and local and national interview workshop leaders (JAD, CD, BK, SM). The questionnaire focused on objective applicant qualifications, qualities and attributes displayed during interviews (Appendix 1). Content, length, and reliability of physician understanding were assessed via feedback from local HM group leaders.

Respondents were asked to provide nonidentifying demographics and their role in their HM group’s hiring process. If they reported no role, the survey was terminated. Subsequent standardized HM group demographic questions were adapted from the Society of Hospital Medicine (SHM) State of Hospital Medicine Report.⁵

Survey questions were multiple choice, ranking and free-response aimed at understanding how respondents assess HM candidate attributes, skills, and behavior. For ranking questions, answer choice order was randomized to reduce answer order-based bias. One free-response question asked the respondent to provide a unique interview question they use that “reveals the most about a hospitalist candidate.” Responses were then individually inserted into the list of choices for a subsequent ranking question regarding the most important qualities a candidate must demonstrate.

Respondents were asked four open-ended questions designed to understand the approach to candidate assessment: (1) use of unique interview questions (as above); (2) identification of “red flags” during interviews; (3) distinctions between assessment of long-term (LT) career hospitalist candidates versus short-term (ST) candidates (eg, those seeking positions prior to fellowship); and (4) key qualifications of ST candidates.

Survey Administration

Survey recipients were identified via SHM administrative rosters. Surveys were distributed electronically via SHM to all current nontrainee physician members who reported a United States mailing address. The survey was determined to not constitute human subjects research by the Beth Israel Deaconess Medical Center Committee on Clinical Investigations.

Data Analysis

Multiple-choice responses were analyzed descriptively. For ranking-type questions, answers were weighted based on ranking order.

Responses to all open-ended survey questions were analyzed using thematic analysis. We used an iterative process to develop and refine codes identifying key concepts that emerged from the data. Three authors independently coded survey responses. As a group, research team members established the coding framework and resolved discrepancies via discussion to achieve consensus.

Survey links were sent to 8,398 e-mail addresses, of which 7,306 were undeliverable or unopened, leaving 1,092 total eligible respondents. Of these, 347 (31.8%) responded.

A total of 236 respondents reported having a formal role in HM hiring. Of these roles, 79.0% were one-on-one interviewers, 49.6% group interviewers, 45.5% telephone/videoconference interviewers, 41.5% participated on a selection committee, and 32.1% identified as the ultimate decision-maker. Regarding graduate medical education teaching status, 42.0% of respondents identified their primary workplace as a community/affiliated teaching hospital, 33.05% as a university-based teaching hospital, and 23.0% as a nonteaching hospital. Additional characteristics are reported in Appendix 2.

Quantitative Analysis

Respondents ranked the top five qualifications of HM candidates and the top five qualities a candidate should demonstrate on the interview day to be considered for hiring (Table 1).

When asked to rate agreement with the statement “I evaluate and consider all hospital medicine candidates similarly, regardless of whether they articulate an interest in hospital medicine as a long-term career or as a short-term position before fellowship,” 99 (57.23%) respondents disagreed.

Qualitative Analysis

Thematic analysis of responses to open-ended survey questions identified several “red flag” themes (Table 2). Negative interactions with current providers or staff were commonly noted. Additional red flags were a lack of knowledge or interest in the specific HM group, an inability to articulate career goals, or abnormalities in employment history or application materials. Respondents identified an overly strong focus on lifestyle or salary as factors that might limit a candidate’s chance of advancing in the hiring process.

Responses to free-text questions additionally highlighted preferred questioning techniques and approaches to HM candidate assessment (Appendix 3). Many interview questions addressed candidate interest in a particular HM program and candidate responses to challenging scenarios they had encountered. Other questions explored career development. Respondents wanted LT candidates to have specific HM career goals, while they expected ST candidates to demonstrate commitment to and appreciation of HM as a discipline.

Some respondents described their approach to candidate assessment in terms of investment and risk. LT candidates were often viewed as investments in stability and performance; they were evaluated on current abilities and future potential as related to group-specific goals. Some respondents viewed hiring ST candidates as more risky given concerns that they might be less engaged or integrated with the group. Others viewed the hiring of LT candidates as comparably more risky, relating the longer time commitment to the potential for higher impact on the group and patient care. Accordingly, these respondents viewed ST candidate hiring as less risky, estimating their shorter time commitment as having less of a positive or negative impact, with the benefit of addressing urgent staffing issues or unfilled less desirable positions. One respondent summarized: “If they plan to be a career candidate, I care more about them as people and future coworkers. Short term folks are great if we are in a pinch and can deal with personality issues for a short period of time.”

Respondents also described how valued candidate qualities could help mitigate the risk inherent in hiring, especially for ST hires. Strong interpersonal and teamwork skills were highlighted, as well as a demonstrated record of clinical excellence, evidenced by strong training backgrounds and superlative references. A key factor aiding in ST hiring decisions was prior knowledge of the candidate, such as residents or moonlighters previously working in the respondent’s institution. This allowed for familiarity with the candidate’s clinical acumen as well as perceived ease of onboarding and knowledge of the system.

We present the results of a national survey of hospitalists identifying candidate attributes, skills, and behaviors viewed most favorably by those involved in the HM hiring process. To our knowledge, this is the first research to be published on the topic of evaluating HM candidates.

Survey respondents identified demonstrable HM candidate clinical skills and experience as highly important, consistent with prior research identifying clinical skills as being among those that hospitalists most value.⁶ Based on these responses, job seekers should be prepared to discuss objective measures of clinical experience when appropriate, such as number of cases seen or procedures performed. HM groups may accordingly consider the use of hiring rubrics or scoring systems to standardize these measures and reduce bias.

Respondents also highly valued more subjective assessments of HM applicants’ candidacy. The most highly ranked action item was a candidate’s ability to meaningfully respond to a respondent’s customized interview question. There was also a preference for candidates who were knowledgeable about and interested in the specifics of a particular HM group. The high value placed on these elements may suggest the need for formalized coaching or interview preparation for HM candidates. Similarly, interviewer emphasis on customized questions may also highlight an opportunity for HM groups to internally standardize how to best approach subjective components of the interview.

Our heterogeneous findings on the distinctions between ST and LT candidate hiring practices support the need for additional research on the ST HM job market. Until then, our findings reinforce the importance of applicant transparency about ST versus LT career goals. Although many programs may prefer LT candidates over ST candidates, our results suggest ST candidates may benefit from targeting groups with ST needs and using the application process as an opportunity to highlight certain mitigating strengths.

Our study has limitations. While our population included diverse national representation, the response rate and demographics of our respondents may limit generalizability beyond our study population. Respondents represented multiple perspectives within the HM hiring process and were not limited to those making the final hiring decisions. For questions with prespecified multiple-choice answers, answer choices may have influenced participant responses. Our conclusions are based on the reported preferences of those involved in the HM hiring process and not actual hiring behavior. Future research should attempt to identify factors (eg, region, graduate medical education status, practice setting type) that may be responsible for some of the heterogeneous themes we observed in our analysis.

Our research represents introductory work into the previously unpublished topic of HM-specific hiring practices. These findings may provide relevant insight for trainees considering careers in HM, hospitalists reentering the job market, and those involved in career advising, professional development and the HM hiring process.

Acknowledgments

The authors would like to acknowledge current and former members of SHM’s Physicians in Training Committee whose feedback and leadership helped to inspire this project, as well as those students, residents, and hospitalists who have participated in our Hospital Medicine Annual Meeting interview workshop.

Disclosures

The authors have no conflicts of interest to disclose.

The United States health system has been criticized for its overuse of aggressive and medically ineffective life-sustaining therapies (LST).¹ Some professional societies have elevated dialog about end-of-life (EOL) care to a quality measure,² expecting that more open discussion will achieve more “goal-concordant care”³ and appropriate use of LST. However, even when Advanced Directives (AD) or Physician Orders for Life-Sustaining Therapy (POLST) have been created, their directions are not always followed in the hospital. This perspective discusses how preventable errors allow for use of LST even when patients designated it as unwanted. Two cases, chosen from several similar ones, are highlighted, demonstrating both human and system errors.

During the time of these events, the hospital policy required admission orders to contain a “code status” designation in the electronic medical record (EMR). All active and historical code status orders were listed chronologically and all AD and POLST documents were scanned into a special section of the EMR. Hospital policy, consistent with professional society guidelines,^4,5 stated that patients with AD/POLST limiting EOL support should have individualized discussion about resuscitation options in the event of a periprocedural critical event. Automatic suspension or reinstatement of limited code orders was not permitted.

A 62-year-old woman with refractory heart failure was admitted with recurrence. The admitting code order was “initiate CPR/intubation” even though a POLST order written 10 months earlier indicating “do not intubate” was visible in the EMR. A more recent POLST indicating “No CPR/No intubation” accompanied the patient in the ambulance and was placed at bedside, but not scanned. There was no documented discussion of code status that might have explained the POLST/code order disparity. Notably, during two prior admissions within the year, “full code” orders had also been placed. On the fifth hospital day, the patient was found in respiratory distress and unresponsive. A “code” was called. ICU staff, after confirming full code status, intubated the patient emergently and commenced other invasive ICU interventions. Family members brought the preexisting POLST to medical attention within hours of the code but could not agree on immediate extubation. Over the next week, multiple prognosis discussions were held with the patient (when responsive) and family. Ultimately, the patient failed to improve and indicated a desire to be extubated, dying a few hours later.

A 94-year-old woman was admitted from assisted living with a traumatic subcapital femur fracture. Admission code orders were “initiate CPR/intubation” despite the presence in the EMR of a POLST ordering “no CPR/no intubation.” The patient underwent hemiarthroplasty. There was no documented discussion of AD/POLST by the surgeon, anesthesiologist, or other operating room personnel even though the patient was alert and competent. On postoperative day one, she was found to be bradycardic and hypotensive. A code was called. After confirming full code status in the EMR, cardiac compressions were begun, followed by intubation. Immediately afterward, family members indicated that the patient had a POLST limiting EOL care. When the healthcare proxy was reached hours later, she directed the patient be extubated. The patient died 16 minutes later.

Data on the frequency of unwanted CPR/intubation due to medical error are scarce. In the US, several lawsuits arising from unwanted CPR and intubation have achieved notoriety, but registries of legal cases⁶ probably underestimate the frequency of this harm. In a study of incorrect code status orders at Canadian hospitals, 35% of 308 patients with limited care preferences had full code orders in the chart.⁷ It is unclear how many of these expressed preferences also had legal documents available. There was considerable variability among hospitals, suggesting that local practices and culture were important factors.

Spot audits of 121 of our own patient charts (median age 77 years) on oncology, geriatrics, and cardiac units at our institution found 36 (30%) with AD/POLST that clearly limited life-sustaining treatments. Of these, 14 (39%) had discrepant full code orders. A review of these discrepant orders showed no medical documentation to indicate that the discrepancy was purposeful.

A root cause analysis (RCA) of cases of unwanted resuscitation, including interviews with involved nurses, medical staff, and operating room, hospitalist, and medical informatics leadership, revealed several types of error, both human and system. These pitfalls are probably common to several hospitals, and the solutions developed may be helpful as well (Table).

Haste leads to poor communication with the patient and family. Emergency departments and admitting services can be hectic. Clinicians facing time and acuity pressure may give short shrift to the essential activity of validating patient choices, regardless of whether an AD or POLST is available. Poor communication was the major factor allowing for discrepancy in the Canadian study.⁷ Avoiding prognostic frankness is a well-known coping strategy for both clinicians and patients^8,9 but in all these cases, that obstacle had been overcome earlier in the clinical course of disease, leaving inattention or haste as the most likely culprit.

“It is not our hospital culture to surveille for code status discrepancies, discuss appropriateness on rounds or at sign out.”

In all reviewed cases of unwanted resuscitation, numerous admitting or attending physicians failed to discuss LST meaningfully despite clinical scenarios that were associated with poor prognosis and should have provoked discussion about medical ineffectiveness. The admitting hospitalist in case 2 stated later that she had listed code choices for the patient who chose full code despite having a POLST stating otherwise. However, that discussion was not in depth, not reviewed for match to her POLST, and not documented.

Moreover, all the cases of AD/POLST and code status discrepancy were on nursing units with daily multidisciplinary rounds and where there had been twice-daily nurse-to-nurse and medical staff–to–medical staff sign out. Queries about code status appropriateness and checks for discrepant AD/POLST and code orders were not standard work. Thus, the medical error was perpetuated.

Analysis of cases of unwanted intubation in postoperative cases indicated that contrary to guidelines,^4,5 careful code status review was not part of the preoperative checklist or presurgical discussion.

The EMR is a well-recognized source of potential medical error.^10,11 Clinicians may rely on the EMR for code status history or as a repository of relevant documents. These are important as a starting place for code status discussions, especially since patients and proxies often cannot accurately recall the existence of an AD/POLST or understand the options being presented.^9,12 In case 1, clinicians partially relied upon the erroneous historical code status already in the chart from two prior admissions. This is a dangerous practice since code status choices have several options and depend upon the clinical situation. In the case of paper AD/POLST documents, the EMR is set up poorly to help the medical team find relevant documents. Furthermore, the EMR clinical decision support capabilities do not interact with paper documents, so no assistance in pointing out discrepancies is available. In addition, the scanning process itself can be problematic since scanning of paper documents was not performed until after the patient was discharged, thus hiding the most up-to-date documents from the personnel even if they had sought them. Moreover, our scanning process had been labeling documents with the date of scanning and not the date of completion, making it difficult to find the “active” order.

Interviews with different clinicians revealed widespread knowledge deficits, including appreciation of the POLST as durable across different medical institutions, effective differences between POLST and AD, location of POLST/AD within the EMR, recommendations of professional society guidelines on suspending DNR for procedures, hospital policy on same, the need to check for updates in bedside paper documents, and whether family members can overrule patients’ stated wishes. Education tends to be the most common form of recommendation after RCA and may be the least efficacious in risk mitigation,¹³ but in this case, education reinforced by new EMR capabilities was an essential part of the solutions bundle (Table).

AD/POLST and similar tools are complex, and the choices are not binary. They are subject to change depending upon the medical context and the patient status and may be poorly understood by patients and clinicians.¹⁴ Accordingly, writing a goal-concordant code status order demands time and attention and as much nuanced medical judgment as any other medical problem faced by hospital-based clinicians. Though time-consuming, discussion with the patient or the surrogate should be considered as “standard work.” To facilitate this, a mandatory affirmative statement about review of LST choices was added to admission templates, procedural areas, and clinician sign outs (Table).

Unwanted, and therefore unwarranted, resuscitation violates autonomy and creates distress, anger, and distrust among patients and families. The distress extends also to frontline clinicians who are committed to “do no harm” in every other aspect of their professional lives.

Respecting and translating patients’ AD/POLST or similar tools into goal-concordant code status order is an essential professional commitment. Respect for patient safety and autonomy demands that we do it well, teach it well, and hold each other accountable.

Disclosures

The authors have nothing disclose.

The United States health system has been criticized for its overuse of aggressive and medically ineffective life-sustaining therapies (LST).¹ Some professional societies have elevated dialog about end-of-life (EOL) care to a quality measure,² expecting that more open discussion will achieve more “goal-concordant care”³ and appropriate use of LST. However, even when Advanced Directives (AD) or Physician Orders for Life-Sustaining Therapy (POLST) have been created, their directions are not always followed in the hospital. This perspective discusses how preventable errors allow for use of LST even when patients designated it as unwanted. Two cases, chosen from several similar ones, are highlighted, demonstrating both human and system errors.

During the time of these events, the hospital policy required admission orders to contain a “code status” designation in the electronic medical record (EMR). All active and historical code status orders were listed chronologically and all AD and POLST documents were scanned into a special section of the EMR. Hospital policy, consistent with professional society guidelines,^4,5 stated that patients with AD/POLST limiting EOL support should have individualized discussion about resuscitation options in the event of a periprocedural critical event. Automatic suspension or reinstatement of limited code orders was not permitted.

A 62-year-old woman with refractory heart failure was admitted with recurrence. The admitting code order was “initiate CPR/intubation” even though a POLST order written 10 months earlier indicating “do not intubate” was visible in the EMR. A more recent POLST indicating “No CPR/No intubation” accompanied the patient in the ambulance and was placed at bedside, but not scanned. There was no documented discussion of code status that might have explained the POLST/code order disparity. Notably, during two prior admissions within the year, “full code” orders had also been placed. On the fifth hospital day, the patient was found in respiratory distress and unresponsive. A “code” was called. ICU staff, after confirming full code status, intubated the patient emergently and commenced other invasive ICU interventions. Family members brought the preexisting POLST to medical attention within hours of the code but could not agree on immediate extubation. Over the next week, multiple prognosis discussions were held with the patient (when responsive) and family. Ultimately, the patient failed to improve and indicated a desire to be extubated, dying a few hours later.

A 94-year-old woman was admitted from assisted living with a traumatic subcapital femur fracture. Admission code orders were “initiate CPR/intubation” despite the presence in the EMR of a POLST ordering “no CPR/no intubation.” The patient underwent hemiarthroplasty. There was no documented discussion of AD/POLST by the surgeon, anesthesiologist, or other operating room personnel even though the patient was alert and competent. On postoperative day one, she was found to be bradycardic and hypotensive. A code was called. After confirming full code status in the EMR, cardiac compressions were begun, followed by intubation. Immediately afterward, family members indicated that the patient had a POLST limiting EOL care. When the healthcare proxy was reached hours later, she directed the patient be extubated. The patient died 16 minutes later.

Data on the frequency of unwanted CPR/intubation due to medical error are scarce. In the US, several lawsuits arising from unwanted CPR and intubation have achieved notoriety, but registries of legal cases⁶ probably underestimate the frequency of this harm. In a study of incorrect code status orders at Canadian hospitals, 35% of 308 patients with limited care preferences had full code orders in the chart.⁷ It is unclear how many of these expressed preferences also had legal documents available. There was considerable variability among hospitals, suggesting that local practices and culture were important factors.

Spot audits of 121 of our own patient charts (median age 77 years) on oncology, geriatrics, and cardiac units at our institution found 36 (30%) with AD/POLST that clearly limited life-sustaining treatments. Of these, 14 (39%) had discrepant full code orders. A review of these discrepant orders showed no medical documentation to indicate that the discrepancy was purposeful.

A root cause analysis (RCA) of cases of unwanted resuscitation, including interviews with involved nurses, medical staff, and operating room, hospitalist, and medical informatics leadership, revealed several types of error, both human and system. These pitfalls are probably common to several hospitals, and the solutions developed may be helpful as well (Table).

Haste leads to poor communication with the patient and family. Emergency departments and admitting services can be hectic. Clinicians facing time and acuity pressure may give short shrift to the essential activity of validating patient choices, regardless of whether an AD or POLST is available. Poor communication was the major factor allowing for discrepancy in the Canadian study.⁷ Avoiding prognostic frankness is a well-known coping strategy for both clinicians and patients^8,9 but in all these cases, that obstacle had been overcome earlier in the clinical course of disease, leaving inattention or haste as the most likely culprit.

“It is not our hospital culture to surveille for code status discrepancies, discuss appropriateness on rounds or at sign out.”

In all reviewed cases of unwanted resuscitation, numerous admitting or attending physicians failed to discuss LST meaningfully despite clinical scenarios that were associated with poor prognosis and should have provoked discussion about medical ineffectiveness. The admitting hospitalist in case 2 stated later that she had listed code choices for the patient who chose full code despite having a POLST stating otherwise. However, that discussion was not in depth, not reviewed for match to her POLST, and not documented.

Moreover, all the cases of AD/POLST and code status discrepancy were on nursing units with daily multidisciplinary rounds and where there had been twice-daily nurse-to-nurse and medical staff–to–medical staff sign out. Queries about code status appropriateness and checks for discrepant AD/POLST and code orders were not standard work. Thus, the medical error was perpetuated.

Analysis of cases of unwanted intubation in postoperative cases indicated that contrary to guidelines,^4,5 careful code status review was not part of the preoperative checklist or presurgical discussion.

The EMR is a well-recognized source of potential medical error.^10,11 Clinicians may rely on the EMR for code status history or as a repository of relevant documents. These are important as a starting place for code status discussions, especially since patients and proxies often cannot accurately recall the existence of an AD/POLST or understand the options being presented.^9,12 In case 1, clinicians partially relied upon the erroneous historical code status already in the chart from two prior admissions. This is a dangerous practice since code status choices have several options and depend upon the clinical situation. In the case of paper AD/POLST documents, the EMR is set up poorly to help the medical team find relevant documents. Furthermore, the EMR clinical decision support capabilities do not interact with paper documents, so no assistance in pointing out discrepancies is available. In addition, the scanning process itself can be problematic since scanning of paper documents was not performed until after the patient was discharged, thus hiding the most up-to-date documents from the personnel even if they had sought them. Moreover, our scanning process had been labeling documents with the date of scanning and not the date of completion, making it difficult to find the “active” order.

Interviews with different clinicians revealed widespread knowledge deficits, including appreciation of the POLST as durable across different medical institutions, effective differences between POLST and AD, location of POLST/AD within the EMR, recommendations of professional society guidelines on suspending DNR for procedures, hospital policy on same, the need to check for updates in bedside paper documents, and whether family members can overrule patients’ stated wishes. Education tends to be the most common form of recommendation after RCA and may be the least efficacious in risk mitigation,¹³ but in this case, education reinforced by new EMR capabilities was an essential part of the solutions bundle (Table).

AD/POLST and similar tools are complex, and the choices are not binary. They are subject to change depending upon the medical context and the patient status and may be poorly understood by patients and clinicians.¹⁴ Accordingly, writing a goal-concordant code status order demands time and attention and as much nuanced medical judgment as any other medical problem faced by hospital-based clinicians. Though time-consuming, discussion with the patient or the surrogate should be considered as “standard work.” To facilitate this, a mandatory affirmative statement about review of LST choices was added to admission templates, procedural areas, and clinician sign outs (Table).

Unwanted, and therefore unwarranted, resuscitation violates autonomy and creates distress, anger, and distrust among patients and families. The distress extends also to frontline clinicians who are committed to “do no harm” in every other aspect of their professional lives.

Respecting and translating patients’ AD/POLST or similar tools into goal-concordant code status order is an essential professional commitment. Respect for patient safety and autonomy demands that we do it well, teach it well, and hold each other accountable.

Disclosures

The authors have nothing disclose.

The United States health system has been criticized for its overuse of aggressive and medically ineffective life-sustaining therapies (LST).¹ Some professional societies have elevated dialog about end-of-life (EOL) care to a quality measure,² expecting that more open discussion will achieve more “goal-concordant care”³ and appropriate use of LST. However, even when Advanced Directives (AD) or Physician Orders for Life-Sustaining Therapy (POLST) have been created, their directions are not always followed in the hospital. This perspective discusses how preventable errors allow for use of LST even when patients designated it as unwanted. Two cases, chosen from several similar ones, are highlighted, demonstrating both human and system errors.

During the time of these events, the hospital policy required admission orders to contain a “code status” designation in the electronic medical record (EMR). All active and historical code status orders were listed chronologically and all AD and POLST documents were scanned into a special section of the EMR. Hospital policy, consistent with professional society guidelines,^4,5 stated that patients with AD/POLST limiting EOL support should have individualized discussion about resuscitation options in the event of a periprocedural critical event. Automatic suspension or reinstatement of limited code orders was not permitted.

A 62-year-old woman with refractory heart failure was admitted with recurrence. The admitting code order was “initiate CPR/intubation” even though a POLST order written 10 months earlier indicating “do not intubate” was visible in the EMR. A more recent POLST indicating “No CPR/No intubation” accompanied the patient in the ambulance and was placed at bedside, but not scanned. There was no documented discussion of code status that might have explained the POLST/code order disparity. Notably, during two prior admissions within the year, “full code” orders had also been placed. On the fifth hospital day, the patient was found in respiratory distress and unresponsive. A “code” was called. ICU staff, after confirming full code status, intubated the patient emergently and commenced other invasive ICU interventions. Family members brought the preexisting POLST to medical attention within hours of the code but could not agree on immediate extubation. Over the next week, multiple prognosis discussions were held with the patient (when responsive) and family. Ultimately, the patient failed to improve and indicated a desire to be extubated, dying a few hours later.

A 94-year-old woman was admitted from assisted living with a traumatic subcapital femur fracture. Admission code orders were “initiate CPR/intubation” despite the presence in the EMR of a POLST ordering “no CPR/no intubation.” The patient underwent hemiarthroplasty. There was no documented discussion of AD/POLST by the surgeon, anesthesiologist, or other operating room personnel even though the patient was alert and competent. On postoperative day one, she was found to be bradycardic and hypotensive. A code was called. After confirming full code status in the EMR, cardiac compressions were begun, followed by intubation. Immediately afterward, family members indicated that the patient had a POLST limiting EOL care. When the healthcare proxy was reached hours later, she directed the patient be extubated. The patient died 16 minutes later.

Data on the frequency of unwanted CPR/intubation due to medical error are scarce. In the US, several lawsuits arising from unwanted CPR and intubation have achieved notoriety, but registries of legal cases⁶ probably underestimate the frequency of this harm. In a study of incorrect code status orders at Canadian hospitals, 35% of 308 patients with limited care preferences had full code orders in the chart.⁷ It is unclear how many of these expressed preferences also had legal documents available. There was considerable variability among hospitals, suggesting that local practices and culture were important factors.

Spot audits of 121 of our own patient charts (median age 77 years) on oncology, geriatrics, and cardiac units at our institution found 36 (30%) with AD/POLST that clearly limited life-sustaining treatments. Of these, 14 (39%) had discrepant full code orders. A review of these discrepant orders showed no medical documentation to indicate that the discrepancy was purposeful.

A root cause analysis (RCA) of cases of unwanted resuscitation, including interviews with involved nurses, medical staff, and operating room, hospitalist, and medical informatics leadership, revealed several types of error, both human and system. These pitfalls are probably common to several hospitals, and the solutions developed may be helpful as well (Table).

Haste leads to poor communication with the patient and family. Emergency departments and admitting services can be hectic. Clinicians facing time and acuity pressure may give short shrift to the essential activity of validating patient choices, regardless of whether an AD or POLST is available. Poor communication was the major factor allowing for discrepancy in the Canadian study.⁷ Avoiding prognostic frankness is a well-known coping strategy for both clinicians and patients^8,9 but in all these cases, that obstacle had been overcome earlier in the clinical course of disease, leaving inattention or haste as the most likely culprit.

“It is not our hospital culture to surveille for code status discrepancies, discuss appropriateness on rounds or at sign out.”

In all reviewed cases of unwanted resuscitation, numerous admitting or attending physicians failed to discuss LST meaningfully despite clinical scenarios that were associated with poor prognosis and should have provoked discussion about medical ineffectiveness. The admitting hospitalist in case 2 stated later that she had listed code choices for the patient who chose full code despite having a POLST stating otherwise. However, that discussion was not in depth, not reviewed for match to her POLST, and not documented.

Moreover, all the cases of AD/POLST and code status discrepancy were on nursing units with daily multidisciplinary rounds and where there had been twice-daily nurse-to-nurse and medical staff–to–medical staff sign out. Queries about code status appropriateness and checks for discrepant AD/POLST and code orders were not standard work. Thus, the medical error was perpetuated.

Analysis of cases of unwanted intubation in postoperative cases indicated that contrary to guidelines,^4,5 careful code status review was not part of the preoperative checklist or presurgical discussion.

The EMR is a well-recognized source of potential medical error.^10,11 Clinicians may rely on the EMR for code status history or as a repository of relevant documents. These are important as a starting place for code status discussions, especially since patients and proxies often cannot accurately recall the existence of an AD/POLST or understand the options being presented.^9,12 In case 1, clinicians partially relied upon the erroneous historical code status already in the chart from two prior admissions. This is a dangerous practice since code status choices have several options and depend upon the clinical situation. In the case of paper AD/POLST documents, the EMR is set up poorly to help the medical team find relevant documents. Furthermore, the EMR clinical decision support capabilities do not interact with paper documents, so no assistance in pointing out discrepancies is available. In addition, the scanning process itself can be problematic since scanning of paper documents was not performed until after the patient was discharged, thus hiding the most up-to-date documents from the personnel even if they had sought them. Moreover, our scanning process had been labeling documents with the date of scanning and not the date of completion, making it difficult to find the “active” order.

Interviews with different clinicians revealed widespread knowledge deficits, including appreciation of the POLST as durable across different medical institutions, effective differences between POLST and AD, location of POLST/AD within the EMR, recommendations of professional society guidelines on suspending DNR for procedures, hospital policy on same, the need to check for updates in bedside paper documents, and whether family members can overrule patients’ stated wishes. Education tends to be the most common form of recommendation after RCA and may be the least efficacious in risk mitigation,¹³ but in this case, education reinforced by new EMR capabilities was an essential part of the solutions bundle (Table).

AD/POLST and similar tools are complex, and the choices are not binary. They are subject to change depending upon the medical context and the patient status and may be poorly understood by patients and clinicians.¹⁴ Accordingly, writing a goal-concordant code status order demands time and attention and as much nuanced medical judgment as any other medical problem faced by hospital-based clinicians. Though time-consuming, discussion with the patient or the surrogate should be considered as “standard work.” To facilitate this, a mandatory affirmative statement about review of LST choices was added to admission templates, procedural areas, and clinician sign outs (Table).

Unwanted, and therefore unwarranted, resuscitation violates autonomy and creates distress, anger, and distrust among patients and families. The distress extends also to frontline clinicians who are committed to “do no harm” in every other aspect of their professional lives.

Respecting and translating patients’ AD/POLST or similar tools into goal-concordant code status order is an essential professional commitment. Respect for patient safety and autonomy demands that we do it well, teach it well, and hold each other accountable.

Disclosures

The authors have nothing disclose.

Opioid prescribing has dramatically increased in the United States (US) over the past two decades, fueling the current crisis of opioid-related adverse events and deaths.¹ Understanding the potential contributors to this increased prescribing is paramount to developing effective strategies for preventing propagation. In this issue of the Journal of Hospital Medicine, Burden et al. report the results of a cross-sectional observational study investigating the rates of opioid receipt, patient satisfaction with pain control, and other perceptions of pain management in a sample of patients from geographically diverse US hospitals compared with patients hospitalized in seven other countries.² Although cultural influences on pain perceptions have been demonstrated by others previously, this is the first study to measure opioid receipt and patient satisfaction with pain control across an international sample of hospitalized patients. This study provides crucial insights into key differences in the culture of prescribing and patient expectations between the US and other countries and, in doing so, begins to shed light on potential targets ripe for further investigation and intervention.

First, they found that US patients reported greater levels of pain severity than patients hospitalized in other countries, especially among those not taking opioids before admission. However, even after adjusting for these differences in pain severity, opioids were still prescribed more frequently in the US than in other countries. These findings suggest differences in both patients’ experience of pain and physicians’ propensity to prescribe opioids in the US compared with other countries. Furthermore, beliefs and expectations about pain control differed between hospitalized patients in the US versus other countries. For example, patients in other countries were more likely to endorse the statement “Good patients avoid talking about pain” than patients in the US. This may, in part, contribute to the difference in reported pain severity between the US and other countries.

Finally, and perhaps most interestingly, although US patients who were opioid-naive before hospitalization did report greater satisfaction with pain control than patients in other countries, this difference was not attributable to greater opioid receipt. In fact, opioid receipt was not associated with increased satisfaction with pain control, regardless of country. Studies in other settings, such as the emergency department³ and postoperative settings,⁴ have similarly failed to demonstrate an association between opioid receipt and patient satisfaction. This is not entirely surprising given that studies comparing pain relief between opioid and nonopioid analgesics routinely demonstrate similar efficacy of the two approaches across several conditions.^{5, 6}

This study clearly demonstrates differences in opioid prescribing patterns and patients’ expectations of pain control in sampled hospitals in the US compared to those in other countries; however, there are noteworthy limitations. First, not all regions were sampled within the United States; hospitals in the northeast regions, previously demonstrated to have lower opioid prescribing rates,⁷ were notably absent. Second, the small number of non-US hospitals and the small sample size in those hospitals limit the ability to draw firm conclusions. The results are nonetheless consistent with anecdotal experience. For example, a recent opinion article in the New York Times describes the experience of a US patient undergoing surgery in Germany;⁸ the differences the author observes in terms of expectations around pain control, associated messaging, and ultimately, prescribing practices between the two countries are striking.

In response to studies demonstrating underassessment and undertreatment of pain in hospitalized patients in the late 20^th century,⁹ well-intentioned initiatives have promoted more frequent pain assessment and more aggressive pain control. In the context of the current opioid crisis, Burden et al. provide compelling data supporting the idea that the pendulum has swung too far in the US. This international study suggests that curbing the US opioid crisis will require a true culture shift, not just in providers’ analgesic prescribing patterns but also in messaging around pain and patient expectations.

Disclosures

The authors have nothing to disclose.

Funding

Dr. Herzig was funded by grant number K23AG042459 from the National Institute on Aging and R01HS026215 from the Agency for Healthcare Research and Quality.

Opioid prescribing has dramatically increased in the United States (US) over the past two decades, fueling the current crisis of opioid-related adverse events and deaths.¹ Understanding the potential contributors to this increased prescribing is paramount to developing effective strategies for preventing propagation. In this issue of the Journal of Hospital Medicine, Burden et al. report the results of a cross-sectional observational study investigating the rates of opioid receipt, patient satisfaction with pain control, and other perceptions of pain management in a sample of patients from geographically diverse US hospitals compared with patients hospitalized in seven other countries.² Although cultural influences on pain perceptions have been demonstrated by others previously, this is the first study to measure opioid receipt and patient satisfaction with pain control across an international sample of hospitalized patients. This study provides crucial insights into key differences in the culture of prescribing and patient expectations between the US and other countries and, in doing so, begins to shed light on potential targets ripe for further investigation and intervention.

First, they found that US patients reported greater levels of pain severity than patients hospitalized in other countries, especially among those not taking opioids before admission. However, even after adjusting for these differences in pain severity, opioids were still prescribed more frequently in the US than in other countries. These findings suggest differences in both patients’ experience of pain and physicians’ propensity to prescribe opioids in the US compared with other countries. Furthermore, beliefs and expectations about pain control differed between hospitalized patients in the US versus other countries. For example, patients in other countries were more likely to endorse the statement “Good patients avoid talking about pain” than patients in the US. This may, in part, contribute to the difference in reported pain severity between the US and other countries.

Finally, and perhaps most interestingly, although US patients who were opioid-naive before hospitalization did report greater satisfaction with pain control than patients in other countries, this difference was not attributable to greater opioid receipt. In fact, opioid receipt was not associated with increased satisfaction with pain control, regardless of country. Studies in other settings, such as the emergency department³ and postoperative settings,⁴ have similarly failed to demonstrate an association between opioid receipt and patient satisfaction. This is not entirely surprising given that studies comparing pain relief between opioid and nonopioid analgesics routinely demonstrate similar efficacy of the two approaches across several conditions.^{5, 6}

This study clearly demonstrates differences in opioid prescribing patterns and patients’ expectations of pain control in sampled hospitals in the US compared to those in other countries; however, there are noteworthy limitations. First, not all regions were sampled within the United States; hospitals in the northeast regions, previously demonstrated to have lower opioid prescribing rates,⁷ were notably absent. Second, the small number of non-US hospitals and the small sample size in those hospitals limit the ability to draw firm conclusions. The results are nonetheless consistent with anecdotal experience. For example, a recent opinion article in the New York Times describes the experience of a US patient undergoing surgery in Germany;⁸ the differences the author observes in terms of expectations around pain control, associated messaging, and ultimately, prescribing practices between the two countries are striking.

In response to studies demonstrating underassessment and undertreatment of pain in hospitalized patients in the late 20^th century,⁹ well-intentioned initiatives have promoted more frequent pain assessment and more aggressive pain control. In the context of the current opioid crisis, Burden et al. provide compelling data supporting the idea that the pendulum has swung too far in the US. This international study suggests that curbing the US opioid crisis will require a true culture shift, not just in providers’ analgesic prescribing patterns but also in messaging around pain and patient expectations.

Disclosures

The authors have nothing to disclose.

Funding

Dr. Herzig was funded by grant number K23AG042459 from the National Institute on Aging and R01HS026215 from the Agency for Healthcare Research and Quality.

Opioid prescribing has dramatically increased in the United States (US) over the past two decades, fueling the current crisis of opioid-related adverse events and deaths.¹ Understanding the potential contributors to this increased prescribing is paramount to developing effective strategies for preventing propagation. In this issue of the Journal of Hospital Medicine, Burden et al. report the results of a cross-sectional observational study investigating the rates of opioid receipt, patient satisfaction with pain control, and other perceptions of pain management in a sample of patients from geographically diverse US hospitals compared with patients hospitalized in seven other countries.² Although cultural influences on pain perceptions have been demonstrated by others previously, this is the first study to measure opioid receipt and patient satisfaction with pain control across an international sample of hospitalized patients. This study provides crucial insights into key differences in the culture of prescribing and patient expectations between the US and other countries and, in doing so, begins to shed light on potential targets ripe for further investigation and intervention.

First, they found that US patients reported greater levels of pain severity than patients hospitalized in other countries, especially among those not taking opioids before admission. However, even after adjusting for these differences in pain severity, opioids were still prescribed more frequently in the US than in other countries. These findings suggest differences in both patients’ experience of pain and physicians’ propensity to prescribe opioids in the US compared with other countries. Furthermore, beliefs and expectations about pain control differed between hospitalized patients in the US versus other countries. For example, patients in other countries were more likely to endorse the statement “Good patients avoid talking about pain” than patients in the US. This may, in part, contribute to the difference in reported pain severity between the US and other countries.

Finally, and perhaps most interestingly, although US patients who were opioid-naive before hospitalization did report greater satisfaction with pain control than patients in other countries, this difference was not attributable to greater opioid receipt. In fact, opioid receipt was not associated with increased satisfaction with pain control, regardless of country. Studies in other settings, such as the emergency department³ and postoperative settings,⁴ have similarly failed to demonstrate an association between opioid receipt and patient satisfaction. This is not entirely surprising given that studies comparing pain relief between opioid and nonopioid analgesics routinely demonstrate similar efficacy of the two approaches across several conditions.^{5, 6}

This study clearly demonstrates differences in opioid prescribing patterns and patients’ expectations of pain control in sampled hospitals in the US compared to those in other countries; however, there are noteworthy limitations. First, not all regions were sampled within the United States; hospitals in the northeast regions, previously demonstrated to have lower opioid prescribing rates,⁷ were notably absent. Second, the small number of non-US hospitals and the small sample size in those hospitals limit the ability to draw firm conclusions. The results are nonetheless consistent with anecdotal experience. For example, a recent opinion article in the New York Times describes the experience of a US patient undergoing surgery in Germany;⁸ the differences the author observes in terms of expectations around pain control, associated messaging, and ultimately, prescribing practices between the two countries are striking.

In response to studies demonstrating underassessment and undertreatment of pain in hospitalized patients in the late 20^th century,⁹ well-intentioned initiatives have promoted more frequent pain assessment and more aggressive pain control. In the context of the current opioid crisis, Burden et al. provide compelling data supporting the idea that the pendulum has swung too far in the US. This international study suggests that curbing the US opioid crisis will require a true culture shift, not just in providers’ analgesic prescribing patterns but also in messaging around pain and patient expectations.

Disclosures

The authors have nothing to disclose.

Funding

Dr. Herzig was funded by grant number K23AG042459 from the National Institute on Aging and R01HS026215 from the Agency for Healthcare Research and Quality.

Since 2000, the United States has seen a marked increase in opioid prescribing^1-3 and opioid-related complications, including overdoses, hospitalizations, and deaths.^2,4,5 A study from 2015 showed that more than one-third of the US civilian noninstitutionalized population reported receiving an opioid prescription in the prior year, with 12.5% reporting misuse, and, of those, 16.7% reported a prescription use disorder.⁶ While there has been a slight decrease in opioid prescriptions in the US since 2012, rates of opioid prescribing in 2015 were three times higher than in 1999 and approximately four times higher than in Europe in 2015.^3,7

Pain is commonly reported by hospitalized patients,^8,9 and opioids are often a mainstay of treatment;^9,10 however, treatment with opioids can have a number of adverse outcomes.^2,10,11 Short-term exposure to opioids can lead to long-term use,^12-16 and patients on opioids are at an increased risk for subsequent hospitalization and longer inpatient lengths of stay.⁵

Physician prescribing practices for opioids and patient expectations for pain control vary as a function of geographic region and culture,^10,12,17,18 and pain is influenced by the cultural context in which it occurs.^17,19-22 Treatment of pain may also be affected by limited access to or restrictions on selected medications, as well as by cultural biases.²³ Whether these variations in the treatment of pain are reflected in patients’ satisfaction with pain control is uncertain.

We sought to compare the inpatient analgesic prescribing practices and patients’ perceptions of pain control for medical patients in four teaching hospitals in the US and in seven teaching hospitals in seven other countries.

Study Design

We utilized a cross-sectional, observational design. The study was approved by the Institutional Review Boards at all participating sites.

Setting

The study was conducted at 11 academic hospitals in eight countries from October 8, 2013 to August 31, 2015. Sites in the US included Denver Health in Denver, Colorado; the University of Colorado Hospital in Aurora, Colorado; Hennepin Healthcare in Minneapolis, Minnesota; and Legacy Health in Portland, Oregon. Sites outside the US included McMaster University in Hamilton, Ontario, Canada; Hospital de la Santa Creu i Sant Pau, Universitat Autonòma de Barcelona in Barcelona, Spain; the University of Study of Milan and the University Ospedale “Luigi Sacco” in Milan, Italy, the National Taiwan University Hospital, in Taipei, Taiwan, the University of Ulsan College of Medicine, Asan Medical Center, in Seoul, Korea, the Imperial College, Chelsea and Westminster Hospital, in London, United Kingdom and Dunedin Hospital, Dunedin, New Zealand.

Inclusion and Exclusion Criteria

We included patients 18-89 years of age (20-89 in Taiwan because patients under 20 years of age in this country are a restricted group with respect to participating in research), admitted to an internal medicine service from the Emergency Department or Urgent Care clinic with an acute illness for a minimum of 24 hours (with time zero defined as the time care was initiated in the Emergency Department or Urgent Care Clinic), who reported pain at some time during the first 24-36 hours of their hospitalization and who provided informed consent. In the US, “admission” included both observation and inpatient status. We limited the patient population to those admitted via emergency departments and urgent care clinics in order to enroll similar patient populations across sites.

Scheduled admissions, patients transferred from an outside facility, patients admitted directly from a clinic, and those receiving care in intensive care units were excluded. We also excluded patients who were incarcerated, pregnant, those who received major surgery within the previous 14 days, those with a known diagnosis of active cancer, and those who were receiving palliative or hospice care. Patients receiving care from an investigator in the study at the time of enrollment were not eligible due to the potential conflict of interest.

Patient Screening

Primary teams were contacted to determine if any patients on their service might meet the criteria for inclusion in the study on preselected study days chosen on the basis of the research team’s availability. Identified patients were then screened to establish if they met the eligibility criteria. Patients were asked directly if they had experienced pain during their preadmission evaluation or during their hospitalization.

Data Collection

All patients were hospitalized at the time they gave consent and when data were collected. Data were collected via interviews with patients, as well as through chart review. We recorded patients’ age, gender, race, admitting diagnosis(es), length of stay, psychiatric illness, illicit drug use, whether they reported receiving opioid analgesics at the time of hospitalization, whether they were prescribed opioids and/or nonopioid analgesics during their hospitalization, the median and maximum doses of opioids prescribed and dispensed, and whether they were discharged on opioids. The question of illicit drug use was asked of all patients with the exception of those hospitalized in South Korea due to potential legal implications.

Opioid prescribing and receipt of opioids was recorded based upon current provider orders and medication administration records, respectively. Perception of and satisfaction with pain control was assessed with the American Pain Society Patient Outcome Questionnaire–Modified (APS-POQ-Modified).^24,25 Versions of this survey have been validated in English as well as in other languages and cultures.^26-28 Because hospitalization practices could differ across hospitals and in different countries, we compared patients’ severity of illness by using Charlson comorbidity scores. Consent forms and the APS-POQ were translated into each country’s primary language according to established processes.²⁹ The survey was filled out by having site investigators read questions aloud and by use of a large-font visual analog scale to aid patients’ verbal responses.

Data were collected and managed using a secure, web-based application electronic data capture tool (Research Electronic Data Capture [REDCap], Nashville, Tennessee), hosted at Denver Health.³⁰

Study Size

Preliminary data from the internal medicine units at our institution suggested that 40% of patients without cancer received opioid analgesics during their hospitalization. Assuming 90% power to detect an absolute difference in the proportion of inpatient medical patients who are receiving opioid analgesics during their hospital stay of 17%, a two-sided type 1 error rate of 0.05, six hospitals in the US, and nine hospitals from all other countries, we calculated an initial sample size of 150 patients per site. This sample size was considered feasible for enrollment in a busy inpatient clinical setting. Study end points were to either reach the goal number of patients (150 per site) or the predetermined study end date, whichever came first.

Data Analysis

We generated means with standard deviations (SDs) and medians with interquartile ranges (IQRs) for normally and nonnormally distributed continuous variables, respectively, and frequencies for categorical variables. We used linear mixed modeling for the analysis of continuous variables. For binary outcomes, our data were fitted to a generalized linear mixed model with logit as the link function and a binary distribution. For ordinal variables, specifically patient-reported satisfaction with pain control and the opinion statements, the data were fitted to a generalized linear mixed model with a cumulative logit link and a multinomial distribution. Hospital was included as a random effect in all models to account for patients cared for in the same hospital.

Country of origin, dichotomized as US or non-US, was the independent variable of interest for all models. An interaction term for exposure to opioids prior to admission and country was entered into all models to explore whether differences in the effect of country existed for patients who reported taking opioids prior to admission and those who did not.

The models for the frequency with which analgesics were given, doses of opioids given during hospitalization and at discharge, patient-reported pain score, and patient-reported satisfaction with pain control were adjusted for (1) age, (2) gender, (3) Charlson Comorbidity Index, (4) length of stay, (5) history of illicit drug use, (6) history of psychiatric illness, (7) daily dose in morphine milligram equivalents (MME) for opioids prior to admission, (8) average pain score, and (9) hospital. The patient-reported satisfaction with pain control model was also adjusted for whether or not opioids were given to the patient during their hospitalization. P < .05 was considered to indicate significance. All analyses were performed using SAS Enterprise Guide 7.1 (SAS Institute, Inc., Cary, North Carolina). We reported data on medications that were prescribed and dispensed (as opposed to just prescribed and not necessarily given). Opioids prescribed at discharge represented the total possible opioids that could be given based upon the order/prescription (eg, oxycodone 5 mg every 6 hours as needed for pain would be counted as 20 mg/24 hours maximum possible dose followed by conversion to MME).

Missing Data

When there were missing data, a query was sent to sites to verify if the data were retrievable. If retrievable, the data were then entered. Data were missing in 5% and 2% of patients who did or did not report taking an opioid prior to admission, respectively. If a variable was included in a specific statistical test, then subjects with missing data were excluded from that analysis (ie, complete case analysis).

We approached 1,309 eligible patients, of which 981 provided informed consent, for a response rate of 75%; 503 from the US and 478 patients from other countries (Figure). In unadjusted analyses, we found no significant differences between US and non-US patients in age (mean age 51, SD 15 vs 59, SD 19; P = .30), race, ethnicity, or Charlson comorbidity index scores (median 2, IQR 1-3 vs 3, IQR 1-4; P = .45). US patients had shorter lengths of stay (median 3 days, IQR 2-4 vs 6 days, IQR 3-11; P = .04), a more frequent history of illicit drug use (33% vs 6%; P = .003), a higher frequency of psychiatric illness (27% vs 8%; P < .0001), and more were receiving opioid analgesics prior to admission (38% vs 17%; P = .007) than those hospitalized in other countries (Table 1, Appendix 1). The primary admitting diagnoses for all patients in the study are listed in Appendix 2. Opioid prescribing practices across the individual sites are shown in Appendix 3.

Patients Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found that more patients in the US were given opioids during their hospitalization and in higher doses than patients from other countries and more were prescribed opioids at discharge. Fewer patients in the US were dispensed nonopioid analgesics during their hospitalization than patients from other countries, but this difference was not significant (Table 2). Appendix 4 shows the types of nonopioid pain medications prescribed in the US and other countries.

After adjustment for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys. We found no significant difference in satisfaction with pain control between patients from the US and other countries in the models, regardless of whether we included average pain score or opioid receipt during hospitalization in the model (Table 3).

In unadjusted analyses, compared with patients hospitalized in other countries, more patients in the US stated that they would like a stronger dose of analgesic if they were still in pain, though the difference was nonsignificant, and US patients were more likely to agree with the statement that people become addicted to pain medication easily and less likely to agree with the statement that it is easier to endure pain than deal with the side effects of pain medications (Table 3).

Patients Not Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found no significant difference in the proportion of US patients provided with nonopioid pain medications during their hospitalization compared with patients in other countries, but a greater percentage of US patients were given opioids during their hospitalization and at discharge and in higher doses (Table 2).

After adjusting for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys and greater pain severity in the 24-36 hours prior to completing the survey than patients from other countries, but we found no difference in patient satisfaction with pain control (Table 3). After we included the average pain score and whether or not opioids were given to the patient during their hospitalization in this model, patients in the US were more likely to report a higher level of satisfaction with pain control than patients in all other countries (P = .001).

Patient Satisfaction and Opioid Receipt

Among patients cared for in the US, after controlling for the average pain score, we did not find a significant association between receiving opioids while in the hospital and satisfaction with pain control for patients who either did or did not endorse taking opioids prior to admission (P = .38 and P = .24, respectively). Among patients cared for in all other countries, after controlling for the average pain score, we found a significant association between receiving opioids while in the hospital and a lower level of satisfaction with pain control for patients who reported taking opioids prior to admission (P = .02) but not for patients who did not report taking opioids prior to admission (P = .08).

Compared with patients hospitalized in other countries, a greater percentage of those hospitalized in the US were prescribed opioid analgesics both during hospitalization and at the time of discharge, even after adjustment for pain severity. In addition, patients hospitalized in the US reported greater pain severity at the time they completed their pain surveys and in the 24 to 36 hours prior to completing the survey than patients from other countries. In this sample, satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Our study also suggests that opioid receipt did not lead to improved patient satisfaction with pain control.

The frequency with which we observed opioid analgesics being prescribed during hospitalization in US hospitals (79%) was higher than the 51% of patients who received opioids reported by Herzig and colleagues.¹⁰ Patients in our study had a higher prevalence of illicit drug abuse and psychiatric illness, and our study only included patients who reported pain at some point during their hospitalization. We also studied prescribing practices through analysis of provider orders and medication administration records at the time the patient was hospitalized.

While we observed that physicians in the US more frequently prescribed opioid analgesics during hospitalizations than physicians working in other countries, we also observed that patients in the US reported higher levels of pain during their hospitalization. After adjusting for a number of variables, including pain severity, however, we still found that opioids were more commonly prescribed during hospitalizations by physicians working in the US sites studied than by physicians in the non-US sites.

Opioid prescribing practices varied across the sites sampled in our study. While the US sites, Taiwan, and Korea tended to be heavier utilizers of opioids during hospitalization, there were notable differences in discharge prescribing of opioids, with the US sites more commonly prescribing opioids and higher MME for patients who did not report taking opioids prior to their hospitalization (Appendix 3). A sensitivity analysis was conducted excluding South Korea from modeling, given that patients there were not asked about illicit opioid use. There were no important changes in the magnitude or direction of the results.

Our study supports previous studies indicating that there are cultural and societal differences when it comes to the experience of pain and the expectations around pain control.^17,20-22,31 Much of the focus on reducing opioid utilization has been on provider practices³² and on prescription drug monitoring programs.³³ Our findings suggest that another area of focus that may be important in mitigating the opioid epidemic is patient expectations of pain control.

Our study has a number of strengths. First, we included 11 hospitals from eight different countries. Second, we believe this is the first study to assess opioid prescribing and dispensing practices during hospitalization as well as at the time of discharge. Third, patient perceptions of pain control were assessed in conjunction with analgesic prescribing and were assessed during hospitalization. Fourth, we had high response rates for patient participation in our study. Fifth, we found much larger differences in opioid prescribing than anticipated, and thus, while we did not achieve the sample size originally planned for either the number of hospitals or patients enrolled per hospital, we were sufficiently powered. This is likely secondary to the fact that the population we studied was one that specifically reported pain, resulting in the larger differences seen.

Our study also had a number of limitations. First, the prescribing practices in countries other than the US are represented by only one hospital per country and, in some countries, by limited numbers of patients. While we studied four sites in the US, we did not have a site in the Northeast, a region previously shown to have lower prescribing rates.¹⁰ Additionally, patient samples for the US sites compared with the sites in other countries varied considerably with respect to ethnicity. While some studies in US patients have shown that opioid prescribing may vary based on race/ethnicity,³⁴ we are uncertain as to how this might impact a study that crosses multiple countries. We also had a low number of patients receiving opioids prior to hospitalization for several of the non-US countries, which reduced the power to detect differences in this subgroup. Previous research has shown that there are wide variations in prescribing practices even within countries;^10,12,18 therefore, caution should be taken when generalizing our findings. Second, we assessed analgesic prescribing patterns and pain control during the first 24 to 36 hours of hospitalization and did not consider hospital days beyond this timeframe with the exception of noting what medications were prescribed at discharge. We chose this methodology in an attempt to eliminate as many differences that might exist in the duration of hospitalization across many countries. Third, investigators in the study administered the survey, and respondents may have been affected by social desirability bias in how the survey questions were answered. Because investigators were not a part of the care team of any study patients, we believe this to be unlikely. Fourth, our study was conducted from October 8, 2013 to August 31, 2015 and the opioid epidemic is dynamic. Accordingly, our data may not reflect current opioid prescribing practices or patients’ current beliefs regarding pain control. Fifth, we did not collect demographic data on the patients who did not participate and could not look for systematic differences between participants and nonparticipants. Sixth, we relied on patients to self-report whether they were taking opioids prior to hospitalization or using illicit drugs. Seventh, we found comorbid mental health conditions to be more frequent in the US population studied. Previous work has shown regional variation in mental health conditions,^35,36 which could have affected our findings. To account for this, our models included psychiatric illness.

Our data suggest that physicians in the US may prescribe opioids more frequently during patients’ hospitalizations and at discharge than their colleagues in other countries. We also found that patient satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Although the small number of hospitals included in our sample coupled with the small sample size in some of the non-US countries limits the generalizability of our findings, the data suggest that reducing the opioid epidemic in the US may require addressing patients’ expectations regarding pain control in addition to providers’ inpatient analgesic prescribing patterns.

Disclosures

The authors report no conflicts of interest.

Funding

The authors report no funding source for this work.

Since 2000, the United States has seen a marked increase in opioid prescribing^1-3 and opioid-related complications, including overdoses, hospitalizations, and deaths.^2,4,5 A study from 2015 showed that more than one-third of the US civilian noninstitutionalized population reported receiving an opioid prescription in the prior year, with 12.5% reporting misuse, and, of those, 16.7% reported a prescription use disorder.⁶ While there has been a slight decrease in opioid prescriptions in the US since 2012, rates of opioid prescribing in 2015 were three times higher than in 1999 and approximately four times higher than in Europe in 2015.^3,7

Pain is commonly reported by hospitalized patients,^8,9 and opioids are often a mainstay of treatment;^9,10 however, treatment with opioids can have a number of adverse outcomes.^2,10,11 Short-term exposure to opioids can lead to long-term use,^12-16 and patients on opioids are at an increased risk for subsequent hospitalization and longer inpatient lengths of stay.⁵

Physician prescribing practices for opioids and patient expectations for pain control vary as a function of geographic region and culture,^10,12,17,18 and pain is influenced by the cultural context in which it occurs.^17,19-22 Treatment of pain may also be affected by limited access to or restrictions on selected medications, as well as by cultural biases.²³ Whether these variations in the treatment of pain are reflected in patients’ satisfaction with pain control is uncertain.

We sought to compare the inpatient analgesic prescribing practices and patients’ perceptions of pain control for medical patients in four teaching hospitals in the US and in seven teaching hospitals in seven other countries.

Study Design

We utilized a cross-sectional, observational design. The study was approved by the Institutional Review Boards at all participating sites.

Setting

The study was conducted at 11 academic hospitals in eight countries from October 8, 2013 to August 31, 2015. Sites in the US included Denver Health in Denver, Colorado; the University of Colorado Hospital in Aurora, Colorado; Hennepin Healthcare in Minneapolis, Minnesota; and Legacy Health in Portland, Oregon. Sites outside the US included McMaster University in Hamilton, Ontario, Canada; Hospital de la Santa Creu i Sant Pau, Universitat Autonòma de Barcelona in Barcelona, Spain; the University of Study of Milan and the University Ospedale “Luigi Sacco” in Milan, Italy, the National Taiwan University Hospital, in Taipei, Taiwan, the University of Ulsan College of Medicine, Asan Medical Center, in Seoul, Korea, the Imperial College, Chelsea and Westminster Hospital, in London, United Kingdom and Dunedin Hospital, Dunedin, New Zealand.

Inclusion and Exclusion Criteria

We included patients 18-89 years of age (20-89 in Taiwan because patients under 20 years of age in this country are a restricted group with respect to participating in research), admitted to an internal medicine service from the Emergency Department or Urgent Care clinic with an acute illness for a minimum of 24 hours (with time zero defined as the time care was initiated in the Emergency Department or Urgent Care Clinic), who reported pain at some time during the first 24-36 hours of their hospitalization and who provided informed consent. In the US, “admission” included both observation and inpatient status. We limited the patient population to those admitted via emergency departments and urgent care clinics in order to enroll similar patient populations across sites.

Scheduled admissions, patients transferred from an outside facility, patients admitted directly from a clinic, and those receiving care in intensive care units were excluded. We also excluded patients who were incarcerated, pregnant, those who received major surgery within the previous 14 days, those with a known diagnosis of active cancer, and those who were receiving palliative or hospice care. Patients receiving care from an investigator in the study at the time of enrollment were not eligible due to the potential conflict of interest.

Patient Screening

Primary teams were contacted to determine if any patients on their service might meet the criteria for inclusion in the study on preselected study days chosen on the basis of the research team’s availability. Identified patients were then screened to establish if they met the eligibility criteria. Patients were asked directly if they had experienced pain during their preadmission evaluation or during their hospitalization.

Data Collection

All patients were hospitalized at the time they gave consent and when data were collected. Data were collected via interviews with patients, as well as through chart review. We recorded patients’ age, gender, race, admitting diagnosis(es), length of stay, psychiatric illness, illicit drug use, whether they reported receiving opioid analgesics at the time of hospitalization, whether they were prescribed opioids and/or nonopioid analgesics during their hospitalization, the median and maximum doses of opioids prescribed and dispensed, and whether they were discharged on opioids. The question of illicit drug use was asked of all patients with the exception of those hospitalized in South Korea due to potential legal implications.

Opioid prescribing and receipt of opioids was recorded based upon current provider orders and medication administration records, respectively. Perception of and satisfaction with pain control was assessed with the American Pain Society Patient Outcome Questionnaire–Modified (APS-POQ-Modified).^24,25 Versions of this survey have been validated in English as well as in other languages and cultures.^26-28 Because hospitalization practices could differ across hospitals and in different countries, we compared patients’ severity of illness by using Charlson comorbidity scores. Consent forms and the APS-POQ were translated into each country’s primary language according to established processes.²⁹ The survey was filled out by having site investigators read questions aloud and by use of a large-font visual analog scale to aid patients’ verbal responses.

Data were collected and managed using a secure, web-based application electronic data capture tool (Research Electronic Data Capture [REDCap], Nashville, Tennessee), hosted at Denver Health.³⁰

Study Size

Preliminary data from the internal medicine units at our institution suggested that 40% of patients without cancer received opioid analgesics during their hospitalization. Assuming 90% power to detect an absolute difference in the proportion of inpatient medical patients who are receiving opioid analgesics during their hospital stay of 17%, a two-sided type 1 error rate of 0.05, six hospitals in the US, and nine hospitals from all other countries, we calculated an initial sample size of 150 patients per site. This sample size was considered feasible for enrollment in a busy inpatient clinical setting. Study end points were to either reach the goal number of patients (150 per site) or the predetermined study end date, whichever came first.

Data Analysis

We generated means with standard deviations (SDs) and medians with interquartile ranges (IQRs) for normally and nonnormally distributed continuous variables, respectively, and frequencies for categorical variables. We used linear mixed modeling for the analysis of continuous variables. For binary outcomes, our data were fitted to a generalized linear mixed model with logit as the link function and a binary distribution. For ordinal variables, specifically patient-reported satisfaction with pain control and the opinion statements, the data were fitted to a generalized linear mixed model with a cumulative logit link and a multinomial distribution. Hospital was included as a random effect in all models to account for patients cared for in the same hospital.

Country of origin, dichotomized as US or non-US, was the independent variable of interest for all models. An interaction term for exposure to opioids prior to admission and country was entered into all models to explore whether differences in the effect of country existed for patients who reported taking opioids prior to admission and those who did not.

The models for the frequency with which analgesics were given, doses of opioids given during hospitalization and at discharge, patient-reported pain score, and patient-reported satisfaction with pain control were adjusted for (1) age, (2) gender, (3) Charlson Comorbidity Index, (4) length of stay, (5) history of illicit drug use, (6) history of psychiatric illness, (7) daily dose in morphine milligram equivalents (MME) for opioids prior to admission, (8) average pain score, and (9) hospital. The patient-reported satisfaction with pain control model was also adjusted for whether or not opioids were given to the patient during their hospitalization. P < .05 was considered to indicate significance. All analyses were performed using SAS Enterprise Guide 7.1 (SAS Institute, Inc., Cary, North Carolina). We reported data on medications that were prescribed and dispensed (as opposed to just prescribed and not necessarily given). Opioids prescribed at discharge represented the total possible opioids that could be given based upon the order/prescription (eg, oxycodone 5 mg every 6 hours as needed for pain would be counted as 20 mg/24 hours maximum possible dose followed by conversion to MME).

Missing Data

When there were missing data, a query was sent to sites to verify if the data were retrievable. If retrievable, the data were then entered. Data were missing in 5% and 2% of patients who did or did not report taking an opioid prior to admission, respectively. If a variable was included in a specific statistical test, then subjects with missing data were excluded from that analysis (ie, complete case analysis).

We approached 1,309 eligible patients, of which 981 provided informed consent, for a response rate of 75%; 503 from the US and 478 patients from other countries (Figure). In unadjusted analyses, we found no significant differences between US and non-US patients in age (mean age 51, SD 15 vs 59, SD 19; P = .30), race, ethnicity, or Charlson comorbidity index scores (median 2, IQR 1-3 vs 3, IQR 1-4; P = .45). US patients had shorter lengths of stay (median 3 days, IQR 2-4 vs 6 days, IQR 3-11; P = .04), a more frequent history of illicit drug use (33% vs 6%; P = .003), a higher frequency of psychiatric illness (27% vs 8%; P < .0001), and more were receiving opioid analgesics prior to admission (38% vs 17%; P = .007) than those hospitalized in other countries (Table 1, Appendix 1). The primary admitting diagnoses for all patients in the study are listed in Appendix 2. Opioid prescribing practices across the individual sites are shown in Appendix 3.

Patients Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found that more patients in the US were given opioids during their hospitalization and in higher doses than patients from other countries and more were prescribed opioids at discharge. Fewer patients in the US were dispensed nonopioid analgesics during their hospitalization than patients from other countries, but this difference was not significant (Table 2). Appendix 4 shows the types of nonopioid pain medications prescribed in the US and other countries.

After adjustment for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys. We found no significant difference in satisfaction with pain control between patients from the US and other countries in the models, regardless of whether we included average pain score or opioid receipt during hospitalization in the model (Table 3).

In unadjusted analyses, compared with patients hospitalized in other countries, more patients in the US stated that they would like a stronger dose of analgesic if they were still in pain, though the difference was nonsignificant, and US patients were more likely to agree with the statement that people become addicted to pain medication easily and less likely to agree with the statement that it is easier to endure pain than deal with the side effects of pain medications (Table 3).

Patients Not Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found no significant difference in the proportion of US patients provided with nonopioid pain medications during their hospitalization compared with patients in other countries, but a greater percentage of US patients were given opioids during their hospitalization and at discharge and in higher doses (Table 2).

After adjusting for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys and greater pain severity in the 24-36 hours prior to completing the survey than patients from other countries, but we found no difference in patient satisfaction with pain control (Table 3). After we included the average pain score and whether or not opioids were given to the patient during their hospitalization in this model, patients in the US were more likely to report a higher level of satisfaction with pain control than patients in all other countries (P = .001).

Patient Satisfaction and Opioid Receipt

Among patients cared for in the US, after controlling for the average pain score, we did not find a significant association between receiving opioids while in the hospital and satisfaction with pain control for patients who either did or did not endorse taking opioids prior to admission (P = .38 and P = .24, respectively). Among patients cared for in all other countries, after controlling for the average pain score, we found a significant association between receiving opioids while in the hospital and a lower level of satisfaction with pain control for patients who reported taking opioids prior to admission (P = .02) but not for patients who did not report taking opioids prior to admission (P = .08).

Compared with patients hospitalized in other countries, a greater percentage of those hospitalized in the US were prescribed opioid analgesics both during hospitalization and at the time of discharge, even after adjustment for pain severity. In addition, patients hospitalized in the US reported greater pain severity at the time they completed their pain surveys and in the 24 to 36 hours prior to completing the survey than patients from other countries. In this sample, satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Our study also suggests that opioid receipt did not lead to improved patient satisfaction with pain control.

The frequency with which we observed opioid analgesics being prescribed during hospitalization in US hospitals (79%) was higher than the 51% of patients who received opioids reported by Herzig and colleagues.¹⁰ Patients in our study had a higher prevalence of illicit drug abuse and psychiatric illness, and our study only included patients who reported pain at some point during their hospitalization. We also studied prescribing practices through analysis of provider orders and medication administration records at the time the patient was hospitalized.

While we observed that physicians in the US more frequently prescribed opioid analgesics during hospitalizations than physicians working in other countries, we also observed that patients in the US reported higher levels of pain during their hospitalization. After adjusting for a number of variables, including pain severity, however, we still found that opioids were more commonly prescribed during hospitalizations by physicians working in the US sites studied than by physicians in the non-US sites.

Opioid prescribing practices varied across the sites sampled in our study. While the US sites, Taiwan, and Korea tended to be heavier utilizers of opioids during hospitalization, there were notable differences in discharge prescribing of opioids, with the US sites more commonly prescribing opioids and higher MME for patients who did not report taking opioids prior to their hospitalization (Appendix 3). A sensitivity analysis was conducted excluding South Korea from modeling, given that patients there were not asked about illicit opioid use. There were no important changes in the magnitude or direction of the results.

Our study supports previous studies indicating that there are cultural and societal differences when it comes to the experience of pain and the expectations around pain control.^17,20-22,31 Much of the focus on reducing opioid utilization has been on provider practices³² and on prescription drug monitoring programs.³³ Our findings suggest that another area of focus that may be important in mitigating the opioid epidemic is patient expectations of pain control.

Our study has a number of strengths. First, we included 11 hospitals from eight different countries. Second, we believe this is the first study to assess opioid prescribing and dispensing practices during hospitalization as well as at the time of discharge. Third, patient perceptions of pain control were assessed in conjunction with analgesic prescribing and were assessed during hospitalization. Fourth, we had high response rates for patient participation in our study. Fifth, we found much larger differences in opioid prescribing than anticipated, and thus, while we did not achieve the sample size originally planned for either the number of hospitals or patients enrolled per hospital, we were sufficiently powered. This is likely secondary to the fact that the population we studied was one that specifically reported pain, resulting in the larger differences seen.

Our study also had a number of limitations. First, the prescribing practices in countries other than the US are represented by only one hospital per country and, in some countries, by limited numbers of patients. While we studied four sites in the US, we did not have a site in the Northeast, a region previously shown to have lower prescribing rates.¹⁰ Additionally, patient samples for the US sites compared with the sites in other countries varied considerably with respect to ethnicity. While some studies in US patients have shown that opioid prescribing may vary based on race/ethnicity,³⁴ we are uncertain as to how this might impact a study that crosses multiple countries. We also had a low number of patients receiving opioids prior to hospitalization for several of the non-US countries, which reduced the power to detect differences in this subgroup. Previous research has shown that there are wide variations in prescribing practices even within countries;^10,12,18 therefore, caution should be taken when generalizing our findings. Second, we assessed analgesic prescribing patterns and pain control during the first 24 to 36 hours of hospitalization and did not consider hospital days beyond this timeframe with the exception of noting what medications were prescribed at discharge. We chose this methodology in an attempt to eliminate as many differences that might exist in the duration of hospitalization across many countries. Third, investigators in the study administered the survey, and respondents may have been affected by social desirability bias in how the survey questions were answered. Because investigators were not a part of the care team of any study patients, we believe this to be unlikely. Fourth, our study was conducted from October 8, 2013 to August 31, 2015 and the opioid epidemic is dynamic. Accordingly, our data may not reflect current opioid prescribing practices or patients’ current beliefs regarding pain control. Fifth, we did not collect demographic data on the patients who did not participate and could not look for systematic differences between participants and nonparticipants. Sixth, we relied on patients to self-report whether they were taking opioids prior to hospitalization or using illicit drugs. Seventh, we found comorbid mental health conditions to be more frequent in the US population studied. Previous work has shown regional variation in mental health conditions,^35,36 which could have affected our findings. To account for this, our models included psychiatric illness.

Our data suggest that physicians in the US may prescribe opioids more frequently during patients’ hospitalizations and at discharge than their colleagues in other countries. We also found that patient satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Although the small number of hospitals included in our sample coupled with the small sample size in some of the non-US countries limits the generalizability of our findings, the data suggest that reducing the opioid epidemic in the US may require addressing patients’ expectations regarding pain control in addition to providers’ inpatient analgesic prescribing patterns.

Disclosures

The authors report no conflicts of interest.

Funding

The authors report no funding source for this work.

Since 2000, the United States has seen a marked increase in opioid prescribing^1-3 and opioid-related complications, including overdoses, hospitalizations, and deaths.^2,4,5 A study from 2015 showed that more than one-third of the US civilian noninstitutionalized population reported receiving an opioid prescription in the prior year, with 12.5% reporting misuse, and, of those, 16.7% reported a prescription use disorder.⁶ While there has been a slight decrease in opioid prescriptions in the US since 2012, rates of opioid prescribing in 2015 were three times higher than in 1999 and approximately four times higher than in Europe in 2015.^3,7

Pain is commonly reported by hospitalized patients,^8,9 and opioids are often a mainstay of treatment;^9,10 however, treatment with opioids can have a number of adverse outcomes.^2,10,11 Short-term exposure to opioids can lead to long-term use,^12-16 and patients on opioids are at an increased risk for subsequent hospitalization and longer inpatient lengths of stay.⁵

Physician prescribing practices for opioids and patient expectations for pain control vary as a function of geographic region and culture,^10,12,17,18 and pain is influenced by the cultural context in which it occurs.^17,19-22 Treatment of pain may also be affected by limited access to or restrictions on selected medications, as well as by cultural biases.²³ Whether these variations in the treatment of pain are reflected in patients’ satisfaction with pain control is uncertain.

We sought to compare the inpatient analgesic prescribing practices and patients’ perceptions of pain control for medical patients in four teaching hospitals in the US and in seven teaching hospitals in seven other countries.

Study Design

We utilized a cross-sectional, observational design. The study was approved by the Institutional Review Boards at all participating sites.

Setting

The study was conducted at 11 academic hospitals in eight countries from October 8, 2013 to August 31, 2015. Sites in the US included Denver Health in Denver, Colorado; the University of Colorado Hospital in Aurora, Colorado; Hennepin Healthcare in Minneapolis, Minnesota; and Legacy Health in Portland, Oregon. Sites outside the US included McMaster University in Hamilton, Ontario, Canada; Hospital de la Santa Creu i Sant Pau, Universitat Autonòma de Barcelona in Barcelona, Spain; the University of Study of Milan and the University Ospedale “Luigi Sacco” in Milan, Italy, the National Taiwan University Hospital, in Taipei, Taiwan, the University of Ulsan College of Medicine, Asan Medical Center, in Seoul, Korea, the Imperial College, Chelsea and Westminster Hospital, in London, United Kingdom and Dunedin Hospital, Dunedin, New Zealand.

Inclusion and Exclusion Criteria

We included patients 18-89 years of age (20-89 in Taiwan because patients under 20 years of age in this country are a restricted group with respect to participating in research), admitted to an internal medicine service from the Emergency Department or Urgent Care clinic with an acute illness for a minimum of 24 hours (with time zero defined as the time care was initiated in the Emergency Department or Urgent Care Clinic), who reported pain at some time during the first 24-36 hours of their hospitalization and who provided informed consent. In the US, “admission” included both observation and inpatient status. We limited the patient population to those admitted via emergency departments and urgent care clinics in order to enroll similar patient populations across sites.

Scheduled admissions, patients transferred from an outside facility, patients admitted directly from a clinic, and those receiving care in intensive care units were excluded. We also excluded patients who were incarcerated, pregnant, those who received major surgery within the previous 14 days, those with a known diagnosis of active cancer, and those who were receiving palliative or hospice care. Patients receiving care from an investigator in the study at the time of enrollment were not eligible due to the potential conflict of interest.

Patient Screening

Primary teams were contacted to determine if any patients on their service might meet the criteria for inclusion in the study on preselected study days chosen on the basis of the research team’s availability. Identified patients were then screened to establish if they met the eligibility criteria. Patients were asked directly if they had experienced pain during their preadmission evaluation or during their hospitalization.

Data Collection

All patients were hospitalized at the time they gave consent and when data were collected. Data were collected via interviews with patients, as well as through chart review. We recorded patients’ age, gender, race, admitting diagnosis(es), length of stay, psychiatric illness, illicit drug use, whether they reported receiving opioid analgesics at the time of hospitalization, whether they were prescribed opioids and/or nonopioid analgesics during their hospitalization, the median and maximum doses of opioids prescribed and dispensed, and whether they were discharged on opioids. The question of illicit drug use was asked of all patients with the exception of those hospitalized in South Korea due to potential legal implications.

Opioid prescribing and receipt of opioids was recorded based upon current provider orders and medication administration records, respectively. Perception of and satisfaction with pain control was assessed with the American Pain Society Patient Outcome Questionnaire–Modified (APS-POQ-Modified).^24,25 Versions of this survey have been validated in English as well as in other languages and cultures.^26-28 Because hospitalization practices could differ across hospitals and in different countries, we compared patients’ severity of illness by using Charlson comorbidity scores. Consent forms and the APS-POQ were translated into each country’s primary language according to established processes.²⁹ The survey was filled out by having site investigators read questions aloud and by use of a large-font visual analog scale to aid patients’ verbal responses.

Data were collected and managed using a secure, web-based application electronic data capture tool (Research Electronic Data Capture [REDCap], Nashville, Tennessee), hosted at Denver Health.³⁰

Study Size

Preliminary data from the internal medicine units at our institution suggested that 40% of patients without cancer received opioid analgesics during their hospitalization. Assuming 90% power to detect an absolute difference in the proportion of inpatient medical patients who are receiving opioid analgesics during their hospital stay of 17%, a two-sided type 1 error rate of 0.05, six hospitals in the US, and nine hospitals from all other countries, we calculated an initial sample size of 150 patients per site. This sample size was considered feasible for enrollment in a busy inpatient clinical setting. Study end points were to either reach the goal number of patients (150 per site) or the predetermined study end date, whichever came first.

Data Analysis

We generated means with standard deviations (SDs) and medians with interquartile ranges (IQRs) for normally and nonnormally distributed continuous variables, respectively, and frequencies for categorical variables. We used linear mixed modeling for the analysis of continuous variables. For binary outcomes, our data were fitted to a generalized linear mixed model with logit as the link function and a binary distribution. For ordinal variables, specifically patient-reported satisfaction with pain control and the opinion statements, the data were fitted to a generalized linear mixed model with a cumulative logit link and a multinomial distribution. Hospital was included as a random effect in all models to account for patients cared for in the same hospital.

Country of origin, dichotomized as US or non-US, was the independent variable of interest for all models. An interaction term for exposure to opioids prior to admission and country was entered into all models to explore whether differences in the effect of country existed for patients who reported taking opioids prior to admission and those who did not.

The models for the frequency with which analgesics were given, doses of opioids given during hospitalization and at discharge, patient-reported pain score, and patient-reported satisfaction with pain control were adjusted for (1) age, (2) gender, (3) Charlson Comorbidity Index, (4) length of stay, (5) history of illicit drug use, (6) history of psychiatric illness, (7) daily dose in morphine milligram equivalents (MME) for opioids prior to admission, (8) average pain score, and (9) hospital. The patient-reported satisfaction with pain control model was also adjusted for whether or not opioids were given to the patient during their hospitalization. P < .05 was considered to indicate significance. All analyses were performed using SAS Enterprise Guide 7.1 (SAS Institute, Inc., Cary, North Carolina). We reported data on medications that were prescribed and dispensed (as opposed to just prescribed and not necessarily given). Opioids prescribed at discharge represented the total possible opioids that could be given based upon the order/prescription (eg, oxycodone 5 mg every 6 hours as needed for pain would be counted as 20 mg/24 hours maximum possible dose followed by conversion to MME).

Missing Data

When there were missing data, a query was sent to sites to verify if the data were retrievable. If retrievable, the data were then entered. Data were missing in 5% and 2% of patients who did or did not report taking an opioid prior to admission, respectively. If a variable was included in a specific statistical test, then subjects with missing data were excluded from that analysis (ie, complete case analysis).

We approached 1,309 eligible patients, of which 981 provided informed consent, for a response rate of 75%; 503 from the US and 478 patients from other countries (Figure). In unadjusted analyses, we found no significant differences between US and non-US patients in age (mean age 51, SD 15 vs 59, SD 19; P = .30), race, ethnicity, or Charlson comorbidity index scores (median 2, IQR 1-3 vs 3, IQR 1-4; P = .45). US patients had shorter lengths of stay (median 3 days, IQR 2-4 vs 6 days, IQR 3-11; P = .04), a more frequent history of illicit drug use (33% vs 6%; P = .003), a higher frequency of psychiatric illness (27% vs 8%; P < .0001), and more were receiving opioid analgesics prior to admission (38% vs 17%; P = .007) than those hospitalized in other countries (Table 1, Appendix 1). The primary admitting diagnoses for all patients in the study are listed in Appendix 2. Opioid prescribing practices across the individual sites are shown in Appendix 3.

Patients Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found that more patients in the US were given opioids during their hospitalization and in higher doses than patients from other countries and more were prescribed opioids at discharge. Fewer patients in the US were dispensed nonopioid analgesics during their hospitalization than patients from other countries, but this difference was not significant (Table 2). Appendix 4 shows the types of nonopioid pain medications prescribed in the US and other countries.

After adjustment for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys. We found no significant difference in satisfaction with pain control between patients from the US and other countries in the models, regardless of whether we included average pain score or opioid receipt during hospitalization in the model (Table 3).

In unadjusted analyses, compared with patients hospitalized in other countries, more patients in the US stated that they would like a stronger dose of analgesic if they were still in pain, though the difference was nonsignificant, and US patients were more likely to agree with the statement that people become addicted to pain medication easily and less likely to agree with the statement that it is easier to endure pain than deal with the side effects of pain medications (Table 3).

Patients Not Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found no significant difference in the proportion of US patients provided with nonopioid pain medications during their hospitalization compared with patients in other countries, but a greater percentage of US patients were given opioids during their hospitalization and at discharge and in higher doses (Table 2).

After adjusting for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys and greater pain severity in the 24-36 hours prior to completing the survey than patients from other countries, but we found no difference in patient satisfaction with pain control (Table 3). After we included the average pain score and whether or not opioids were given to the patient during their hospitalization in this model, patients in the US were more likely to report a higher level of satisfaction with pain control than patients in all other countries (P = .001).

Patient Satisfaction and Opioid Receipt

Among patients cared for in the US, after controlling for the average pain score, we did not find a significant association between receiving opioids while in the hospital and satisfaction with pain control for patients who either did or did not endorse taking opioids prior to admission (P = .38 and P = .24, respectively). Among patients cared for in all other countries, after controlling for the average pain score, we found a significant association between receiving opioids while in the hospital and a lower level of satisfaction with pain control for patients who reported taking opioids prior to admission (P = .02) but not for patients who did not report taking opioids prior to admission (P = .08).

Compared with patients hospitalized in other countries, a greater percentage of those hospitalized in the US were prescribed opioid analgesics both during hospitalization and at the time of discharge, even after adjustment for pain severity. In addition, patients hospitalized in the US reported greater pain severity at the time they completed their pain surveys and in the 24 to 36 hours prior to completing the survey than patients from other countries. In this sample, satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Our study also suggests that opioid receipt did not lead to improved patient satisfaction with pain control.

The frequency with which we observed opioid analgesics being prescribed during hospitalization in US hospitals (79%) was higher than the 51% of patients who received opioids reported by Herzig and colleagues.¹⁰ Patients in our study had a higher prevalence of illicit drug abuse and psychiatric illness, and our study only included patients who reported pain at some point during their hospitalization. We also studied prescribing practices through analysis of provider orders and medication administration records at the time the patient was hospitalized.

While we observed that physicians in the US more frequently prescribed opioid analgesics during hospitalizations than physicians working in other countries, we also observed that patients in the US reported higher levels of pain during their hospitalization. After adjusting for a number of variables, including pain severity, however, we still found that opioids were more commonly prescribed during hospitalizations by physicians working in the US sites studied than by physicians in the non-US sites.

Opioid prescribing practices varied across the sites sampled in our study. While the US sites, Taiwan, and Korea tended to be heavier utilizers of opioids during hospitalization, there were notable differences in discharge prescribing of opioids, with the US sites more commonly prescribing opioids and higher MME for patients who did not report taking opioids prior to their hospitalization (Appendix 3). A sensitivity analysis was conducted excluding South Korea from modeling, given that patients there were not asked about illicit opioid use. There were no important changes in the magnitude or direction of the results.

Our study supports previous studies indicating that there are cultural and societal differences when it comes to the experience of pain and the expectations around pain control.^17,20-22,31 Much of the focus on reducing opioid utilization has been on provider practices³² and on prescription drug monitoring programs.³³ Our findings suggest that another area of focus that may be important in mitigating the opioid epidemic is patient expectations of pain control.

Our study has a number of strengths. First, we included 11 hospitals from eight different countries. Second, we believe this is the first study to assess opioid prescribing and dispensing practices during hospitalization as well as at the time of discharge. Third, patient perceptions of pain control were assessed in conjunction with analgesic prescribing and were assessed during hospitalization. Fourth, we had high response rates for patient participation in our study. Fifth, we found much larger differences in opioid prescribing than anticipated, and thus, while we did not achieve the sample size originally planned for either the number of hospitals or patients enrolled per hospital, we were sufficiently powered. This is likely secondary to the fact that the population we studied was one that specifically reported pain, resulting in the larger differences seen.

Our study also had a number of limitations. First, the prescribing practices in countries other than the US are represented by only one hospital per country and, in some countries, by limited numbers of patients. While we studied four sites in the US, we did not have a site in the Northeast, a region previously shown to have lower prescribing rates.¹⁰ Additionally, patient samples for the US sites compared with the sites in other countries varied considerably with respect to ethnicity. While some studies in US patients have shown that opioid prescribing may vary based on race/ethnicity,³⁴ we are uncertain as to how this might impact a study that crosses multiple countries. We also had a low number of patients receiving opioids prior to hospitalization for several of the non-US countries, which reduced the power to detect differences in this subgroup. Previous research has shown that there are wide variations in prescribing practices even within countries;^10,12,18 therefore, caution should be taken when generalizing our findings. Second, we assessed analgesic prescribing patterns and pain control during the first 24 to 36 hours of hospitalization and did not consider hospital days beyond this timeframe with the exception of noting what medications were prescribed at discharge. We chose this methodology in an attempt to eliminate as many differences that might exist in the duration of hospitalization across many countries. Third, investigators in the study administered the survey, and respondents may have been affected by social desirability bias in how the survey questions were answered. Because investigators were not a part of the care team of any study patients, we believe this to be unlikely. Fourth, our study was conducted from October 8, 2013 to August 31, 2015 and the opioid epidemic is dynamic. Accordingly, our data may not reflect current opioid prescribing practices or patients’ current beliefs regarding pain control. Fifth, we did not collect demographic data on the patients who did not participate and could not look for systematic differences between participants and nonparticipants. Sixth, we relied on patients to self-report whether they were taking opioids prior to hospitalization or using illicit drugs. Seventh, we found comorbid mental health conditions to be more frequent in the US population studied. Previous work has shown regional variation in mental health conditions,^35,36 which could have affected our findings. To account for this, our models included psychiatric illness.

Our data suggest that physicians in the US may prescribe opioids more frequently during patients’ hospitalizations and at discharge than their colleagues in other countries. We also found that patient satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Although the small number of hospitals included in our sample coupled with the small sample size in some of the non-US countries limits the generalizability of our findings, the data suggest that reducing the opioid epidemic in the US may require addressing patients’ expectations regarding pain control in addition to providers’ inpatient analgesic prescribing patterns.

Disclosures

The authors report no conflicts of interest.

Funding

The authors report no funding source for this work.

Intravenous (IV) antibiotics are commonly used in hospitalized pediatric patients to treat bacterial infections. Antimicrobial stewardship guidelines published by the Infectious Diseases Society of America (IDSA) recommend institutions develop a systematic plan to convert from IV to enteral antibiotics, as early transition may reduce healthcare costs, decrease length of stay (LOS), and avoid prolonged IV access complications¹ such as extravasation, thrombosis, and catheter-associated infections.^2-5

Pediatric patients with community-acquired pneumonia (CAP) and mild skin and soft tissue infections (SSTI) may not require IV antibiotics, even if the patient is hospitalized.⁶ Although national guidelines for pediatric CAP and SSTI recommend IV antibiotics for hospitalized patients, these guidelines state that mild infections may be treated with enteral antibiotics and emphasize discontinuation of IV antibiotics when the patient meets discharge criteria.^7,8 Furthermore, several enteral antibiotics used for the treatment of CAP and SSTI, such as cephalexin and clindamycin,⁹ have excellent bioavailability (>90%) or can achieve sufficient concentrations to attain the pharmacodynamic target (ie, amoxicillin and trimethoprim–sulfamethoxazole).^10,11 Nonetheless, the guidelines do not explicitly outline criteria regarding the transition from IV to enteral antibiotics.^7,8

At our institution, patients admitted to Hospital Medicine (HM) often remained on IV antibiotics until discharge. Data review revealed that antibiotic treatment of CAP and SSTI posed the greatest opportunity for early conversion to enteral therapy based on the high frequency of admissions and the ability of commonly used enteral antibiotics to attain pharmacodynamic targets. We sought to change practice culture by decoupling transition to enteral antibiotics from discharge and use administration of other enteral medications as an objective indicator for transition. Our aim was to increase the proportion of enterally administered antibiotic doses for HM patients aged >60 days admitted with uncomplicated CAP or SSTI from 44% to 75% in eight months.

Context

Cincinnati Children’s Hospital Medical Center (CCHMC) is a large, urban, academic hospital. The HM division has 45 attendings and admits >8,000 general pediatric patients annually. The five HM teams at the main campus consist of attendings, fellows, residents, and medical students. One HM team serves as the resident quality improvement (QI) team where residents collaborate in a longitudinal study under the guidance of QI-trained coaches. The focus of this QI initiative was determined by resident consensus and aligned with a high-value care curriculum.¹²

To identify the target patient population, we investigated IV antimicrobials frequently used in HM patients. Ampicillin and clindamycin are commonly used IV antibiotics, most frequently corresponding with the diagnoses of CAP and SSTI, respectively, accounting for half of all antibiotic use on the HM service. Amoxicillin, the enteral equivalent of ampicillin, can achieve sufficient concentrations to attain the pharmacodynamic target at infection sites, and clindamycin has high bioavailability, making them ideal options for early transition. Our institution’s robust antimicrobial stewardship program has published local guidelines on using amoxicillin as the enteral antibiotic of choice for uncomplicated CAP, but it does not provide guidance on the timing of transition for either CAP or SSTI; the clinical team makes this decision.

HM attendings were surveyed to determine the criteria used to transition from IV to enteral antibiotics for patients with CAP or SSTI. The survey illustrated practice variability with providers using differing clinical criteria to signal the timing of transition. Additionally, only 49% of respondents (n = 37) rated themselves as “very comfortable” with residents making autonomous decisions to transition to enteral antibiotics. We chose to use the administration of other enteral medications, instead of discharge readiness, as an objective indicator of a patient’s readiness to transition to enteral antibiotics, given the low-risk patient population and the ability of the enteral antibiotics commonly used for CAP and SSTI to achieve pharmacodynamic targets.

The study population included patients aged >60 days admitted to HM with CAP or SSTI treated with any antibiotic. We excluded patients with potential complications or significant progression of their disease process, including patients with parapneumonic effusions or chest tubes, patients who underwent bronchoscopy, and patients with osteomyelitis, septic arthritis, or preseptal or orbital cellulitis. Past medical history and clinical status on admission were not used to exclude patients.

Interventions

Our multidisciplinary team, formed in January 2017, included HM attendings, HM fellows, pediatric residents, a critical care attending, a pharmacy resident, and an antimicrobial stewardship pharmacist. Under the guidance of QI coaches, the residents on the HM QI team developed and tested all interventions on their team and then determined which interventions would spread to the other four teams. The nursing director of our primary HM unit disseminated project updates to bedside nurses. A simplified failure mode and effects analysis identified areas for improvement and potential interventions. Interventions focused on the following key drivers (Figure 1): increased prescriber awareness of medication charge, standardization of conversion from IV to enteral antibiotics, clear definition of the patients ready for transition, ongoing evaluation of the antimicrobial plan, timely recognition by prescribers of patients ready for transition, culture shift regarding the appropriate administration route in the inpatient setting, and transparency of data. The team implemented sequential Plan-Do-Study-Act (PDSA) cycles¹³ to test the interventions.

Charge Table

To improve knowledge about the increased charge for commonly used IV medications compared with enteral formulations, a table comparing relative charges was shared during monthly resident morning conferences and at an HM faculty meeting. The table included charge comparisons between ampicillin and amoxicillin and IV and enteral clindamycin.

Standardized Language in Electronic Health Record (EHR) Antibiotic Plan on Rounds

Standardized language to document antibiotic transition plans was added to admission and progress note templates in the EHR. The standard template prompted residents to (1) define clinical transition criteria, (2) discuss attending comfort with transition overnight (based on survey results), and (3) document patient preference of solid or liquid dosage forms. Plans were reviewed and updated daily. We hypothesized that since residents use the information in the daily progress notes, including assessments and plans, to present on rounds, inclusion of the transition criteria in the note would prompt transition plan discussions.

Communication Bundle

To promote early transition to enteral antibiotics, we standardized the discussion about antibiotic transition between residents and attendings. During a weekly preexisting meeting, the resident QI team reviewed preferences for transitions with the new service attending. By identifying attending preferences early, residents were able to proactively transition patients who met the criteria (eg, antibiotic transition in the evening instead of waiting until morning rounds). This discussion also provided an opportunity to engage service attendings in the QI efforts, which were also shared at HM faculty meetings quarterly.

Recognizing that in times of high census, discussion of patient plans may be abbreviated during rounds, residents were asked to identify all patients on IV antibiotics while reviewing patient medication orders prior to rounds. As part of an existing daily prerounds huddle to discuss rounding logistics, residents listed all patients on IV antibiotics and discussed which patients were ready for transition. If patients could not be transitioned immediately, the team identified the transition criteria.

At preexisting evening huddles between overnight shift HM residents and the evening HM attending, residents identified patients who were prescribed IV antibiotics and discussed readiness for enteral transition. If a patient could be transitioned overnight, enteral antibiotic orders were placed. Overnight residents were also encouraged to review the transition criteria with families upon admission.

Real-time Identification of Failures and Feedback

For two weeks, the EHR was queried daily to identify patients admitted for uncomplicated CAP and SSTI who were on antibiotics as well as other enteral medications. A failure was defined as an IV antibiotic dose given to a patient who was administered any enteral medication. Residents on the QI team approached residents on other HM teams whenever patients were identified as a failed transition to learn about failure reasons.

Study of the Interventions

Data for HM patients who met the inclusion criteria were collected weekly from January 2016 through June 2018 via EHR query. We initially searched for diagnoses that fit under the disease categories of pneumonia and SSTI in the EHR, which generated a list of International Classification of Disease-9 and -10 Diagnosis codes (Appendix Figure 1). The query identified patients based on these codes and reported whether the identified patients took a dose of any enteral medication, excluding nystatin, sildenafil, tacrolimus, and mouthwashes, which are commonly continued during NPO status due to no need for absorption or limited parenteral options. It also reported the ordered route of administration for the queried antibiotics (Appendix Figure 1).

The 2016 calendar year established our baseline to account for seasonal variability. Data were reported weekly and reviewed to evaluate the impact of PDSA cycles and inform new interventions.

Measures

Our process measure was the total number of enteral antibiotic doses divided by all antibiotic doses in patients receiving any enteral medication. We reasoned that if patients were well enough to take medications enterally, they could be given an enteral antibiotic that is highly bioavailable or readily achieves concentrations that attain pharmacodynamic targets. This practice change was a culture shift, decoupling the switch to enteral antibiotics from discharge readiness. Our EHR query reported only the antibiotic doses given to patients who took an enteral medication on the day of antibiotic administration and excluded patients who received only IV medications.

Outcome measures included antimicrobial costs per patient encounter using average wholesale prices, which were reported in our EHR query, and LOS. To ensure that transitions of IV to enteral antibiotics were not negatively impacting patient outcomes, patient readmissions within seven days served as a balancing measure.

Analysis

An annotated statistical process control p-chart tracked the impact of interventions on the proportion of antibiotic doses that were enterally administered during hospitalization. An x-bar and an s-chart tracked the impact of interventions on antimicrobial costs per patient encounter and on LOS. A p-chart and an encounters-between g-chart were used to evaluate the impact of our interventions on readmissions. Control chart rules for identifying special cause were used for center line shifts.¹⁴

Ethical Considerations

This study was part of a larger study of the residency high-value care curriculum,¹² which was deemed exempt by the CCHMC IRB.

The baseline data collected included 372 patients and the postintervention period in 2017 included 326 patients (Table). Approximately two-thirds of patients had a diagnosis of CAP.

The percentage of antibiotic doses given enterally increased from 44% to 80% within eight months (Figure 2). When studying the impact of interventions, residents on the HM QI team found that the standard EHR template added to daily notes did not consistently prompt residents to discuss antibiotic plans and thus was abandoned. Initial improvement coincided with standardizing discussions between residents and attendings regarding transitions. Furthermore, discussion of all patients on IV antibiotics during the prerounds huddle allowed for reliable, daily communication about antibiotic plans and was subsequently spread to and adopted by all HM teams. The percentage of enterally administered antibiotic doses increased to >75% after the evening huddle, which involved all HM teams, and real-time identification of failures on all HM teams with provider feedback. Despite variability when the total number of antibiotic doses prescribed per week was low (<10), we demonstrated sustainability for 11 months (Figure 2), during which the prerounds and evening huddle discussions were continued and an updated control chart was shown monthly to residents during their educational conferences.

Summary

Using improvement science, we promoted earlier transition to enteral antibiotics for children hospitalized with uncomplicated CAP and SSTI by linking the decision for transition to the ability to take other enteral medications, rather than to discharge readiness. We increased the percentage of enterally administered antibiotic doses in this patient population from 44% to 80% in eight months. Although we did not observe a decrease in LOS as previously noted in a cost analysis study comparing pediatric patients with CAP treated with oral antibiotics versus those treated with IV antibiotics,¹⁵ we did find a decrease in LOS variability and in antimicrobial costs to our patients. These cost savings did not include potential savings from nursing or pharmacy labor. In addition, we noted a decrease in the variability in antibiotic prescribing practice, which demonstrates provider ability and willingness to couple antibiotic route transition to an objective characteristic (administration of other enteral medications).

A strength of our study was that residents, the most frequent prescribers of antibiotics on our HM service, were highly involved in the QI initiative, including defining the SMART aim, identifying key drivers, developing interventions, and completing sequential PDSA cycles. Under the guidance of QI-trained coaches, residents developed feasible interventions and assessed their success in real time. Consistent with other studies,^16,17 resident buy-in and involvement led to the success of our improvement study.

Interpretation

Despite emerging evidence regarding the timing of transition to enteral antibiotics, several factors impeded early transition at our institution, including physician culture, variable practice habits, and hospital workflow. Evidence supports the use of enteral antibiotics in immunocompetent children hospitalized for uncomplicated CAP who do not have chronic lung disease, are not in shock, and have oxygen saturations >85%.⁶ Although existing literature suggests that in pediatric patients admitted for SSTIs not involving the eye or bone, IV antibiotics may be transitioned when clinical improvement, evidenced by a reduction in fever or erythema, is noted,⁶ enteral antibiotics that achieve appropriate concentrations to attain pharmacodynamic targets should have the same efficacy as that of IV antibiotics.⁹ Using the criterion of administration of any medication enterally to identify a patient’s readiness to transition, we were able to overcome practice variation among providers who may have differing opinions of what constitutes clinical improvement. Of note, new evidence is emerging on predictors of enteral antibiotic treatment failure in patients with CAP and SSTI to guide transition timing, but these studies have largely focused on the adult population or were performed in the outpatient and emergency department (ED) settings.^18,19 Regardless, the stable number of encounters between readmissions in our patient population likely indicates that treatment failure in these patients was rare.

Rising healthcare costs have led to concerns around sustainability of the healthcare system;^20,21 tackling overuse in clinical practice, as in our study, is one mitigation strategy. Several studies have used QI methods to facilitate the provision of high-value care through the decrease of continuous monitor overuse and extraneous ordering of electrolytes.^22,23 Our QI study adds to the high-value care literature by safely decreasing the use of IV antibiotics. One retrospective study demonstrated that a one-day decrease in the use of IV antibiotics in pneumonia resulted in decreased costs without an increase in readmissions, similar to our findings.²⁴ In adults, QI initiatives aimed at improving early transition of antibiotics utilized electronic trigger tools.^25,26 Fischer et al. used active orders for scheduled enteral medications or an enteral diet as indication that a patient’s IV medications could be converted to enteral form.²⁶

Our work is not without limitations. The list of ICD-9 and -10 codes used to query the EHR did not capture all diagnoses that would be considered as uncomplicated CAP or SSTI. However, we included an extensive list of diagnoses to ensure that the majority of patients meeting our inclusion criteria were captured. Our process measure did not account for patients on IV antibiotics who were not administered other enteral medications but tolerating an enteral diet. These patients were not identified in our EHR query and were not included in our process measure as a failure. However, in latter interventions, residents identified all patients on IV antibiotics, so that patients not identified by our EHR query benefited from our work. Furthermore, this QI study was conducted at a single institution and several interventions took advantage of preexisting structured huddles and a resident QI curriculum, which may not exist at other institutions. Our study does highlight that engaging frontline providers, such as residents, to review antibiotic orders consistently and question the appropriateness of the administration route is key to making incremental changes in prescribing practices.

Through a partnership between HM and Pharmacy and with substantial resident involvement, we improved the transition of IV antibiotics in patients with CAP or SSTI by increasing the percentage of enterally administered antibiotic doses and reducing antimicrobial costs and variability in antibiotic prescribing practices. This work illustrates how reducing overuse of IV antibiotics promotes high-value care and aligns with initiatives to prevent avoidable harm.²⁷ Our work highlights that standardized discussions about medication orders to create consensus around enteral antibiotic transitions, real-time feedback, and challenging the status quo can influence practice habits and effect change.

Next steps include testing automated methods to notify providers of opportunities for transition from IV to enteral antibiotics through embedded clinical decision support, a method similar to the electronic trigger tools used in adult QI studies.^25,26 Since our prerounds huddle includes identifying all patients on IV antibiotics, studying the transition to enteral antibiotics and its effect on prescribing practices in other diagnoses (ie, urinary tract infection and osteomyelitis) may contribute to spreading these efforts. Partnering with our ED colleagues may be an important next step, as several patients admitted to HM on IV antibiotics are given their first dose in the ED.

Acknowledgments

The authors would like to thank the faculty of the James M. Anderson Center for Health Systems Excellence Intermediate Improvement Science Series for their guidance in the planning of this project. The authors would also like to thank Ms. Ursula Bradshaw and Mr. Michael Ponti-Zins for obtaining the hospital data on length of stay and readmissions. The authors acknowledge Dr. Philip Hagedorn for his assistance with the software that queries the electronic health record and Dr. Laura Brower and Dr. Joanna Thomson for their assistance with statistical analysis. The authors are grateful to all the residents and coaches on the QI Hospital Medicine team who contributed ideas on study design and interventions.

Intravenous (IV) antibiotics are commonly used in hospitalized pediatric patients to treat bacterial infections. Antimicrobial stewardship guidelines published by the Infectious Diseases Society of America (IDSA) recommend institutions develop a systematic plan to convert from IV to enteral antibiotics, as early transition may reduce healthcare costs, decrease length of stay (LOS), and avoid prolonged IV access complications¹ such as extravasation, thrombosis, and catheter-associated infections.^2-5

Pediatric patients with community-acquired pneumonia (CAP) and mild skin and soft tissue infections (SSTI) may not require IV antibiotics, even if the patient is hospitalized.⁶ Although national guidelines for pediatric CAP and SSTI recommend IV antibiotics for hospitalized patients, these guidelines state that mild infections may be treated with enteral antibiotics and emphasize discontinuation of IV antibiotics when the patient meets discharge criteria.^7,8 Furthermore, several enteral antibiotics used for the treatment of CAP and SSTI, such as cephalexin and clindamycin,⁹ have excellent bioavailability (>90%) or can achieve sufficient concentrations to attain the pharmacodynamic target (ie, amoxicillin and trimethoprim–sulfamethoxazole).^10,11 Nonetheless, the guidelines do not explicitly outline criteria regarding the transition from IV to enteral antibiotics.^7,8

At our institution, patients admitted to Hospital Medicine (HM) often remained on IV antibiotics until discharge. Data review revealed that antibiotic treatment of CAP and SSTI posed the greatest opportunity for early conversion to enteral therapy based on the high frequency of admissions and the ability of commonly used enteral antibiotics to attain pharmacodynamic targets. We sought to change practice culture by decoupling transition to enteral antibiotics from discharge and use administration of other enteral medications as an objective indicator for transition. Our aim was to increase the proportion of enterally administered antibiotic doses for HM patients aged >60 days admitted with uncomplicated CAP or SSTI from 44% to 75% in eight months.

Context

Cincinnati Children’s Hospital Medical Center (CCHMC) is a large, urban, academic hospital. The HM division has 45 attendings and admits >8,000 general pediatric patients annually. The five HM teams at the main campus consist of attendings, fellows, residents, and medical students. One HM team serves as the resident quality improvement (QI) team where residents collaborate in a longitudinal study under the guidance of QI-trained coaches. The focus of this QI initiative was determined by resident consensus and aligned with a high-value care curriculum.¹²

To identify the target patient population, we investigated IV antimicrobials frequently used in HM patients. Ampicillin and clindamycin are commonly used IV antibiotics, most frequently corresponding with the diagnoses of CAP and SSTI, respectively, accounting for half of all antibiotic use on the HM service. Amoxicillin, the enteral equivalent of ampicillin, can achieve sufficient concentrations to attain the pharmacodynamic target at infection sites, and clindamycin has high bioavailability, making them ideal options for early transition. Our institution’s robust antimicrobial stewardship program has published local guidelines on using amoxicillin as the enteral antibiotic of choice for uncomplicated CAP, but it does not provide guidance on the timing of transition for either CAP or SSTI; the clinical team makes this decision.

HM attendings were surveyed to determine the criteria used to transition from IV to enteral antibiotics for patients with CAP or SSTI. The survey illustrated practice variability with providers using differing clinical criteria to signal the timing of transition. Additionally, only 49% of respondents (n = 37) rated themselves as “very comfortable” with residents making autonomous decisions to transition to enteral antibiotics. We chose to use the administration of other enteral medications, instead of discharge readiness, as an objective indicator of a patient’s readiness to transition to enteral antibiotics, given the low-risk patient population and the ability of the enteral antibiotics commonly used for CAP and SSTI to achieve pharmacodynamic targets.

The study population included patients aged >60 days admitted to HM with CAP or SSTI treated with any antibiotic. We excluded patients with potential complications or significant progression of their disease process, including patients with parapneumonic effusions or chest tubes, patients who underwent bronchoscopy, and patients with osteomyelitis, septic arthritis, or preseptal or orbital cellulitis. Past medical history and clinical status on admission were not used to exclude patients.

Interventions

Our multidisciplinary team, formed in January 2017, included HM attendings, HM fellows, pediatric residents, a critical care attending, a pharmacy resident, and an antimicrobial stewardship pharmacist. Under the guidance of QI coaches, the residents on the HM QI team developed and tested all interventions on their team and then determined which interventions would spread to the other four teams. The nursing director of our primary HM unit disseminated project updates to bedside nurses. A simplified failure mode and effects analysis identified areas for improvement and potential interventions. Interventions focused on the following key drivers (Figure 1): increased prescriber awareness of medication charge, standardization of conversion from IV to enteral antibiotics, clear definition of the patients ready for transition, ongoing evaluation of the antimicrobial plan, timely recognition by prescribers of patients ready for transition, culture shift regarding the appropriate administration route in the inpatient setting, and transparency of data. The team implemented sequential Plan-Do-Study-Act (PDSA) cycles¹³ to test the interventions.

Charge Table

To improve knowledge about the increased charge for commonly used IV medications compared with enteral formulations, a table comparing relative charges was shared during monthly resident morning conferences and at an HM faculty meeting. The table included charge comparisons between ampicillin and amoxicillin and IV and enteral clindamycin.

Standardized Language in Electronic Health Record (EHR) Antibiotic Plan on Rounds

Standardized language to document antibiotic transition plans was added to admission and progress note templates in the EHR. The standard template prompted residents to (1) define clinical transition criteria, (2) discuss attending comfort with transition overnight (based on survey results), and (3) document patient preference of solid or liquid dosage forms. Plans were reviewed and updated daily. We hypothesized that since residents use the information in the daily progress notes, including assessments and plans, to present on rounds, inclusion of the transition criteria in the note would prompt transition plan discussions.

Communication Bundle

To promote early transition to enteral antibiotics, we standardized the discussion about antibiotic transition between residents and attendings. During a weekly preexisting meeting, the resident QI team reviewed preferences for transitions with the new service attending. By identifying attending preferences early, residents were able to proactively transition patients who met the criteria (eg, antibiotic transition in the evening instead of waiting until morning rounds). This discussion also provided an opportunity to engage service attendings in the QI efforts, which were also shared at HM faculty meetings quarterly.

Recognizing that in times of high census, discussion of patient plans may be abbreviated during rounds, residents were asked to identify all patients on IV antibiotics while reviewing patient medication orders prior to rounds. As part of an existing daily prerounds huddle to discuss rounding logistics, residents listed all patients on IV antibiotics and discussed which patients were ready for transition. If patients could not be transitioned immediately, the team identified the transition criteria.

At preexisting evening huddles between overnight shift HM residents and the evening HM attending, residents identified patients who were prescribed IV antibiotics and discussed readiness for enteral transition. If a patient could be transitioned overnight, enteral antibiotic orders were placed. Overnight residents were also encouraged to review the transition criteria with families upon admission.

Real-time Identification of Failures and Feedback

For two weeks, the EHR was queried daily to identify patients admitted for uncomplicated CAP and SSTI who were on antibiotics as well as other enteral medications. A failure was defined as an IV antibiotic dose given to a patient who was administered any enteral medication. Residents on the QI team approached residents on other HM teams whenever patients were identified as a failed transition to learn about failure reasons.

Study of the Interventions

Data for HM patients who met the inclusion criteria were collected weekly from January 2016 through June 2018 via EHR query. We initially searched for diagnoses that fit under the disease categories of pneumonia and SSTI in the EHR, which generated a list of International Classification of Disease-9 and -10 Diagnosis codes (Appendix Figure 1). The query identified patients based on these codes and reported whether the identified patients took a dose of any enteral medication, excluding nystatin, sildenafil, tacrolimus, and mouthwashes, which are commonly continued during NPO status due to no need for absorption or limited parenteral options. It also reported the ordered route of administration for the queried antibiotics (Appendix Figure 1).

The 2016 calendar year established our baseline to account for seasonal variability. Data were reported weekly and reviewed to evaluate the impact of PDSA cycles and inform new interventions.

Measures

Our process measure was the total number of enteral antibiotic doses divided by all antibiotic doses in patients receiving any enteral medication. We reasoned that if patients were well enough to take medications enterally, they could be given an enteral antibiotic that is highly bioavailable or readily achieves concentrations that attain pharmacodynamic targets. This practice change was a culture shift, decoupling the switch to enteral antibiotics from discharge readiness. Our EHR query reported only the antibiotic doses given to patients who took an enteral medication on the day of antibiotic administration and excluded patients who received only IV medications.

Outcome measures included antimicrobial costs per patient encounter using average wholesale prices, which were reported in our EHR query, and LOS. To ensure that transitions of IV to enteral antibiotics were not negatively impacting patient outcomes, patient readmissions within seven days served as a balancing measure.

Analysis

An annotated statistical process control p-chart tracked the impact of interventions on the proportion of antibiotic doses that were enterally administered during hospitalization. An x-bar and an s-chart tracked the impact of interventions on antimicrobial costs per patient encounter and on LOS. A p-chart and an encounters-between g-chart were used to evaluate the impact of our interventions on readmissions. Control chart rules for identifying special cause were used for center line shifts.¹⁴

Ethical Considerations

This study was part of a larger study of the residency high-value care curriculum,¹² which was deemed exempt by the CCHMC IRB.

The baseline data collected included 372 patients and the postintervention period in 2017 included 326 patients (Table). Approximately two-thirds of patients had a diagnosis of CAP.

The percentage of antibiotic doses given enterally increased from 44% to 80% within eight months (Figure 2). When studying the impact of interventions, residents on the HM QI team found that the standard EHR template added to daily notes did not consistently prompt residents to discuss antibiotic plans and thus was abandoned. Initial improvement coincided with standardizing discussions between residents and attendings regarding transitions. Furthermore, discussion of all patients on IV antibiotics during the prerounds huddle allowed for reliable, daily communication about antibiotic plans and was subsequently spread to and adopted by all HM teams. The percentage of enterally administered antibiotic doses increased to >75% after the evening huddle, which involved all HM teams, and real-time identification of failures on all HM teams with provider feedback. Despite variability when the total number of antibiotic doses prescribed per week was low (<10), we demonstrated sustainability for 11 months (Figure 2), during which the prerounds and evening huddle discussions were continued and an updated control chart was shown monthly to residents during their educational conferences.

Summary

Using improvement science, we promoted earlier transition to enteral antibiotics for children hospitalized with uncomplicated CAP and SSTI by linking the decision for transition to the ability to take other enteral medications, rather than to discharge readiness. We increased the percentage of enterally administered antibiotic doses in this patient population from 44% to 80% in eight months. Although we did not observe a decrease in LOS as previously noted in a cost analysis study comparing pediatric patients with CAP treated with oral antibiotics versus those treated with IV antibiotics,¹⁵ we did find a decrease in LOS variability and in antimicrobial costs to our patients. These cost savings did not include potential savings from nursing or pharmacy labor. In addition, we noted a decrease in the variability in antibiotic prescribing practice, which demonstrates provider ability and willingness to couple antibiotic route transition to an objective characteristic (administration of other enteral medications).

A strength of our study was that residents, the most frequent prescribers of antibiotics on our HM service, were highly involved in the QI initiative, including defining the SMART aim, identifying key drivers, developing interventions, and completing sequential PDSA cycles. Under the guidance of QI-trained coaches, residents developed feasible interventions and assessed their success in real time. Consistent with other studies,^16,17 resident buy-in and involvement led to the success of our improvement study.

Interpretation

Despite emerging evidence regarding the timing of transition to enteral antibiotics, several factors impeded early transition at our institution, including physician culture, variable practice habits, and hospital workflow. Evidence supports the use of enteral antibiotics in immunocompetent children hospitalized for uncomplicated CAP who do not have chronic lung disease, are not in shock, and have oxygen saturations >85%.⁶ Although existing literature suggests that in pediatric patients admitted for SSTIs not involving the eye or bone, IV antibiotics may be transitioned when clinical improvement, evidenced by a reduction in fever or erythema, is noted,⁶ enteral antibiotics that achieve appropriate concentrations to attain pharmacodynamic targets should have the same efficacy as that of IV antibiotics.⁹ Using the criterion of administration of any medication enterally to identify a patient’s readiness to transition, we were able to overcome practice variation among providers who may have differing opinions of what constitutes clinical improvement. Of note, new evidence is emerging on predictors of enteral antibiotic treatment failure in patients with CAP and SSTI to guide transition timing, but these studies have largely focused on the adult population or were performed in the outpatient and emergency department (ED) settings.^18,19 Regardless, the stable number of encounters between readmissions in our patient population likely indicates that treatment failure in these patients was rare.

Rising healthcare costs have led to concerns around sustainability of the healthcare system;^20,21 tackling overuse in clinical practice, as in our study, is one mitigation strategy. Several studies have used QI methods to facilitate the provision of high-value care through the decrease of continuous monitor overuse and extraneous ordering of electrolytes.^22,23 Our QI study adds to the high-value care literature by safely decreasing the use of IV antibiotics. One retrospective study demonstrated that a one-day decrease in the use of IV antibiotics in pneumonia resulted in decreased costs without an increase in readmissions, similar to our findings.²⁴ In adults, QI initiatives aimed at improving early transition of antibiotics utilized electronic trigger tools.^25,26 Fischer et al. used active orders for scheduled enteral medications or an enteral diet as indication that a patient’s IV medications could be converted to enteral form.²⁶

Our work is not without limitations. The list of ICD-9 and -10 codes used to query the EHR did not capture all diagnoses that would be considered as uncomplicated CAP or SSTI. However, we included an extensive list of diagnoses to ensure that the majority of patients meeting our inclusion criteria were captured. Our process measure did not account for patients on IV antibiotics who were not administered other enteral medications but tolerating an enteral diet. These patients were not identified in our EHR query and were not included in our process measure as a failure. However, in latter interventions, residents identified all patients on IV antibiotics, so that patients not identified by our EHR query benefited from our work. Furthermore, this QI study was conducted at a single institution and several interventions took advantage of preexisting structured huddles and a resident QI curriculum, which may not exist at other institutions. Our study does highlight that engaging frontline providers, such as residents, to review antibiotic orders consistently and question the appropriateness of the administration route is key to making incremental changes in prescribing practices.

Through a partnership between HM and Pharmacy and with substantial resident involvement, we improved the transition of IV antibiotics in patients with CAP or SSTI by increasing the percentage of enterally administered antibiotic doses and reducing antimicrobial costs and variability in antibiotic prescribing practices. This work illustrates how reducing overuse of IV antibiotics promotes high-value care and aligns with initiatives to prevent avoidable harm.²⁷ Our work highlights that standardized discussions about medication orders to create consensus around enteral antibiotic transitions, real-time feedback, and challenging the status quo can influence practice habits and effect change.

Next steps include testing automated methods to notify providers of opportunities for transition from IV to enteral antibiotics through embedded clinical decision support, a method similar to the electronic trigger tools used in adult QI studies.^25,26 Since our prerounds huddle includes identifying all patients on IV antibiotics, studying the transition to enteral antibiotics and its effect on prescribing practices in other diagnoses (ie, urinary tract infection and osteomyelitis) may contribute to spreading these efforts. Partnering with our ED colleagues may be an important next step, as several patients admitted to HM on IV antibiotics are given their first dose in the ED.

Acknowledgments

The authors would like to thank the faculty of the James M. Anderson Center for Health Systems Excellence Intermediate Improvement Science Series for their guidance in the planning of this project. The authors would also like to thank Ms. Ursula Bradshaw and Mr. Michael Ponti-Zins for obtaining the hospital data on length of stay and readmissions. The authors acknowledge Dr. Philip Hagedorn for his assistance with the software that queries the electronic health record and Dr. Laura Brower and Dr. Joanna Thomson for their assistance with statistical analysis. The authors are grateful to all the residents and coaches on the QI Hospital Medicine team who contributed ideas on study design and interventions.

Intravenous (IV) antibiotics are commonly used in hospitalized pediatric patients to treat bacterial infections. Antimicrobial stewardship guidelines published by the Infectious Diseases Society of America (IDSA) recommend institutions develop a systematic plan to convert from IV to enteral antibiotics, as early transition may reduce healthcare costs, decrease length of stay (LOS), and avoid prolonged IV access complications¹ such as extravasation, thrombosis, and catheter-associated infections.^2-5

Pediatric patients with community-acquired pneumonia (CAP) and mild skin and soft tissue infections (SSTI) may not require IV antibiotics, even if the patient is hospitalized.⁶ Although national guidelines for pediatric CAP and SSTI recommend IV antibiotics for hospitalized patients, these guidelines state that mild infections may be treated with enteral antibiotics and emphasize discontinuation of IV antibiotics when the patient meets discharge criteria.^7,8 Furthermore, several enteral antibiotics used for the treatment of CAP and SSTI, such as cephalexin and clindamycin,⁹ have excellent bioavailability (>90%) or can achieve sufficient concentrations to attain the pharmacodynamic target (ie, amoxicillin and trimethoprim–sulfamethoxazole).^10,11 Nonetheless, the guidelines do not explicitly outline criteria regarding the transition from IV to enteral antibiotics.^7,8

At our institution, patients admitted to Hospital Medicine (HM) often remained on IV antibiotics until discharge. Data review revealed that antibiotic treatment of CAP and SSTI posed the greatest opportunity for early conversion to enteral therapy based on the high frequency of admissions and the ability of commonly used enteral antibiotics to attain pharmacodynamic targets. We sought to change practice culture by decoupling transition to enteral antibiotics from discharge and use administration of other enteral medications as an objective indicator for transition. Our aim was to increase the proportion of enterally administered antibiotic doses for HM patients aged >60 days admitted with uncomplicated CAP or SSTI from 44% to 75% in eight months.

Context

Cincinnati Children’s Hospital Medical Center (CCHMC) is a large, urban, academic hospital. The HM division has 45 attendings and admits >8,000 general pediatric patients annually. The five HM teams at the main campus consist of attendings, fellows, residents, and medical students. One HM team serves as the resident quality improvement (QI) team where residents collaborate in a longitudinal study under the guidance of QI-trained coaches. The focus of this QI initiative was determined by resident consensus and aligned with a high-value care curriculum.¹²

To identify the target patient population, we investigated IV antimicrobials frequently used in HM patients. Ampicillin and clindamycin are commonly used IV antibiotics, most frequently corresponding with the diagnoses of CAP and SSTI, respectively, accounting for half of all antibiotic use on the HM service. Amoxicillin, the enteral equivalent of ampicillin, can achieve sufficient concentrations to attain the pharmacodynamic target at infection sites, and clindamycin has high bioavailability, making them ideal options for early transition. Our institution’s robust antimicrobial stewardship program has published local guidelines on using amoxicillin as the enteral antibiotic of choice for uncomplicated CAP, but it does not provide guidance on the timing of transition for either CAP or SSTI; the clinical team makes this decision.

HM attendings were surveyed to determine the criteria used to transition from IV to enteral antibiotics for patients with CAP or SSTI. The survey illustrated practice variability with providers using differing clinical criteria to signal the timing of transition. Additionally, only 49% of respondents (n = 37) rated themselves as “very comfortable” with residents making autonomous decisions to transition to enteral antibiotics. We chose to use the administration of other enteral medications, instead of discharge readiness, as an objective indicator of a patient’s readiness to transition to enteral antibiotics, given the low-risk patient population and the ability of the enteral antibiotics commonly used for CAP and SSTI to achieve pharmacodynamic targets.

The study population included patients aged >60 days admitted to HM with CAP or SSTI treated with any antibiotic. We excluded patients with potential complications or significant progression of their disease process, including patients with parapneumonic effusions or chest tubes, patients who underwent bronchoscopy, and patients with osteomyelitis, septic arthritis, or preseptal or orbital cellulitis. Past medical history and clinical status on admission were not used to exclude patients.

Interventions

Our multidisciplinary team, formed in January 2017, included HM attendings, HM fellows, pediatric residents, a critical care attending, a pharmacy resident, and an antimicrobial stewardship pharmacist. Under the guidance of QI coaches, the residents on the HM QI team developed and tested all interventions on their team and then determined which interventions would spread to the other four teams. The nursing director of our primary HM unit disseminated project updates to bedside nurses. A simplified failure mode and effects analysis identified areas for improvement and potential interventions. Interventions focused on the following key drivers (Figure 1): increased prescriber awareness of medication charge, standardization of conversion from IV to enteral antibiotics, clear definition of the patients ready for transition, ongoing evaluation of the antimicrobial plan, timely recognition by prescribers of patients ready for transition, culture shift regarding the appropriate administration route in the inpatient setting, and transparency of data. The team implemented sequential Plan-Do-Study-Act (PDSA) cycles¹³ to test the interventions.

Charge Table

To improve knowledge about the increased charge for commonly used IV medications compared with enteral formulations, a table comparing relative charges was shared during monthly resident morning conferences and at an HM faculty meeting. The table included charge comparisons between ampicillin and amoxicillin and IV and enteral clindamycin.

Standardized Language in Electronic Health Record (EHR) Antibiotic Plan on Rounds

Standardized language to document antibiotic transition plans was added to admission and progress note templates in the EHR. The standard template prompted residents to (1) define clinical transition criteria, (2) discuss attending comfort with transition overnight (based on survey results), and (3) document patient preference of solid or liquid dosage forms. Plans were reviewed and updated daily. We hypothesized that since residents use the information in the daily progress notes, including assessments and plans, to present on rounds, inclusion of the transition criteria in the note would prompt transition plan discussions.

Communication Bundle

To promote early transition to enteral antibiotics, we standardized the discussion about antibiotic transition between residents and attendings. During a weekly preexisting meeting, the resident QI team reviewed preferences for transitions with the new service attending. By identifying attending preferences early, residents were able to proactively transition patients who met the criteria (eg, antibiotic transition in the evening instead of waiting until morning rounds). This discussion also provided an opportunity to engage service attendings in the QI efforts, which were also shared at HM faculty meetings quarterly.

Recognizing that in times of high census, discussion of patient plans may be abbreviated during rounds, residents were asked to identify all patients on IV antibiotics while reviewing patient medication orders prior to rounds. As part of an existing daily prerounds huddle to discuss rounding logistics, residents listed all patients on IV antibiotics and discussed which patients were ready for transition. If patients could not be transitioned immediately, the team identified the transition criteria.

At preexisting evening huddles between overnight shift HM residents and the evening HM attending, residents identified patients who were prescribed IV antibiotics and discussed readiness for enteral transition. If a patient could be transitioned overnight, enteral antibiotic orders were placed. Overnight residents were also encouraged to review the transition criteria with families upon admission.

Real-time Identification of Failures and Feedback

For two weeks, the EHR was queried daily to identify patients admitted for uncomplicated CAP and SSTI who were on antibiotics as well as other enteral medications. A failure was defined as an IV antibiotic dose given to a patient who was administered any enteral medication. Residents on the QI team approached residents on other HM teams whenever patients were identified as a failed transition to learn about failure reasons.

Study of the Interventions

Data for HM patients who met the inclusion criteria were collected weekly from January 2016 through June 2018 via EHR query. We initially searched for diagnoses that fit under the disease categories of pneumonia and SSTI in the EHR, which generated a list of International Classification of Disease-9 and -10 Diagnosis codes (Appendix Figure 1). The query identified patients based on these codes and reported whether the identified patients took a dose of any enteral medication, excluding nystatin, sildenafil, tacrolimus, and mouthwashes, which are commonly continued during NPO status due to no need for absorption or limited parenteral options. It also reported the ordered route of administration for the queried antibiotics (Appendix Figure 1).

The 2016 calendar year established our baseline to account for seasonal variability. Data were reported weekly and reviewed to evaluate the impact of PDSA cycles and inform new interventions.

Measures

Our process measure was the total number of enteral antibiotic doses divided by all antibiotic doses in patients receiving any enteral medication. We reasoned that if patients were well enough to take medications enterally, they could be given an enteral antibiotic that is highly bioavailable or readily achieves concentrations that attain pharmacodynamic targets. This practice change was a culture shift, decoupling the switch to enteral antibiotics from discharge readiness. Our EHR query reported only the antibiotic doses given to patients who took an enteral medication on the day of antibiotic administration and excluded patients who received only IV medications.

Outcome measures included antimicrobial costs per patient encounter using average wholesale prices, which were reported in our EHR query, and LOS. To ensure that transitions of IV to enteral antibiotics were not negatively impacting patient outcomes, patient readmissions within seven days served as a balancing measure.

Analysis

An annotated statistical process control p-chart tracked the impact of interventions on the proportion of antibiotic doses that were enterally administered during hospitalization. An x-bar and an s-chart tracked the impact of interventions on antimicrobial costs per patient encounter and on LOS. A p-chart and an encounters-between g-chart were used to evaluate the impact of our interventions on readmissions. Control chart rules for identifying special cause were used for center line shifts.¹⁴

Ethical Considerations

This study was part of a larger study of the residency high-value care curriculum,¹² which was deemed exempt by the CCHMC IRB.

The baseline data collected included 372 patients and the postintervention period in 2017 included 326 patients (Table). Approximately two-thirds of patients had a diagnosis of CAP.

The percentage of antibiotic doses given enterally increased from 44% to 80% within eight months (Figure 2). When studying the impact of interventions, residents on the HM QI team found that the standard EHR template added to daily notes did not consistently prompt residents to discuss antibiotic plans and thus was abandoned. Initial improvement coincided with standardizing discussions between residents and attendings regarding transitions. Furthermore, discussion of all patients on IV antibiotics during the prerounds huddle allowed for reliable, daily communication about antibiotic plans and was subsequently spread to and adopted by all HM teams. The percentage of enterally administered antibiotic doses increased to >75% after the evening huddle, which involved all HM teams, and real-time identification of failures on all HM teams with provider feedback. Despite variability when the total number of antibiotic doses prescribed per week was low (<10), we demonstrated sustainability for 11 months (Figure 2), during which the prerounds and evening huddle discussions were continued and an updated control chart was shown monthly to residents during their educational conferences.

Summary

Using improvement science, we promoted earlier transition to enteral antibiotics for children hospitalized with uncomplicated CAP and SSTI by linking the decision for transition to the ability to take other enteral medications, rather than to discharge readiness. We increased the percentage of enterally administered antibiotic doses in this patient population from 44% to 80% in eight months. Although we did not observe a decrease in LOS as previously noted in a cost analysis study comparing pediatric patients with CAP treated with oral antibiotics versus those treated with IV antibiotics,¹⁵ we did find a decrease in LOS variability and in antimicrobial costs to our patients. These cost savings did not include potential savings from nursing or pharmacy labor. In addition, we noted a decrease in the variability in antibiotic prescribing practice, which demonstrates provider ability and willingness to couple antibiotic route transition to an objective characteristic (administration of other enteral medications).

A strength of our study was that residents, the most frequent prescribers of antibiotics on our HM service, were highly involved in the QI initiative, including defining the SMART aim, identifying key drivers, developing interventions, and completing sequential PDSA cycles. Under the guidance of QI-trained coaches, residents developed feasible interventions and assessed their success in real time. Consistent with other studies,^16,17 resident buy-in and involvement led to the success of our improvement study.

Interpretation

Despite emerging evidence regarding the timing of transition to enteral antibiotics, several factors impeded early transition at our institution, including physician culture, variable practice habits, and hospital workflow. Evidence supports the use of enteral antibiotics in immunocompetent children hospitalized for uncomplicated CAP who do not have chronic lung disease, are not in shock, and have oxygen saturations >85%.⁶ Although existing literature suggests that in pediatric patients admitted for SSTIs not involving the eye or bone, IV antibiotics may be transitioned when clinical improvement, evidenced by a reduction in fever or erythema, is noted,⁶ enteral antibiotics that achieve appropriate concentrations to attain pharmacodynamic targets should have the same efficacy as that of IV antibiotics.⁹ Using the criterion of administration of any medication enterally to identify a patient’s readiness to transition, we were able to overcome practice variation among providers who may have differing opinions of what constitutes clinical improvement. Of note, new evidence is emerging on predictors of enteral antibiotic treatment failure in patients with CAP and SSTI to guide transition timing, but these studies have largely focused on the adult population or were performed in the outpatient and emergency department (ED) settings.^18,19 Regardless, the stable number of encounters between readmissions in our patient population likely indicates that treatment failure in these patients was rare.

Rising healthcare costs have led to concerns around sustainability of the healthcare system;^20,21 tackling overuse in clinical practice, as in our study, is one mitigation strategy. Several studies have used QI methods to facilitate the provision of high-value care through the decrease of continuous monitor overuse and extraneous ordering of electrolytes.^22,23 Our QI study adds to the high-value care literature by safely decreasing the use of IV antibiotics. One retrospective study demonstrated that a one-day decrease in the use of IV antibiotics in pneumonia resulted in decreased costs without an increase in readmissions, similar to our findings.²⁴ In adults, QI initiatives aimed at improving early transition of antibiotics utilized electronic trigger tools.^25,26 Fischer et al. used active orders for scheduled enteral medications or an enteral diet as indication that a patient’s IV medications could be converted to enteral form.²⁶

Our work is not without limitations. The list of ICD-9 and -10 codes used to query the EHR did not capture all diagnoses that would be considered as uncomplicated CAP or SSTI. However, we included an extensive list of diagnoses to ensure that the majority of patients meeting our inclusion criteria were captured. Our process measure did not account for patients on IV antibiotics who were not administered other enteral medications but tolerating an enteral diet. These patients were not identified in our EHR query and were not included in our process measure as a failure. However, in latter interventions, residents identified all patients on IV antibiotics, so that patients not identified by our EHR query benefited from our work. Furthermore, this QI study was conducted at a single institution and several interventions took advantage of preexisting structured huddles and a resident QI curriculum, which may not exist at other institutions. Our study does highlight that engaging frontline providers, such as residents, to review antibiotic orders consistently and question the appropriateness of the administration route is key to making incremental changes in prescribing practices.

Through a partnership between HM and Pharmacy and with substantial resident involvement, we improved the transition of IV antibiotics in patients with CAP or SSTI by increasing the percentage of enterally administered antibiotic doses and reducing antimicrobial costs and variability in antibiotic prescribing practices. This work illustrates how reducing overuse of IV antibiotics promotes high-value care and aligns with initiatives to prevent avoidable harm.²⁷ Our work highlights that standardized discussions about medication orders to create consensus around enteral antibiotic transitions, real-time feedback, and challenging the status quo can influence practice habits and effect change.

Next steps include testing automated methods to notify providers of opportunities for transition from IV to enteral antibiotics through embedded clinical decision support, a method similar to the electronic trigger tools used in adult QI studies.^25,26 Since our prerounds huddle includes identifying all patients on IV antibiotics, studying the transition to enteral antibiotics and its effect on prescribing practices in other diagnoses (ie, urinary tract infection and osteomyelitis) may contribute to spreading these efforts. Partnering with our ED colleagues may be an important next step, as several patients admitted to HM on IV antibiotics are given their first dose in the ED.

Acknowledgments

The authors would like to thank the faculty of the James M. Anderson Center for Health Systems Excellence Intermediate Improvement Science Series for their guidance in the planning of this project. The authors would also like to thank Ms. Ursula Bradshaw and Mr. Michael Ponti-Zins for obtaining the hospital data on length of stay and readmissions. The authors acknowledge Dr. Philip Hagedorn for his assistance with the software that queries the electronic health record and Dr. Laura Brower and Dr. Joanna Thomson for their assistance with statistical analysis. The authors are grateful to all the residents and coaches on the QI Hospital Medicine team who contributed ideas on study design and interventions.

Heart failure (HF) is a leading cause of hospital admission and mortality, accounting for approximately 900,000 discharges in 2014.¹ One-year all-cause mortality risk has been estimated at 17% after hospitalization,² and roughly 50% of deaths are related to sudden cardiac death, mostly due to ventricular arrhythmia.³Potassium abnormalities occur frequently in hospitalized patients with HF, and serum potassium levels outside of the normal reference range (<3.5 and >5.0 mEq/L) have been consistently shown to predict morbidity and mortality.^4-9 However, confusion still surrounds the acute management of patients with potassium values in the lower normal range (3.5-4.0 mEq/L). Conventional clinical wisdom suggests that these patients must maintain a higher serum potassium, with a minimum value of 4.0 mEq/L often cited as the target value.¹⁰ Despite the limited evidence in the acute HF population underlying this practice, clinicians often reflexively order potassium supplementation to reach this goal.

The principles underlying potassium management in acute HF are complex. Both low and high values have been linked to fatal arrhythmias, notably ventricular fibrillation, and small serum changes often reflect large total body potassium fluctuations.¹¹ Recent literature links hypokalemia to general membrane hypoexcitability, skeletal muscle hyporeflexia, and arrhythmias initiated by reduced sodium-potassium adenosine triphosphatase activity, leading to increased intracellular calcium and regional variations in action potential duration.¹² Potassium abnormalities are common at admission and may be exacerbated by both acute illness and treatments given during hospitalization, including baseline potassium, acute kidney injury, aggressive diuretic therapy, or other potassium-related treatments and conditions.¹³ The success of potassium repletion may also be affected by the choice of HF therapies.¹⁴

The belief that patients with HF must maintain a potassium >4.0 mEq/L remains pervasive, with at least one family medicine guideline recommending that patients with HF maintain a serum potassium level >4.0 mEq/L.¹⁵ Considering this uncertainty and that potassium repletion in hospitalized patients is a daily occurrence consuming a noteworthy amount of healthcare resources, we aimed to evaluate the association between differences in normal inpatient serum potassium levels and outcomes in a large cohort of patients hospitalized for an acute HF exacerbation who presented with serum potassium within normal range (3.5-5.0 mEq/L).

Data Sources and Cohort Definition

The Institutional Review Board at Baystate Medical Center approved this study. We identified patients with HF who were admitted for more than 72 hours between January 2010 and December 2012 to hospitals contributing to the HealthFacts database, a multihospital dataset derived from the comprehensive electronic health records of 116 geographically and structurally diverse hospitals throughout the United States (Cerner Corp.). HealthFacts—which includes date-stamped pharmacy, laboratory, and billing information—contains records of more than 84 million acute admissions, emergency room visits, and ambulatory visits. We limited the sample to hospitals that contributed to the pharmacy, laboratory, and diagnosis segments.

We included patients who had a principal International Classification of Disease (ICD-9-CM) diagnosis of HF or a principal diagnosis of respiratory failure with secondary diagnosis of HF (ICD-9-CM codes for HF: 402.01, 402.11, 402.91, 404.01, 404.03, 404.11, 404.13, 404.91, 404.93, 428.xx¹⁶ and for respiratory failure: 518.81, 518.82, 518.84) and were 18 years or older. We ensured that patients were treated for acute decompensated HF during the hospitalization by restricting the cohort to patients in whom at least one HF therapy (eg, loop diuretics, metolazone, inotropes, and intra-aortic balloon pump) was initiated within the first two days of hospitalization. We excluded patients with a pediatric or psychiatric attending physician, those with elective admissions, and those who were transferred from or to another acute care facility because we could not accurately determine the onset or subsequent course of their illness.

Definition of Variables Describing Serum Potassium Levels

We limited the sample to patients hospitalized for longer than 72 hours in order to observe how initial potassium values influenced outcomes over the course of hospitalization. We chose an exposure window of 72 hours because this allowed, on average, three potential observations of serum potassium per patient. We further restricted the sample to those who had a normal potassium value (3.5-5.0 mEq/L) at admission (defined as 24 hours prior to admission through midnight of the day of admission) to ensure that the included patients did not have abnormal potassium values upon presentation. We identified the period of time from 24 hours prior to admission through 72 hours following admission as “the exposure window” (the time during which patients were eligible to be classified into average serum potassium levels of <4.0, 4.0-4.5, or >4.5 mEq/L). We excluded patients who, during this window, had fewer than three serum potassium levels drawn (“exposure” levels could be disproportionately influenced by a single value) or received sodium polystyrene (as this would indicate that the physicians felt the potassium was dangerously high). For patients with repeated hospitalizations, we randomly selected one visit for inclusion to reduce the risk of survivor bias. We calculated the mean of all serum potassium levels during the exposure window, including the admission value, and then evaluated two different categorizations of mean serum potassium, based on categories of risk previously reported in the literature:^8,17,18: (1) <4.0, 4.0-4.5, or >4.5 mEq/L and (2) <4.0 versus ≥4.0 mEq/L.

Outcomes

We assessed three outcomes: in-hospital mortality, transfer to an intensive care unit (ICU), and length of stay (LOS). Admission to the ICU was defined as any evidence, after the exposure window, that the patient received care in the ICU. We excluded patients with ICU admissions during the exposure window from the analysis of this outcome. We calculated LOS as the difference between discharge date/time and the admission date/time.

Covariates and Comorbidity Adjustment

We obtained information on patient demographics (age and race) and identified the presence of comorbid conditions using previously derived and validated models.^19,20 We then further quantified these conditions into a single combined score to adjust for differences in presenting illness severity (including kidney disease) and help reduce confounding.²¹ To account for presenting severity of illness, we calculated the Laboratory-based Acute Physiology Score (LAPS-2).^22,23 LAPS-2 was developed for predicting mortality risk in general medical patients, but we previously externally validated it against other published clinical HF models in a cohort of patients hospitalized with acute decompensated HF.⁵LAPS-2 includes fourteen laboratory values at the time of admission (including blood urea nitrogen, creatinine, and anion gap) to calculate a score.^22,23 Thus, we adjusted for differences in baseline characteristics, including admission renal function.

Potassium Repletion

We evaluated whether patients received potassium during the exposure window (defined as any supplemental potassium order during the hospital stay) and the total number of days the patient was eligible for repletion (defined as a serum potassium result that was <4.0 mEq/L). We then recorded the total number of days repletion was given (using medication orders). We also calculated the ratio of days that repletion was received to the days that the patient was eligible for repletion. We also recorded all instances in which serum potassium values were <3.5 mEq/L at any time during the exposure window

Analysis

We evaluated the differences in patient characteristics across serum potassium categories. Categorical variables are presented as frequencies and percentages, whereas continuous variables are presented as means and standard deviations. For binary outcomes, we used generalized estimating equations (with a binomial family and logit link and clustering by hospital) to estimate incidence and calculate unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs). For LOS, we estimated the median and 95% CIs using quantile regression with clustered standard errors.²⁴ We calculated all models using both a binary exposure (<4.0 versus ≥4.0 mEq/L) and a three-level categorization (<4.0, 4.0-4.5, and >4.5 mEq/L) to explore the effects at the highest potassium level. We adjusted all models for age, race, LAPS-2 score, and combined comorbidity score. We conducted two sensitivity analyses. First, we restricted our sample to those who never received potassium during the exposure window, as these patients may be different than patients who required potassium repletion. Second, we stratified our findings by the presence or absence of acute or chronic renal insufficiency (defined as an admission creatinine >1 or the presence of a diagnostic code for renal insufficiency, as defined by Elixhauser et al.).^19,21 Statistical significance was set at an alpha of 0.05. Analysis was completed using Stata v15.1, StataCorp LP, College Station, Texas.

Cohort Description

We identified patients from 56 geographically diverse US hospitals, although most were located in either the northeast (n = 21; 38%) or south (n = 18; 32%). A total of 59% of the hospitals were teaching hospitals, and nearly 95% were in an urban setting. We identified 13,163 patients with HF, of which 4,995 (38.0%) met the inclusion criteria. We excluded 3,744 (28.4%) patients with LOS < 72 hours, 2,210 (16.8%) with admission potassium values outside of the defined range, and 896 (6.8%) with fewer than three potassium values during the exposure window. Of the patients who met the inclusion criteria, 2,080 (41.6%), 2,326 (46.6%), and 589 (11.8%) were categorized in the <4.0, 4.0-4.5, and >4.5 mEq/L groups, respectively (Table 1). The groups were clinically similar in terms of age, sex, illness severity (LAPS-2), and comorbidity score. Compared with other racial groups, black patients had higher potassium values. While the <4.0 and 4.0-4.5 mEq/L groups were relatively similar, the group with mean potassium >4.5 mEq/L had higher admission creatinine and a greater prevalence of chronic kidney disease, deficiency anemias, and chronic obstructive pulmonary disease (Table 1).

Serum Potassium Values

Individuals’ mean serum potassium within the 72-hour exposure window ranged from 2.9 to 5.8 mEq/L (Table 2). In the <4.0, 4-4.5, and >4.5 mEq/L cohorts respectively, patients had a median serum potassium of 3.8 mEq/L (2.9-3.9), 4.2 mEq/L (4.0-4.5), and 4.7 mEq/L (4.5-5.8) during the exposure window. Approximately half of the patients in the <4.0 mEq/L group had a serum potassium <3.5 mEq/L at some point during the exposure window. In contrast, <10% of the other groups had this low value during the exposure window.

Potassium Repletion

Patients in the <4.0 mEq/L group were much more likely to receive potassium repletion during the exposure window when compared with the 4.0-4.5 mEq/L (71.5% vs 40.5%) and >4.5 mEq/L (71.5% vs 26.7%) groups. On days that they were eligible for repletion (defined as a daily potassium value <4.0 mEq/L), patients with mean serum potassium >4.0 mEq/L were less likely to receive potassium repletion compared with those with values <4.0 mEq/L. There were 592 (28.5%), 1,383 (59.5%), and 432 (73.3%) patients in the <4.0, 4-4.5, and >4,5 mEq/L groups, respectively, who did not receive potassium repletion therapy during the exposure window.

Relationship of Serum Potassium Levels and Outcomes

Overall, 3.7% (n = 187) of patients died during the hospitalization, 2.4% (n = 98) were admitted to the ICU after the exposure window, and the median LOS was 5.6 days. We did not observe a significant association between mean serum potassium of <4.0 or 4.0-4.5 mEq/L and increased risk of mortality, ICU transfer, or LOS (Table 3). Our unadjusted analysis showed that patients with values >4.5 mEq/L had worse outcomes, including more deaths (5.3%; OR = 1.55; 95% CI: 1.01 to 2.39) and ICU admission (3.8%; OR = 2.10; 95% CI: 1.16 to 3.80) compared with those with values <4.0 mEq/L (Table 3). We also found that, compared with the <4.0 mEq/L group, the >4.5 mEq/L group showed just over a half-day longer LOS (0.6 days; 95% CI: 0.0 to 1.0; Table 3). However, we found that mortality and ICU admission results were attenuated after adjustment for age, race, comorbidity score, and LAPS-2 and were no longer statistically significant, whereas the association with LOS was consistent after adjustment. When using a binary exposure (<4.0 versus ≥4.0 mEq/L), we observed no association between mean potassium value and increased risk of mortality, ICU transfer, or LOS both before and after adjustment for age, race, LAPS-2, and comorbidity score (data not shown).

Sensitivity Analyses

In the sensitivity analysis restricted to those who did not receive potassium repletion during the exposure window, we continued to observe no association between the <4.0 and 4.0-4.5 mEq/L groups and outcomes (Table 3). In adjusted models for the >4.5 versus <4.0 mEq/L groups, risk estimates for mortality were similar to the full sample, but statistical significance was lost (OR = 1.56; 95% CI: 0.81 to 3.01). Adjusted risk estimates for ICU transfer were attenuated and not statistically significant (OR = 1.40; 95% CI: 0.60 to 3.26). However, LOS estimates were very similar to that observed in the full dataset (0.6 days; 95% CI: 0.1 to 1.2).

When stratifying our results by the presence or absence of acute or chronic renal insufficiency, we continued to observe no increased risk of any outcome in the 4.0-4.5 mEq/L compared with the <4.0 mEq/L groups across all strata (Table 4). Interestingly, even after adjustment, we did find that most of the increased risk of mortality and ICU admission in the >4.5 versus <4.0 mEq/L groups was among those without renal insufficiency (mortality OR = 3.03; ICU admission OR = 3.00) and was not statistically significant in those with renal insufficiency (mortality OR = 1.27; ICU admission OR = 1.63). Adjusted LOS estimates remained relatively similar in this stratified analysis.

The best approach to mild serum potassium value abnormalities in patients hospitalized with HF remains unclear. Many physicians reflexively replete potassium to ensure all patients maintain a serum value of >4.0 mEq/L.¹⁵ Yet, in this large observational study of patients hospitalized with an acute HF exacerbation, we found little evidence of association between serum potassium <4.0 mEq/L and negative outcomes.

Compared with those with mean potassium values <4.0 mEq/L (in unadjusted models), there was an association between potassium values of >4.5 mEq/L and increased risk of mortality and ICU transfer. This association was attenuated after adjustment, suggesting that factors beyond potassium values influenced the observed relationship. These findings seem to suggest that unobserved differences in the >4.5 mEq/L group (there were observed differences in this group, eg, greater presenting severity and higher comorbidity scores, suggesting that there were also unobserved differences), and not average potassium value, were the reasons for the observed differences in outcomes. However, we cannot rule out the possibility that potassium >4.5 mEq/L has some associated increased risk compared with mean potassium values of <4.0 mEq/L for patients hospitalized with acute decompensated HF.

Patients in our study routinely received exogenous potassium: more than 70% of patients received repletion at least once, although it is notable that the majority of patients in the 4.0-4.5 and >4.5 mEq/L groups did not receive repletion. Despite this practice, the data supporting this approach to potassium management for patients hospitalized with HF remain mixed. A serum potassium decline of >15% during an acute HF hospital stay has been reported as a predictor of all-cause mortality after controlling for disease severity and associated comorbidities, including renal function.²⁵ However, this study was focused on decline in admission potassium rather than an absolute cut-off (eg, >4.0 mEq/L). Additionally, potassium levels <3.9 mEq/L were associated with increased mortality in patients with acute HF following a myocardial infarction, but this study was not focused on patients with HF.²⁶ Most of the prior literature in patients with HF was conducted in patients in outpatient settings and examined patients who were not experiencing acute exacerbations. MacDonald and Struthers advocate that patients with HF have their potassium maintained above 4.0 mEq/L but did not specify whether this included patients with acute HF exacerbations.¹⁰ Additionally, many studies evaluating potassium repletion were conducted before widespread availability of angiotensin-converting enzyme (ACE) inhibitors or potassium-sparing diuretics, including spironolactone. Prior work has consistently reported that hyperkalemia, defined as serum potassium >4.5 mEq/L, is associated with mortality in patients with acute HF over the course of hospitalization (which aligned with the results from our sensitivity analysis), but concurrent medication regimens and underlying impaired renal function likely accounted for most of this association.¹⁷ The picture is further complicated as patients with acute HF presenting with hypokalemia may be at risk for subsequent hyperkalemia, and potassium repletion can stimulate aldosterone secretion, potentially exacerbating underlying HF.^27,28

These data are observational and are unlikely to change practice. However, daily potassium repletion represents a huge cost in time, money, and effort to the health system. Furthermore, the greatest burden occurs for the patients, who have labs drawn and values checked routinely and potassium administered orally or parenterally. While future randomized clinical trials (RCTs) would best examine the benefits of repletion, future pragmatic trials could attempt to disentangle the associated risks and benefits of potassium repletion in the absence of RCTs. Additionally, such studies could better take into account the role of concurrent medication use (like ACEs or angiotensin II receptor blockers), as well as assess the role of chronic renal insufficiency, acute kidney injury, and magnesium levels.²⁹

This study has limitations. Its retrospective design leads to unmeasured confounding; however, we adjusted for multiple variables (including LAPS-2), which reflect the severity of disease at admission and underlying kidney function at presentation, as well as other comorbid conditions. In addition, data from the cohort only extend to 2012, so more recent changes in practice may not be completely reflected. The nature of the data did not allow us to directly investigate the relationship between serum potassium and arrhythmias, although ICU transfer and mortality were used as surrogates. We were not able to examine the relationship between acute and chronic renal failure and potassium, as this was beyond the scope of this analysis. Given the hypothesis-generating nature of this study, adjustment for additional confounders, including concurrent medication use, was beyond the scope of this analysis.

In conclusion, the benefit of a serum potassium level >4.0 mEq/L in patients admitted with HF remains unclear. We did not observe that mean potassium values <4.0 mEq/L were associated with worse outcomes, and, more concerning, there may be some risk for patients with mean values >4.5 mEq/L.

Acknowledgments

Dr. Lagu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Disclosures

The authors report no potential conflicts of interest. Dr. Lagu has served as a consultant for the Yale Center for Outcomes Research and Evaluation, under contract to the Centers for Medicare and Medicaid Services, for which she has provided clinical and methodological expertise and input on the development, reevaluation, and implementation of hospital outcome and efficiency measures.

Funding

Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number K01HL114745 and R01 HL139985-01A1. Dr. Stefan is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number K01HL114631-01A1. Dr. Pack is supported by NHLBI 1K23HL135440. Dr. Lindenauer is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number 1K24HL132008.

Disclaimer

The views expressed in this manuscript do not necessarily reflect those of the Yale Center for Outcomes Research and Evaluation or the Centers for Medicare and Medicaid Services.

Heart failure (HF) is a leading cause of hospital admission and mortality, accounting for approximately 900,000 discharges in 2014.¹ One-year all-cause mortality risk has been estimated at 17% after hospitalization,² and roughly 50% of deaths are related to sudden cardiac death, mostly due to ventricular arrhythmia.³Potassium abnormalities occur frequently in hospitalized patients with HF, and serum potassium levels outside of the normal reference range (<3.5 and >5.0 mEq/L) have been consistently shown to predict morbidity and mortality.^4-9 However, confusion still surrounds the acute management of patients with potassium values in the lower normal range (3.5-4.0 mEq/L). Conventional clinical wisdom suggests that these patients must maintain a higher serum potassium, with a minimum value of 4.0 mEq/L often cited as the target value.¹⁰ Despite the limited evidence in the acute HF population underlying this practice, clinicians often reflexively order potassium supplementation to reach this goal.

The principles underlying potassium management in acute HF are complex. Both low and high values have been linked to fatal arrhythmias, notably ventricular fibrillation, and small serum changes often reflect large total body potassium fluctuations.¹¹ Recent literature links hypokalemia to general membrane hypoexcitability, skeletal muscle hyporeflexia, and arrhythmias initiated by reduced sodium-potassium adenosine triphosphatase activity, leading to increased intracellular calcium and regional variations in action potential duration.¹² Potassium abnormalities are common at admission and may be exacerbated by both acute illness and treatments given during hospitalization, including baseline potassium, acute kidney injury, aggressive diuretic therapy, or other potassium-related treatments and conditions.¹³ The success of potassium repletion may also be affected by the choice of HF therapies.¹⁴

The belief that patients with HF must maintain a potassium >4.0 mEq/L remains pervasive, with at least one family medicine guideline recommending that patients with HF maintain a serum potassium level >4.0 mEq/L.¹⁵ Considering this uncertainty and that potassium repletion in hospitalized patients is a daily occurrence consuming a noteworthy amount of healthcare resources, we aimed to evaluate the association between differences in normal inpatient serum potassium levels and outcomes in a large cohort of patients hospitalized for an acute HF exacerbation who presented with serum potassium within normal range (3.5-5.0 mEq/L).

Data Sources and Cohort Definition

The Institutional Review Board at Baystate Medical Center approved this study. We identified patients with HF who were admitted for more than 72 hours between January 2010 and December 2012 to hospitals contributing to the HealthFacts database, a multihospital dataset derived from the comprehensive electronic health records of 116 geographically and structurally diverse hospitals throughout the United States (Cerner Corp.). HealthFacts—which includes date-stamped pharmacy, laboratory, and billing information—contains records of more than 84 million acute admissions, emergency room visits, and ambulatory visits. We limited the sample to hospitals that contributed to the pharmacy, laboratory, and diagnosis segments.

We included patients who had a principal International Classification of Disease (ICD-9-CM) diagnosis of HF or a principal diagnosis of respiratory failure with secondary diagnosis of HF (ICD-9-CM codes for HF: 402.01, 402.11, 402.91, 404.01, 404.03, 404.11, 404.13, 404.91, 404.93, 428.xx¹⁶ and for respiratory failure: 518.81, 518.82, 518.84) and were 18 years or older. We ensured that patients were treated for acute decompensated HF during the hospitalization by restricting the cohort to patients in whom at least one HF therapy (eg, loop diuretics, metolazone, inotropes, and intra-aortic balloon pump) was initiated within the first two days of hospitalization. We excluded patients with a pediatric or psychiatric attending physician, those with elective admissions, and those who were transferred from or to another acute care facility because we could not accurately determine the onset or subsequent course of their illness.

Definition of Variables Describing Serum Potassium Levels

We limited the sample to patients hospitalized for longer than 72 hours in order to observe how initial potassium values influenced outcomes over the course of hospitalization. We chose an exposure window of 72 hours because this allowed, on average, three potential observations of serum potassium per patient. We further restricted the sample to those who had a normal potassium value (3.5-5.0 mEq/L) at admission (defined as 24 hours prior to admission through midnight of the day of admission) to ensure that the included patients did not have abnormal potassium values upon presentation. We identified the period of time from 24 hours prior to admission through 72 hours following admission as “the exposure window” (the time during which patients were eligible to be classified into average serum potassium levels of <4.0, 4.0-4.5, or >4.5 mEq/L). We excluded patients who, during this window, had fewer than three serum potassium levels drawn (“exposure” levels could be disproportionately influenced by a single value) or received sodium polystyrene (as this would indicate that the physicians felt the potassium was dangerously high). For patients with repeated hospitalizations, we randomly selected one visit for inclusion to reduce the risk of survivor bias. We calculated the mean of all serum potassium levels during the exposure window, including the admission value, and then evaluated two different categorizations of mean serum potassium, based on categories of risk previously reported in the literature:^8,17,18: (1) <4.0, 4.0-4.5, or >4.5 mEq/L and (2) <4.0 versus ≥4.0 mEq/L.

Outcomes

We assessed three outcomes: in-hospital mortality, transfer to an intensive care unit (ICU), and length of stay (LOS). Admission to the ICU was defined as any evidence, after the exposure window, that the patient received care in the ICU. We excluded patients with ICU admissions during the exposure window from the analysis of this outcome. We calculated LOS as the difference between discharge date/time and the admission date/time.

Covariates and Comorbidity Adjustment

We obtained information on patient demographics (age and race) and identified the presence of comorbid conditions using previously derived and validated models.^19,20 We then further quantified these conditions into a single combined score to adjust for differences in presenting illness severity (including kidney disease) and help reduce confounding.²¹ To account for presenting severity of illness, we calculated the Laboratory-based Acute Physiology Score (LAPS-2).^22,23 LAPS-2 was developed for predicting mortality risk in general medical patients, but we previously externally validated it against other published clinical HF models in a cohort of patients hospitalized with acute decompensated HF.⁵LAPS-2 includes fourteen laboratory values at the time of admission (including blood urea nitrogen, creatinine, and anion gap) to calculate a score.^22,23 Thus, we adjusted for differences in baseline characteristics, including admission renal function.

Potassium Repletion

We evaluated whether patients received potassium during the exposure window (defined as any supplemental potassium order during the hospital stay) and the total number of days the patient was eligible for repletion (defined as a serum potassium result that was <4.0 mEq/L). We then recorded the total number of days repletion was given (using medication orders). We also calculated the ratio of days that repletion was received to the days that the patient was eligible for repletion. We also recorded all instances in which serum potassium values were <3.5 mEq/L at any time during the exposure window

Analysis

We evaluated the differences in patient characteristics across serum potassium categories. Categorical variables are presented as frequencies and percentages, whereas continuous variables are presented as means and standard deviations. For binary outcomes, we used generalized estimating equations (with a binomial family and logit link and clustering by hospital) to estimate incidence and calculate unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs). For LOS, we estimated the median and 95% CIs using quantile regression with clustered standard errors.²⁴ We calculated all models using both a binary exposure (<4.0 versus ≥4.0 mEq/L) and a three-level categorization (<4.0, 4.0-4.5, and >4.5 mEq/L) to explore the effects at the highest potassium level. We adjusted all models for age, race, LAPS-2 score, and combined comorbidity score. We conducted two sensitivity analyses. First, we restricted our sample to those who never received potassium during the exposure window, as these patients may be different than patients who required potassium repletion. Second, we stratified our findings by the presence or absence of acute or chronic renal insufficiency (defined as an admission creatinine >1 or the presence of a diagnostic code for renal insufficiency, as defined by Elixhauser et al.).^19,21 Statistical significance was set at an alpha of 0.05. Analysis was completed using Stata v15.1, StataCorp LP, College Station, Texas.

Cohort Description

We identified patients from 56 geographically diverse US hospitals, although most were located in either the northeast (n = 21; 38%) or south (n = 18; 32%). A total of 59% of the hospitals were teaching hospitals, and nearly 95% were in an urban setting. We identified 13,163 patients with HF, of which 4,995 (38.0%) met the inclusion criteria. We excluded 3,744 (28.4%) patients with LOS < 72 hours, 2,210 (16.8%) with admission potassium values outside of the defined range, and 896 (6.8%) with fewer than three potassium values during the exposure window. Of the patients who met the inclusion criteria, 2,080 (41.6%), 2,326 (46.6%), and 589 (11.8%) were categorized in the <4.0, 4.0-4.5, and >4.5 mEq/L groups, respectively (Table 1). The groups were clinically similar in terms of age, sex, illness severity (LAPS-2), and comorbidity score. Compared with other racial groups, black patients had higher potassium values. While the <4.0 and 4.0-4.5 mEq/L groups were relatively similar, the group with mean potassium >4.5 mEq/L had higher admission creatinine and a greater prevalence of chronic kidney disease, deficiency anemias, and chronic obstructive pulmonary disease (Table 1).

Serum Potassium Values

Individuals’ mean serum potassium within the 72-hour exposure window ranged from 2.9 to 5.8 mEq/L (Table 2). In the <4.0, 4-4.5, and >4.5 mEq/L cohorts respectively, patients had a median serum potassium of 3.8 mEq/L (2.9-3.9), 4.2 mEq/L (4.0-4.5), and 4.7 mEq/L (4.5-5.8) during the exposure window. Approximately half of the patients in the <4.0 mEq/L group had a serum potassium <3.5 mEq/L at some point during the exposure window. In contrast, <10% of the other groups had this low value during the exposure window.

Potassium Repletion

Patients in the <4.0 mEq/L group were much more likely to receive potassium repletion during the exposure window when compared with the 4.0-4.5 mEq/L (71.5% vs 40.5%) and >4.5 mEq/L (71.5% vs 26.7%) groups. On days that they were eligible for repletion (defined as a daily potassium value <4.0 mEq/L), patients with mean serum potassium >4.0 mEq/L were less likely to receive potassium repletion compared with those with values <4.0 mEq/L. There were 592 (28.5%), 1,383 (59.5%), and 432 (73.3%) patients in the <4.0, 4-4.5, and >4,5 mEq/L groups, respectively, who did not receive potassium repletion therapy during the exposure window.

Relationship of Serum Potassium Levels and Outcomes

Overall, 3.7% (n = 187) of patients died during the hospitalization, 2.4% (n = 98) were admitted to the ICU after the exposure window, and the median LOS was 5.6 days. We did not observe a significant association between mean serum potassium of <4.0 or 4.0-4.5 mEq/L and increased risk of mortality, ICU transfer, or LOS (Table 3). Our unadjusted analysis showed that patients with values >4.5 mEq/L had worse outcomes, including more deaths (5.3%; OR = 1.55; 95% CI: 1.01 to 2.39) and ICU admission (3.8%; OR = 2.10; 95% CI: 1.16 to 3.80) compared with those with values <4.0 mEq/L (Table 3). We also found that, compared with the <4.0 mEq/L group, the >4.5 mEq/L group showed just over a half-day longer LOS (0.6 days; 95% CI: 0.0 to 1.0; Table 3). However, we found that mortality and ICU admission results were attenuated after adjustment for age, race, comorbidity score, and LAPS-2 and were no longer statistically significant, whereas the association with LOS was consistent after adjustment. When using a binary exposure (<4.0 versus ≥4.0 mEq/L), we observed no association between mean potassium value and increased risk of mortality, ICU transfer, or LOS both before and after adjustment for age, race, LAPS-2, and comorbidity score (data not shown).

Sensitivity Analyses

In the sensitivity analysis restricted to those who did not receive potassium repletion during the exposure window, we continued to observe no association between the <4.0 and 4.0-4.5 mEq/L groups and outcomes (Table 3). In adjusted models for the >4.5 versus <4.0 mEq/L groups, risk estimates for mortality were similar to the full sample, but statistical significance was lost (OR = 1.56; 95% CI: 0.81 to 3.01). Adjusted risk estimates for ICU transfer were attenuated and not statistically significant (OR = 1.40; 95% CI: 0.60 to 3.26). However, LOS estimates were very similar to that observed in the full dataset (0.6 days; 95% CI: 0.1 to 1.2).

When stratifying our results by the presence or absence of acute or chronic renal insufficiency, we continued to observe no increased risk of any outcome in the 4.0-4.5 mEq/L compared with the <4.0 mEq/L groups across all strata (Table 4). Interestingly, even after adjustment, we did find that most of the increased risk of mortality and ICU admission in the >4.5 versus <4.0 mEq/L groups was among those without renal insufficiency (mortality OR = 3.03; ICU admission OR = 3.00) and was not statistically significant in those with renal insufficiency (mortality OR = 1.27; ICU admission OR = 1.63). Adjusted LOS estimates remained relatively similar in this stratified analysis.

The best approach to mild serum potassium value abnormalities in patients hospitalized with HF remains unclear. Many physicians reflexively replete potassium to ensure all patients maintain a serum value of >4.0 mEq/L.¹⁵ Yet, in this large observational study of patients hospitalized with an acute HF exacerbation, we found little evidence of association between serum potassium <4.0 mEq/L and negative outcomes.

Compared with those with mean potassium values <4.0 mEq/L (in unadjusted models), there was an association between potassium values of >4.5 mEq/L and increased risk of mortality and ICU transfer. This association was attenuated after adjustment, suggesting that factors beyond potassium values influenced the observed relationship. These findings seem to suggest that unobserved differences in the >4.5 mEq/L group (there were observed differences in this group, eg, greater presenting severity and higher comorbidity scores, suggesting that there were also unobserved differences), and not average potassium value, were the reasons for the observed differences in outcomes. However, we cannot rule out the possibility that potassium >4.5 mEq/L has some associated increased risk compared with mean potassium values of <4.0 mEq/L for patients hospitalized with acute decompensated HF.

Patients in our study routinely received exogenous potassium: more than 70% of patients received repletion at least once, although it is notable that the majority of patients in the 4.0-4.5 and >4.5 mEq/L groups did not receive repletion. Despite this practice, the data supporting this approach to potassium management for patients hospitalized with HF remain mixed. A serum potassium decline of >15% during an acute HF hospital stay has been reported as a predictor of all-cause mortality after controlling for disease severity and associated comorbidities, including renal function.²⁵ However, this study was focused on decline in admission potassium rather than an absolute cut-off (eg, >4.0 mEq/L). Additionally, potassium levels <3.9 mEq/L were associated with increased mortality in patients with acute HF following a myocardial infarction, but this study was not focused on patients with HF.²⁶ Most of the prior literature in patients with HF was conducted in patients in outpatient settings and examined patients who were not experiencing acute exacerbations. MacDonald and Struthers advocate that patients with HF have their potassium maintained above 4.0 mEq/L but did not specify whether this included patients with acute HF exacerbations.¹⁰ Additionally, many studies evaluating potassium repletion were conducted before widespread availability of angiotensin-converting enzyme (ACE) inhibitors or potassium-sparing diuretics, including spironolactone. Prior work has consistently reported that hyperkalemia, defined as serum potassium >4.5 mEq/L, is associated with mortality in patients with acute HF over the course of hospitalization (which aligned with the results from our sensitivity analysis), but concurrent medication regimens and underlying impaired renal function likely accounted for most of this association.¹⁷ The picture is further complicated as patients with acute HF presenting with hypokalemia may be at risk for subsequent hyperkalemia, and potassium repletion can stimulate aldosterone secretion, potentially exacerbating underlying HF.^27,28

These data are observational and are unlikely to change practice. However, daily potassium repletion represents a huge cost in time, money, and effort to the health system. Furthermore, the greatest burden occurs for the patients, who have labs drawn and values checked routinely and potassium administered orally or parenterally. While future randomized clinical trials (RCTs) would best examine the benefits of repletion, future pragmatic trials could attempt to disentangle the associated risks and benefits of potassium repletion in the absence of RCTs. Additionally, such studies could better take into account the role of concurrent medication use (like ACEs or angiotensin II receptor blockers), as well as assess the role of chronic renal insufficiency, acute kidney injury, and magnesium levels.²⁹

This study has limitations. Its retrospective design leads to unmeasured confounding; however, we adjusted for multiple variables (including LAPS-2), which reflect the severity of disease at admission and underlying kidney function at presentation, as well as other comorbid conditions. In addition, data from the cohort only extend to 2012, so more recent changes in practice may not be completely reflected. The nature of the data did not allow us to directly investigate the relationship between serum potassium and arrhythmias, although ICU transfer and mortality were used as surrogates. We were not able to examine the relationship between acute and chronic renal failure and potassium, as this was beyond the scope of this analysis. Given the hypothesis-generating nature of this study, adjustment for additional confounders, including concurrent medication use, was beyond the scope of this analysis.

In conclusion, the benefit of a serum potassium level >4.0 mEq/L in patients admitted with HF remains unclear. We did not observe that mean potassium values <4.0 mEq/L were associated with worse outcomes, and, more concerning, there may be some risk for patients with mean values >4.5 mEq/L.

Acknowledgments

Dr. Lagu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Disclosures

The authors report no potential conflicts of interest. Dr. Lagu has served as a consultant for the Yale Center for Outcomes Research and Evaluation, under contract to the Centers for Medicare and Medicaid Services, for which she has provided clinical and methodological expertise and input on the development, reevaluation, and implementation of hospital outcome and efficiency measures.

Funding

Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number K01HL114745 and R01 HL139985-01A1. Dr. Stefan is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number K01HL114631-01A1. Dr. Pack is supported by NHLBI 1K23HL135440. Dr. Lindenauer is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number 1K24HL132008.

Disclaimer

The views expressed in this manuscript do not necessarily reflect those of the Yale Center for Outcomes Research and Evaluation or the Centers for Medicare and Medicaid Services.

Heart failure (HF) is a leading cause of hospital admission and mortality, accounting for approximately 900,000 discharges in 2014.¹ One-year all-cause mortality risk has been estimated at 17% after hospitalization,² and roughly 50% of deaths are related to sudden cardiac death, mostly due to ventricular arrhythmia.³Potassium abnormalities occur frequently in hospitalized patients with HF, and serum potassium levels outside of the normal reference range (<3.5 and >5.0 mEq/L) have been consistently shown to predict morbidity and mortality.^4-9 However, confusion still surrounds the acute management of patients with potassium values in the lower normal range (3.5-4.0 mEq/L). Conventional clinical wisdom suggests that these patients must maintain a higher serum potassium, with a minimum value of 4.0 mEq/L often cited as the target value.¹⁰ Despite the limited evidence in the acute HF population underlying this practice, clinicians often reflexively order potassium supplementation to reach this goal.

The principles underlying potassium management in acute HF are complex. Both low and high values have been linked to fatal arrhythmias, notably ventricular fibrillation, and small serum changes often reflect large total body potassium fluctuations.¹¹ Recent literature links hypokalemia to general membrane hypoexcitability, skeletal muscle hyporeflexia, and arrhythmias initiated by reduced sodium-potassium adenosine triphosphatase activity, leading to increased intracellular calcium and regional variations in action potential duration.¹² Potassium abnormalities are common at admission and may be exacerbated by both acute illness and treatments given during hospitalization, including baseline potassium, acute kidney injury, aggressive diuretic therapy, or other potassium-related treatments and conditions.¹³ The success of potassium repletion may also be affected by the choice of HF therapies.¹⁴

The belief that patients with HF must maintain a potassium >4.0 mEq/L remains pervasive, with at least one family medicine guideline recommending that patients with HF maintain a serum potassium level >4.0 mEq/L.¹⁵ Considering this uncertainty and that potassium repletion in hospitalized patients is a daily occurrence consuming a noteworthy amount of healthcare resources, we aimed to evaluate the association between differences in normal inpatient serum potassium levels and outcomes in a large cohort of patients hospitalized for an acute HF exacerbation who presented with serum potassium within normal range (3.5-5.0 mEq/L).

Data Sources and Cohort Definition

The Institutional Review Board at Baystate Medical Center approved this study. We identified patients with HF who were admitted for more than 72 hours between January 2010 and December 2012 to hospitals contributing to the HealthFacts database, a multihospital dataset derived from the comprehensive electronic health records of 116 geographically and structurally diverse hospitals throughout the United States (Cerner Corp.). HealthFacts—which includes date-stamped pharmacy, laboratory, and billing information—contains records of more than 84 million acute admissions, emergency room visits, and ambulatory visits. We limited the sample to hospitals that contributed to the pharmacy, laboratory, and diagnosis segments.

We included patients who had a principal International Classification of Disease (ICD-9-CM) diagnosis of HF or a principal diagnosis of respiratory failure with secondary diagnosis of HF (ICD-9-CM codes for HF: 402.01, 402.11, 402.91, 404.01, 404.03, 404.11, 404.13, 404.91, 404.93, 428.xx¹⁶ and for respiratory failure: 518.81, 518.82, 518.84) and were 18 years or older. We ensured that patients were treated for acute decompensated HF during the hospitalization by restricting the cohort to patients in whom at least one HF therapy (eg, loop diuretics, metolazone, inotropes, and intra-aortic balloon pump) was initiated within the first two days of hospitalization. We excluded patients with a pediatric or psychiatric attending physician, those with elective admissions, and those who were transferred from or to another acute care facility because we could not accurately determine the onset or subsequent course of their illness.

Definition of Variables Describing Serum Potassium Levels

We limited the sample to patients hospitalized for longer than 72 hours in order to observe how initial potassium values influenced outcomes over the course of hospitalization. We chose an exposure window of 72 hours because this allowed, on average, three potential observations of serum potassium per patient. We further restricted the sample to those who had a normal potassium value (3.5-5.0 mEq/L) at admission (defined as 24 hours prior to admission through midnight of the day of admission) to ensure that the included patients did not have abnormal potassium values upon presentation. We identified the period of time from 24 hours prior to admission through 72 hours following admission as “the exposure window” (the time during which patients were eligible to be classified into average serum potassium levels of <4.0, 4.0-4.5, or >4.5 mEq/L). We excluded patients who, during this window, had fewer than three serum potassium levels drawn (“exposure” levels could be disproportionately influenced by a single value) or received sodium polystyrene (as this would indicate that the physicians felt the potassium was dangerously high). For patients with repeated hospitalizations, we randomly selected one visit for inclusion to reduce the risk of survivor bias. We calculated the mean of all serum potassium levels during the exposure window, including the admission value, and then evaluated two different categorizations of mean serum potassium, based on categories of risk previously reported in the literature:^8,17,18: (1) <4.0, 4.0-4.5, or >4.5 mEq/L and (2) <4.0 versus ≥4.0 mEq/L.

Outcomes

We assessed three outcomes: in-hospital mortality, transfer to an intensive care unit (ICU), and length of stay (LOS). Admission to the ICU was defined as any evidence, after the exposure window, that the patient received care in the ICU. We excluded patients with ICU admissions during the exposure window from the analysis of this outcome. We calculated LOS as the difference between discharge date/time and the admission date/time.

Covariates and Comorbidity Adjustment

We obtained information on patient demographics (age and race) and identified the presence of comorbid conditions using previously derived and validated models.^19,20 We then further quantified these conditions into a single combined score to adjust for differences in presenting illness severity (including kidney disease) and help reduce confounding.²¹ To account for presenting severity of illness, we calculated the Laboratory-based Acute Physiology Score (LAPS-2).^22,23 LAPS-2 was developed for predicting mortality risk in general medical patients, but we previously externally validated it against other published clinical HF models in a cohort of patients hospitalized with acute decompensated HF.⁵LAPS-2 includes fourteen laboratory values at the time of admission (including blood urea nitrogen, creatinine, and anion gap) to calculate a score.^22,23 Thus, we adjusted for differences in baseline characteristics, including admission renal function.

Potassium Repletion

We evaluated whether patients received potassium during the exposure window (defined as any supplemental potassium order during the hospital stay) and the total number of days the patient was eligible for repletion (defined as a serum potassium result that was <4.0 mEq/L). We then recorded the total number of days repletion was given (using medication orders). We also calculated the ratio of days that repletion was received to the days that the patient was eligible for repletion. We also recorded all instances in which serum potassium values were <3.5 mEq/L at any time during the exposure window

Analysis

We evaluated the differences in patient characteristics across serum potassium categories. Categorical variables are presented as frequencies and percentages, whereas continuous variables are presented as means and standard deviations. For binary outcomes, we used generalized estimating equations (with a binomial family and logit link and clustering by hospital) to estimate incidence and calculate unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs). For LOS, we estimated the median and 95% CIs using quantile regression with clustered standard errors.²⁴ We calculated all models using both a binary exposure (<4.0 versus ≥4.0 mEq/L) and a three-level categorization (<4.0, 4.0-4.5, and >4.5 mEq/L) to explore the effects at the highest potassium level. We adjusted all models for age, race, LAPS-2 score, and combined comorbidity score. We conducted two sensitivity analyses. First, we restricted our sample to those who never received potassium during the exposure window, as these patients may be different than patients who required potassium repletion. Second, we stratified our findings by the presence or absence of acute or chronic renal insufficiency (defined as an admission creatinine >1 or the presence of a diagnostic code for renal insufficiency, as defined by Elixhauser et al.).^19,21 Statistical significance was set at an alpha of 0.05. Analysis was completed using Stata v15.1, StataCorp LP, College Station, Texas.

Cohort Description

We identified patients from 56 geographically diverse US hospitals, although most were located in either the northeast (n = 21; 38%) or south (n = 18; 32%). A total of 59% of the hospitals were teaching hospitals, and nearly 95% were in an urban setting. We identified 13,163 patients with HF, of which 4,995 (38.0%) met the inclusion criteria. We excluded 3,744 (28.4%) patients with LOS < 72 hours, 2,210 (16.8%) with admission potassium values outside of the defined range, and 896 (6.8%) with fewer than three potassium values during the exposure window. Of the patients who met the inclusion criteria, 2,080 (41.6%), 2,326 (46.6%), and 589 (11.8%) were categorized in the <4.0, 4.0-4.5, and >4.5 mEq/L groups, respectively (Table 1). The groups were clinically similar in terms of age, sex, illness severity (LAPS-2), and comorbidity score. Compared with other racial groups, black patients had higher potassium values. While the <4.0 and 4.0-4.5 mEq/L groups were relatively similar, the group with mean potassium >4.5 mEq/L had higher admission creatinine and a greater prevalence of chronic kidney disease, deficiency anemias, and chronic obstructive pulmonary disease (Table 1).

Serum Potassium Values

Individuals’ mean serum potassium within the 72-hour exposure window ranged from 2.9 to 5.8 mEq/L (Table 2). In the <4.0, 4-4.5, and >4.5 mEq/L cohorts respectively, patients had a median serum potassium of 3.8 mEq/L (2.9-3.9), 4.2 mEq/L (4.0-4.5), and 4.7 mEq/L (4.5-5.8) during the exposure window. Approximately half of the patients in the <4.0 mEq/L group had a serum potassium <3.5 mEq/L at some point during the exposure window. In contrast, <10% of the other groups had this low value during the exposure window.

Potassium Repletion

Patients in the <4.0 mEq/L group were much more likely to receive potassium repletion during the exposure window when compared with the 4.0-4.5 mEq/L (71.5% vs 40.5%) and >4.5 mEq/L (71.5% vs 26.7%) groups. On days that they were eligible for repletion (defined as a daily potassium value <4.0 mEq/L), patients with mean serum potassium >4.0 mEq/L were less likely to receive potassium repletion compared with those with values <4.0 mEq/L. There were 592 (28.5%), 1,383 (59.5%), and 432 (73.3%) patients in the <4.0, 4-4.5, and >4,5 mEq/L groups, respectively, who did not receive potassium repletion therapy during the exposure window.

Relationship of Serum Potassium Levels and Outcomes

Overall, 3.7% (n = 187) of patients died during the hospitalization, 2.4% (n = 98) were admitted to the ICU after the exposure window, and the median LOS was 5.6 days. We did not observe a significant association between mean serum potassium of <4.0 or 4.0-4.5 mEq/L and increased risk of mortality, ICU transfer, or LOS (Table 3). Our unadjusted analysis showed that patients with values >4.5 mEq/L had worse outcomes, including more deaths (5.3%; OR = 1.55; 95% CI: 1.01 to 2.39) and ICU admission (3.8%; OR = 2.10; 95% CI: 1.16 to 3.80) compared with those with values <4.0 mEq/L (Table 3). We also found that, compared with the <4.0 mEq/L group, the >4.5 mEq/L group showed just over a half-day longer LOS (0.6 days; 95% CI: 0.0 to 1.0; Table 3). However, we found that mortality and ICU admission results were attenuated after adjustment for age, race, comorbidity score, and LAPS-2 and were no longer statistically significant, whereas the association with LOS was consistent after adjustment. When using a binary exposure (<4.0 versus ≥4.0 mEq/L), we observed no association between mean potassium value and increased risk of mortality, ICU transfer, or LOS both before and after adjustment for age, race, LAPS-2, and comorbidity score (data not shown).

Sensitivity Analyses

In the sensitivity analysis restricted to those who did not receive potassium repletion during the exposure window, we continued to observe no association between the <4.0 and 4.0-4.5 mEq/L groups and outcomes (Table 3). In adjusted models for the >4.5 versus <4.0 mEq/L groups, risk estimates for mortality were similar to the full sample, but statistical significance was lost (OR = 1.56; 95% CI: 0.81 to 3.01). Adjusted risk estimates for ICU transfer were attenuated and not statistically significant (OR = 1.40; 95% CI: 0.60 to 3.26). However, LOS estimates were very similar to that observed in the full dataset (0.6 days; 95% CI: 0.1 to 1.2).

When stratifying our results by the presence or absence of acute or chronic renal insufficiency, we continued to observe no increased risk of any outcome in the 4.0-4.5 mEq/L compared with the <4.0 mEq/L groups across all strata (Table 4). Interestingly, even after adjustment, we did find that most of the increased risk of mortality and ICU admission in the >4.5 versus <4.0 mEq/L groups was among those without renal insufficiency (mortality OR = 3.03; ICU admission OR = 3.00) and was not statistically significant in those with renal insufficiency (mortality OR = 1.27; ICU admission OR = 1.63). Adjusted LOS estimates remained relatively similar in this stratified analysis.

The best approach to mild serum potassium value abnormalities in patients hospitalized with HF remains unclear. Many physicians reflexively replete potassium to ensure all patients maintain a serum value of >4.0 mEq/L.¹⁵ Yet, in this large observational study of patients hospitalized with an acute HF exacerbation, we found little evidence of association between serum potassium <4.0 mEq/L and negative outcomes.

Compared with those with mean potassium values <4.0 mEq/L (in unadjusted models), there was an association between potassium values of >4.5 mEq/L and increased risk of mortality and ICU transfer. This association was attenuated after adjustment, suggesting that factors beyond potassium values influenced the observed relationship. These findings seem to suggest that unobserved differences in the >4.5 mEq/L group (there were observed differences in this group, eg, greater presenting severity and higher comorbidity scores, suggesting that there were also unobserved differences), and not average potassium value, were the reasons for the observed differences in outcomes. However, we cannot rule out the possibility that potassium >4.5 mEq/L has some associated increased risk compared with mean potassium values of <4.0 mEq/L for patients hospitalized with acute decompensated HF.

Patients in our study routinely received exogenous potassium: more than 70% of patients received repletion at least once, although it is notable that the majority of patients in the 4.0-4.5 and >4.5 mEq/L groups did not receive repletion. Despite this practice, the data supporting this approach to potassium management for patients hospitalized with HF remain mixed. A serum potassium decline of >15% during an acute HF hospital stay has been reported as a predictor of all-cause mortality after controlling for disease severity and associated comorbidities, including renal function.²⁵ However, this study was focused on decline in admission potassium rather than an absolute cut-off (eg, >4.0 mEq/L). Additionally, potassium levels <3.9 mEq/L were associated with increased mortality in patients with acute HF following a myocardial infarction, but this study was not focused on patients with HF.²⁶ Most of the prior literature in patients with HF was conducted in patients in outpatient settings and examined patients who were not experiencing acute exacerbations. MacDonald and Struthers advocate that patients with HF have their potassium maintained above 4.0 mEq/L but did not specify whether this included patients with acute HF exacerbations.¹⁰ Additionally, many studies evaluating potassium repletion were conducted before widespread availability of angiotensin-converting enzyme (ACE) inhibitors or potassium-sparing diuretics, including spironolactone. Prior work has consistently reported that hyperkalemia, defined as serum potassium >4.5 mEq/L, is associated with mortality in patients with acute HF over the course of hospitalization (which aligned with the results from our sensitivity analysis), but concurrent medication regimens and underlying impaired renal function likely accounted for most of this association.¹⁷ The picture is further complicated as patients with acute HF presenting with hypokalemia may be at risk for subsequent hyperkalemia, and potassium repletion can stimulate aldosterone secretion, potentially exacerbating underlying HF.^27,28

These data are observational and are unlikely to change practice. However, daily potassium repletion represents a huge cost in time, money, and effort to the health system. Furthermore, the greatest burden occurs for the patients, who have labs drawn and values checked routinely and potassium administered orally or parenterally. While future randomized clinical trials (RCTs) would best examine the benefits of repletion, future pragmatic trials could attempt to disentangle the associated risks and benefits of potassium repletion in the absence of RCTs. Additionally, such studies could better take into account the role of concurrent medication use (like ACEs or angiotensin II receptor blockers), as well as assess the role of chronic renal insufficiency, acute kidney injury, and magnesium levels.²⁹

This study has limitations. Its retrospective design leads to unmeasured confounding; however, we adjusted for multiple variables (including LAPS-2), which reflect the severity of disease at admission and underlying kidney function at presentation, as well as other comorbid conditions. In addition, data from the cohort only extend to 2012, so more recent changes in practice may not be completely reflected. The nature of the data did not allow us to directly investigate the relationship between serum potassium and arrhythmias, although ICU transfer and mortality were used as surrogates. We were not able to examine the relationship between acute and chronic renal failure and potassium, as this was beyond the scope of this analysis. Given the hypothesis-generating nature of this study, adjustment for additional confounders, including concurrent medication use, was beyond the scope of this analysis.

In conclusion, the benefit of a serum potassium level >4.0 mEq/L in patients admitted with HF remains unclear. We did not observe that mean potassium values <4.0 mEq/L were associated with worse outcomes, and, more concerning, there may be some risk for patients with mean values >4.5 mEq/L.

Acknowledgments

Dr. Lagu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Disclosures

The authors report no potential conflicts of interest. Dr. Lagu has served as a consultant for the Yale Center for Outcomes Research and Evaluation, under contract to the Centers for Medicare and Medicaid Services, for which she has provided clinical and methodological expertise and input on the development, reevaluation, and implementation of hospital outcome and efficiency measures.

Funding

Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number K01HL114745 and R01 HL139985-01A1. Dr. Stefan is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number K01HL114631-01A1. Dr. Pack is supported by NHLBI 1K23HL135440. Dr. Lindenauer is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number 1K24HL132008.

Disclaimer

The views expressed in this manuscript do not necessarily reflect those of the Yale Center for Outcomes Research and Evaluation or the Centers for Medicare and Medicaid Services.

The field of hospital medicine has expanded rapidly since its inception in the late 1990s, and currently, most hospitals in the United States employ or contract with hospital medicine groups (HMGs).^1-4 This dramatic growth began in response to several factors: primary care physicians (PCPs) opting out of inpatient care, the increasing acuity and complexity of inpatient care, and cost pressures on hospitals.^5,6 Recent studies associate greater use of hospitalists with increased hospital revenues and modest improvements in hospital financial performance.⁷ However, funding the hospitalist delivery model required hospitals to share the savings hospitalists generate through facility billing and quality incentives.

Hospitalists’ professional fee revenues alone generally do not fund their salaries. An average HMG serving adult patients requires $176,658 from the hospital to support a full-time physician.⁸ Determining the appropriate level of HMG support typically occurs through negotiation with hospital executives. During the last 10 years, HMG size and hospitalist compensation have risen steadily, combining to increase the hospitalist labor costs borne by hospitals.^4,8 Accordingly, hospital executives in challenging economic environments may pressure HMG leaders to accept diminished support or to demonstrate a better return on the hospital’s investment.

These negotiations are influenced by the beliefs of hospital executives about the value of the hospitalist labor model. Little is known about how hospital and health system executive leadership assess the value of hospitalists. A deeper understanding of executive attitudes and beliefs could inform HMG leaders seeking integrative (“win-win”) outcomes in contract and compensation negotiations. Members of the Society of Hospital Medicine (SHM) Practice Management Committee surveyed hospital executives to guide SHM program development. We sought to analyze transcripts from these interviews to describe how executives assess HMGs and to test the hypothesis that hospital executives apply specific financial models when determining the return on investment (ROI) from subsidizing an HMG.

Study Design, Setting, and Participants

Members of the SHM Practice Management Committee conducted interviews with a convenience sample of 24 key informants representing the following stakeholders at hospitals employing hospitalists: Chief Executive Officers (CEOs), Presidents, Vice Presidents, Chief Medical Officers (CMOs), and Chief Financial Officers (CFOs). Participants were recruited from 17 fee-for-service healthcare organizations, including rural, suburban, urban, community, and academic medical centers. The semi-structured interviews occurred in person between January and March 2018; each one lasted an average of 45 minutes and were designed to guide SHM program and product development. Twenty-eight executives were recruited by e-mail, and four did not complete the interview due to scheduling difficulty. All the participants provided informed consent. The University of Washington Institutional Review Board approved the secondary analysis of deidentified transcripts.

Interview Guide and Data Collection

All interviews followed a guide with eight demographic questions and 10 open-ended questions (Appendix). Cognitive interviews were performed with two hospital executives outside the study cohort, resulting in the addition of one question and rewording one question for clarity. One-on-one interviews were performed by 10 committee members (range, 1-3 interviews). All interview audios were recorded, and no field notes were kept. The goal of the interviews was to obtain an understanding of how hospital executives value the contributions and costs of hospitalist groups.

The interviews began with questions about the informant’s current interactions with hospitalists and the origin of the hospitalist group at their facility. Informants then described the value they feel hospitalists bring to their hospital and occasions they were surprised or dissatisfied with the clinical or financial value delivered by the hospitalists. Participants described how they calculate a return on investment (ROI) for their hospitalist group, nonfinancial benefits and disadvantages to hospitalists, and how they believe hospitalists should participate in risk-sharing contracts.

Data Analysis

The interview audiotapes were transcribed and deidentified. A sample of eight transcripts was verified by participants to ensure accuracy. Three investigators (AAW, RC, CC) reviewed a random sample of five transcripts to identify and codify preliminary themes. We applied a general inductive framework with a content analysis approach. Two investigators (TM and MC) read all transcripts independently, coding the presence of each theme and quotations exemplifying these themes using qualitative analysis software (Dedoose Version 7.0.23, SocioCultural Research Consultants). A third investigator (AAW) read all the transcripts and resolved differences of opinion. Themes and code application were discussed among the study team after the second and fifth transcripts to add or clarify codes. No new codes were identified after the first review of the preliminary codebook, although investigators intermittently used an “unknown” code through the 20^th transcript. After discussion to reach consensus, excerpts initially coded “unknown” were assigned existing codes; the 20^th transcript represents the approximate point of reaching thematic saturation.

Of the 24 participants, 18 (75%) were male, representing a variety of roles: 7 (29.2%) CMOs, 5 (20.8%) Presidents, 5 (20.8%) CFOs, 4 (16.7%) CEOs, and 3 (12.5%) Vice Presidents. The participants represented all regions (Midwest 12 [50%], South 6 [25%], West 4 [16.7%], and East 2 [8.3%], community size (Urban 11 [45.8%], Suburban 8 [33.3%], and Rural 5 [20.8%]), and Hospital Types (Community 11 [45.8%], Multihospital System 5 [20.8%], Academic 5 [20.8%], Safety Net 2 [8.3%], and Critical Access 1 [4.2%]). We present specific themes below and supporting quotations in Tables 1 and 2.

Current Value of the HMG at the Respondent’s Hospital

Most executives reported their hospital’s HMG had operated for over a decade and had developed an earlier, outdated value framework. Interviewees described an initial mix of financial pressures, shifts in physician work preferences, increasing patient acuity, resident labor shortages, and unsolved hospital throughput needs that triggered a reactive conversion from community PCP staffing to hospitalist care teams, followed by refinements to realize value.

“I think initially here it was to deal with the resident caps, right? So, at that moment, the solution that was put in place probably made a lot of sense. If that’s all someone came in with, now I’d be scratching my head and said, what are you thinking?” (President, #2)

Respondents perceived that HMGs provide value in many domains, including financial contributions, high-quality care, organizational efficiency, academics, leadership of interprofessional teams, effective communication, system improvement, and beneficial influence on the care environment and other employees. Regarding the measurable generation of financial benefit, documentation for improved billing accuracy, increased hospital efficiency (eg, lower length of stay, early discharges), and comanagement arrangements were commonly identified.

“I don’t want a urologist with a stethoscope, so I’m happy to have the hospitalists say, ‘Look, I’ll take care of the patient. You do the procedure.’ Well, that’s inherently valuable, whether we measure it or whether we don’t.” (CMO, #21)

Executives generally expressed satisfaction with their HMG’s quality of care and the related pay-for-performance financial benefits from payers, attributing success to hospitalists’ familiarity with inpatient systems and willingness to standardize.

“I just think it’s having one structure, one group to go to, a standard rather than trying to push it through the medical staff.” (VP, #18)

Executives reported that HMGs generate substantial value that is difficult to measure financially. For example, a large bundle of excerpts organized around communication with patients, nurses, and other providers.

“If we have the right hospitalist staff, to engage them with the nursing staff would help to reduce my turnover rate…and create a very positive morale within the nursing units. That’s huge. That’s nonfinancial” (President, #15)

Executives particularly appreciated hospitalists’ work to aggregate input from multiple specialists and present a cohesive explanation to patients. Executives also felt that HMGs create significant unmeasured value by improving processes and outcomes on service lines beyond hospital medicine, achieving this through culture change, involvement in leadership, hospital-wide process redesign, and running rapid response teams. Some executives expressed a desire for hospitalists to assume this global quality responsibility more explicitly as a job expectation.

Executives described how they would evaluate a de novo proposal for hospitalist services, usually enumerating key general domains without explaining specifically how they would measure each element. The following priorities emerged: clinical excellence, capacity to collaborate with hospital leadership, the scope of services provided, cultural fit/alignment, financial performance, contract cost, pay-for-performance measures, and turnover. Regarding financial performance, respondents expected to know the cost of the proposal but lacked a specific price threshold. Instead, they sought to understand the total value of the proposal through its effect on metrics such as facility fees or resource use. Nonetheless, cultural fit was a critical, overriding driver of the hypothetical decision, despite difficulty defining beyond estimates of teamwork, alignment with hospital priorities, and qualities of the group leader.

“For us, it usually ends being how do we mix personally, do we like them?” (CMO, #5)

Alignment and Collaboration

The related concepts of “collaboration” and “alignment” emerged as prominent themes during all interviews. Executives highly valued hospitalist groups that could demonstrate alignment with hospital priorities and often used this concept to summarize the HMG’s success or failure across a group of value domains.

“If you’re just coming in to fill a shift and see 10 patients, you have much less value than somebody who’s going to play that active partnership role… hospitalist services need to partner with hospitals and be intimately involved with the success of the hospital.” (CMO, #20)

Alignment sometimes manifested in a quantified, explicit way, through incentive plans or shared savings plans. However, it most often manifested as a broader sense that the hospitalists’ work targeted the same priorities as the executive leaders and that hospitalists genuinely cared about those priorities. A “shift-work mentality” was expressed by some as the antithesis of alignment. Incorporating hospitalist leaders in hospital leadership and frequent communication arose as mechanisms to increase alignment.

Ways HMGs Fail to Meet Expectations

Respondents described unresolved disadvantages to the hospitalist care model.

“I mean, OPPE, how do you do that for a hospitalist? How can you do it? It’s hard to attribute a patient to someone….it is a weakness and I think we all know it.” (CMO, #21)

Executives also worried about inconsistent handoffs with primary care providers and the field’s demographics, finding it disproportionately comprised of junior or transient physicians. They also hoped that hospitalist innovators would solve clinician burnout and the high cost of inpatient care. Disappointments specific to the local HMG revolved around difficulty developing shared models of value and mechanisms to achieve them.

“I would like to have more dialog between the hospital leadership team and the hospitalist group…I would like to see a little bit more collaboration.” (President, #13)

These challenges emerged not as a deficiency with hospital medicine as a specialty, but a failure at their specific facility to achieve the goal of alignment through joint strategic planning.

Calculating Value

When asked if their hospital had a formal process to evaluate ROI for their HMG, two dominant answers emerged: (1) the executive lacked a formal process for determining ROI and was unaware of one used at their facility or (2) the executive evaluated HMG performance based on multiple measures, including cost, but did not attempt to calculate ROI or a summary value. Several described the financial evaluation process as too difficult or unnecessary.

“No. It’s too difficult to extract that data. I would say the best proxy that we could do it is our case mix index on our medicine service line.” (CMO, #20)

“No, not a formal process, no… I question the value of some of the other things we do with the medical group…but not the value of the hospitalists… I don’t think we’ve done a formal assessment. I appreciate the flexibility, especially in a small hospital.” (President, #10)
 

Rarely, executives described specific financial calculations that served as a proxy for ROI. These included calculating a contribution margin to compare against the cost of salary support or the application of external survey benchmarking comparisons for productivity and salary to evaluate the appropriateness of a limited set of financial indicators. Twice respondents alluded to more sophisticated measurements conducted by the finance department but lacked familiarity with the process. Several executives described ROI calculations for specific projects and discrete business decisions involving hospitalists, particularly considering hiring an additional hospitalist.

Executives generally struggled to recall specific ways that the nonfinancial contributions of hospitalists were incorporated into executive decisions regarding the hospitalist group. Two related themes emerged: first, the belief that hospitals could not function effectively without hospitalists, making their presence an expected cost of doing business. Second, absent measures of HMG ROI, executives appeared to determine an approximate overall value of hospitalists, rather than parsing the various contributions. A few respondents expressed alarm at the rise in hospitalist salaries, whereas others acknowledged market forces beyond their control.

“… there is going to be more of a demand for hospitalists, which is definitely going to drive up the compensation. So, I don’t worry that the compensation will be driven up so high that there won’t be a return [on investment].” (CFO, #16)

Some urged individual hospitalists to develop a deeper understanding of what supports their salary to avoid strained relationships with executives.

Evolution and Risk-Sharing Contracts

Respondents described an evolving conceptualization of the hospitalist’s value, occurring at both a broad, long-term scale and at an incremental, annual scale through minor modifications to incentive pay schemes. For most executives, hiring hospitalists as replacements for PCPs had become necessary and not a source of novel value; many executives described it as “the cost of doing business.” Some described gradually deemphasizing relative value unit (RVU) production to recognize other contributions. Several reported their general appreciation of hospitalists evolved as specific hospitalists matured and demonstrated new contributions to hospital function. Some leaders tried to speculate about future phases of this evolution, although details were sparse.

Among respondents with greater implementation of risk-sharing contracts or ACOs, executives did not describe significantly different goals for hospitalists; executives emphasized that hospitalists should accelerate existing efforts to reduce inpatient costs, length of stay, healthcare-acquired conditions, unnecessary testing, and readmissions. A theme emerged around hospitalists supporting the continuum of care, through improved communication and increased alignment with health systems.

“Where I see the real benefit…is to figure out a way to use hospitalists and match them up with the primary care physicians on the outpatient side to truly develop an integrated population-based medicine practice for all our patients.” (President, #15)

Executives believed that communication and collaboration with PCPs and postacute care providers would attract more measurement.

Our findings provide hospitalists with insight into the approach hospital executives may follow when determining the rationale for and extent of financial support for HMGs. The results did not support our hypothesis that executives commonly determine the appropriate support by summing detailed quantitative models for various HMG contributions. Instead, most hospital executives appear to make decisions about the appropriateness of financial support based on a small number of basic financial or care quality metrics combined with a subjective assessment of the HMG’s broader alignment with hospital priorities. However, we did find substantial evidence that hospital executives’ expectations of hospitalists have evolved in the last decade, creating the potential for dissociation from how hospitalists prioritize and value their own efforts. Together, our findings suggest that enhanced communication, relationship building, and collaboration with hospital leaders may help HMGs to maintain a shared model of value with hospital executives.

The general absence of summary value calculations suggests specific opportunities, benefits, and risks for HMG group leaders (Table 3). An important opportunity relates to the communication agenda about unmeasured or nonfinancial contributions. Although executives recognized many of these, our data suggest a need for HMG leaders to educate hospital leaders about their unmeasured contributions proactively. Although some might recommend doing so by quantifying and financially rewarding key intangible contributions (eg, measuring leadership in culture change⁹), this entails important risks.¹⁰ Some experts propose that the proliferation of physician pay-for-performance schemes threatens medical professionalism, fails patients, and misunderstands what motivates physicians.¹¹ HMG groups that feel undervalued should hesitate before monetizing all aspects of their work, and consider emphasizing relationship-building as a platform for communication about their performance. Achieving better alignment with executives is not just an opportunity for HMG leaders, but for each hospitalist within the group. Although executives wanted to have deeper relationships with group members, this may not be feasible in large organizations. Instead, it is incumbent for HMG leaders to translate executives’ expectations and forge better alignment.

This work contributes new understanding of the expectations executives have for HMGs and individual hospitalists. This highlights opportunities for group leaders, hospitalists, medical educators, and quality improvement experts to produce a hospitalist labor force that can engage in productive and mutually satisfying relationships with hospital leaders. Hospitalists should strive to improve alignment and communication with executive groups.

Disclosures

The authors report no potential conflict of interest.

The field of hospital medicine has expanded rapidly since its inception in the late 1990s, and currently, most hospitals in the United States employ or contract with hospital medicine groups (HMGs).^1-4 This dramatic growth began in response to several factors: primary care physicians (PCPs) opting out of inpatient care, the increasing acuity and complexity of inpatient care, and cost pressures on hospitals.^5,6 Recent studies associate greater use of hospitalists with increased hospital revenues and modest improvements in hospital financial performance.⁷ However, funding the hospitalist delivery model required hospitals to share the savings hospitalists generate through facility billing and quality incentives.

Hospitalists’ professional fee revenues alone generally do not fund their salaries. An average HMG serving adult patients requires $176,658 from the hospital to support a full-time physician.⁸ Determining the appropriate level of HMG support typically occurs through negotiation with hospital executives. During the last 10 years, HMG size and hospitalist compensation have risen steadily, combining to increase the hospitalist labor costs borne by hospitals.^4,8 Accordingly, hospital executives in challenging economic environments may pressure HMG leaders to accept diminished support or to demonstrate a better return on the hospital’s investment.

These negotiations are influenced by the beliefs of hospital executives about the value of the hospitalist labor model. Little is known about how hospital and health system executive leadership assess the value of hospitalists. A deeper understanding of executive attitudes and beliefs could inform HMG leaders seeking integrative (“win-win”) outcomes in contract and compensation negotiations. Members of the Society of Hospital Medicine (SHM) Practice Management Committee surveyed hospital executives to guide SHM program development. We sought to analyze transcripts from these interviews to describe how executives assess HMGs and to test the hypothesis that hospital executives apply specific financial models when determining the return on investment (ROI) from subsidizing an HMG.

Study Design, Setting, and Participants

Members of the SHM Practice Management Committee conducted interviews with a convenience sample of 24 key informants representing the following stakeholders at hospitals employing hospitalists: Chief Executive Officers (CEOs), Presidents, Vice Presidents, Chief Medical Officers (CMOs), and Chief Financial Officers (CFOs). Participants were recruited from 17 fee-for-service healthcare organizations, including rural, suburban, urban, community, and academic medical centers. The semi-structured interviews occurred in person between January and March 2018; each one lasted an average of 45 minutes and were designed to guide SHM program and product development. Twenty-eight executives were recruited by e-mail, and four did not complete the interview due to scheduling difficulty. All the participants provided informed consent. The University of Washington Institutional Review Board approved the secondary analysis of deidentified transcripts.

Interview Guide and Data Collection

All interviews followed a guide with eight demographic questions and 10 open-ended questions (Appendix). Cognitive interviews were performed with two hospital executives outside the study cohort, resulting in the addition of one question and rewording one question for clarity. One-on-one interviews were performed by 10 committee members (range, 1-3 interviews). All interview audios were recorded, and no field notes were kept. The goal of the interviews was to obtain an understanding of how hospital executives value the contributions and costs of hospitalist groups.

The interviews began with questions about the informant’s current interactions with hospitalists and the origin of the hospitalist group at their facility. Informants then described the value they feel hospitalists bring to their hospital and occasions they were surprised or dissatisfied with the clinical or financial value delivered by the hospitalists. Participants described how they calculate a return on investment (ROI) for their hospitalist group, nonfinancial benefits and disadvantages to hospitalists, and how they believe hospitalists should participate in risk-sharing contracts.

Data Analysis

The interview audiotapes were transcribed and deidentified. A sample of eight transcripts was verified by participants to ensure accuracy. Three investigators (AAW, RC, CC) reviewed a random sample of five transcripts to identify and codify preliminary themes. We applied a general inductive framework with a content analysis approach. Two investigators (TM and MC) read all transcripts independently, coding the presence of each theme and quotations exemplifying these themes using qualitative analysis software (Dedoose Version 7.0.23, SocioCultural Research Consultants). A third investigator (AAW) read all the transcripts and resolved differences of opinion. Themes and code application were discussed among the study team after the second and fifth transcripts to add or clarify codes. No new codes were identified after the first review of the preliminary codebook, although investigators intermittently used an “unknown” code through the 20^th transcript. After discussion to reach consensus, excerpts initially coded “unknown” were assigned existing codes; the 20^th transcript represents the approximate point of reaching thematic saturation.

Of the 24 participants, 18 (75%) were male, representing a variety of roles: 7 (29.2%) CMOs, 5 (20.8%) Presidents, 5 (20.8%) CFOs, 4 (16.7%) CEOs, and 3 (12.5%) Vice Presidents. The participants represented all regions (Midwest 12 [50%], South 6 [25%], West 4 [16.7%], and East 2 [8.3%], community size (Urban 11 [45.8%], Suburban 8 [33.3%], and Rural 5 [20.8%]), and Hospital Types (Community 11 [45.8%], Multihospital System 5 [20.8%], Academic 5 [20.8%], Safety Net 2 [8.3%], and Critical Access 1 [4.2%]). We present specific themes below and supporting quotations in Tables 1 and 2.

Current Value of the HMG at the Respondent’s Hospital

Most executives reported their hospital’s HMG had operated for over a decade and had developed an earlier, outdated value framework. Interviewees described an initial mix of financial pressures, shifts in physician work preferences, increasing patient acuity, resident labor shortages, and unsolved hospital throughput needs that triggered a reactive conversion from community PCP staffing to hospitalist care teams, followed by refinements to realize value.

“I think initially here it was to deal with the resident caps, right? So, at that moment, the solution that was put in place probably made a lot of sense. If that’s all someone came in with, now I’d be scratching my head and said, what are you thinking?” (President, #2)

Respondents perceived that HMGs provide value in many domains, including financial contributions, high-quality care, organizational efficiency, academics, leadership of interprofessional teams, effective communication, system improvement, and beneficial influence on the care environment and other employees. Regarding the measurable generation of financial benefit, documentation for improved billing accuracy, increased hospital efficiency (eg, lower length of stay, early discharges), and comanagement arrangements were commonly identified.

“I don’t want a urologist with a stethoscope, so I’m happy to have the hospitalists say, ‘Look, I’ll take care of the patient. You do the procedure.’ Well, that’s inherently valuable, whether we measure it or whether we don’t.” (CMO, #21)

Executives generally expressed satisfaction with their HMG’s quality of care and the related pay-for-performance financial benefits from payers, attributing success to hospitalists’ familiarity with inpatient systems and willingness to standardize.

“I just think it’s having one structure, one group to go to, a standard rather than trying to push it through the medical staff.” (VP, #18)

Executives reported that HMGs generate substantial value that is difficult to measure financially. For example, a large bundle of excerpts organized around communication with patients, nurses, and other providers.

“If we have the right hospitalist staff, to engage them with the nursing staff would help to reduce my turnover rate…and create a very positive morale within the nursing units. That’s huge. That’s nonfinancial” (President, #15)

Executives particularly appreciated hospitalists’ work to aggregate input from multiple specialists and present a cohesive explanation to patients. Executives also felt that HMGs create significant unmeasured value by improving processes and outcomes on service lines beyond hospital medicine, achieving this through culture change, involvement in leadership, hospital-wide process redesign, and running rapid response teams. Some executives expressed a desire for hospitalists to assume this global quality responsibility more explicitly as a job expectation.

Executives described how they would evaluate a de novo proposal for hospitalist services, usually enumerating key general domains without explaining specifically how they would measure each element. The following priorities emerged: clinical excellence, capacity to collaborate with hospital leadership, the scope of services provided, cultural fit/alignment, financial performance, contract cost, pay-for-performance measures, and turnover. Regarding financial performance, respondents expected to know the cost of the proposal but lacked a specific price threshold. Instead, they sought to understand the total value of the proposal through its effect on metrics such as facility fees or resource use. Nonetheless, cultural fit was a critical, overriding driver of the hypothetical decision, despite difficulty defining beyond estimates of teamwork, alignment with hospital priorities, and qualities of the group leader.

“For us, it usually ends being how do we mix personally, do we like them?” (CMO, #5)

Alignment and Collaboration

The related concepts of “collaboration” and “alignment” emerged as prominent themes during all interviews. Executives highly valued hospitalist groups that could demonstrate alignment with hospital priorities and often used this concept to summarize the HMG’s success or failure across a group of value domains.

“If you’re just coming in to fill a shift and see 10 patients, you have much less value than somebody who’s going to play that active partnership role… hospitalist services need to partner with hospitals and be intimately involved with the success of the hospital.” (CMO, #20)

Alignment sometimes manifested in a quantified, explicit way, through incentive plans or shared savings plans. However, it most often manifested as a broader sense that the hospitalists’ work targeted the same priorities as the executive leaders and that hospitalists genuinely cared about those priorities. A “shift-work mentality” was expressed by some as the antithesis of alignment. Incorporating hospitalist leaders in hospital leadership and frequent communication arose as mechanisms to increase alignment.

Ways HMGs Fail to Meet Expectations

Respondents described unresolved disadvantages to the hospitalist care model.

“I mean, OPPE, how do you do that for a hospitalist? How can you do it? It’s hard to attribute a patient to someone….it is a weakness and I think we all know it.” (CMO, #21)

Executives also worried about inconsistent handoffs with primary care providers and the field’s demographics, finding it disproportionately comprised of junior or transient physicians. They also hoped that hospitalist innovators would solve clinician burnout and the high cost of inpatient care. Disappointments specific to the local HMG revolved around difficulty developing shared models of value and mechanisms to achieve them.

“I would like to have more dialog between the hospital leadership team and the hospitalist group…I would like to see a little bit more collaboration.” (President, #13)

These challenges emerged not as a deficiency with hospital medicine as a specialty, but a failure at their specific facility to achieve the goal of alignment through joint strategic planning.

Calculating Value

When asked if their hospital had a formal process to evaluate ROI for their HMG, two dominant answers emerged: (1) the executive lacked a formal process for determining ROI and was unaware of one used at their facility or (2) the executive evaluated HMG performance based on multiple measures, including cost, but did not attempt to calculate ROI or a summary value. Several described the financial evaluation process as too difficult or unnecessary.

“No. It’s too difficult to extract that data. I would say the best proxy that we could do it is our case mix index on our medicine service line.” (CMO, #20)

“No, not a formal process, no… I question the value of some of the other things we do with the medical group…but not the value of the hospitalists… I don’t think we’ve done a formal assessment. I appreciate the flexibility, especially in a small hospital.” (President, #10)
 

Rarely, executives described specific financial calculations that served as a proxy for ROI. These included calculating a contribution margin to compare against the cost of salary support or the application of external survey benchmarking comparisons for productivity and salary to evaluate the appropriateness of a limited set of financial indicators. Twice respondents alluded to more sophisticated measurements conducted by the finance department but lacked familiarity with the process. Several executives described ROI calculations for specific projects and discrete business decisions involving hospitalists, particularly considering hiring an additional hospitalist.

Executives generally struggled to recall specific ways that the nonfinancial contributions of hospitalists were incorporated into executive decisions regarding the hospitalist group. Two related themes emerged: first, the belief that hospitals could not function effectively without hospitalists, making their presence an expected cost of doing business. Second, absent measures of HMG ROI, executives appeared to determine an approximate overall value of hospitalists, rather than parsing the various contributions. A few respondents expressed alarm at the rise in hospitalist salaries, whereas others acknowledged market forces beyond their control.

“… there is going to be more of a demand for hospitalists, which is definitely going to drive up the compensation. So, I don’t worry that the compensation will be driven up so high that there won’t be a return [on investment].” (CFO, #16)

Some urged individual hospitalists to develop a deeper understanding of what supports their salary to avoid strained relationships with executives.

Evolution and Risk-Sharing Contracts

Respondents described an evolving conceptualization of the hospitalist’s value, occurring at both a broad, long-term scale and at an incremental, annual scale through minor modifications to incentive pay schemes. For most executives, hiring hospitalists as replacements for PCPs had become necessary and not a source of novel value; many executives described it as “the cost of doing business.” Some described gradually deemphasizing relative value unit (RVU) production to recognize other contributions. Several reported their general appreciation of hospitalists evolved as specific hospitalists matured and demonstrated new contributions to hospital function. Some leaders tried to speculate about future phases of this evolution, although details were sparse.

Among respondents with greater implementation of risk-sharing contracts or ACOs, executives did not describe significantly different goals for hospitalists; executives emphasized that hospitalists should accelerate existing efforts to reduce inpatient costs, length of stay, healthcare-acquired conditions, unnecessary testing, and readmissions. A theme emerged around hospitalists supporting the continuum of care, through improved communication and increased alignment with health systems.

“Where I see the real benefit…is to figure out a way to use hospitalists and match them up with the primary care physicians on the outpatient side to truly develop an integrated population-based medicine practice for all our patients.” (President, #15)

Executives believed that communication and collaboration with PCPs and postacute care providers would attract more measurement.

Our findings provide hospitalists with insight into the approach hospital executives may follow when determining the rationale for and extent of financial support for HMGs. The results did not support our hypothesis that executives commonly determine the appropriate support by summing detailed quantitative models for various HMG contributions. Instead, most hospital executives appear to make decisions about the appropriateness of financial support based on a small number of basic financial or care quality metrics combined with a subjective assessment of the HMG’s broader alignment with hospital priorities. However, we did find substantial evidence that hospital executives’ expectations of hospitalists have evolved in the last decade, creating the potential for dissociation from how hospitalists prioritize and value their own efforts. Together, our findings suggest that enhanced communication, relationship building, and collaboration with hospital leaders may help HMGs to maintain a shared model of value with hospital executives.

The general absence of summary value calculations suggests specific opportunities, benefits, and risks for HMG group leaders (Table 3). An important opportunity relates to the communication agenda about unmeasured or nonfinancial contributions. Although executives recognized many of these, our data suggest a need for HMG leaders to educate hospital leaders about their unmeasured contributions proactively. Although some might recommend doing so by quantifying and financially rewarding key intangible contributions (eg, measuring leadership in culture change⁹), this entails important risks.¹⁰ Some experts propose that the proliferation of physician pay-for-performance schemes threatens medical professionalism, fails patients, and misunderstands what motivates physicians.¹¹ HMG groups that feel undervalued should hesitate before monetizing all aspects of their work, and consider emphasizing relationship-building as a platform for communication about their performance. Achieving better alignment with executives is not just an opportunity for HMG leaders, but for each hospitalist within the group. Although executives wanted to have deeper relationships with group members, this may not be feasible in large organizations. Instead, it is incumbent for HMG leaders to translate executives’ expectations and forge better alignment.

This work contributes new understanding of the expectations executives have for HMGs and individual hospitalists. This highlights opportunities for group leaders, hospitalists, medical educators, and quality improvement experts to produce a hospitalist labor force that can engage in productive and mutually satisfying relationships with hospital leaders. Hospitalists should strive to improve alignment and communication with executive groups.

Disclosures

The authors report no potential conflict of interest.

The field of hospital medicine has expanded rapidly since its inception in the late 1990s, and currently, most hospitals in the United States employ or contract with hospital medicine groups (HMGs).^1-4 This dramatic growth began in response to several factors: primary care physicians (PCPs) opting out of inpatient care, the increasing acuity and complexity of inpatient care, and cost pressures on hospitals.^5,6 Recent studies associate greater use of hospitalists with increased hospital revenues and modest improvements in hospital financial performance.⁷ However, funding the hospitalist delivery model required hospitals to share the savings hospitalists generate through facility billing and quality incentives.

Hospitalists’ professional fee revenues alone generally do not fund their salaries. An average HMG serving adult patients requires $176,658 from the hospital to support a full-time physician.⁸ Determining the appropriate level of HMG support typically occurs through negotiation with hospital executives. During the last 10 years, HMG size and hospitalist compensation have risen steadily, combining to increase the hospitalist labor costs borne by hospitals.^4,8 Accordingly, hospital executives in challenging economic environments may pressure HMG leaders to accept diminished support or to demonstrate a better return on the hospital’s investment.

These negotiations are influenced by the beliefs of hospital executives about the value of the hospitalist labor model. Little is known about how hospital and health system executive leadership assess the value of hospitalists. A deeper understanding of executive attitudes and beliefs could inform HMG leaders seeking integrative (“win-win”) outcomes in contract and compensation negotiations. Members of the Society of Hospital Medicine (SHM) Practice Management Committee surveyed hospital executives to guide SHM program development. We sought to analyze transcripts from these interviews to describe how executives assess HMGs and to test the hypothesis that hospital executives apply specific financial models when determining the return on investment (ROI) from subsidizing an HMG.

Study Design, Setting, and Participants

Members of the SHM Practice Management Committee conducted interviews with a convenience sample of 24 key informants representing the following stakeholders at hospitals employing hospitalists: Chief Executive Officers (CEOs), Presidents, Vice Presidents, Chief Medical Officers (CMOs), and Chief Financial Officers (CFOs). Participants were recruited from 17 fee-for-service healthcare organizations, including rural, suburban, urban, community, and academic medical centers. The semi-structured interviews occurred in person between January and March 2018; each one lasted an average of 45 minutes and were designed to guide SHM program and product development. Twenty-eight executives were recruited by e-mail, and four did not complete the interview due to scheduling difficulty. All the participants provided informed consent. The University of Washington Institutional Review Board approved the secondary analysis of deidentified transcripts.

Interview Guide and Data Collection

All interviews followed a guide with eight demographic questions and 10 open-ended questions (Appendix). Cognitive interviews were performed with two hospital executives outside the study cohort, resulting in the addition of one question and rewording one question for clarity. One-on-one interviews were performed by 10 committee members (range, 1-3 interviews). All interview audios were recorded, and no field notes were kept. The goal of the interviews was to obtain an understanding of how hospital executives value the contributions and costs of hospitalist groups.

The interviews began with questions about the informant’s current interactions with hospitalists and the origin of the hospitalist group at their facility. Informants then described the value they feel hospitalists bring to their hospital and occasions they were surprised or dissatisfied with the clinical or financial value delivered by the hospitalists. Participants described how they calculate a return on investment (ROI) for their hospitalist group, nonfinancial benefits and disadvantages to hospitalists, and how they believe hospitalists should participate in risk-sharing contracts.

Data Analysis

The interview audiotapes were transcribed and deidentified. A sample of eight transcripts was verified by participants to ensure accuracy. Three investigators (AAW, RC, CC) reviewed a random sample of five transcripts to identify and codify preliminary themes. We applied a general inductive framework with a content analysis approach. Two investigators (TM and MC) read all transcripts independently, coding the presence of each theme and quotations exemplifying these themes using qualitative analysis software (Dedoose Version 7.0.23, SocioCultural Research Consultants). A third investigator (AAW) read all the transcripts and resolved differences of opinion. Themes and code application were discussed among the study team after the second and fifth transcripts to add or clarify codes. No new codes were identified after the first review of the preliminary codebook, although investigators intermittently used an “unknown” code through the 20^th transcript. After discussion to reach consensus, excerpts initially coded “unknown” were assigned existing codes; the 20^th transcript represents the approximate point of reaching thematic saturation.

Of the 24 participants, 18 (75%) were male, representing a variety of roles: 7 (29.2%) CMOs, 5 (20.8%) Presidents, 5 (20.8%) CFOs, 4 (16.7%) CEOs, and 3 (12.5%) Vice Presidents. The participants represented all regions (Midwest 12 [50%], South 6 [25%], West 4 [16.7%], and East 2 [8.3%], community size (Urban 11 [45.8%], Suburban 8 [33.3%], and Rural 5 [20.8%]), and Hospital Types (Community 11 [45.8%], Multihospital System 5 [20.8%], Academic 5 [20.8%], Safety Net 2 [8.3%], and Critical Access 1 [4.2%]). We present specific themes below and supporting quotations in Tables 1 and 2.

Current Value of the HMG at the Respondent’s Hospital

Most executives reported their hospital’s HMG had operated for over a decade and had developed an earlier, outdated value framework. Interviewees described an initial mix of financial pressures, shifts in physician work preferences, increasing patient acuity, resident labor shortages, and unsolved hospital throughput needs that triggered a reactive conversion from community PCP staffing to hospitalist care teams, followed by refinements to realize value.

“I think initially here it was to deal with the resident caps, right? So, at that moment, the solution that was put in place probably made a lot of sense. If that’s all someone came in with, now I’d be scratching my head and said, what are you thinking?” (President, #2)

Respondents perceived that HMGs provide value in many domains, including financial contributions, high-quality care, organizational efficiency, academics, leadership of interprofessional teams, effective communication, system improvement, and beneficial influence on the care environment and other employees. Regarding the measurable generation of financial benefit, documentation for improved billing accuracy, increased hospital efficiency (eg, lower length of stay, early discharges), and comanagement arrangements were commonly identified.

“I don’t want a urologist with a stethoscope, so I’m happy to have the hospitalists say, ‘Look, I’ll take care of the patient. You do the procedure.’ Well, that’s inherently valuable, whether we measure it or whether we don’t.” (CMO, #21)

Executives generally expressed satisfaction with their HMG’s quality of care and the related pay-for-performance financial benefits from payers, attributing success to hospitalists’ familiarity with inpatient systems and willingness to standardize.

“I just think it’s having one structure, one group to go to, a standard rather than trying to push it through the medical staff.” (VP, #18)

Executives reported that HMGs generate substantial value that is difficult to measure financially. For example, a large bundle of excerpts organized around communication with patients, nurses, and other providers.

“If we have the right hospitalist staff, to engage them with the nursing staff would help to reduce my turnover rate…and create a very positive morale within the nursing units. That’s huge. That’s nonfinancial” (President, #15)

Executives particularly appreciated hospitalists’ work to aggregate input from multiple specialists and present a cohesive explanation to patients. Executives also felt that HMGs create significant unmeasured value by improving processes and outcomes on service lines beyond hospital medicine, achieving this through culture change, involvement in leadership, hospital-wide process redesign, and running rapid response teams. Some executives expressed a desire for hospitalists to assume this global quality responsibility more explicitly as a job expectation.

Executives described how they would evaluate a de novo proposal for hospitalist services, usually enumerating key general domains without explaining specifically how they would measure each element. The following priorities emerged: clinical excellence, capacity to collaborate with hospital leadership, the scope of services provided, cultural fit/alignment, financial performance, contract cost, pay-for-performance measures, and turnover. Regarding financial performance, respondents expected to know the cost of the proposal but lacked a specific price threshold. Instead, they sought to understand the total value of the proposal through its effect on metrics such as facility fees or resource use. Nonetheless, cultural fit was a critical, overriding driver of the hypothetical decision, despite difficulty defining beyond estimates of teamwork, alignment with hospital priorities, and qualities of the group leader.

“For us, it usually ends being how do we mix personally, do we like them?” (CMO, #5)

Alignment and Collaboration

The related concepts of “collaboration” and “alignment” emerged as prominent themes during all interviews. Executives highly valued hospitalist groups that could demonstrate alignment with hospital priorities and often used this concept to summarize the HMG’s success or failure across a group of value domains.

“If you’re just coming in to fill a shift and see 10 patients, you have much less value than somebody who’s going to play that active partnership role… hospitalist services need to partner with hospitals and be intimately involved with the success of the hospital.” (CMO, #20)

Alignment sometimes manifested in a quantified, explicit way, through incentive plans or shared savings plans. However, it most often manifested as a broader sense that the hospitalists’ work targeted the same priorities as the executive leaders and that hospitalists genuinely cared about those priorities. A “shift-work mentality” was expressed by some as the antithesis of alignment. Incorporating hospitalist leaders in hospital leadership and frequent communication arose as mechanisms to increase alignment.

Ways HMGs Fail to Meet Expectations

Respondents described unresolved disadvantages to the hospitalist care model.

“I mean, OPPE, how do you do that for a hospitalist? How can you do it? It’s hard to attribute a patient to someone….it is a weakness and I think we all know it.” (CMO, #21)

Executives also worried about inconsistent handoffs with primary care providers and the field’s demographics, finding it disproportionately comprised of junior or transient physicians. They also hoped that hospitalist innovators would solve clinician burnout and the high cost of inpatient care. Disappointments specific to the local HMG revolved around difficulty developing shared models of value and mechanisms to achieve them.

“I would like to have more dialog between the hospital leadership team and the hospitalist group…I would like to see a little bit more collaboration.” (President, #13)

These challenges emerged not as a deficiency with hospital medicine as a specialty, but a failure at their specific facility to achieve the goal of alignment through joint strategic planning.

Calculating Value

When asked if their hospital had a formal process to evaluate ROI for their HMG, two dominant answers emerged: (1) the executive lacked a formal process for determining ROI and was unaware of one used at their facility or (2) the executive evaluated HMG performance based on multiple measures, including cost, but did not attempt to calculate ROI or a summary value. Several described the financial evaluation process as too difficult or unnecessary.

“No. It’s too difficult to extract that data. I would say the best proxy that we could do it is our case mix index on our medicine service line.” (CMO, #20)

“No, not a formal process, no… I question the value of some of the other things we do with the medical group…but not the value of the hospitalists… I don’t think we’ve done a formal assessment. I appreciate the flexibility, especially in a small hospital.” (President, #10)
 

Rarely, executives described specific financial calculations that served as a proxy for ROI. These included calculating a contribution margin to compare against the cost of salary support or the application of external survey benchmarking comparisons for productivity and salary to evaluate the appropriateness of a limited set of financial indicators. Twice respondents alluded to more sophisticated measurements conducted by the finance department but lacked familiarity with the process. Several executives described ROI calculations for specific projects and discrete business decisions involving hospitalists, particularly considering hiring an additional hospitalist.

Executives generally struggled to recall specific ways that the nonfinancial contributions of hospitalists were incorporated into executive decisions regarding the hospitalist group. Two related themes emerged: first, the belief that hospitals could not function effectively without hospitalists, making their presence an expected cost of doing business. Second, absent measures of HMG ROI, executives appeared to determine an approximate overall value of hospitalists, rather than parsing the various contributions. A few respondents expressed alarm at the rise in hospitalist salaries, whereas others acknowledged market forces beyond their control.

“… there is going to be more of a demand for hospitalists, which is definitely going to drive up the compensation. So, I don’t worry that the compensation will be driven up so high that there won’t be a return [on investment].” (CFO, #16)

Some urged individual hospitalists to develop a deeper understanding of what supports their salary to avoid strained relationships with executives.

Evolution and Risk-Sharing Contracts

Respondents described an evolving conceptualization of the hospitalist’s value, occurring at both a broad, long-term scale and at an incremental, annual scale through minor modifications to incentive pay schemes. For most executives, hiring hospitalists as replacements for PCPs had become necessary and not a source of novel value; many executives described it as “the cost of doing business.” Some described gradually deemphasizing relative value unit (RVU) production to recognize other contributions. Several reported their general appreciation of hospitalists evolved as specific hospitalists matured and demonstrated new contributions to hospital function. Some leaders tried to speculate about future phases of this evolution, although details were sparse.

Among respondents with greater implementation of risk-sharing contracts or ACOs, executives did not describe significantly different goals for hospitalists; executives emphasized that hospitalists should accelerate existing efforts to reduce inpatient costs, length of stay, healthcare-acquired conditions, unnecessary testing, and readmissions. A theme emerged around hospitalists supporting the continuum of care, through improved communication and increased alignment with health systems.

“Where I see the real benefit…is to figure out a way to use hospitalists and match them up with the primary care physicians on the outpatient side to truly develop an integrated population-based medicine practice for all our patients.” (President, #15)

Executives believed that communication and collaboration with PCPs and postacute care providers would attract more measurement.

Our findings provide hospitalists with insight into the approach hospital executives may follow when determining the rationale for and extent of financial support for HMGs. The results did not support our hypothesis that executives commonly determine the appropriate support by summing detailed quantitative models for various HMG contributions. Instead, most hospital executives appear to make decisions about the appropriateness of financial support based on a small number of basic financial or care quality metrics combined with a subjective assessment of the HMG’s broader alignment with hospital priorities. However, we did find substantial evidence that hospital executives’ expectations of hospitalists have evolved in the last decade, creating the potential for dissociation from how hospitalists prioritize and value their own efforts. Together, our findings suggest that enhanced communication, relationship building, and collaboration with hospital leaders may help HMGs to maintain a shared model of value with hospital executives.

The general absence of summary value calculations suggests specific opportunities, benefits, and risks for HMG group leaders (Table 3). An important opportunity relates to the communication agenda about unmeasured or nonfinancial contributions. Although executives recognized many of these, our data suggest a need for HMG leaders to educate hospital leaders about their unmeasured contributions proactively. Although some might recommend doing so by quantifying and financially rewarding key intangible contributions (eg, measuring leadership in culture change⁹), this entails important risks.¹⁰ Some experts propose that the proliferation of physician pay-for-performance schemes threatens medical professionalism, fails patients, and misunderstands what motivates physicians.¹¹ HMG groups that feel undervalued should hesitate before monetizing all aspects of their work, and consider emphasizing relationship-building as a platform for communication about their performance. Achieving better alignment with executives is not just an opportunity for HMG leaders, but for each hospitalist within the group. Although executives wanted to have deeper relationships with group members, this may not be feasible in large organizations. Instead, it is incumbent for HMG leaders to translate executives’ expectations and forge better alignment.

This work contributes new understanding of the expectations executives have for HMGs and individual hospitalists. This highlights opportunities for group leaders, hospitalists, medical educators, and quality improvement experts to produce a hospitalist labor force that can engage in productive and mutually satisfying relationships with hospital leaders. Hospitalists should strive to improve alignment and communication with executive groups.

Disclosures

The authors report no potential conflict of interest.

Immigrant children make up the fastest growing segment of the population in the United States.¹ While most immigrant children are fluent in English, approximately 40% live with a parent who has limited English proficiency (LEP; ie, speaks English less than “very well”).^2,3 In pediatrics, LEP status has been associated with longer hospitalizations,⁴ higher hospitalization costs,⁵ increased risk for serious adverse medical events,^4,6 and more frequent emergency department reutilization.⁷ In the inpatient setting, multiple aspects of care present a variety of communication challenges,⁸ which are amplified by shift work and workflow complexity that result in patients and families interacting with numerous providers over the course of an inpatient stay.

Increasing access to trained professional interpreters when caring for LEP patients improves communication, patient satisfaction, adherence, and mortality.^9-12 However, even when access to interpreter services is established, effective use is not guaranteed.¹³ Up to 57% of pediatricians report relying on family members to communicate with LEP patients and their caregivers;⁹ 23% of pediatric residents categorized LEP encounters as frustrating while 78% perceived care of LEP patients to be “misdirected” (eg, delay in diagnosis or discharge) because of associated language barriers.¹⁴

Understanding experiences of frontline inpatient medical providers and interpreters is crucial in identifying challenges and ways to optimize communication for hospitalized LEP patients and families. However, there is a paucity of literature exploring the perspectives of medical providers and interpreters as it relates to communication with hospitalized LEP children and families. In this study, we sought to identify barriers and drivers of effective communication with pediatric patients and families with LEP in the inpatient setting from the perspective of frontline medical providers and interpreters.

Study Design

This qualitative study used Group Level Assessment (GLA), a structured participatory methodology that allows diverse groups of stakeholders to generate and evaluate data in interactive sessions.^15-18 GLA structure promotes active participation, group problem-solving, and development of actionable plans, distinguishing it from focus groups and in-depth semistructured interviews.^15,19 This study received a human subject research exemption by the institutional review board.

Study Setting

Cincinnati Children’s Hospital Medical Center (CCHMC) is a large quaternary care center with ~200 patient encounters each day who require the use of interpreter services. Interpreters (in-person, video, and phone) are utilized during admission, formal family-centered rounds, hospital discharge, and other encounters with physicians, nurses, and other healthcare professionals. In-person interpreters are available in-house for Spanish and Arabic, with 18 additional languages available through regional vendors. Despite available resources, there is no standard way in which medical providers and interpreters work with one another.

Study Participants and Recruitment

Medical providers who care for hospitalized general pediatric patients were eligible to participate, including attending physicians, resident physicians, bedside nurses, and inpatient ancillary staff (eg, respiratory therapists, physical therapists). Interpreters employed by CCHMC with experience in the inpatient setting were also eligible. Individuals were recruited based on published recommendations to optimize discussion and group-thinking.¹⁵ Each participant was asked to take part in one GLA session. Participants were assigned to specific sessions based on roles (ie, physicians, nurses, and interpreters) to maximize engagement and minimize the impact of hierarchy.

Study Procedure

GLA involves a seven-step structured process (Appendix 1): climate setting, generating, appreciating, reflecting, understanding, selecting, and action.^15,18 Qualitative data were generated individually and anonymously by participants on flip charts in response to prompts such as: “I worry that LEP families___,” “The biggest challenge when using interpreter services is___,” and “I find___ works well in providing care for LEP families.” Prompts were developed by study investigators, modified based on input from nursing and interpreter services leadership, and finalized by GLA facilitators. Fifty-one unique prompts were utilized (Appendix 2); the number of prompts used (ranging from 15 to 32 prompts) per session was based on published recommendations.¹⁵ During sessions, study investigators took detailed notes, including verbatim transcription of participant quotes. Upon conclusion of the session, each participant completed a demographic survey, including years of experience, languages spoken and perceived fluency,²⁰ and ethnicity.

Data Analysis

Within each session, under the guidance of trained and experienced GLA facilitators (WB, HV), participants distilled and summarized qualitative data into themes, discussed and prioritized themes, and generated action items. Following completion of all sessions, analyzed data was compiled by the research team to determine similarities and differences across groups based on participant roles, consolidate themes into barriers and drivers of communication with LEP families, and determine any overlap of priorities for action. Findings were shared back with each group to ensure accuracy and relevance.

Participants

A total of 64 individuals participated (Table 1): hospital medicine physicians and residents (56%), inpatient nurses and ancillary staff (16%), and interpreters (28%). While 81% of physicians spoke multiple languages, only 25% reported speaking them well; two physicians were certified to communicate medical information without an interpreter present.

Themes Resulting from GLA Sessions

A total of four barriers (Table 2) and four drivers (Table 3) of effective communication with pediatric LEP patients and their families in the inpatient setting were identified by participants. Participants across all groups, despite enthusiasm around improving communication, were concerned about quality of care LEP families received, noting that the system is “designed to deliver less-good care” and that “we really haven’t figured out how to care for [LEP patients and families] in a [high-]quality and reliable way.” Variation in theme discussion was noted between groups based on participant role: physicians voiced concern about rapport with LEP families, nurses emphasized actionable tasks, and interpreters focused on heightened challenges in times of stress.

Barrier 1: Difficulties Accessing Interpreter Services

Medical providers (physicians and nurses) identified the “opaque process to access [interpreter] services” as one of their biggest challenges when communicating with LEP families. In particular, the process of scheduling interpreters was described as a “black box,” with physicians and nurses expressing difficulty determining if and when in-person interpreters were scheduled and uncertainty about when to use modalities other than in-person interpretation. Participants across groups highlighted the lack of systems knowledge from medical providers and limitations within the system that make predictable, timely, and reliable access to interpreters challenging, especially for uncommon languages. Medical providers desired more in-person interpreters who can “stay as long as clinically indicated,” citing frustration associated with using phone- and video-interpretation (eg, challenges locating technology, unfamiliarity with use, unreliable functionality of equipment). Interpreters voiced wanting to take time to finish each encounter fully without “being in a hurry because the next appointment is coming soon” or “rushing… in [to the next] session sweating.”

Barrier 2: Uncertainty in Communication with LEP Families

Participants across all groups described three areas of uncertainty as detailed in Table 2: (1) what to share and how to prioritize information during encounters with LEP patients and families, (2) what is communicated during interpretation, and (3) what LEP patients and families understand.

Barrier 3: Unclear and Inconsistent Expectations and Roles of Team Members

Given the complexity involved in communication between medical providers, interpreters, and families, participants across all groups reported feeling ill-prepared when navigating hospital encounters with LEP patients and families. Interpreters reported having little to no clinical context, medical providers reported having no knowledge of the assigned interpreter’s style, and both interpreters and medical providers reported that families have little idea of what to expect or how to engage. All groups voiced frustration about the lack of clarity regarding specific roles and scope of practice for each team member during an encounter, where multiple people end up “talking [or] using the interpreter at once.” Interpreters shared their expectations of medical providers to set the pace and lead conversations with LEP families. On the other hand, medical providers expressed a desire for interpreters to provide cultural context to the team without prompting and to interrupt during encounters when necessary to voice concerns or redirect conversations.

Barrier 4: Unmet Family Engagement Expectations

Participants across all groups articulated challenges with establishing rapport with LEP patients and families, sharing concerns that “inadequate communication” due to “cultural or language barriers” ultimately impacts quality of care. Participants reported decreased bidirectional engagement with and from LEP families. Medical providers not only noted difficulty in connecting with LEP families “on a more personal level” and providing frequent medical updates, but also felt that LEP families do not ask questions even when uncertain. Interpreters expressed concerns about medical providers “not [having] enough patience to answer families’ questions” while LEP families “shy away from asking questions.”

Driver 1: Utilizing a Team-Based Approach between Medical Providers and Interpreters

Participants from all groups emphasized that a mutual understanding of roles and shared expectations regarding communication and interpretation style, clinical context, and time constraints would establish a foundation for respect between medical providers and interpreters. They reported that a team-based approach to LEP patient and family encounters were crucial to achieving effective communication.

Driver 2: Understanding the Role of Cultural Context in Providing Culturally Effective Care.

Participants across all groups highlighted three different aspects of cultural context that drive effective communication: (1) medical providers’ perception of the family’s culture; (2) LEP families’ knowledge about the culture and healthcare system in the US, and (3) medical providers insight into their own preconceived ideas about LEP families.

Driver 3: Practicing Empathy for Patients and Families

All participants reported that respect for diversity and consideration of the backgrounds and perspectives of LEP patients and families are necessary. Furthermore, both medical providers and interpreters articulated a need to remain patient and mindful when interacting with LEP families despite challenges, especially since, as noted by interpreters, encounters may “take longer, but it’s for a reason.”

Driver 4: Using Effective Family-Centered Communication Strategies

Participants identified the use of effective family-centered communication principles as a driver to optimal communication. Many of the principles identified by medical providers and interpreters are generally applicable to all hospitalized patients and families regardless of English proficiency: optimizing verbal communication (eg, using shorter sentences, pausing to allow for interpretation), optimizing nonverbal communication (eg, setting, position, and body language), and assessment of family understanding and engagement (eg, use of teach back).

Frontline medical providers and interpreters identified barriers and drivers that impact communication with LEP patients and families during hospitalization. To our knowledge, this is the first study that uses a participatory method to explore the perspectives of medical providers and interpreters who care for LEP children and families in the inpatient setting. Despite existing difficulties and concerns regarding language barriers and its impact on quality of care for hospitalized LEP patients and families, participants were enthusiastic about how identified barriers and drivers may inform future improvement efforts. Notable action steps for future improvement discussed by our participants included: increased use and functionality of technology for timely and predictable access to interpreters, deliberate training for providers focused on delivery of culturally-effective care, consistent use of family-centered communication strategies including teach-back, and implementing interdisciplinary expectation setting through “presessions” before encounters with LEP families.

Participants elaborated on several barriers previously described in the literature including time constraints and technical problems.^14,21,22 Such barriers may serve as deterrents to consistent and appropriate use of interpreters in healthcare settings.⁹ A heavy reliance on off-site interpreters (including phone- or video-interpreters) and lack of knowledge regarding resource availability likely amplified frustration for medical providers. Communication with LEP families can be daunting, especially when medical providers do not care for LEP families or work with interpreters on a regular basis.¹⁴ Standardizing the education of medical providers regarding available resources, as well as the logistics, process, and parameters for scheduling interpreters and using technology, was an action step identified by our GLA participants. Targeted education about the logistics of accessing interpreter services and having standardized ways to make technology use easier (ie, one-touch dialing in hospital rooms) has been associated with increased interpreter use and decreased interpreter-related delays in care.²³

Our frontline medical providers expressed added concern about not spending as much time with LEP families. In fact, LEP families in the literature have perceived medical providers to spend less time with their children compared to their English-proficient counterparts.²⁴ Language and cultural barriers, both perceived and real, may limit medical provider rapport with LEP patients and families¹⁴ and likely contribute to medical providers relying on their preconceived assumptions instead.²⁵ Cultural competency education for medical providers, as highlighted by our GLA participants as an action item, can be used to provide more comprehensive and effective care.^26,27

In addition to enhancing cultural humility through education, our participants emphasized the use of family-centered communication strategies as a driver of optimal family engagement and understanding. Actively inviting questions from families and utilizing teach-back, an established evidence-based strategy^28-30 discussed by our participants, can be particularly powerful in assessing family understanding and engagement. While information should be presented in plain language for families in all encounters,³¹ these evidence-based practices are of particular importance when communicating with LEP families. They promote effective communication, empower families to share concerns in a structured manner, and allow medical providers to address matters in real-time with interpreters present.

Finally, our participants highlighted the need for partnerships between providers and interpreter services, noting unclear roles and expectations among interpreters and medical providers as a major barrier. Specifically, physicians noted confusion regarding the scope of an interpreter’s practice. Participants from GLA sessions discussed the importance of a team-based approach and suggested implementing a “presession” prior to encounters with LEP patients and families. Presessions—a concept well accepted among interpreters and recommended by consensus-based practice guidelines—enable medical providers and interpreters to establish shared expectations about scope of practice, communication, interpretation style, time constraints, and medical context prior to patient encounters.^32,33

There are several limitations to our study. First, individuals who chose to participate were likely highly motivated by their clinical experiences with LEP patients and invested in improving communication with LEP families. Second, the study is limited in generalizability, as it was conducted at a single academic institution in a Midwestern city. Despite regional variations in available resources as well as patient and workforce demographics, our findings regarding major themes are in agreement with previously published literature and further add to our understanding of ways to improve communication with this vulnerable population across the care spectrum. Lastly, we were logistically limited in our ability to elicit the perspectives of LEP families due to the participatory nature of GLA; the need for multiple interpreters to simultaneously interact with LEP individuals would have not only hindered active LEP family participation but may have also biased the data generated by patients and families, as the services interpreters provide during their inpatient stay was the focus of our study. Engaging LEP families in their preferred language using participatory methods should be considered for future studies.

In conclusion, frontline providers of medical and language services identified barriers and drivers impacting the effective use of interpreter services when communicating with LEP families during hospitalization. Our enhanced understanding of barriers and drivers, as well as identified actionable interventions, will inform future improvement of communication and interactions with LEP families that contributes to effective and efficient family centered care. A framework for the development and implementation of organizational strategies aimed at improving communication with LEP families must include a thorough assessment of impact, feasibility, stakeholder involvement, and sustainability of specific interventions. While there is no simple formula to improve language services, health systems should establish and adopt language access policies, standardize communication practices, and develop processes to optimize the use of language services in the hospital. Furthermore, engagement with LEP families to better understand their perceptions and experiences with the healthcare system is crucial to improve communication between medical providers and LEP families in the inpatient setting and should be the subject of future studies.

Disclosures

The authors have no conflicts of interest to disclose.

Funding

No external funding was secured for this study. Dr. Joanna Thomson is supported by the Agency for Healthcare Research and Quality (Grant #K08 HS025138). Dr. Raglin Bignall was supported through a Ruth L. Kirschstein National Research Service Award (T32HP10027) when the study was conducted. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding organizations. The funding organizations had no role in the design, preparation, review, or approval of this paper.

Immigrant children make up the fastest growing segment of the population in the United States.¹ While most immigrant children are fluent in English, approximately 40% live with a parent who has limited English proficiency (LEP; ie, speaks English less than “very well”).^2,3 In pediatrics, LEP status has been associated with longer hospitalizations,⁴ higher hospitalization costs,⁵ increased risk for serious adverse medical events,^4,6 and more frequent emergency department reutilization.⁷ In the inpatient setting, multiple aspects of care present a variety of communication challenges,⁸ which are amplified by shift work and workflow complexity that result in patients and families interacting with numerous providers over the course of an inpatient stay.

Increasing access to trained professional interpreters when caring for LEP patients improves communication, patient satisfaction, adherence, and mortality.^9-12 However, even when access to interpreter services is established, effective use is not guaranteed.¹³ Up to 57% of pediatricians report relying on family members to communicate with LEP patients and their caregivers;⁹ 23% of pediatric residents categorized LEP encounters as frustrating while 78% perceived care of LEP patients to be “misdirected” (eg, delay in diagnosis or discharge) because of associated language barriers.¹⁴

Understanding experiences of frontline inpatient medical providers and interpreters is crucial in identifying challenges and ways to optimize communication for hospitalized LEP patients and families. However, there is a paucity of literature exploring the perspectives of medical providers and interpreters as it relates to communication with hospitalized LEP children and families. In this study, we sought to identify barriers and drivers of effective communication with pediatric patients and families with LEP in the inpatient setting from the perspective of frontline medical providers and interpreters.

Study Design

This qualitative study used Group Level Assessment (GLA), a structured participatory methodology that allows diverse groups of stakeholders to generate and evaluate data in interactive sessions.^15-18 GLA structure promotes active participation, group problem-solving, and development of actionable plans, distinguishing it from focus groups and in-depth semistructured interviews.^15,19 This study received a human subject research exemption by the institutional review board.

Study Setting

Cincinnati Children’s Hospital Medical Center (CCHMC) is a large quaternary care center with ~200 patient encounters each day who require the use of interpreter services. Interpreters (in-person, video, and phone) are utilized during admission, formal family-centered rounds, hospital discharge, and other encounters with physicians, nurses, and other healthcare professionals. In-person interpreters are available in-house for Spanish and Arabic, with 18 additional languages available through regional vendors. Despite available resources, there is no standard way in which medical providers and interpreters work with one another.

Study Participants and Recruitment

Medical providers who care for hospitalized general pediatric patients were eligible to participate, including attending physicians, resident physicians, bedside nurses, and inpatient ancillary staff (eg, respiratory therapists, physical therapists). Interpreters employed by CCHMC with experience in the inpatient setting were also eligible. Individuals were recruited based on published recommendations to optimize discussion and group-thinking.¹⁵ Each participant was asked to take part in one GLA session. Participants were assigned to specific sessions based on roles (ie, physicians, nurses, and interpreters) to maximize engagement and minimize the impact of hierarchy.

Study Procedure

GLA involves a seven-step structured process (Appendix 1): climate setting, generating, appreciating, reflecting, understanding, selecting, and action.^15,18 Qualitative data were generated individually and anonymously by participants on flip charts in response to prompts such as: “I worry that LEP families___,” “The biggest challenge when using interpreter services is___,” and “I find___ works well in providing care for LEP families.” Prompts were developed by study investigators, modified based on input from nursing and interpreter services leadership, and finalized by GLA facilitators. Fifty-one unique prompts were utilized (Appendix 2); the number of prompts used (ranging from 15 to 32 prompts) per session was based on published recommendations.¹⁵ During sessions, study investigators took detailed notes, including verbatim transcription of participant quotes. Upon conclusion of the session, each participant completed a demographic survey, including years of experience, languages spoken and perceived fluency,²⁰ and ethnicity.

Data Analysis

Within each session, under the guidance of trained and experienced GLA facilitators (WB, HV), participants distilled and summarized qualitative data into themes, discussed and prioritized themes, and generated action items. Following completion of all sessions, analyzed data was compiled by the research team to determine similarities and differences across groups based on participant roles, consolidate themes into barriers and drivers of communication with LEP families, and determine any overlap of priorities for action. Findings were shared back with each group to ensure accuracy and relevance.

Participants

A total of 64 individuals participated (Table 1): hospital medicine physicians and residents (56%), inpatient nurses and ancillary staff (16%), and interpreters (28%). While 81% of physicians spoke multiple languages, only 25% reported speaking them well; two physicians were certified to communicate medical information without an interpreter present.

Themes Resulting from GLA Sessions

A total of four barriers (Table 2) and four drivers (Table 3) of effective communication with pediatric LEP patients and their families in the inpatient setting were identified by participants. Participants across all groups, despite enthusiasm around improving communication, were concerned about quality of care LEP families received, noting that the system is “designed to deliver less-good care” and that “we really haven’t figured out how to care for [LEP patients and families] in a [high-]quality and reliable way.” Variation in theme discussion was noted between groups based on participant role: physicians voiced concern about rapport with LEP families, nurses emphasized actionable tasks, and interpreters focused on heightened challenges in times of stress.

Barrier 1: Difficulties Accessing Interpreter Services

Medical providers (physicians and nurses) identified the “opaque process to access [interpreter] services” as one of their biggest challenges when communicating with LEP families. In particular, the process of scheduling interpreters was described as a “black box,” with physicians and nurses expressing difficulty determining if and when in-person interpreters were scheduled and uncertainty about when to use modalities other than in-person interpretation. Participants across groups highlighted the lack of systems knowledge from medical providers and limitations within the system that make predictable, timely, and reliable access to interpreters challenging, especially for uncommon languages. Medical providers desired more in-person interpreters who can “stay as long as clinically indicated,” citing frustration associated with using phone- and video-interpretation (eg, challenges locating technology, unfamiliarity with use, unreliable functionality of equipment). Interpreters voiced wanting to take time to finish each encounter fully without “being in a hurry because the next appointment is coming soon” or “rushing… in [to the next] session sweating.”

Barrier 2: Uncertainty in Communication with LEP Families

Participants across all groups described three areas of uncertainty as detailed in Table 2: (1) what to share and how to prioritize information during encounters with LEP patients and families, (2) what is communicated during interpretation, and (3) what LEP patients and families understand.

Barrier 3: Unclear and Inconsistent Expectations and Roles of Team Members

Given the complexity involved in communication between medical providers, interpreters, and families, participants across all groups reported feeling ill-prepared when navigating hospital encounters with LEP patients and families. Interpreters reported having little to no clinical context, medical providers reported having no knowledge of the assigned interpreter’s style, and both interpreters and medical providers reported that families have little idea of what to expect or how to engage. All groups voiced frustration about the lack of clarity regarding specific roles and scope of practice for each team member during an encounter, where multiple people end up “talking [or] using the interpreter at once.” Interpreters shared their expectations of medical providers to set the pace and lead conversations with LEP families. On the other hand, medical providers expressed a desire for interpreters to provide cultural context to the team without prompting and to interrupt during encounters when necessary to voice concerns or redirect conversations.

Barrier 4: Unmet Family Engagement Expectations

Participants across all groups articulated challenges with establishing rapport with LEP patients and families, sharing concerns that “inadequate communication” due to “cultural or language barriers” ultimately impacts quality of care. Participants reported decreased bidirectional engagement with and from LEP families. Medical providers not only noted difficulty in connecting with LEP families “on a more personal level” and providing frequent medical updates, but also felt that LEP families do not ask questions even when uncertain. Interpreters expressed concerns about medical providers “not [having] enough patience to answer families’ questions” while LEP families “shy away from asking questions.”

Driver 1: Utilizing a Team-Based Approach between Medical Providers and Interpreters

Participants from all groups emphasized that a mutual understanding of roles and shared expectations regarding communication and interpretation style, clinical context, and time constraints would establish a foundation for respect between medical providers and interpreters. They reported that a team-based approach to LEP patient and family encounters were crucial to achieving effective communication.

Driver 2: Understanding the Role of Cultural Context in Providing Culturally Effective Care.

Participants across all groups highlighted three different aspects of cultural context that drive effective communication: (1) medical providers’ perception of the family’s culture; (2) LEP families’ knowledge about the culture and healthcare system in the US, and (3) medical providers insight into their own preconceived ideas about LEP families.

Driver 3: Practicing Empathy for Patients and Families

All participants reported that respect for diversity and consideration of the backgrounds and perspectives of LEP patients and families are necessary. Furthermore, both medical providers and interpreters articulated a need to remain patient and mindful when interacting with LEP families despite challenges, especially since, as noted by interpreters, encounters may “take longer, but it’s for a reason.”

Driver 4: Using Effective Family-Centered Communication Strategies

Participants identified the use of effective family-centered communication principles as a driver to optimal communication. Many of the principles identified by medical providers and interpreters are generally applicable to all hospitalized patients and families regardless of English proficiency: optimizing verbal communication (eg, using shorter sentences, pausing to allow for interpretation), optimizing nonverbal communication (eg, setting, position, and body language), and assessment of family understanding and engagement (eg, use of teach back).

Frontline medical providers and interpreters identified barriers and drivers that impact communication with LEP patients and families during hospitalization. To our knowledge, this is the first study that uses a participatory method to explore the perspectives of medical providers and interpreters who care for LEP children and families in the inpatient setting. Despite existing difficulties and concerns regarding language barriers and its impact on quality of care for hospitalized LEP patients and families, participants were enthusiastic about how identified barriers and drivers may inform future improvement efforts. Notable action steps for future improvement discussed by our participants included: increased use and functionality of technology for timely and predictable access to interpreters, deliberate training for providers focused on delivery of culturally-effective care, consistent use of family-centered communication strategies including teach-back, and implementing interdisciplinary expectation setting through “presessions” before encounters with LEP families.

Participants elaborated on several barriers previously described in the literature including time constraints and technical problems.^14,21,22 Such barriers may serve as deterrents to consistent and appropriate use of interpreters in healthcare settings.⁹ A heavy reliance on off-site interpreters (including phone- or video-interpreters) and lack of knowledge regarding resource availability likely amplified frustration for medical providers. Communication with LEP families can be daunting, especially when medical providers do not care for LEP families or work with interpreters on a regular basis.¹⁴ Standardizing the education of medical providers regarding available resources, as well as the logistics, process, and parameters for scheduling interpreters and using technology, was an action step identified by our GLA participants. Targeted education about the logistics of accessing interpreter services and having standardized ways to make technology use easier (ie, one-touch dialing in hospital rooms) has been associated with increased interpreter use and decreased interpreter-related delays in care.²³

Our frontline medical providers expressed added concern about not spending as much time with LEP families. In fact, LEP families in the literature have perceived medical providers to spend less time with their children compared to their English-proficient counterparts.²⁴ Language and cultural barriers, both perceived and real, may limit medical provider rapport with LEP patients and families¹⁴ and likely contribute to medical providers relying on their preconceived assumptions instead.²⁵ Cultural competency education for medical providers, as highlighted by our GLA participants as an action item, can be used to provide more comprehensive and effective care.^26,27

In addition to enhancing cultural humility through education, our participants emphasized the use of family-centered communication strategies as a driver of optimal family engagement and understanding. Actively inviting questions from families and utilizing teach-back, an established evidence-based strategy^28-30 discussed by our participants, can be particularly powerful in assessing family understanding and engagement. While information should be presented in plain language for families in all encounters,³¹ these evidence-based practices are of particular importance when communicating with LEP families. They promote effective communication, empower families to share concerns in a structured manner, and allow medical providers to address matters in real-time with interpreters present.

Finally, our participants highlighted the need for partnerships between providers and interpreter services, noting unclear roles and expectations among interpreters and medical providers as a major barrier. Specifically, physicians noted confusion regarding the scope of an interpreter’s practice. Participants from GLA sessions discussed the importance of a team-based approach and suggested implementing a “presession” prior to encounters with LEP patients and families. Presessions—a concept well accepted among interpreters and recommended by consensus-based practice guidelines—enable medical providers and interpreters to establish shared expectations about scope of practice, communication, interpretation style, time constraints, and medical context prior to patient encounters.^32,33

There are several limitations to our study. First, individuals who chose to participate were likely highly motivated by their clinical experiences with LEP patients and invested in improving communication with LEP families. Second, the study is limited in generalizability, as it was conducted at a single academic institution in a Midwestern city. Despite regional variations in available resources as well as patient and workforce demographics, our findings regarding major themes are in agreement with previously published literature and further add to our understanding of ways to improve communication with this vulnerable population across the care spectrum. Lastly, we were logistically limited in our ability to elicit the perspectives of LEP families due to the participatory nature of GLA; the need for multiple interpreters to simultaneously interact with LEP individuals would have not only hindered active LEP family participation but may have also biased the data generated by patients and families, as the services interpreters provide during their inpatient stay was the focus of our study. Engaging LEP families in their preferred language using participatory methods should be considered for future studies.

In conclusion, frontline providers of medical and language services identified barriers and drivers impacting the effective use of interpreter services when communicating with LEP families during hospitalization. Our enhanced understanding of barriers and drivers, as well as identified actionable interventions, will inform future improvement of communication and interactions with LEP families that contributes to effective and efficient family centered care. A framework for the development and implementation of organizational strategies aimed at improving communication with LEP families must include a thorough assessment of impact, feasibility, stakeholder involvement, and sustainability of specific interventions. While there is no simple formula to improve language services, health systems should establish and adopt language access policies, standardize communication practices, and develop processes to optimize the use of language services in the hospital. Furthermore, engagement with LEP families to better understand their perceptions and experiences with the healthcare system is crucial to improve communication between medical providers and LEP families in the inpatient setting and should be the subject of future studies.

Disclosures

The authors have no conflicts of interest to disclose.

Funding

No external funding was secured for this study. Dr. Joanna Thomson is supported by the Agency for Healthcare Research and Quality (Grant #K08 HS025138). Dr. Raglin Bignall was supported through a Ruth L. Kirschstein National Research Service Award (T32HP10027) when the study was conducted. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding organizations. The funding organizations had no role in the design, preparation, review, or approval of this paper.

Immigrant children make up the fastest growing segment of the population in the United States.¹ While most immigrant children are fluent in English, approximately 40% live with a parent who has limited English proficiency (LEP; ie, speaks English less than “very well”).^2,3 In pediatrics, LEP status has been associated with longer hospitalizations,⁴ higher hospitalization costs,⁵ increased risk for serious adverse medical events,^4,6 and more frequent emergency department reutilization.⁷ In the inpatient setting, multiple aspects of care present a variety of communication challenges,⁸ which are amplified by shift work and workflow complexity that result in patients and families interacting with numerous providers over the course of an inpatient stay.

Increasing access to trained professional interpreters when caring for LEP patients improves communication, patient satisfaction, adherence, and mortality.^9-12 However, even when access to interpreter services is established, effective use is not guaranteed.¹³ Up to 57% of pediatricians report relying on family members to communicate with LEP patients and their caregivers;⁹ 23% of pediatric residents categorized LEP encounters as frustrating while 78% perceived care of LEP patients to be “misdirected” (eg, delay in diagnosis or discharge) because of associated language barriers.¹⁴

Understanding experiences of frontline inpatient medical providers and interpreters is crucial in identifying challenges and ways to optimize communication for hospitalized LEP patients and families. However, there is a paucity of literature exploring the perspectives of medical providers and interpreters as it relates to communication with hospitalized LEP children and families. In this study, we sought to identify barriers and drivers of effective communication with pediatric patients and families with LEP in the inpatient setting from the perspective of frontline medical providers and interpreters.

Study Design

This qualitative study used Group Level Assessment (GLA), a structured participatory methodology that allows diverse groups of stakeholders to generate and evaluate data in interactive sessions.^15-18 GLA structure promotes active participation, group problem-solving, and development of actionable plans, distinguishing it from focus groups and in-depth semistructured interviews.^15,19 This study received a human subject research exemption by the institutional review board.

Study Setting

Cincinnati Children’s Hospital Medical Center (CCHMC) is a large quaternary care center with ~200 patient encounters each day who require the use of interpreter services. Interpreters (in-person, video, and phone) are utilized during admission, formal family-centered rounds, hospital discharge, and other encounters with physicians, nurses, and other healthcare professionals. In-person interpreters are available in-house for Spanish and Arabic, with 18 additional languages available through regional vendors. Despite available resources, there is no standard way in which medical providers and interpreters work with one another.

Study Participants and Recruitment

Medical providers who care for hospitalized general pediatric patients were eligible to participate, including attending physicians, resident physicians, bedside nurses, and inpatient ancillary staff (eg, respiratory therapists, physical therapists). Interpreters employed by CCHMC with experience in the inpatient setting were also eligible. Individuals were recruited based on published recommendations to optimize discussion and group-thinking.¹⁵ Each participant was asked to take part in one GLA session. Participants were assigned to specific sessions based on roles (ie, physicians, nurses, and interpreters) to maximize engagement and minimize the impact of hierarchy.

Study Procedure

GLA involves a seven-step structured process (Appendix 1): climate setting, generating, appreciating, reflecting, understanding, selecting, and action.^15,18 Qualitative data were generated individually and anonymously by participants on flip charts in response to prompts such as: “I worry that LEP families___,” “The biggest challenge when using interpreter services is___,” and “I find___ works well in providing care for LEP families.” Prompts were developed by study investigators, modified based on input from nursing and interpreter services leadership, and finalized by GLA facilitators. Fifty-one unique prompts were utilized (Appendix 2); the number of prompts used (ranging from 15 to 32 prompts) per session was based on published recommendations.¹⁵ During sessions, study investigators took detailed notes, including verbatim transcription of participant quotes. Upon conclusion of the session, each participant completed a demographic survey, including years of experience, languages spoken and perceived fluency,²⁰ and ethnicity.

Data Analysis

Within each session, under the guidance of trained and experienced GLA facilitators (WB, HV), participants distilled and summarized qualitative data into themes, discussed and prioritized themes, and generated action items. Following completion of all sessions, analyzed data was compiled by the research team to determine similarities and differences across groups based on participant roles, consolidate themes into barriers and drivers of communication with LEP families, and determine any overlap of priorities for action. Findings were shared back with each group to ensure accuracy and relevance.

Participants

A total of 64 individuals participated (Table 1): hospital medicine physicians and residents (56%), inpatient nurses and ancillary staff (16%), and interpreters (28%). While 81% of physicians spoke multiple languages, only 25% reported speaking them well; two physicians were certified to communicate medical information without an interpreter present.

Themes Resulting from GLA Sessions

A total of four barriers (Table 2) and four drivers (Table 3) of effective communication with pediatric LEP patients and their families in the inpatient setting were identified by participants. Participants across all groups, despite enthusiasm around improving communication, were concerned about quality of care LEP families received, noting that the system is “designed to deliver less-good care” and that “we really haven’t figured out how to care for [LEP patients and families] in a [high-]quality and reliable way.” Variation in theme discussion was noted between groups based on participant role: physicians voiced concern about rapport with LEP families, nurses emphasized actionable tasks, and interpreters focused on heightened challenges in times of stress.

Barrier 1: Difficulties Accessing Interpreter Services

Medical providers (physicians and nurses) identified the “opaque process to access [interpreter] services” as one of their biggest challenges when communicating with LEP families. In particular, the process of scheduling interpreters was described as a “black box,” with physicians and nurses expressing difficulty determining if and when in-person interpreters were scheduled and uncertainty about when to use modalities other than in-person interpretation. Participants across groups highlighted the lack of systems knowledge from medical providers and limitations within the system that make predictable, timely, and reliable access to interpreters challenging, especially for uncommon languages. Medical providers desired more in-person interpreters who can “stay as long as clinically indicated,” citing frustration associated with using phone- and video-interpretation (eg, challenges locating technology, unfamiliarity with use, unreliable functionality of equipment). Interpreters voiced wanting to take time to finish each encounter fully without “being in a hurry because the next appointment is coming soon” or “rushing… in [to the next] session sweating.”

Barrier 2: Uncertainty in Communication with LEP Families

Participants across all groups described three areas of uncertainty as detailed in Table 2: (1) what to share and how to prioritize information during encounters with LEP patients and families, (2) what is communicated during interpretation, and (3) what LEP patients and families understand.

Barrier 3: Unclear and Inconsistent Expectations and Roles of Team Members

Given the complexity involved in communication between medical providers, interpreters, and families, participants across all groups reported feeling ill-prepared when navigating hospital encounters with LEP patients and families. Interpreters reported having little to no clinical context, medical providers reported having no knowledge of the assigned interpreter’s style, and both interpreters and medical providers reported that families have little idea of what to expect or how to engage. All groups voiced frustration about the lack of clarity regarding specific roles and scope of practice for each team member during an encounter, where multiple people end up “talking [or] using the interpreter at once.” Interpreters shared their expectations of medical providers to set the pace and lead conversations with LEP families. On the other hand, medical providers expressed a desire for interpreters to provide cultural context to the team without prompting and to interrupt during encounters when necessary to voice concerns or redirect conversations.

Barrier 4: Unmet Family Engagement Expectations

Participants across all groups articulated challenges with establishing rapport with LEP patients and families, sharing concerns that “inadequate communication” due to “cultural or language barriers” ultimately impacts quality of care. Participants reported decreased bidirectional engagement with and from LEP families. Medical providers not only noted difficulty in connecting with LEP families “on a more personal level” and providing frequent medical updates, but also felt that LEP families do not ask questions even when uncertain. Interpreters expressed concerns about medical providers “not [having] enough patience to answer families’ questions” while LEP families “shy away from asking questions.”

Driver 1: Utilizing a Team-Based Approach between Medical Providers and Interpreters

Participants from all groups emphasized that a mutual understanding of roles and shared expectations regarding communication and interpretation style, clinical context, and time constraints would establish a foundation for respect between medical providers and interpreters. They reported that a team-based approach to LEP patient and family encounters were crucial to achieving effective communication.

Driver 2: Understanding the Role of Cultural Context in Providing Culturally Effective Care.

Participants across all groups highlighted three different aspects of cultural context that drive effective communication: (1) medical providers’ perception of the family’s culture; (2) LEP families’ knowledge about the culture and healthcare system in the US, and (3) medical providers insight into their own preconceived ideas about LEP families.

Driver 3: Practicing Empathy for Patients and Families

All participants reported that respect for diversity and consideration of the backgrounds and perspectives of LEP patients and families are necessary. Furthermore, both medical providers and interpreters articulated a need to remain patient and mindful when interacting with LEP families despite challenges, especially since, as noted by interpreters, encounters may “take longer, but it’s for a reason.”

Driver 4: Using Effective Family-Centered Communication Strategies

Participants identified the use of effective family-centered communication principles as a driver to optimal communication. Many of the principles identified by medical providers and interpreters are generally applicable to all hospitalized patients and families regardless of English proficiency: optimizing verbal communication (eg, using shorter sentences, pausing to allow for interpretation), optimizing nonverbal communication (eg, setting, position, and body language), and assessment of family understanding and engagement (eg, use of teach back).

Frontline medical providers and interpreters identified barriers and drivers that impact communication with LEP patients and families during hospitalization. To our knowledge, this is the first study that uses a participatory method to explore the perspectives of medical providers and interpreters who care for LEP children and families in the inpatient setting. Despite existing difficulties and concerns regarding language barriers and its impact on quality of care for hospitalized LEP patients and families, participants were enthusiastic about how identified barriers and drivers may inform future improvement efforts. Notable action steps for future improvement discussed by our participants included: increased use and functionality of technology for timely and predictable access to interpreters, deliberate training for providers focused on delivery of culturally-effective care, consistent use of family-centered communication strategies including teach-back, and implementing interdisciplinary expectation setting through “presessions” before encounters with LEP families.

Participants elaborated on several barriers previously described in the literature including time constraints and technical problems.^14,21,22 Such barriers may serve as deterrents to consistent and appropriate use of interpreters in healthcare settings.⁹ A heavy reliance on off-site interpreters (including phone- or video-interpreters) and lack of knowledge regarding resource availability likely amplified frustration for medical providers. Communication with LEP families can be daunting, especially when medical providers do not care for LEP families or work with interpreters on a regular basis.¹⁴ Standardizing the education of medical providers regarding available resources, as well as the logistics, process, and parameters for scheduling interpreters and using technology, was an action step identified by our GLA participants. Targeted education about the logistics of accessing interpreter services and having standardized ways to make technology use easier (ie, one-touch dialing in hospital rooms) has been associated with increased interpreter use and decreased interpreter-related delays in care.²³

Our frontline medical providers expressed added concern about not spending as much time with LEP families. In fact, LEP families in the literature have perceived medical providers to spend less time with their children compared to their English-proficient counterparts.²⁴ Language and cultural barriers, both perceived and real, may limit medical provider rapport with LEP patients and families¹⁴ and likely contribute to medical providers relying on their preconceived assumptions instead.²⁵ Cultural competency education for medical providers, as highlighted by our GLA participants as an action item, can be used to provide more comprehensive and effective care.^26,27

In addition to enhancing cultural humility through education, our participants emphasized the use of family-centered communication strategies as a driver of optimal family engagement and understanding. Actively inviting questions from families and utilizing teach-back, an established evidence-based strategy^28-30 discussed by our participants, can be particularly powerful in assessing family understanding and engagement. While information should be presented in plain language for families in all encounters,³¹ these evidence-based practices are of particular importance when communicating with LEP families. They promote effective communication, empower families to share concerns in a structured manner, and allow medical providers to address matters in real-time with interpreters present.

Finally, our participants highlighted the need for partnerships between providers and interpreter services, noting unclear roles and expectations among interpreters and medical providers as a major barrier. Specifically, physicians noted confusion regarding the scope of an interpreter’s practice. Participants from GLA sessions discussed the importance of a team-based approach and suggested implementing a “presession” prior to encounters with LEP patients and families. Presessions—a concept well accepted among interpreters and recommended by consensus-based practice guidelines—enable medical providers and interpreters to establish shared expectations about scope of practice, communication, interpretation style, time constraints, and medical context prior to patient encounters.^32,33

There are several limitations to our study. First, individuals who chose to participate were likely highly motivated by their clinical experiences with LEP patients and invested in improving communication with LEP families. Second, the study is limited in generalizability, as it was conducted at a single academic institution in a Midwestern city. Despite regional variations in available resources as well as patient and workforce demographics, our findings regarding major themes are in agreement with previously published literature and further add to our understanding of ways to improve communication with this vulnerable population across the care spectrum. Lastly, we were logistically limited in our ability to elicit the perspectives of LEP families due to the participatory nature of GLA; the need for multiple interpreters to simultaneously interact with LEP individuals would have not only hindered active LEP family participation but may have also biased the data generated by patients and families, as the services interpreters provide during their inpatient stay was the focus of our study. Engaging LEP families in their preferred language using participatory methods should be considered for future studies.

In conclusion, frontline providers of medical and language services identified barriers and drivers impacting the effective use of interpreter services when communicating with LEP families during hospitalization. Our enhanced understanding of barriers and drivers, as well as identified actionable interventions, will inform future improvement of communication and interactions with LEP families that contributes to effective and efficient family centered care. A framework for the development and implementation of organizational strategies aimed at improving communication with LEP families must include a thorough assessment of impact, feasibility, stakeholder involvement, and sustainability of specific interventions. While there is no simple formula to improve language services, health systems should establish and adopt language access policies, standardize communication practices, and develop processes to optimize the use of language services in the hospital. Furthermore, engagement with LEP families to better understand their perceptions and experiences with the healthcare system is crucial to improve communication between medical providers and LEP families in the inpatient setting and should be the subject of future studies.

Disclosures

The authors have no conflicts of interest to disclose.

Funding

No external funding was secured for this study. Dr. Joanna Thomson is supported by the Agency for Healthcare Research and Quality (Grant #K08 HS025138). Dr. Raglin Bignall was supported through a Ruth L. Kirschstein National Research Service Award (T32HP10027) when the study was conducted. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding organizations. The funding organizations had no role in the design, preparation, review, or approval of this paper.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason” series reviews practices which have become common parts of hospital care but which may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent “black and white” conclusions or clinical practice standards, but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

A four-year-old girl, with a history of one wheezing episode, presents to the emergency department (ED) with wheezing, tachypnea, and respiratory distress. She receives three successive treatments of short-acting bronchodilators and is given one dose of dexamethasone, after which she improves significantly. Because of persistent tachypnea and wheezing, she is admitted for further management. By the next day she is much improved, now requiring bronchodilator treatment every four hours. She receives a second dose of dexamethasone to complete her steroid burst. Was the trajectory of this patient’s illness altered by treatment with systemic corticosteroids (SCS)? Is there any benefit to SCS treatment in a wheezing preschool-aged patient?

Wheezing is common in preschool-aged children (ages 2-5 years), with up to half in this age group having experienced a wheezing episode and up to one-third, recurrent wheezing.^1,2 Young children with wheezing require ED visits and hospitalizations at much higher rates than older children and adults.³ Several studies have also demonstrated that children in this age group have higher rates of SCS prescriptions compared with older children.^4,5 Despite the high prevalence of wheezing in this age group, there is great heterogeneity in the etiology and clinical progression of early childhood wheezing, with up to six described phenotypes each with varying levels of association with the development of asthma.⁶ Given the high frequency of asthma, preschool-aged children admitted with wheezing are often treated with SCS, as this is the standard of care for an acute asthma exacerbation.⁷

The benefit of SCS in school-aged children and adolescents with multitrigger asthma exacerbation is well established and includes shorter time to resolution of acute illness and reduction in relapses.⁸ Because of these benefits, expert panels and regulatory agencies often include preschool-aged children in treatment recommendations for the older age groups.^7,9,10 Consequently, apart from infants diagnosed with bronchiolitis, SCS remain a common and accepted treatment for young children presenting with asthma-like symptoms.^4,5

Some data suggest that there may be clinical benefit from treatment with SCS in preschool children who wheeze. A recent trial by Foster et al. included 605 children, aged 24-72 months, presenting to a pediatric ED with wheeze plus viral upper respiratory symptoms.¹¹ Patients were randomized to receive a three-day course of prednisolone (1 mg/kg) or placebo. The primary outcome was length of hospital stay until ready for discharge, which they found was significantly longer for placebo-treated patients (540 minutes) versus prednisolone (370 minutes).

There are few randomized controlled trials evaluating the efficacy of SCS in preschool-aged children with viral-induced wheezing, and these children are often grouped with younger or older children in studies. While limited in number, these studies have evaluated SCS efficacy with acute wheezing in preschool-aged children in outpatient, ED, and inpatient settings (Appendix Table).^12-16 The majority of trials of SCS in this age group have shown mixed or negative results.

Admission rates for preschoolers with viral wheezing were not statistically different in those receiving oral prednisolone versus placebo in a study conducted by Oomen et al. evaluating outpatient, parent-initiated prednisolone.¹⁴ Tal et al. found overall benefit with reduced admission rate for patients treated in the ED with methylprednisolone versus placebo; however, this finding was not statistically significant in patients 24-54 months old.¹⁶

For those requiring hospitalization, length of hospital stay and time until readiness to discharge were the primary outcomes assessed by Panickar et al. and Jartti et al. Neither study found a statistically significant difference between groups who received oral prednisolone versus placebo for 3 or 5 days. Secondary outcomes such as symptom scores, symptom duration, albuterol use, and 60-day relapse rate were also not improved in those taking oral prednisolone compared with placebo.^14,15

The mixed results of studies assessing the efficacy of SCS in preschool-aged wheezing children may be attributed to the fact that wheezing in this age group likely represents multiple underlying processes. Most acute wheezing at this age is not associated with atopy and is often triggered by viral respiratory tract infections.¹⁷ Furthermore, 90% of wheezing in children under the age of five years does not persist to the asthma phenotype (recurrent episodes with multiple triggers, airway obstruction, and hyper-responsiveness) once they reach school age.¹⁸

While SCS are generally not expensive, their use is not without cost. Studies of oral corticosteroid use in children with asthma have shown adverse effects including vomiting, hypertension, and impaired growth.¹⁹ Children with recurrent wheeze receiving SCS may demonstrate biochemical hypothalamic-pituitary-axis dysfunction.²⁰ Given the high utilization and SCS prescription rates in this age group, reducing the use of SCS with wheezing episodes could have a large clinical and financial impact.^3,4 These medications should be used judiciously in order to balance benefit with potential risks.

Given that there is diversity in the phenotype of preschool-aged children who wheeze, it is possible that a subset of these children would benefit from SCS. Some studies have shown that certain groups of patients derive benefit, including those with rhinovirus infection, eczema, and children at higher risk for multitrigger asthma.^11,13 Children who have atopic wheeze are more likely to have persistent symptoms that may eventually be diagnosed as asthma.¹⁸ These children will have airway inflammation secondary to eosinophilic infiltration and may be responsive to SCS at times of exacerbation. However, attempts to classify preschool children based on risk of asthma have not shown consistent results.

The Asthma Predictive Index (API), a tool developed as a part of the Tucson Children’s Respiratory Study, uses clinical factors including history of wheeze, atopic dermatitis, and allergic rhinitis to determine a young child’s risk of having asthma symptoms after age six years.²¹ Jartti et al. and Panickar et al. used the API to stratify patients based on future asthma risk.^13,15 The high risk group in the Jartti et al. study showed the benefit of SCS, while there was no benefit in the Panickar et al. study. When Oommen et al. also attempted to stratify asthma risk using levels of blood eosinophil proteins, which when elevated, are predictive of persistent wheeze.¹⁴ There was no difference in drug efficacy between patients with high and low blood eosinophil proteins. Although Foster et al. demonstrated shorter length of stay (LOS) with SCS overall, this was only seen in the subgroup with a previous diagnosis of asthma.

Patients presenting with severe disease (including those requiring critical care or with the highest symptom scores) have mostly been excluded from these studies. Although patients with severe disease often receive steroids, there is insufficient evidence of the efficacy of SCS in this population.^12,13,15,22 Foster et al. did include patients with high symptom scores (although they excluded patients with “critical wheeze”) and found that the efficacy of SCS was clearest for those with severe presentations.¹¹

Finally, some studies have demonstrated a virus-specific effect, with a reduction in time to readiness for discharge and reduction in recurrent wheeze in children treated with prednisolone who were positive for rhinovirus.^12,23 Rhinovirus infection has also been associated with allergic sensitization and recurrent wheezing.^23,24 However, rhinovirus-specific steroid responsiveness has not been consistently replicated by other investigators.¹¹

The majority of preschool-aged children presenting with wheeze in the care of hospitalists have mild to moderate symptoms, triggered by viral infections.²² It can be helpful to categorize the wheezing child as atopic or nonatopic. Laboratory studies such as allergen-specific IgE, peripheral eosinophil count, and exhaled nitric oxide can aid in predicting response to asthma medications and progression to the classic asthma phenotype.²⁵ In the absence of these diagnostic studies, which are often costly and challenging to obtain in young children, a clinical score such as the API, or the recently validated Pediatric Asthma Risk Score (PARS), can help to assess future risk of developing multitrigger asthma.^21,26 A positive API requires a history of more than three episodes of wheeze over the past year as well as one major (physician-diagnosed atopic dermatitis or parental asthma) or two minor (peripheral blood eosinophilia, physician-diagnosed allergic rhinitis, or wheezing apart from colds) criteria.¹⁷ It has a sensitivity of 57% and specificity of 81%.²⁶ The PARS uses the presence of parental asthma, eczema, early wheezing, wheezing apart from colds, African-American race, and ≥2 positive skin prick tests to predict asthma. The sensitivity and specificity of PARS are similar to the API at 68% and 79%, respectively.²⁶

Given the mixed results from studies evaluating the benefit of SCS in preschoolers with atopic symptoms and/or a positive API, evidence is lacking to guide decision-making in these children.^13-15 However, it is reasonable to treat those at higher risk for future multitrigger asthma with SCS. There is also insufficient evidence to determine whether those with more severe disease or those infected with particular viral pathogens may benefit. Therefore, for the majority of children presenting with viral-induced wheezing, with a negative API or low PARS, there is no evidence that treatment with an SCS provides benefit in the form of reduced LOS, reduction in clinical symptoms, treatment failure, or relapse rate.

• Do not routinely treat with SCS preschool-aged children who have episodic wheezing triggered by viral respiratory tract infections and who do not have risk factors for persistent asthma.
• For preschool-aged children with a history of atopy, a positive API, or elevated PARS, SCS can be considered during admissions for respiratory distress and wheezing.
• Preschool-aged children presenting with severe disease or requiring intensive care may benefit from SCS, but there is insufficient evidence to conclude whether this practice provides benefit.

Current evidence does not support the routine use of SCS for preschool-aged children admitted for mild to moderate wheezing episodes. The majority of these children have viral episodic wheeze that does not develop into the asthma phenotype. For children with severe disease or at higher risk for asthma, SCS may be considered, although there remains insufficient evidence as to their efficacy. The patient in the introductory case lacks risk factors that would suggest SCS responsiveness (eg, positive API, previous asthma diagnosis, inhaled corticosteroid use, or severe disease) and would likely receive no clinical benefit from dexamethasone treatment.

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

Disclosures

Dr. Jennifer O’Toole consulted with and received honoraria payment from the I-PASS Patient Safety Institute. She also holds stock options in the I-PASS Patient Safety Institute, a nonpublicly traded company. Drs. Jones and Hubbell have nothing to disclose.

Funding

Dr. Thomson was supported by the Agency for Healthcare Research and Quality under award number K08HS025138.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason” series reviews practices which have become common parts of hospital care but which may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent “black and white” conclusions or clinical practice standards, but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

A four-year-old girl, with a history of one wheezing episode, presents to the emergency department (ED) with wheezing, tachypnea, and respiratory distress. She receives three successive treatments of short-acting bronchodilators and is given one dose of dexamethasone, after which she improves significantly. Because of persistent tachypnea and wheezing, she is admitted for further management. By the next day she is much improved, now requiring bronchodilator treatment every four hours. She receives a second dose of dexamethasone to complete her steroid burst. Was the trajectory of this patient’s illness altered by treatment with systemic corticosteroids (SCS)? Is there any benefit to SCS treatment in a wheezing preschool-aged patient?

Wheezing is common in preschool-aged children (ages 2-5 years), with up to half in this age group having experienced a wheezing episode and up to one-third, recurrent wheezing.^1,2 Young children with wheezing require ED visits and hospitalizations at much higher rates than older children and adults.³ Several studies have also demonstrated that children in this age group have higher rates of SCS prescriptions compared with older children.^4,5 Despite the high prevalence of wheezing in this age group, there is great heterogeneity in the etiology and clinical progression of early childhood wheezing, with up to six described phenotypes each with varying levels of association with the development of asthma.⁶ Given the high frequency of asthma, preschool-aged children admitted with wheezing are often treated with SCS, as this is the standard of care for an acute asthma exacerbation.⁷

The benefit of SCS in school-aged children and adolescents with multitrigger asthma exacerbation is well established and includes shorter time to resolution of acute illness and reduction in relapses.⁸ Because of these benefits, expert panels and regulatory agencies often include preschool-aged children in treatment recommendations for the older age groups.^7,9,10 Consequently, apart from infants diagnosed with bronchiolitis, SCS remain a common and accepted treatment for young children presenting with asthma-like symptoms.^4,5

Some data suggest that there may be clinical benefit from treatment with SCS in preschool children who wheeze. A recent trial by Foster et al. included 605 children, aged 24-72 months, presenting to a pediatric ED with wheeze plus viral upper respiratory symptoms.¹¹ Patients were randomized to receive a three-day course of prednisolone (1 mg/kg) or placebo. The primary outcome was length of hospital stay until ready for discharge, which they found was significantly longer for placebo-treated patients (540 minutes) versus prednisolone (370 minutes).

There are few randomized controlled trials evaluating the efficacy of SCS in preschool-aged children with viral-induced wheezing, and these children are often grouped with younger or older children in studies. While limited in number, these studies have evaluated SCS efficacy with acute wheezing in preschool-aged children in outpatient, ED, and inpatient settings (Appendix Table).^12-16 The majority of trials of SCS in this age group have shown mixed or negative results.

Admission rates for preschoolers with viral wheezing were not statistically different in those receiving oral prednisolone versus placebo in a study conducted by Oomen et al. evaluating outpatient, parent-initiated prednisolone.¹⁴ Tal et al. found overall benefit with reduced admission rate for patients treated in the ED with methylprednisolone versus placebo; however, this finding was not statistically significant in patients 24-54 months old.¹⁶

For those requiring hospitalization, length of hospital stay and time until readiness to discharge were the primary outcomes assessed by Panickar et al. and Jartti et al. Neither study found a statistically significant difference between groups who received oral prednisolone versus placebo for 3 or 5 days. Secondary outcomes such as symptom scores, symptom duration, albuterol use, and 60-day relapse rate were also not improved in those taking oral prednisolone compared with placebo.^14,15

The mixed results of studies assessing the efficacy of SCS in preschool-aged wheezing children may be attributed to the fact that wheezing in this age group likely represents multiple underlying processes. Most acute wheezing at this age is not associated with atopy and is often triggered by viral respiratory tract infections.¹⁷ Furthermore, 90% of wheezing in children under the age of five years does not persist to the asthma phenotype (recurrent episodes with multiple triggers, airway obstruction, and hyper-responsiveness) once they reach school age.¹⁸

While SCS are generally not expensive, their use is not without cost. Studies of oral corticosteroid use in children with asthma have shown adverse effects including vomiting, hypertension, and impaired growth.¹⁹ Children with recurrent wheeze receiving SCS may demonstrate biochemical hypothalamic-pituitary-axis dysfunction.²⁰ Given the high utilization and SCS prescription rates in this age group, reducing the use of SCS with wheezing episodes could have a large clinical and financial impact.^3,4 These medications should be used judiciously in order to balance benefit with potential risks.

Given that there is diversity in the phenotype of preschool-aged children who wheeze, it is possible that a subset of these children would benefit from SCS. Some studies have shown that certain groups of patients derive benefit, including those with rhinovirus infection, eczema, and children at higher risk for multitrigger asthma.^11,13 Children who have atopic wheeze are more likely to have persistent symptoms that may eventually be diagnosed as asthma.¹⁸ These children will have airway inflammation secondary to eosinophilic infiltration and may be responsive to SCS at times of exacerbation. However, attempts to classify preschool children based on risk of asthma have not shown consistent results.

The Asthma Predictive Index (API), a tool developed as a part of the Tucson Children’s Respiratory Study, uses clinical factors including history of wheeze, atopic dermatitis, and allergic rhinitis to determine a young child’s risk of having asthma symptoms after age six years.²¹ Jartti et al. and Panickar et al. used the API to stratify patients based on future asthma risk.^13,15 The high risk group in the Jartti et al. study showed the benefit of SCS, while there was no benefit in the Panickar et al. study. When Oommen et al. also attempted to stratify asthma risk using levels of blood eosinophil proteins, which when elevated, are predictive of persistent wheeze.¹⁴ There was no difference in drug efficacy between patients with high and low blood eosinophil proteins. Although Foster et al. demonstrated shorter length of stay (LOS) with SCS overall, this was only seen in the subgroup with a previous diagnosis of asthma.

Patients presenting with severe disease (including those requiring critical care or with the highest symptom scores) have mostly been excluded from these studies. Although patients with severe disease often receive steroids, there is insufficient evidence of the efficacy of SCS in this population.^12,13,15,22 Foster et al. did include patients with high symptom scores (although they excluded patients with “critical wheeze”) and found that the efficacy of SCS was clearest for those with severe presentations.¹¹

Finally, some studies have demonstrated a virus-specific effect, with a reduction in time to readiness for discharge and reduction in recurrent wheeze in children treated with prednisolone who were positive for rhinovirus.^12,23 Rhinovirus infection has also been associated with allergic sensitization and recurrent wheezing.^23,24 However, rhinovirus-specific steroid responsiveness has not been consistently replicated by other investigators.¹¹

The majority of preschool-aged children presenting with wheeze in the care of hospitalists have mild to moderate symptoms, triggered by viral infections.²² It can be helpful to categorize the wheezing child as atopic or nonatopic. Laboratory studies such as allergen-specific IgE, peripheral eosinophil count, and exhaled nitric oxide can aid in predicting response to asthma medications and progression to the classic asthma phenotype.²⁵ In the absence of these diagnostic studies, which are often costly and challenging to obtain in young children, a clinical score such as the API, or the recently validated Pediatric Asthma Risk Score (PARS), can help to assess future risk of developing multitrigger asthma.^21,26 A positive API requires a history of more than three episodes of wheeze over the past year as well as one major (physician-diagnosed atopic dermatitis or parental asthma) or two minor (peripheral blood eosinophilia, physician-diagnosed allergic rhinitis, or wheezing apart from colds) criteria.¹⁷ It has a sensitivity of 57% and specificity of 81%.²⁶ The PARS uses the presence of parental asthma, eczema, early wheezing, wheezing apart from colds, African-American race, and ≥2 positive skin prick tests to predict asthma. The sensitivity and specificity of PARS are similar to the API at 68% and 79%, respectively.²⁶

Given the mixed results from studies evaluating the benefit of SCS in preschoolers with atopic symptoms and/or a positive API, evidence is lacking to guide decision-making in these children.^13-15 However, it is reasonable to treat those at higher risk for future multitrigger asthma with SCS. There is also insufficient evidence to determine whether those with more severe disease or those infected with particular viral pathogens may benefit. Therefore, for the majority of children presenting with viral-induced wheezing, with a negative API or low PARS, there is no evidence that treatment with an SCS provides benefit in the form of reduced LOS, reduction in clinical symptoms, treatment failure, or relapse rate.

• Do not routinely treat with SCS preschool-aged children who have episodic wheezing triggered by viral respiratory tract infections and who do not have risk factors for persistent asthma.
• For preschool-aged children with a history of atopy, a positive API, or elevated PARS, SCS can be considered during admissions for respiratory distress and wheezing.
• Preschool-aged children presenting with severe disease or requiring intensive care may benefit from SCS, but there is insufficient evidence to conclude whether this practice provides benefit.

Current evidence does not support the routine use of SCS for preschool-aged children admitted for mild to moderate wheezing episodes. The majority of these children have viral episodic wheeze that does not develop into the asthma phenotype. For children with severe disease or at higher risk for asthma, SCS may be considered, although there remains insufficient evidence as to their efficacy. The patient in the introductory case lacks risk factors that would suggest SCS responsiveness (eg, positive API, previous asthma diagnosis, inhaled corticosteroid use, or severe disease) and would likely receive no clinical benefit from dexamethasone treatment.

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

Disclosures

Dr. Jennifer O’Toole consulted with and received honoraria payment from the I-PASS Patient Safety Institute. She also holds stock options in the I-PASS Patient Safety Institute, a nonpublicly traded company. Drs. Jones and Hubbell have nothing to disclose.

Funding

Dr. Thomson was supported by the Agency for Healthcare Research and Quality under award number K08HS025138.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason” series reviews practices which have become common parts of hospital care but which may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent “black and white” conclusions or clinical practice standards, but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

A four-year-old girl, with a history of one wheezing episode, presents to the emergency department (ED) with wheezing, tachypnea, and respiratory distress. She receives three successive treatments of short-acting bronchodilators and is given one dose of dexamethasone, after which she improves significantly. Because of persistent tachypnea and wheezing, she is admitted for further management. By the next day she is much improved, now requiring bronchodilator treatment every four hours. She receives a second dose of dexamethasone to complete her steroid burst. Was the trajectory of this patient’s illness altered by treatment with systemic corticosteroids (SCS)? Is there any benefit to SCS treatment in a wheezing preschool-aged patient?

Wheezing is common in preschool-aged children (ages 2-5 years), with up to half in this age group having experienced a wheezing episode and up to one-third, recurrent wheezing.^1,2 Young children with wheezing require ED visits and hospitalizations at much higher rates than older children and adults.³ Several studies have also demonstrated that children in this age group have higher rates of SCS prescriptions compared with older children.^4,5 Despite the high prevalence of wheezing in this age group, there is great heterogeneity in the etiology and clinical progression of early childhood wheezing, with up to six described phenotypes each with varying levels of association with the development of asthma.⁶ Given the high frequency of asthma, preschool-aged children admitted with wheezing are often treated with SCS, as this is the standard of care for an acute asthma exacerbation.⁷

The benefit of SCS in school-aged children and adolescents with multitrigger asthma exacerbation is well established and includes shorter time to resolution of acute illness and reduction in relapses.⁸ Because of these benefits, expert panels and regulatory agencies often include preschool-aged children in treatment recommendations for the older age groups.^7,9,10 Consequently, apart from infants diagnosed with bronchiolitis, SCS remain a common and accepted treatment for young children presenting with asthma-like symptoms.^4,5

Some data suggest that there may be clinical benefit from treatment with SCS in preschool children who wheeze. A recent trial by Foster et al. included 605 children, aged 24-72 months, presenting to a pediatric ED with wheeze plus viral upper respiratory symptoms.¹¹ Patients were randomized to receive a three-day course of prednisolone (1 mg/kg) or placebo. The primary outcome was length of hospital stay until ready for discharge, which they found was significantly longer for placebo-treated patients (540 minutes) versus prednisolone (370 minutes).

There are few randomized controlled trials evaluating the efficacy of SCS in preschool-aged children with viral-induced wheezing, and these children are often grouped with younger or older children in studies. While limited in number, these studies have evaluated SCS efficacy with acute wheezing in preschool-aged children in outpatient, ED, and inpatient settings (Appendix Table).^12-16 The majority of trials of SCS in this age group have shown mixed or negative results.

Admission rates for preschoolers with viral wheezing were not statistically different in those receiving oral prednisolone versus placebo in a study conducted by Oomen et al. evaluating outpatient, parent-initiated prednisolone.¹⁴ Tal et al. found overall benefit with reduced admission rate for patients treated in the ED with methylprednisolone versus placebo; however, this finding was not statistically significant in patients 24-54 months old.¹⁶

For those requiring hospitalization, length of hospital stay and time until readiness to discharge were the primary outcomes assessed by Panickar et al. and Jartti et al. Neither study found a statistically significant difference between groups who received oral prednisolone versus placebo for 3 or 5 days. Secondary outcomes such as symptom scores, symptom duration, albuterol use, and 60-day relapse rate were also not improved in those taking oral prednisolone compared with placebo.^14,15

The mixed results of studies assessing the efficacy of SCS in preschool-aged wheezing children may be attributed to the fact that wheezing in this age group likely represents multiple underlying processes. Most acute wheezing at this age is not associated with atopy and is often triggered by viral respiratory tract infections.¹⁷ Furthermore, 90% of wheezing in children under the age of five years does not persist to the asthma phenotype (recurrent episodes with multiple triggers, airway obstruction, and hyper-responsiveness) once they reach school age.¹⁸

While SCS are generally not expensive, their use is not without cost. Studies of oral corticosteroid use in children with asthma have shown adverse effects including vomiting, hypertension, and impaired growth.¹⁹ Children with recurrent wheeze receiving SCS may demonstrate biochemical hypothalamic-pituitary-axis dysfunction.²⁰ Given the high utilization and SCS prescription rates in this age group, reducing the use of SCS with wheezing episodes could have a large clinical and financial impact.^3,4 These medications should be used judiciously in order to balance benefit with potential risks.

Given that there is diversity in the phenotype of preschool-aged children who wheeze, it is possible that a subset of these children would benefit from SCS. Some studies have shown that certain groups of patients derive benefit, including those with rhinovirus infection, eczema, and children at higher risk for multitrigger asthma.^11,13 Children who have atopic wheeze are more likely to have persistent symptoms that may eventually be diagnosed as asthma.¹⁸ These children will have airway inflammation secondary to eosinophilic infiltration and may be responsive to SCS at times of exacerbation. However, attempts to classify preschool children based on risk of asthma have not shown consistent results.

The Asthma Predictive Index (API), a tool developed as a part of the Tucson Children’s Respiratory Study, uses clinical factors including history of wheeze, atopic dermatitis, and allergic rhinitis to determine a young child’s risk of having asthma symptoms after age six years.²¹ Jartti et al. and Panickar et al. used the API to stratify patients based on future asthma risk.^13,15 The high risk group in the Jartti et al. study showed the benefit of SCS, while there was no benefit in the Panickar et al. study. When Oommen et al. also attempted to stratify asthma risk using levels of blood eosinophil proteins, which when elevated, are predictive of persistent wheeze.¹⁴ There was no difference in drug efficacy between patients with high and low blood eosinophil proteins. Although Foster et al. demonstrated shorter length of stay (LOS) with SCS overall, this was only seen in the subgroup with a previous diagnosis of asthma.

Patients presenting with severe disease (including those requiring critical care or with the highest symptom scores) have mostly been excluded from these studies. Although patients with severe disease often receive steroids, there is insufficient evidence of the efficacy of SCS in this population.^12,13,15,22 Foster et al. did include patients with high symptom scores (although they excluded patients with “critical wheeze”) and found that the efficacy of SCS was clearest for those with severe presentations.¹¹

Finally, some studies have demonstrated a virus-specific effect, with a reduction in time to readiness for discharge and reduction in recurrent wheeze in children treated with prednisolone who were positive for rhinovirus.^12,23 Rhinovirus infection has also been associated with allergic sensitization and recurrent wheezing.^23,24 However, rhinovirus-specific steroid responsiveness has not been consistently replicated by other investigators.¹¹

The majority of preschool-aged children presenting with wheeze in the care of hospitalists have mild to moderate symptoms, triggered by viral infections.²² It can be helpful to categorize the wheezing child as atopic or nonatopic. Laboratory studies such as allergen-specific IgE, peripheral eosinophil count, and exhaled nitric oxide can aid in predicting response to asthma medications and progression to the classic asthma phenotype.²⁵ In the absence of these diagnostic studies, which are often costly and challenging to obtain in young children, a clinical score such as the API, or the recently validated Pediatric Asthma Risk Score (PARS), can help to assess future risk of developing multitrigger asthma.^21,26 A positive API requires a history of more than three episodes of wheeze over the past year as well as one major (physician-diagnosed atopic dermatitis or parental asthma) or two minor (peripheral blood eosinophilia, physician-diagnosed allergic rhinitis, or wheezing apart from colds) criteria.¹⁷ It has a sensitivity of 57% and specificity of 81%.²⁶ The PARS uses the presence of parental asthma, eczema, early wheezing, wheezing apart from colds, African-American race, and ≥2 positive skin prick tests to predict asthma. The sensitivity and specificity of PARS are similar to the API at 68% and 79%, respectively.²⁶

Given the mixed results from studies evaluating the benefit of SCS in preschoolers with atopic symptoms and/or a positive API, evidence is lacking to guide decision-making in these children.^13-15 However, it is reasonable to treat those at higher risk for future multitrigger asthma with SCS. There is also insufficient evidence to determine whether those with more severe disease or those infected with particular viral pathogens may benefit. Therefore, for the majority of children presenting with viral-induced wheezing, with a negative API or low PARS, there is no evidence that treatment with an SCS provides benefit in the form of reduced LOS, reduction in clinical symptoms, treatment failure, or relapse rate.

• Do not routinely treat with SCS preschool-aged children who have episodic wheezing triggered by viral respiratory tract infections and who do not have risk factors for persistent asthma.
• For preschool-aged children with a history of atopy, a positive API, or elevated PARS, SCS can be considered during admissions for respiratory distress and wheezing.
• Preschool-aged children presenting with severe disease or requiring intensive care may benefit from SCS, but there is insufficient evidence to conclude whether this practice provides benefit.

Current evidence does not support the routine use of SCS for preschool-aged children admitted for mild to moderate wheezing episodes. The majority of these children have viral episodic wheeze that does not develop into the asthma phenotype. For children with severe disease or at higher risk for asthma, SCS may be considered, although there remains insufficient evidence as to their efficacy. The patient in the introductory case lacks risk factors that would suggest SCS responsiveness (eg, positive API, previous asthma diagnosis, inhaled corticosteroid use, or severe disease) and would likely receive no clinical benefit from dexamethasone treatment.

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

Disclosures

Dr. Jennifer O’Toole consulted with and received honoraria payment from the I-PASS Patient Safety Institute. She also holds stock options in the I-PASS Patient Safety Institute, a nonpublicly traded company. Drs. Jones and Hubbell have nothing to disclose.

Funding

Dr. Thomson was supported by the Agency for Healthcare Research and Quality under award number K08HS025138.

Electrolyte imbalances, per se, predispose to ventricular ectopy and, in extreme cases, sudden cardiac death.¹ As these outcomes are more common in the presence of intrinsic heart disease, serum electrolytes—particularly potassium and magnesium—are routinely monitored and made replete in patients with myocardial infarction (MI) or acute decompensated heart failure (ADHF).

Patients hospitalized with ADHF often present with metabolic derangements and varying degrees of chronic adaptations in their renin–angiotensin–aldosterone system.^1,2 In addition, during an ADHF hospitalization, they are subjected to guideline-directed medical therapy (GDMT), commonly in escalating doses, that exhibit well-established effects on serum potassium levels, including diuretics, angiotensin-converting-enzyme inhibitors, angiotensin receptor blockers, beta blockers, and mineralocorticoid receptor antagonists. Thus, there are myriad ways patients hospitalized for ADHF might experience electrolyte abnormalities.

In this issue of the Journal of Hospital Medicine, O’Sullivan et al. explore the associations between mean 72-hour serum potassium and important clinical outcomes—in-hospital mortality, transfer to an intensive care unit (ICU), and length of stay (LOS)—among patients with normal admission serum potassium hospitalized for ADHF.³ Through a retrospective review of electronic records from 116 hospitals, the authors identified 4,995 initially normokalemic heart failure (HF; identified by ICD-9 codes) patients and grouped them into low-normal (3.5-4.0 mEq/L), normal (4.0-4.5 mEq/L), and high-normal (4.5-5.0 mEq/L) potassium groups.³ Adjustments were made for composite scores encapsulating other lab abnormalities and comorbidities.

Over the 72-hour exposure window, the authors observed no statistically significant difference in mortality, ICU transfer, or LOS between the low-normal and normal potassium groups.³ Moreover, in a sensitivity analysis of patients who did not receive potassium supplementation, there remained statistically similar rates of mortality, ICU transfer, and LOS.³ Together, these findings suggest that maintenance of potassium >4 mEq/L may not be efficacious for preventing in-hospital complications of ADHF.³ In fact, they observed more frequent mortality and ICU transfer in patients who had high-normal potassium. This group, however, had a higher burden of chronic kidney disease and illness severity on presentation and was less likely to receive supplemental potassium.³

ADHF accounts for more than one million hospital admissions annually with one in four patients readmitted within 30 days; estimated costs surpass $30 billion.² Reducing unnecessary expenditures in the management of HF through evidence-based guidelines is paramount. Electrolyte repletion in the setting of ADHF may represent one such opportunity by reducing excess phlebotomy, laboratory services, and potassium supplementation. Patient experience may also improve from curbing these cumbersome practices. While society guidelines endorse potassium repletion in MI to reduce the risk of ventricular arrhythmia,⁴ there is no uniform consensus in ADHF. As the authors cite, existing data regarding ideal potassium levels in patients with ADHF is lacking, with current evidence drawn from small observational studies. The present study, being much larger in size and being linked with observed rates of active potassium supplementation, provides some of the strongest evidence to date that a potassium goal of >4 mEq/L may not be efficacious at reducing ADHF-related complications in the generalized HF population.

While it remains uncertain if avoiding low-normal potassium levels in ADHF is beneficial, over the long term, intermediate-range potassium levels are clearly associated with the lowest HF-related mortality. In a study of over 2,000 HF patients who underwent longitudinal potassium monitoring, mortality was distributed along a U-shaped curve with highest mortality at the extremes of kalemia and a nadir at a level of 4.3 mEq/L.⁵

A major limitation of the present study is that it does not account for variability within the ADHF population. Firstly, knowledge regarding the use of GDMT, which not only affects serum potassium (all GDMTs) but also reduces the likelihood of arrhythmias (beta blockers), would have been informative. Moreover, the authors do not have access to data regarding incident arrhythmia and instead use ICU admission as a surrogate. In addition, ADHF patients in this study varied greatly in illness severity, ranging from those receiving initial therapy with loop diuretics alone to those requiring augmentation with thiazides and even the use of temporary mechanical circulatory support.³ Escalating loop diuretic or metolazone use not only is associated with increased mortality⁶ but often results in impressive natriuresis and, potentially dangerous, kaliuresis secondary to the sequential nephron blockade.⁷ Those who underwent extensive potassium swings in the study may not be appropriately captured using 72-hour serum potassium averages. Additionally, this study did not assess for quantity of diuresis, which is known to affect serum potassium values. It is possible that those with low-normal potassium represent patients who underwent more effective diuresis and therefore were discharged sooner. Adding to the variability, ADHF in this study encompassed both systolic (HF with a reduced ejection fraction) and diastolic (HF with a preserved ejection fraction) HF although, perhaps not surprisingly, there were marked differences in the HF subtype by potassium group—the proportions with only diastolic dysfunction were 37.1%, 39.0%, and 45.8% in the low-normal, normal, and high-normal groups, respectively (P = .0174).³ Given the known heterogeneity between these two HF subtypes,⁸ particularly with respect to their response to mortality-reducing GDMT,^2,8 the results may be significantly confounded.

Relatedly, by excluding initially hypokalemic patients, the authors have lost considerable power and broad generalizability as these patients likely represent those at greatest risk of recurrent hypokalemia and its attendant complications during admission.

This study should be lauded for critically appraising the ubiquitous practice of electrolyte repletion. The authors present compelling preliminary data suggesting that maintenance of potassium >4 mEq/L in the general ADHF population is not efficacious at preventing ADHF complications and, as a corollary, is likely not cost-effective. However, we agree with the authors that a randomized controlled trial will be needed to change clinical practice. Ideally, such a study would account for HF subtype and GDMT use and could compare rates of arrhythmia, AHDF-related death, and all-cause mortality in patients maintained to goal normokalemia (>3.5 mEq/L) versus “high goal” (>4 mEq/L) with repletion. Only these types of studies will provide the strength of evidence needed to end a practice as well engrained in modern medicine as “high-goal ‘lytes”.

Disclosures

Dr. Blaha reports grants from NIH, grants from FDA, grants from AHA, grants and personal fees from Amgen Foundation, grants from Aetna Foundation, personal fees from Sanofi, personal fees from Regeneron, and personal fees from Novartis, from Novo Nordisk, and from Bayer, outside the submitted work. Dr. Dudum and Dr. Lahti have nothing to disclose.

Electrolyte imbalances, per se, predispose to ventricular ectopy and, in extreme cases, sudden cardiac death.¹ As these outcomes are more common in the presence of intrinsic heart disease, serum electrolytes—particularly potassium and magnesium—are routinely monitored and made replete in patients with myocardial infarction (MI) or acute decompensated heart failure (ADHF).

Patients hospitalized with ADHF often present with metabolic derangements and varying degrees of chronic adaptations in their renin–angiotensin–aldosterone system.^1,2 In addition, during an ADHF hospitalization, they are subjected to guideline-directed medical therapy (GDMT), commonly in escalating doses, that exhibit well-established effects on serum potassium levels, including diuretics, angiotensin-converting-enzyme inhibitors, angiotensin receptor blockers, beta blockers, and mineralocorticoid receptor antagonists. Thus, there are myriad ways patients hospitalized for ADHF might experience electrolyte abnormalities.

In this issue of the Journal of Hospital Medicine, O’Sullivan et al. explore the associations between mean 72-hour serum potassium and important clinical outcomes—in-hospital mortality, transfer to an intensive care unit (ICU), and length of stay (LOS)—among patients with normal admission serum potassium hospitalized for ADHF.³ Through a retrospective review of electronic records from 116 hospitals, the authors identified 4,995 initially normokalemic heart failure (HF; identified by ICD-9 codes) patients and grouped them into low-normal (3.5-4.0 mEq/L), normal (4.0-4.5 mEq/L), and high-normal (4.5-5.0 mEq/L) potassium groups.³ Adjustments were made for composite scores encapsulating other lab abnormalities and comorbidities.

Over the 72-hour exposure window, the authors observed no statistically significant difference in mortality, ICU transfer, or LOS between the low-normal and normal potassium groups.³ Moreover, in a sensitivity analysis of patients who did not receive potassium supplementation, there remained statistically similar rates of mortality, ICU transfer, and LOS.³ Together, these findings suggest that maintenance of potassium >4 mEq/L may not be efficacious for preventing in-hospital complications of ADHF.³ In fact, they observed more frequent mortality and ICU transfer in patients who had high-normal potassium. This group, however, had a higher burden of chronic kidney disease and illness severity on presentation and was less likely to receive supplemental potassium.³

ADHF accounts for more than one million hospital admissions annually with one in four patients readmitted within 30 days; estimated costs surpass $30 billion.² Reducing unnecessary expenditures in the management of HF through evidence-based guidelines is paramount. Electrolyte repletion in the setting of ADHF may represent one such opportunity by reducing excess phlebotomy, laboratory services, and potassium supplementation. Patient experience may also improve from curbing these cumbersome practices. While society guidelines endorse potassium repletion in MI to reduce the risk of ventricular arrhythmia,⁴ there is no uniform consensus in ADHF. As the authors cite, existing data regarding ideal potassium levels in patients with ADHF is lacking, with current evidence drawn from small observational studies. The present study, being much larger in size and being linked with observed rates of active potassium supplementation, provides some of the strongest evidence to date that a potassium goal of >4 mEq/L may not be efficacious at reducing ADHF-related complications in the generalized HF population.

While it remains uncertain if avoiding low-normal potassium levels in ADHF is beneficial, over the long term, intermediate-range potassium levels are clearly associated with the lowest HF-related mortality. In a study of over 2,000 HF patients who underwent longitudinal potassium monitoring, mortality was distributed along a U-shaped curve with highest mortality at the extremes of kalemia and a nadir at a level of 4.3 mEq/L.⁵

A major limitation of the present study is that it does not account for variability within the ADHF population. Firstly, knowledge regarding the use of GDMT, which not only affects serum potassium (all GDMTs) but also reduces the likelihood of arrhythmias (beta blockers), would have been informative. Moreover, the authors do not have access to data regarding incident arrhythmia and instead use ICU admission as a surrogate. In addition, ADHF patients in this study varied greatly in illness severity, ranging from those receiving initial therapy with loop diuretics alone to those requiring augmentation with thiazides and even the use of temporary mechanical circulatory support.³ Escalating loop diuretic or metolazone use not only is associated with increased mortality⁶ but often results in impressive natriuresis and, potentially dangerous, kaliuresis secondary to the sequential nephron blockade.⁷ Those who underwent extensive potassium swings in the study may not be appropriately captured using 72-hour serum potassium averages. Additionally, this study did not assess for quantity of diuresis, which is known to affect serum potassium values. It is possible that those with low-normal potassium represent patients who underwent more effective diuresis and therefore were discharged sooner. Adding to the variability, ADHF in this study encompassed both systolic (HF with a reduced ejection fraction) and diastolic (HF with a preserved ejection fraction) HF although, perhaps not surprisingly, there were marked differences in the HF subtype by potassium group—the proportions with only diastolic dysfunction were 37.1%, 39.0%, and 45.8% in the low-normal, normal, and high-normal groups, respectively (P = .0174).³ Given the known heterogeneity between these two HF subtypes,⁸ particularly with respect to their response to mortality-reducing GDMT,^2,8 the results may be significantly confounded.

Relatedly, by excluding initially hypokalemic patients, the authors have lost considerable power and broad generalizability as these patients likely represent those at greatest risk of recurrent hypokalemia and its attendant complications during admission.

This study should be lauded for critically appraising the ubiquitous practice of electrolyte repletion. The authors present compelling preliminary data suggesting that maintenance of potassium >4 mEq/L in the general ADHF population is not efficacious at preventing ADHF complications and, as a corollary, is likely not cost-effective. However, we agree with the authors that a randomized controlled trial will be needed to change clinical practice. Ideally, such a study would account for HF subtype and GDMT use and could compare rates of arrhythmia, AHDF-related death, and all-cause mortality in patients maintained to goal normokalemia (>3.5 mEq/L) versus “high goal” (>4 mEq/L) with repletion. Only these types of studies will provide the strength of evidence needed to end a practice as well engrained in modern medicine as “high-goal ‘lytes”.

Disclosures

Dr. Blaha reports grants from NIH, grants from FDA, grants from AHA, grants and personal fees from Amgen Foundation, grants from Aetna Foundation, personal fees from Sanofi, personal fees from Regeneron, and personal fees from Novartis, from Novo Nordisk, and from Bayer, outside the submitted work. Dr. Dudum and Dr. Lahti have nothing to disclose.

Electrolyte imbalances, per se, predispose to ventricular ectopy and, in extreme cases, sudden cardiac death.¹ As these outcomes are more common in the presence of intrinsic heart disease, serum electrolytes—particularly potassium and magnesium—are routinely monitored and made replete in patients with myocardial infarction (MI) or acute decompensated heart failure (ADHF).

Patients hospitalized with ADHF often present with metabolic derangements and varying degrees of chronic adaptations in their renin–angiotensin–aldosterone system.^1,2 In addition, during an ADHF hospitalization, they are subjected to guideline-directed medical therapy (GDMT), commonly in escalating doses, that exhibit well-established effects on serum potassium levels, including diuretics, angiotensin-converting-enzyme inhibitors, angiotensin receptor blockers, beta blockers, and mineralocorticoid receptor antagonists. Thus, there are myriad ways patients hospitalized for ADHF might experience electrolyte abnormalities.

In this issue of the Journal of Hospital Medicine, O’Sullivan et al. explore the associations between mean 72-hour serum potassium and important clinical outcomes—in-hospital mortality, transfer to an intensive care unit (ICU), and length of stay (LOS)—among patients with normal admission serum potassium hospitalized for ADHF.³ Through a retrospective review of electronic records from 116 hospitals, the authors identified 4,995 initially normokalemic heart failure (HF; identified by ICD-9 codes) patients and grouped them into low-normal (3.5-4.0 mEq/L), normal (4.0-4.5 mEq/L), and high-normal (4.5-5.0 mEq/L) potassium groups.³ Adjustments were made for composite scores encapsulating other lab abnormalities and comorbidities.

Over the 72-hour exposure window, the authors observed no statistically significant difference in mortality, ICU transfer, or LOS between the low-normal and normal potassium groups.³ Moreover, in a sensitivity analysis of patients who did not receive potassium supplementation, there remained statistically similar rates of mortality, ICU transfer, and LOS.³ Together, these findings suggest that maintenance of potassium >4 mEq/L may not be efficacious for preventing in-hospital complications of ADHF.³ In fact, they observed more frequent mortality and ICU transfer in patients who had high-normal potassium. This group, however, had a higher burden of chronic kidney disease and illness severity on presentation and was less likely to receive supplemental potassium.³

ADHF accounts for more than one million hospital admissions annually with one in four patients readmitted within 30 days; estimated costs surpass $30 billion.² Reducing unnecessary expenditures in the management of HF through evidence-based guidelines is paramount. Electrolyte repletion in the setting of ADHF may represent one such opportunity by reducing excess phlebotomy, laboratory services, and potassium supplementation. Patient experience may also improve from curbing these cumbersome practices. While society guidelines endorse potassium repletion in MI to reduce the risk of ventricular arrhythmia,⁴ there is no uniform consensus in ADHF. As the authors cite, existing data regarding ideal potassium levels in patients with ADHF is lacking, with current evidence drawn from small observational studies. The present study, being much larger in size and being linked with observed rates of active potassium supplementation, provides some of the strongest evidence to date that a potassium goal of >4 mEq/L may not be efficacious at reducing ADHF-related complications in the generalized HF population.

While it remains uncertain if avoiding low-normal potassium levels in ADHF is beneficial, over the long term, intermediate-range potassium levels are clearly associated with the lowest HF-related mortality. In a study of over 2,000 HF patients who underwent longitudinal potassium monitoring, mortality was distributed along a U-shaped curve with highest mortality at the extremes of kalemia and a nadir at a level of 4.3 mEq/L.⁵

A major limitation of the present study is that it does not account for variability within the ADHF population. Firstly, knowledge regarding the use of GDMT, which not only affects serum potassium (all GDMTs) but also reduces the likelihood of arrhythmias (beta blockers), would have been informative. Moreover, the authors do not have access to data regarding incident arrhythmia and instead use ICU admission as a surrogate. In addition, ADHF patients in this study varied greatly in illness severity, ranging from those receiving initial therapy with loop diuretics alone to those requiring augmentation with thiazides and even the use of temporary mechanical circulatory support.³ Escalating loop diuretic or metolazone use not only is associated with increased mortality⁶ but often results in impressive natriuresis and, potentially dangerous, kaliuresis secondary to the sequential nephron blockade.⁷ Those who underwent extensive potassium swings in the study may not be appropriately captured using 72-hour serum potassium averages. Additionally, this study did not assess for quantity of diuresis, which is known to affect serum potassium values. It is possible that those with low-normal potassium represent patients who underwent more effective diuresis and therefore were discharged sooner. Adding to the variability, ADHF in this study encompassed both systolic (HF with a reduced ejection fraction) and diastolic (HF with a preserved ejection fraction) HF although, perhaps not surprisingly, there were marked differences in the HF subtype by potassium group—the proportions with only diastolic dysfunction were 37.1%, 39.0%, and 45.8% in the low-normal, normal, and high-normal groups, respectively (P = .0174).³ Given the known heterogeneity between these two HF subtypes,⁸ particularly with respect to their response to mortality-reducing GDMT,^2,8 the results may be significantly confounded.

Relatedly, by excluding initially hypokalemic patients, the authors have lost considerable power and broad generalizability as these patients likely represent those at greatest risk of recurrent hypokalemia and its attendant complications during admission.

This study should be lauded for critically appraising the ubiquitous practice of electrolyte repletion. The authors present compelling preliminary data suggesting that maintenance of potassium >4 mEq/L in the general ADHF population is not efficacious at preventing ADHF complications and, as a corollary, is likely not cost-effective. However, we agree with the authors that a randomized controlled trial will be needed to change clinical practice. Ideally, such a study would account for HF subtype and GDMT use and could compare rates of arrhythmia, AHDF-related death, and all-cause mortality in patients maintained to goal normokalemia (>3.5 mEq/L) versus “high goal” (>4 mEq/L) with repletion. Only these types of studies will provide the strength of evidence needed to end a practice as well engrained in modern medicine as “high-goal ‘lytes”.

Disclosures

Dr. Blaha reports grants from NIH, grants from FDA, grants from AHA, grants and personal fees from Amgen Foundation, grants from Aetna Foundation, personal fees from Sanofi, personal fees from Regeneron, and personal fees from Novartis, from Novo Nordisk, and from Bayer, outside the submitted work. Dr. Dudum and Dr. Lahti have nothing to disclose.