Despite recent advances made in medicine, gender-based disparities persist.^1-3 In particular, women with children have barriers to career advancement and show evidence of slower career advancement.^1,2 Multiple challenges for working women experiencing motherhood have been described. In academic medicine in the United States, women have limited access to paid parental leave.^4-6 For women who choose to breastfeed, there is limited time, space, and support available for breastfeeding.⁷ Furthermore, sleep deprivation in the postpartum period significantly impacts the ability to function at work.⁸

Hospital medicine is a unique specialty as it comprises 47% women, 80% of whom are aged less than 40 years, suggesting that a large portion are women of childbearing age.⁹ The field poses known challenges to this population, including shift work, atypical schedules, and unpredictable hours. We conducted a descriptive qualitative study to improve our understanding of the experience of female academic hospitalists who have experienced pregnancy, parental leave, and the return to work as faculty. Our goal was to both explore the challenges to undergoing this experience and discover solutions to support female academic hospitalists.

Study Design

We conducted a qualitative descriptive study of female hospitalists recruited from academic institutions represented in Society of Hospital Medicine (SHM) committees. Interviews were conducted between November 2017 and February 2018. Participants completed an informed consent and a demographic survey prior to the interview. Each interview lasted approximately 30 minutes; discussions were recorded on digital records and transcribed verbatim. This protocol was reviewed and granted exemption by the Institutional Review Board at the University of Colorado.

Population

We recruited participants from a selection of hospital medicine groups nationally, chosen from SHM committee representation. A purposeful snowball approach was used to identify hospitalists from representative programs and seek their recommendation for hospitalists from other targeted programs. Ten hospitalists were approached by e-mail to determine their interest in participation, and all of them agreed to participate. Each participant experienced new parenthood within the last seven years.

Framework

We constructed our interview to represent the following timeline associated with having children as it pertains to a hospitalist position: pregnancy, parental leave, and the return to work. The interview guide was structured to invoke the positive aspects, challenges, and solutions within each domain (Appendix 1).

Analysis

Codes were inductively developed from the interview data by a team of three board-certified internal medicine physicians (E.G., A.M., and C.J.), one of whom had prior training and experience with qualitative interviews and analysis (C.J.). Among the coders, two (E.G. and A.M.) conducted the semistructured interviews. Code disparities were reconciled by team consensus, where the primary coder facilitated the discussions. Themes were developed inductively from the codes, and the analysis was completed using a team-based iterative approach that was facilitated using ATLAS.ti.¹⁰ Thematic saturation was achieved. This study was approved by the Colorado Multiple Institutional Review Board.

The demographics and the characteristics of the hospital medicine group are shown in Table 1. Although we asked questions about both the positive and challenging aspects of the experience of parenthood, the interviews tended to focus more on the challenges faced and on areas for optimization.

Paid Parental leave

Most of the participants described inadequate paid parental leave, with minimal transparency in the processes for ensuring time off following the birth of their child, resulting in “haggling” with bosses, human resources, and the administrative staff. Rarely was a formal parental leave policy in place. Once a parental leave plan was established, several women reported the financial burden associated with a leave that was partially, or fully, unpaid.

“All of my leave was unpaid. .. managed to finagle short-term disability into paying for it… the system was otherwise set up to screw me financially.”

For the three women who did experience sufficient paid parental leave, they recognized the financial and emotional benefit and suggested that further optimization would include a prebirth schedule to account for the physical challenges and potential complications.

Physical Challenges

All of the women described significant physical challenges when working during pregnancy, resulting in limited bandwidth for additional academic activities outside of direct clinical care responsibilities.

“Exhaustion that hits you in your pregnancy and then you have to round. I used to lie on the floor of my office, take a little nap, wake up, write some notes, go home, take another nap, wake up, write some more notes.”

Upon return to work, women reported additional physical challenges related to sleep deprivation, impacting their productivity with academic work and emotional well-being.

“I came back from maternity leave and I was sleep-deprived and exhausted, I didn’t have the energy. All of these great projects that I had started or dreamed of … dwindled and died on the vine.”

Solutions suggested by the participants included creation of a flexible schedule with a ramp-up and ramp-down period around the birth.

Breastfeeding

The majority of participants in this study encountered several challenges associated with a shared goal of breastfeeding according to evidence-based guidelines.¹¹ Designated pumping areas were often inconveniently located and not conducive to multitasking.

“It’s two chairs that are behind a curtain in a women’s locker room in the basement of the hospital, that are tiny and gross. No computers, so I felt like I was wasting time.”

One hospitalist described carving out time for pumping in her office while multitasking with clinical work.

“I would get to work, set up, and pump while chart reviewing. Then I would go and see people… and come back to my office and pump and write a few notes. And go out and see more patients, and then pump and write a few more notes. And then pump, and then go home. I was like a cow.”

Women highlighted the barriers that could be optimized such as creating time in the clinical schedule for pumping, a physical space to breastfeed or pump, and accessible milk storage facilities.

Career Opportunities

When asked about the impact of parental leave on career opportunities, a few of the women described a phenomenon of no longer being asked to participate or being left out of prior projects.

“People didn’t want to offer you things or give you things because they realize you’re having this transition in your life. Not out of animosity, but out of courtesy that they don’t want to fill up your place even more. Her plate is full; we are not going to ask her to do anything extra.”

However, two women specifically reported a supportive environment without a loss of opportunities, often referenced as a boss who “saved” projects for their return.

Colleague Responses

One participant used the term “microaggressions,” to describe passive aggressions encountered by their colleagues or leadership.

“(A colleague) was diagnosed with pre-eclampsia, and very urgently had to deliver and couldn’t cover a week of shifts…She was asked initially to find her own coverage…Not treating (pregnancy) similar to other serious illnesses is what I would term a microaggression.”

Yet, women in our study also reported positive responses from colleagues and the importance of support networks of physician mothers (Table 2).

Empathy in Patient Care

Finally, the experience of motherhood impacted all of the women as physicians, described as increased empathy, patience, and understanding of difficult family situations.

“I’m just more sensitive to people’s lives outside the hospital, so, you know, when it’s difficult for a family member to get there because they have three other kids they are taking care of or, somebody that says they are leaving AMA, but it’s because they have a sick kid at home. I just have a better context for that.”

Gender disparities persist in both internal medicine and hospital medicine.¹ Providers in this descriptive qualitative study suggested that the following factors contribute: lack of paid parental leave and the associated financial penalties, loss of career opportunities, the physical challenges associated with pregnancy, decreasing productivity, and the amount of time and effort involved in breastfeeding. However, the participants also shared valuable ideas for future solutions to relieve the challenges imposed on working physician mothers (Table 2).

Breaking the Glass Ceiling

Participants noted the importance of a paid leave policy that encompasses not only maternity leave but also a flexible scheduling period before and after the leave to account for the challenges of pregnancy and new motherhood. Paid parental leave is rare in academic settings, but studies from other industries show that when women take paid leave, they are more likely to remain in the workforce 9-12 months afterward, work more weekly hours, and feel more loyal to their organization.^12,13 In the rare instance when negotiations around leave violate local policy or the law, women should be encouraged to seek guidance from their human resources department.

Me Too: Building Solidarity

Women in our study reported the value of a supportive workplace in easing their transition into motherhood. Specifically, they noted that a supportive boss who protected their career opportunities prevented momentum loss in their career trajectory. Access to mutual supports such as the Physicians Mom Group, a well-established Facebook group comprising more than 70,000 women, was referenced as a meaningful way to share joys and tribulations related to balancing a career as a physician and motherhood. Growth of similar support systems within institutions will further support this experience.

Time’s Up: The Promotion Clock

Women in our study described a prolonged period of diminished productivity related to having children, coinciding with a set time to promotion in academics. Flexible promotion schedules may impact women’s ability to successfully undergo promotion.

The aim of this study was to represent a shared set of experiences of female academic hospitalists who participated; therefore, the results may not be generalizable beyond this group. Due to the use of a purposeful snowball approach, there was a potential for selection bias. Future research may include comparing the experience of women at institutions that offer paid leave versus those that do not and the impact on retention, promotion, and well-being.

Women in hospital medicine encounter several challenges to having children, but they are also motivated to provide solutions. Efforts to improve the institutional and cultural landscape to better support women physicians with children are critical to prevent attrition of women and ensure equitable academic promotion and achievement of leadership positions.

Disclosures

The authors have no conflicts of interest to report.

Author Contributions

Each author was involved in the creation of the study protocol, data collection and analysis, and creation of the manuscript.

Despite recent advances made in medicine, gender-based disparities persist.^1-3 In particular, women with children have barriers to career advancement and show evidence of slower career advancement.^1,2 Multiple challenges for working women experiencing motherhood have been described. In academic medicine in the United States, women have limited access to paid parental leave.^4-6 For women who choose to breastfeed, there is limited time, space, and support available for breastfeeding.⁷ Furthermore, sleep deprivation in the postpartum period significantly impacts the ability to function at work.⁸

Hospital medicine is a unique specialty as it comprises 47% women, 80% of whom are aged less than 40 years, suggesting that a large portion are women of childbearing age.⁹ The field poses known challenges to this population, including shift work, atypical schedules, and unpredictable hours. We conducted a descriptive qualitative study to improve our understanding of the experience of female academic hospitalists who have experienced pregnancy, parental leave, and the return to work as faculty. Our goal was to both explore the challenges to undergoing this experience and discover solutions to support female academic hospitalists.

Study Design

We conducted a qualitative descriptive study of female hospitalists recruited from academic institutions represented in Society of Hospital Medicine (SHM) committees. Interviews were conducted between November 2017 and February 2018. Participants completed an informed consent and a demographic survey prior to the interview. Each interview lasted approximately 30 minutes; discussions were recorded on digital records and transcribed verbatim. This protocol was reviewed and granted exemption by the Institutional Review Board at the University of Colorado.

Population

We recruited participants from a selection of hospital medicine groups nationally, chosen from SHM committee representation. A purposeful snowball approach was used to identify hospitalists from representative programs and seek their recommendation for hospitalists from other targeted programs. Ten hospitalists were approached by e-mail to determine their interest in participation, and all of them agreed to participate. Each participant experienced new parenthood within the last seven years.

Framework

We constructed our interview to represent the following timeline associated with having children as it pertains to a hospitalist position: pregnancy, parental leave, and the return to work. The interview guide was structured to invoke the positive aspects, challenges, and solutions within each domain (Appendix 1).

Analysis

Codes were inductively developed from the interview data by a team of three board-certified internal medicine physicians (E.G., A.M., and C.J.), one of whom had prior training and experience with qualitative interviews and analysis (C.J.). Among the coders, two (E.G. and A.M.) conducted the semistructured interviews. Code disparities were reconciled by team consensus, where the primary coder facilitated the discussions. Themes were developed inductively from the codes, and the analysis was completed using a team-based iterative approach that was facilitated using ATLAS.ti.¹⁰ Thematic saturation was achieved. This study was approved by the Colorado Multiple Institutional Review Board.

The demographics and the characteristics of the hospital medicine group are shown in Table 1. Although we asked questions about both the positive and challenging aspects of the experience of parenthood, the interviews tended to focus more on the challenges faced and on areas for optimization.

Paid Parental leave

Most of the participants described inadequate paid parental leave, with minimal transparency in the processes for ensuring time off following the birth of their child, resulting in “haggling” with bosses, human resources, and the administrative staff. Rarely was a formal parental leave policy in place. Once a parental leave plan was established, several women reported the financial burden associated with a leave that was partially, or fully, unpaid.

“All of my leave was unpaid. .. managed to finagle short-term disability into paying for it… the system was otherwise set up to screw me financially.”

For the three women who did experience sufficient paid parental leave, they recognized the financial and emotional benefit and suggested that further optimization would include a prebirth schedule to account for the physical challenges and potential complications.

Physical Challenges

All of the women described significant physical challenges when working during pregnancy, resulting in limited bandwidth for additional academic activities outside of direct clinical care responsibilities.

“Exhaustion that hits you in your pregnancy and then you have to round. I used to lie on the floor of my office, take a little nap, wake up, write some notes, go home, take another nap, wake up, write some more notes.”

Upon return to work, women reported additional physical challenges related to sleep deprivation, impacting their productivity with academic work and emotional well-being.

“I came back from maternity leave and I was sleep-deprived and exhausted, I didn’t have the energy. All of these great projects that I had started or dreamed of … dwindled and died on the vine.”

Solutions suggested by the participants included creation of a flexible schedule with a ramp-up and ramp-down period around the birth.

Breastfeeding

The majority of participants in this study encountered several challenges associated with a shared goal of breastfeeding according to evidence-based guidelines.¹¹ Designated pumping areas were often inconveniently located and not conducive to multitasking.

“It’s two chairs that are behind a curtain in a women’s locker room in the basement of the hospital, that are tiny and gross. No computers, so I felt like I was wasting time.”

One hospitalist described carving out time for pumping in her office while multitasking with clinical work.

“I would get to work, set up, and pump while chart reviewing. Then I would go and see people… and come back to my office and pump and write a few notes. And go out and see more patients, and then pump and write a few more notes. And then pump, and then go home. I was like a cow.”

Women highlighted the barriers that could be optimized such as creating time in the clinical schedule for pumping, a physical space to breastfeed or pump, and accessible milk storage facilities.

Career Opportunities

When asked about the impact of parental leave on career opportunities, a few of the women described a phenomenon of no longer being asked to participate or being left out of prior projects.

“People didn’t want to offer you things or give you things because they realize you’re having this transition in your life. Not out of animosity, but out of courtesy that they don’t want to fill up your place even more. Her plate is full; we are not going to ask her to do anything extra.”

However, two women specifically reported a supportive environment without a loss of opportunities, often referenced as a boss who “saved” projects for their return.

Colleague Responses

One participant used the term “microaggressions,” to describe passive aggressions encountered by their colleagues or leadership.

“(A colleague) was diagnosed with pre-eclampsia, and very urgently had to deliver and couldn’t cover a week of shifts…She was asked initially to find her own coverage…Not treating (pregnancy) similar to other serious illnesses is what I would term a microaggression.”

Yet, women in our study also reported positive responses from colleagues and the importance of support networks of physician mothers (Table 2).

Empathy in Patient Care

Finally, the experience of motherhood impacted all of the women as physicians, described as increased empathy, patience, and understanding of difficult family situations.

“I’m just more sensitive to people’s lives outside the hospital, so, you know, when it’s difficult for a family member to get there because they have three other kids they are taking care of or, somebody that says they are leaving AMA, but it’s because they have a sick kid at home. I just have a better context for that.”

Gender disparities persist in both internal medicine and hospital medicine.¹ Providers in this descriptive qualitative study suggested that the following factors contribute: lack of paid parental leave and the associated financial penalties, loss of career opportunities, the physical challenges associated with pregnancy, decreasing productivity, and the amount of time and effort involved in breastfeeding. However, the participants also shared valuable ideas for future solutions to relieve the challenges imposed on working physician mothers (Table 2).

Breaking the Glass Ceiling

Participants noted the importance of a paid leave policy that encompasses not only maternity leave but also a flexible scheduling period before and after the leave to account for the challenges of pregnancy and new motherhood. Paid parental leave is rare in academic settings, but studies from other industries show that when women take paid leave, they are more likely to remain in the workforce 9-12 months afterward, work more weekly hours, and feel more loyal to their organization.^12,13 In the rare instance when negotiations around leave violate local policy or the law, women should be encouraged to seek guidance from their human resources department.

Me Too: Building Solidarity

Women in our study reported the value of a supportive workplace in easing their transition into motherhood. Specifically, they noted that a supportive boss who protected their career opportunities prevented momentum loss in their career trajectory. Access to mutual supports such as the Physicians Mom Group, a well-established Facebook group comprising more than 70,000 women, was referenced as a meaningful way to share joys and tribulations related to balancing a career as a physician and motherhood. Growth of similar support systems within institutions will further support this experience.

Time’s Up: The Promotion Clock

Women in our study described a prolonged period of diminished productivity related to having children, coinciding with a set time to promotion in academics. Flexible promotion schedules may impact women’s ability to successfully undergo promotion.

The aim of this study was to represent a shared set of experiences of female academic hospitalists who participated; therefore, the results may not be generalizable beyond this group. Due to the use of a purposeful snowball approach, there was a potential for selection bias. Future research may include comparing the experience of women at institutions that offer paid leave versus those that do not and the impact on retention, promotion, and well-being.

Women in hospital medicine encounter several challenges to having children, but they are also motivated to provide solutions. Efforts to improve the institutional and cultural landscape to better support women physicians with children are critical to prevent attrition of women and ensure equitable academic promotion and achievement of leadership positions.

Disclosures

The authors have no conflicts of interest to report.

Author Contributions

Each author was involved in the creation of the study protocol, data collection and analysis, and creation of the manuscript.

Despite recent advances made in medicine, gender-based disparities persist.^1-3 In particular, women with children have barriers to career advancement and show evidence of slower career advancement.^1,2 Multiple challenges for working women experiencing motherhood have been described. In academic medicine in the United States, women have limited access to paid parental leave.^4-6 For women who choose to breastfeed, there is limited time, space, and support available for breastfeeding.⁷ Furthermore, sleep deprivation in the postpartum period significantly impacts the ability to function at work.⁸

Hospital medicine is a unique specialty as it comprises 47% women, 80% of whom are aged less than 40 years, suggesting that a large portion are women of childbearing age.⁹ The field poses known challenges to this population, including shift work, atypical schedules, and unpredictable hours. We conducted a descriptive qualitative study to improve our understanding of the experience of female academic hospitalists who have experienced pregnancy, parental leave, and the return to work as faculty. Our goal was to both explore the challenges to undergoing this experience and discover solutions to support female academic hospitalists.

Study Design

We conducted a qualitative descriptive study of female hospitalists recruited from academic institutions represented in Society of Hospital Medicine (SHM) committees. Interviews were conducted between November 2017 and February 2018. Participants completed an informed consent and a demographic survey prior to the interview. Each interview lasted approximately 30 minutes; discussions were recorded on digital records and transcribed verbatim. This protocol was reviewed and granted exemption by the Institutional Review Board at the University of Colorado.

Population

We recruited participants from a selection of hospital medicine groups nationally, chosen from SHM committee representation. A purposeful snowball approach was used to identify hospitalists from representative programs and seek their recommendation for hospitalists from other targeted programs. Ten hospitalists were approached by e-mail to determine their interest in participation, and all of them agreed to participate. Each participant experienced new parenthood within the last seven years.

Framework

We constructed our interview to represent the following timeline associated with having children as it pertains to a hospitalist position: pregnancy, parental leave, and the return to work. The interview guide was structured to invoke the positive aspects, challenges, and solutions within each domain (Appendix 1).

Analysis

Codes were inductively developed from the interview data by a team of three board-certified internal medicine physicians (E.G., A.M., and C.J.), one of whom had prior training and experience with qualitative interviews and analysis (C.J.). Among the coders, two (E.G. and A.M.) conducted the semistructured interviews. Code disparities were reconciled by team consensus, where the primary coder facilitated the discussions. Themes were developed inductively from the codes, and the analysis was completed using a team-based iterative approach that was facilitated using ATLAS.ti.¹⁰ Thematic saturation was achieved. This study was approved by the Colorado Multiple Institutional Review Board.

The demographics and the characteristics of the hospital medicine group are shown in Table 1. Although we asked questions about both the positive and challenging aspects of the experience of parenthood, the interviews tended to focus more on the challenges faced and on areas for optimization.

Paid Parental leave

Most of the participants described inadequate paid parental leave, with minimal transparency in the processes for ensuring time off following the birth of their child, resulting in “haggling” with bosses, human resources, and the administrative staff. Rarely was a formal parental leave policy in place. Once a parental leave plan was established, several women reported the financial burden associated with a leave that was partially, or fully, unpaid.

“All of my leave was unpaid. .. managed to finagle short-term disability into paying for it… the system was otherwise set up to screw me financially.”

For the three women who did experience sufficient paid parental leave, they recognized the financial and emotional benefit and suggested that further optimization would include a prebirth schedule to account for the physical challenges and potential complications.

Physical Challenges

All of the women described significant physical challenges when working during pregnancy, resulting in limited bandwidth for additional academic activities outside of direct clinical care responsibilities.

“Exhaustion that hits you in your pregnancy and then you have to round. I used to lie on the floor of my office, take a little nap, wake up, write some notes, go home, take another nap, wake up, write some more notes.”

Upon return to work, women reported additional physical challenges related to sleep deprivation, impacting their productivity with academic work and emotional well-being.

“I came back from maternity leave and I was sleep-deprived and exhausted, I didn’t have the energy. All of these great projects that I had started or dreamed of … dwindled and died on the vine.”

Solutions suggested by the participants included creation of a flexible schedule with a ramp-up and ramp-down period around the birth.

Breastfeeding

The majority of participants in this study encountered several challenges associated with a shared goal of breastfeeding according to evidence-based guidelines.¹¹ Designated pumping areas were often inconveniently located and not conducive to multitasking.

“It’s two chairs that are behind a curtain in a women’s locker room in the basement of the hospital, that are tiny and gross. No computers, so I felt like I was wasting time.”

One hospitalist described carving out time for pumping in her office while multitasking with clinical work.

“I would get to work, set up, and pump while chart reviewing. Then I would go and see people… and come back to my office and pump and write a few notes. And go out and see more patients, and then pump and write a few more notes. And then pump, and then go home. I was like a cow.”

Women highlighted the barriers that could be optimized such as creating time in the clinical schedule for pumping, a physical space to breastfeed or pump, and accessible milk storage facilities.

Career Opportunities

When asked about the impact of parental leave on career opportunities, a few of the women described a phenomenon of no longer being asked to participate or being left out of prior projects.

“People didn’t want to offer you things or give you things because they realize you’re having this transition in your life. Not out of animosity, but out of courtesy that they don’t want to fill up your place even more. Her plate is full; we are not going to ask her to do anything extra.”

However, two women specifically reported a supportive environment without a loss of opportunities, often referenced as a boss who “saved” projects for their return.

Colleague Responses

One participant used the term “microaggressions,” to describe passive aggressions encountered by their colleagues or leadership.

“(A colleague) was diagnosed with pre-eclampsia, and very urgently had to deliver and couldn’t cover a week of shifts…She was asked initially to find her own coverage…Not treating (pregnancy) similar to other serious illnesses is what I would term a microaggression.”

Yet, women in our study also reported positive responses from colleagues and the importance of support networks of physician mothers (Table 2).

Empathy in Patient Care

Finally, the experience of motherhood impacted all of the women as physicians, described as increased empathy, patience, and understanding of difficult family situations.

“I’m just more sensitive to people’s lives outside the hospital, so, you know, when it’s difficult for a family member to get there because they have three other kids they are taking care of or, somebody that says they are leaving AMA, but it’s because they have a sick kid at home. I just have a better context for that.”

Gender disparities persist in both internal medicine and hospital medicine.¹ Providers in this descriptive qualitative study suggested that the following factors contribute: lack of paid parental leave and the associated financial penalties, loss of career opportunities, the physical challenges associated with pregnancy, decreasing productivity, and the amount of time and effort involved in breastfeeding. However, the participants also shared valuable ideas for future solutions to relieve the challenges imposed on working physician mothers (Table 2).

Breaking the Glass Ceiling

Participants noted the importance of a paid leave policy that encompasses not only maternity leave but also a flexible scheduling period before and after the leave to account for the challenges of pregnancy and new motherhood. Paid parental leave is rare in academic settings, but studies from other industries show that when women take paid leave, they are more likely to remain in the workforce 9-12 months afterward, work more weekly hours, and feel more loyal to their organization.^12,13 In the rare instance when negotiations around leave violate local policy or the law, women should be encouraged to seek guidance from their human resources department.

Me Too: Building Solidarity

Women in our study reported the value of a supportive workplace in easing their transition into motherhood. Specifically, they noted that a supportive boss who protected their career opportunities prevented momentum loss in their career trajectory. Access to mutual supports such as the Physicians Mom Group, a well-established Facebook group comprising more than 70,000 women, was referenced as a meaningful way to share joys and tribulations related to balancing a career as a physician and motherhood. Growth of similar support systems within institutions will further support this experience.

Time’s Up: The Promotion Clock

Women in our study described a prolonged period of diminished productivity related to having children, coinciding with a set time to promotion in academics. Flexible promotion schedules may impact women’s ability to successfully undergo promotion.

The aim of this study was to represent a shared set of experiences of female academic hospitalists who participated; therefore, the results may not be generalizable beyond this group. Due to the use of a purposeful snowball approach, there was a potential for selection bias. Future research may include comparing the experience of women at institutions that offer paid leave versus those that do not and the impact on retention, promotion, and well-being.

Women in hospital medicine encounter several challenges to having children, but they are also motivated to provide solutions. Efforts to improve the institutional and cultural landscape to better support women physicians with children are critical to prevent attrition of women and ensure equitable academic promotion and achievement of leadership positions.

Disclosures

The authors have no conflicts of interest to report.

Author Contributions

Each author was involved in the creation of the study protocol, data collection and analysis, and creation of the manuscript.

The role of internists in consultation has considerably expanded over the past half century. Consulting general internists increasingly work across disciplines to coordinate complex care.^1,2 Some internists assume a “comanagement” role with surgical specialties. This role requires sharing responsibility and accountability and involvement in admission/discharge processes.^3-6 Internal medicine (IM) residents are required to serve as consultants.⁷ Yet, aside from observations collected 30 to 40 years ago, limited information is available for guiding educators in developing consultative curricula.^2,8-10 We sought to assess current consultative practices across a sample of IM training programs. Specifically, we examined which services consult IM and their reasons for consultation (RFCs).

We collected data on consultation requests at 11 US academic medical centers (AMCs). We applied a selective sampling approach that leveraged existing relationships and interest in consultative medicine to identify institutions across a variety of geographic locations. We collected data regarding the consult service structure at each site, including data on the presence or absence of comanagement services and consult requests received.

Data Collection Tool

Investigators at the University of Texas Health San Antonio (UTHSA) drafted the data collection tool. Iterative feedback on the data collection tool was obtained from the research consortium (final tool, Supplemental Figure). Data collected included service requesting consultation, RFC, time request was made (day/night), who first saw the patient (eg, resident, attending), whether requesting and consulting providers verbally communicated, and whether patients were transferred to medicine. Respondents also estimated how often RFCs were encountered during their general medicine services.

To streamline data collection, we used click boxes and drop-down lists that included diagnoses and symptoms. The use of these predetermined RFCs was based on prior studies and discussion with the research consortium on common RFCs in clinical practice. A write-in field was also included. Respondents could select multiple RFCs in the case of multiple questions. Respondents also provided data regarding clinical issues that were incidentally identified during their initial patient assessments. Incidentally identified issues are hereafter called “additional RFCs” for differentiation from stated RFCs. Prior to data collection, the tool was piloted at UTHSA.

Data Collection, Categorization, and Analysis

Participants submitted data using Survey Monkey (Palo Alto, California). Emails with the survey link were sent daily. Specific participants for each data collection period were chosen by each site. Days with no data entry were confirmed by the study coordinator. Each institution collected data for four 2-week periods from July 2014 to July 2015 for a total of 8 weeks. We did not track follow-up encounters. Repeat consultations for different reasons were considered new consults.

All survey responses and free-text RFC entries were independently reviewed and categorized by 2 authors (E.W. and M.S.). New categories were created if needed. If reviewers disagreed, a third reviewer (C.M.) reviewed the RFC. The research consortium reviewed the final list of categories and entries.

We calculated descriptive statistics using SAS version 9.3 (SAS Institute, Inc., Cary, North Carolina). Each analysis used complete responses for each survey component. We separately analyzed services with and without comanagement components. The study was approved by UTHSA’s Institutional Review Board.

A total of 11 AMCs that represent 9 academic affiliations participated in this study (Table 1). Of the 11 AMCs, 7 were public nonprofit, 3 were private nonprofit, and 1 was a Veterans Health Administration facility. Out of the 11 AMCs, 9 sites included residents on the consult service, and the rotation was required at 6 of the sites. Most sites with residents had a formal curriculum that ranged from curated articles to online modules. Out of the 11 services, 4 were consult and comanagement services. All 4 co-managed orthopedic patients, and 1 also included other patients.

Data for 1,264 patient encounters with 2,778 RFCs were collected. A total of 1,218 of the surveys (96.4%) were fully completed, and only 5 surveys were missing data for multiple questions. A total of 7 sites adhered to the planned protocol. Among the sites, 1 site had 1 incomplete collection period, 1 site missed 1 collection period, and 1 site missed 2 collection periods.

Most consultations (87.1%) were requested during the day. Many patients (55.9%) were initially seen by residents, and 32.4% of the patients were initially seen by an attending. Respondents reported communicating verbally with the requesting team in 93.9% of instances. Among the patients, 7.8% were transferred to medicine following initial consultation. This percentage was higher (10.2%) in services without comanagement.

The average number of new consults per day per site was 2.24. The range for individual sites was 1.36-3.48. The maximum number of new consults in 1 day was 10. All sites had at least 1 day without new consults. The mean number of RFCs per encounter was 2.20 (median 2, range 1-13). In 226 of 360 encounters in which comanagement was an RFC, the respondent enumerated the other specific RFCs addressed. In these encounters, the mean number of RFCs (in addition to comanagement) was 3.02.

Most requests (82.2%) originated from surgical services. Among all surgical services, orthopedic surgery requested the highest number of consultations (67.5% for services with a comanagement component; 28.5% for services without) and 81.2% of the 360 comanagement encounters. Refer to Supplemental Table 1 for detailed information on the services that requested consultation.

The most common RFC was comanagement (13.0% across the entire study; 23.3% for services with a comanagement component; Table 2). For services without comanagement, preoperative evaluation was the most common RFC (16.4%). Other frequent RFCs across the entire study included blood pressure management (8.9%), glycemic management (7.2%), and renal failure (3.9%). Additional (unstated) RFCs were addressed in 944 patients (34.0%), and blood pressure management was the most common additional RFC.

Our study provides insights into the consultative landscape of AMCs and identified who consults IMs and their RFCs. Thus, our study has implications for resident consultative education. The consult services included in our study presented varied structures, including those that require medicine consultation as a resident rotation and those with comanagement agreements. Consistent with the results of prior studies, surgical services requested the majority of consults, with orthopedic surgery generating the highest number of requests. Consultation requests from neurosurgery were higher than previously reported.^2,8,9

Our study reveals that comanagement and preoperative evaluation are the most common RFCs and are the least commonly encountered RFCs in IM inpatient services. The broad nature of these RFCs speaks to an increasing need for comprehensive consultative care. Consultants addressed a wide range of clinical issues, including rare entities that defy easy categorization (eg, Moyamoya disease). This broad landscape presents challenges in focusing curricular content areas outside of comanagement and preoperative evaluation but does provide evidence “to expect the unexpected” in IM consultation, as has been previously noted.⁸

In over a third of encounters, consultants addressed an issue that was not stated in the initial RFC. Consultants also addressed more than 2 RFCs per encounter. These observations suggest that medicine consult services may be essentially comanaging some patients even when a comanagement care model is not formally in place. These findings provide rationale for the continued expansion of comanagement services.¹¹

Our study provides further evidence that, in modern consultative practice, “determining your customer” is more important than “determining the question.”^12-14 We work in an era in which comanagement services are increasingly prevalent but are not ubiquitous and in which IM consultants routinely address multiple issues. Prior studies indicated that most surgeons do not believe that consults should be limited to specific questions and instead prefer comanagement.¹³ Understanding the expectations of the requesting physician is therefore important and highlights the importance of verbal communication at the time of initial consultation. Ongoing interprofessional communication is a vital skill that residents should acquire.

Our study has several limitations. Although our sites represented a varied sample, we focused on AMCs. Therefore, our study may not reflect consultative experiences in nonacademic hospitals or sites without dedicated consult services. Trade-offs exist in our data collection approach, which provided predetermined RFCs. We selected our methodology to facilitate data entry and to aid RFC categorization. Nevertheless, it may have lessened the clinical nuance of submitted data. The provision of predetermined RFCs may have influenced issue selection by the respondents. However, in 473 encounters (37.4%), the survey respondents provided free-text entries for the stated RFC, and 944 additional RFCs were written in as responses. These results demonstrated that respondents did not limit themselves to the predetermined list. We did not perform chart reviews to validate data. Finally, our data were a cross-section of initial consultations. We lack information on subsequent diagnoses or additional clinical issues that developed later.

In conclusion, we found varied consultative experiences across AMCs. However, preoperative evaluation and perioperative comanagement – particularly of orthopedic and neurosurgical patients – were common and should be included in curricula. Faculty should recognize the unique nature of IM consultation to prepare residents. Specifically, faculty should prepare residents to expect to identify and address unstated medical issues and to provide comprehensive assessments regardless of whether the consultative structure has a comanagement component. Given the unique nature of consultative IM work and the possibility of discordant expectations between consulting and requesting physicians, perhaps the most valuable skill to impart to residents is effective and regular communication.

Medicine Consult/Comanagement Consortium Members

The Medicine Consult/Comanagement Consortium consists of: Mary Anderson Wallace, MD, Brian Wolfe, MD (University of Colorado), Meridale Baggett, MD, Douglas Wright, MD, PhD (Harvard University), Joyeeta G. Dastidar MD, Maureen Kelly, MD (Columbia University), Leonard S. Feldman, MD (Johns Hopkins University), Cecily J. Gallup, MD, MPH (University of California, San Francisco), Paul J. Grant, MD (University of Michigan), Craig R. Keenan, MD (University of California, Davis), Fletcher Penney, MD (Medical University of South Carolina).

Acknowledgments

The authors thank the clinicians at each site who were involved in data collection for this study, including Barbara Statland, MD. The authors also thank Timothy Niessen, MD for data and physician coordination and Musarrat Nahid, MSc. for statistical analysis.

Disclosures

Paul J. Grant receives royalties from the medical textbook Perioperative Medicine: Medical Consultation and Comanagement, Wiley Publishing 2012. Craig R. Keenan receives medicolegal consultation fees from Weiss-Salinas Law Group and American Psychiatric Association Publishers for book royalties. All other authors declare that they do not have any conflicts of interest.

Funding Information

The research reported here was supported by the Department of Veterans Affairs, Veterans Health Administration. Investigator salary support is provided through the South Texas Veterans Health Care System. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or our institutions.

The role of internists in consultation has considerably expanded over the past half century. Consulting general internists increasingly work across disciplines to coordinate complex care.^1,2 Some internists assume a “comanagement” role with surgical specialties. This role requires sharing responsibility and accountability and involvement in admission/discharge processes.^3-6 Internal medicine (IM) residents are required to serve as consultants.⁷ Yet, aside from observations collected 30 to 40 years ago, limited information is available for guiding educators in developing consultative curricula.^2,8-10 We sought to assess current consultative practices across a sample of IM training programs. Specifically, we examined which services consult IM and their reasons for consultation (RFCs).

We collected data on consultation requests at 11 US academic medical centers (AMCs). We applied a selective sampling approach that leveraged existing relationships and interest in consultative medicine to identify institutions across a variety of geographic locations. We collected data regarding the consult service structure at each site, including data on the presence or absence of comanagement services and consult requests received.

Data Collection Tool

Investigators at the University of Texas Health San Antonio (UTHSA) drafted the data collection tool. Iterative feedback on the data collection tool was obtained from the research consortium (final tool, Supplemental Figure). Data collected included service requesting consultation, RFC, time request was made (day/night), who first saw the patient (eg, resident, attending), whether requesting and consulting providers verbally communicated, and whether patients were transferred to medicine. Respondents also estimated how often RFCs were encountered during their general medicine services.

To streamline data collection, we used click boxes and drop-down lists that included diagnoses and symptoms. The use of these predetermined RFCs was based on prior studies and discussion with the research consortium on common RFCs in clinical practice. A write-in field was also included. Respondents could select multiple RFCs in the case of multiple questions. Respondents also provided data regarding clinical issues that were incidentally identified during their initial patient assessments. Incidentally identified issues are hereafter called “additional RFCs” for differentiation from stated RFCs. Prior to data collection, the tool was piloted at UTHSA.

Data Collection, Categorization, and Analysis

Participants submitted data using Survey Monkey (Palo Alto, California). Emails with the survey link were sent daily. Specific participants for each data collection period were chosen by each site. Days with no data entry were confirmed by the study coordinator. Each institution collected data for four 2-week periods from July 2014 to July 2015 for a total of 8 weeks. We did not track follow-up encounters. Repeat consultations for different reasons were considered new consults.

All survey responses and free-text RFC entries were independently reviewed and categorized by 2 authors (E.W. and M.S.). New categories were created if needed. If reviewers disagreed, a third reviewer (C.M.) reviewed the RFC. The research consortium reviewed the final list of categories and entries.

We calculated descriptive statistics using SAS version 9.3 (SAS Institute, Inc., Cary, North Carolina). Each analysis used complete responses for each survey component. We separately analyzed services with and without comanagement components. The study was approved by UTHSA’s Institutional Review Board.

A total of 11 AMCs that represent 9 academic affiliations participated in this study (Table 1). Of the 11 AMCs, 7 were public nonprofit, 3 were private nonprofit, and 1 was a Veterans Health Administration facility. Out of the 11 AMCs, 9 sites included residents on the consult service, and the rotation was required at 6 of the sites. Most sites with residents had a formal curriculum that ranged from curated articles to online modules. Out of the 11 services, 4 were consult and comanagement services. All 4 co-managed orthopedic patients, and 1 also included other patients.

Data for 1,264 patient encounters with 2,778 RFCs were collected. A total of 1,218 of the surveys (96.4%) were fully completed, and only 5 surveys were missing data for multiple questions. A total of 7 sites adhered to the planned protocol. Among the sites, 1 site had 1 incomplete collection period, 1 site missed 1 collection period, and 1 site missed 2 collection periods.

Most consultations (87.1%) were requested during the day. Many patients (55.9%) were initially seen by residents, and 32.4% of the patients were initially seen by an attending. Respondents reported communicating verbally with the requesting team in 93.9% of instances. Among the patients, 7.8% were transferred to medicine following initial consultation. This percentage was higher (10.2%) in services without comanagement.

The average number of new consults per day per site was 2.24. The range for individual sites was 1.36-3.48. The maximum number of new consults in 1 day was 10. All sites had at least 1 day without new consults. The mean number of RFCs per encounter was 2.20 (median 2, range 1-13). In 226 of 360 encounters in which comanagement was an RFC, the respondent enumerated the other specific RFCs addressed. In these encounters, the mean number of RFCs (in addition to comanagement) was 3.02.

Most requests (82.2%) originated from surgical services. Among all surgical services, orthopedic surgery requested the highest number of consultations (67.5% for services with a comanagement component; 28.5% for services without) and 81.2% of the 360 comanagement encounters. Refer to Supplemental Table 1 for detailed information on the services that requested consultation.

The most common RFC was comanagement (13.0% across the entire study; 23.3% for services with a comanagement component; Table 2). For services without comanagement, preoperative evaluation was the most common RFC (16.4%). Other frequent RFCs across the entire study included blood pressure management (8.9%), glycemic management (7.2%), and renal failure (3.9%). Additional (unstated) RFCs were addressed in 944 patients (34.0%), and blood pressure management was the most common additional RFC.

Our study provides insights into the consultative landscape of AMCs and identified who consults IMs and their RFCs. Thus, our study has implications for resident consultative education. The consult services included in our study presented varied structures, including those that require medicine consultation as a resident rotation and those with comanagement agreements. Consistent with the results of prior studies, surgical services requested the majority of consults, with orthopedic surgery generating the highest number of requests. Consultation requests from neurosurgery were higher than previously reported.^2,8,9

Our study reveals that comanagement and preoperative evaluation are the most common RFCs and are the least commonly encountered RFCs in IM inpatient services. The broad nature of these RFCs speaks to an increasing need for comprehensive consultative care. Consultants addressed a wide range of clinical issues, including rare entities that defy easy categorization (eg, Moyamoya disease). This broad landscape presents challenges in focusing curricular content areas outside of comanagement and preoperative evaluation but does provide evidence “to expect the unexpected” in IM consultation, as has been previously noted.⁸

In over a third of encounters, consultants addressed an issue that was not stated in the initial RFC. Consultants also addressed more than 2 RFCs per encounter. These observations suggest that medicine consult services may be essentially comanaging some patients even when a comanagement care model is not formally in place. These findings provide rationale for the continued expansion of comanagement services.¹¹

Our study provides further evidence that, in modern consultative practice, “determining your customer” is more important than “determining the question.”^12-14 We work in an era in which comanagement services are increasingly prevalent but are not ubiquitous and in which IM consultants routinely address multiple issues. Prior studies indicated that most surgeons do not believe that consults should be limited to specific questions and instead prefer comanagement.¹³ Understanding the expectations of the requesting physician is therefore important and highlights the importance of verbal communication at the time of initial consultation. Ongoing interprofessional communication is a vital skill that residents should acquire.

Our study has several limitations. Although our sites represented a varied sample, we focused on AMCs. Therefore, our study may not reflect consultative experiences in nonacademic hospitals or sites without dedicated consult services. Trade-offs exist in our data collection approach, which provided predetermined RFCs. We selected our methodology to facilitate data entry and to aid RFC categorization. Nevertheless, it may have lessened the clinical nuance of submitted data. The provision of predetermined RFCs may have influenced issue selection by the respondents. However, in 473 encounters (37.4%), the survey respondents provided free-text entries for the stated RFC, and 944 additional RFCs were written in as responses. These results demonstrated that respondents did not limit themselves to the predetermined list. We did not perform chart reviews to validate data. Finally, our data were a cross-section of initial consultations. We lack information on subsequent diagnoses or additional clinical issues that developed later.

In conclusion, we found varied consultative experiences across AMCs. However, preoperative evaluation and perioperative comanagement – particularly of orthopedic and neurosurgical patients – were common and should be included in curricula. Faculty should recognize the unique nature of IM consultation to prepare residents. Specifically, faculty should prepare residents to expect to identify and address unstated medical issues and to provide comprehensive assessments regardless of whether the consultative structure has a comanagement component. Given the unique nature of consultative IM work and the possibility of discordant expectations between consulting and requesting physicians, perhaps the most valuable skill to impart to residents is effective and regular communication.

Medicine Consult/Comanagement Consortium Members

The Medicine Consult/Comanagement Consortium consists of: Mary Anderson Wallace, MD, Brian Wolfe, MD (University of Colorado), Meridale Baggett, MD, Douglas Wright, MD, PhD (Harvard University), Joyeeta G. Dastidar MD, Maureen Kelly, MD (Columbia University), Leonard S. Feldman, MD (Johns Hopkins University), Cecily J. Gallup, MD, MPH (University of California, San Francisco), Paul J. Grant, MD (University of Michigan), Craig R. Keenan, MD (University of California, Davis), Fletcher Penney, MD (Medical University of South Carolina).

Acknowledgments

The authors thank the clinicians at each site who were involved in data collection for this study, including Barbara Statland, MD. The authors also thank Timothy Niessen, MD for data and physician coordination and Musarrat Nahid, MSc. for statistical analysis.

Disclosures

Paul J. Grant receives royalties from the medical textbook Perioperative Medicine: Medical Consultation and Comanagement, Wiley Publishing 2012. Craig R. Keenan receives medicolegal consultation fees from Weiss-Salinas Law Group and American Psychiatric Association Publishers for book royalties. All other authors declare that they do not have any conflicts of interest.

Funding Information

The research reported here was supported by the Department of Veterans Affairs, Veterans Health Administration. Investigator salary support is provided through the South Texas Veterans Health Care System. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or our institutions.

The role of internists in consultation has considerably expanded over the past half century. Consulting general internists increasingly work across disciplines to coordinate complex care.^1,2 Some internists assume a “comanagement” role with surgical specialties. This role requires sharing responsibility and accountability and involvement in admission/discharge processes.^3-6 Internal medicine (IM) residents are required to serve as consultants.⁷ Yet, aside from observations collected 30 to 40 years ago, limited information is available for guiding educators in developing consultative curricula.^2,8-10 We sought to assess current consultative practices across a sample of IM training programs. Specifically, we examined which services consult IM and their reasons for consultation (RFCs).

We collected data on consultation requests at 11 US academic medical centers (AMCs). We applied a selective sampling approach that leveraged existing relationships and interest in consultative medicine to identify institutions across a variety of geographic locations. We collected data regarding the consult service structure at each site, including data on the presence or absence of comanagement services and consult requests received.

Data Collection Tool

Investigators at the University of Texas Health San Antonio (UTHSA) drafted the data collection tool. Iterative feedback on the data collection tool was obtained from the research consortium (final tool, Supplemental Figure). Data collected included service requesting consultation, RFC, time request was made (day/night), who first saw the patient (eg, resident, attending), whether requesting and consulting providers verbally communicated, and whether patients were transferred to medicine. Respondents also estimated how often RFCs were encountered during their general medicine services.

To streamline data collection, we used click boxes and drop-down lists that included diagnoses and symptoms. The use of these predetermined RFCs was based on prior studies and discussion with the research consortium on common RFCs in clinical practice. A write-in field was also included. Respondents could select multiple RFCs in the case of multiple questions. Respondents also provided data regarding clinical issues that were incidentally identified during their initial patient assessments. Incidentally identified issues are hereafter called “additional RFCs” for differentiation from stated RFCs. Prior to data collection, the tool was piloted at UTHSA.

Data Collection, Categorization, and Analysis

Participants submitted data using Survey Monkey (Palo Alto, California). Emails with the survey link were sent daily. Specific participants for each data collection period were chosen by each site. Days with no data entry were confirmed by the study coordinator. Each institution collected data for four 2-week periods from July 2014 to July 2015 for a total of 8 weeks. We did not track follow-up encounters. Repeat consultations for different reasons were considered new consults.

All survey responses and free-text RFC entries were independently reviewed and categorized by 2 authors (E.W. and M.S.). New categories were created if needed. If reviewers disagreed, a third reviewer (C.M.) reviewed the RFC. The research consortium reviewed the final list of categories and entries.

We calculated descriptive statistics using SAS version 9.3 (SAS Institute, Inc., Cary, North Carolina). Each analysis used complete responses for each survey component. We separately analyzed services with and without comanagement components. The study was approved by UTHSA’s Institutional Review Board.

A total of 11 AMCs that represent 9 academic affiliations participated in this study (Table 1). Of the 11 AMCs, 7 were public nonprofit, 3 were private nonprofit, and 1 was a Veterans Health Administration facility. Out of the 11 AMCs, 9 sites included residents on the consult service, and the rotation was required at 6 of the sites. Most sites with residents had a formal curriculum that ranged from curated articles to online modules. Out of the 11 services, 4 were consult and comanagement services. All 4 co-managed orthopedic patients, and 1 also included other patients.

Data for 1,264 patient encounters with 2,778 RFCs were collected. A total of 1,218 of the surveys (96.4%) were fully completed, and only 5 surveys were missing data for multiple questions. A total of 7 sites adhered to the planned protocol. Among the sites, 1 site had 1 incomplete collection period, 1 site missed 1 collection period, and 1 site missed 2 collection periods.

Most consultations (87.1%) were requested during the day. Many patients (55.9%) were initially seen by residents, and 32.4% of the patients were initially seen by an attending. Respondents reported communicating verbally with the requesting team in 93.9% of instances. Among the patients, 7.8% were transferred to medicine following initial consultation. This percentage was higher (10.2%) in services without comanagement.

The average number of new consults per day per site was 2.24. The range for individual sites was 1.36-3.48. The maximum number of new consults in 1 day was 10. All sites had at least 1 day without new consults. The mean number of RFCs per encounter was 2.20 (median 2, range 1-13). In 226 of 360 encounters in which comanagement was an RFC, the respondent enumerated the other specific RFCs addressed. In these encounters, the mean number of RFCs (in addition to comanagement) was 3.02.

Most requests (82.2%) originated from surgical services. Among all surgical services, orthopedic surgery requested the highest number of consultations (67.5% for services with a comanagement component; 28.5% for services without) and 81.2% of the 360 comanagement encounters. Refer to Supplemental Table 1 for detailed information on the services that requested consultation.

The most common RFC was comanagement (13.0% across the entire study; 23.3% for services with a comanagement component; Table 2). For services without comanagement, preoperative evaluation was the most common RFC (16.4%). Other frequent RFCs across the entire study included blood pressure management (8.9%), glycemic management (7.2%), and renal failure (3.9%). Additional (unstated) RFCs were addressed in 944 patients (34.0%), and blood pressure management was the most common additional RFC.

Our study provides insights into the consultative landscape of AMCs and identified who consults IMs and their RFCs. Thus, our study has implications for resident consultative education. The consult services included in our study presented varied structures, including those that require medicine consultation as a resident rotation and those with comanagement agreements. Consistent with the results of prior studies, surgical services requested the majority of consults, with orthopedic surgery generating the highest number of requests. Consultation requests from neurosurgery were higher than previously reported.^2,8,9

Our study reveals that comanagement and preoperative evaluation are the most common RFCs and are the least commonly encountered RFCs in IM inpatient services. The broad nature of these RFCs speaks to an increasing need for comprehensive consultative care. Consultants addressed a wide range of clinical issues, including rare entities that defy easy categorization (eg, Moyamoya disease). This broad landscape presents challenges in focusing curricular content areas outside of comanagement and preoperative evaluation but does provide evidence “to expect the unexpected” in IM consultation, as has been previously noted.⁸

In over a third of encounters, consultants addressed an issue that was not stated in the initial RFC. Consultants also addressed more than 2 RFCs per encounter. These observations suggest that medicine consult services may be essentially comanaging some patients even when a comanagement care model is not formally in place. These findings provide rationale for the continued expansion of comanagement services.¹¹

Our study provides further evidence that, in modern consultative practice, “determining your customer” is more important than “determining the question.”^12-14 We work in an era in which comanagement services are increasingly prevalent but are not ubiquitous and in which IM consultants routinely address multiple issues. Prior studies indicated that most surgeons do not believe that consults should be limited to specific questions and instead prefer comanagement.¹³ Understanding the expectations of the requesting physician is therefore important and highlights the importance of verbal communication at the time of initial consultation. Ongoing interprofessional communication is a vital skill that residents should acquire.

Our study has several limitations. Although our sites represented a varied sample, we focused on AMCs. Therefore, our study may not reflect consultative experiences in nonacademic hospitals or sites without dedicated consult services. Trade-offs exist in our data collection approach, which provided predetermined RFCs. We selected our methodology to facilitate data entry and to aid RFC categorization. Nevertheless, it may have lessened the clinical nuance of submitted data. The provision of predetermined RFCs may have influenced issue selection by the respondents. However, in 473 encounters (37.4%), the survey respondents provided free-text entries for the stated RFC, and 944 additional RFCs were written in as responses. These results demonstrated that respondents did not limit themselves to the predetermined list. We did not perform chart reviews to validate data. Finally, our data were a cross-section of initial consultations. We lack information on subsequent diagnoses or additional clinical issues that developed later.

In conclusion, we found varied consultative experiences across AMCs. However, preoperative evaluation and perioperative comanagement – particularly of orthopedic and neurosurgical patients – were common and should be included in curricula. Faculty should recognize the unique nature of IM consultation to prepare residents. Specifically, faculty should prepare residents to expect to identify and address unstated medical issues and to provide comprehensive assessments regardless of whether the consultative structure has a comanagement component. Given the unique nature of consultative IM work and the possibility of discordant expectations between consulting and requesting physicians, perhaps the most valuable skill to impart to residents is effective and regular communication.

Medicine Consult/Comanagement Consortium Members

The Medicine Consult/Comanagement Consortium consists of: Mary Anderson Wallace, MD, Brian Wolfe, MD (University of Colorado), Meridale Baggett, MD, Douglas Wright, MD, PhD (Harvard University), Joyeeta G. Dastidar MD, Maureen Kelly, MD (Columbia University), Leonard S. Feldman, MD (Johns Hopkins University), Cecily J. Gallup, MD, MPH (University of California, San Francisco), Paul J. Grant, MD (University of Michigan), Craig R. Keenan, MD (University of California, Davis), Fletcher Penney, MD (Medical University of South Carolina).

Acknowledgments

The authors thank the clinicians at each site who were involved in data collection for this study, including Barbara Statland, MD. The authors also thank Timothy Niessen, MD for data and physician coordination and Musarrat Nahid, MSc. for statistical analysis.

Disclosures

Paul J. Grant receives royalties from the medical textbook Perioperative Medicine: Medical Consultation and Comanagement, Wiley Publishing 2012. Craig R. Keenan receives medicolegal consultation fees from Weiss-Salinas Law Group and American Psychiatric Association Publishers for book royalties. All other authors declare that they do not have any conflicts of interest.

Funding Information

The research reported here was supported by the Department of Veterans Affairs, Veterans Health Administration. Investigator salary support is provided through the South Texas Veterans Health Care System. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or our institutions.

Routine laboratory testing in hospitalized patients is common, with a high prevalence of unnecessary tests that do not contribute to patient management.¹ Excessive laboratory testing of hospitalized patients can contribute to anemia² and may cause patient discomfort, additional unnecessary testing resulting from false positive results, and higher out-of-pocket patient costs. Excessive testing can impact hospital budgets both directly (though direct costs are often low) and indirectly through costly downstream services and prolonged hospital stay.³ As part of the American Board of Internal Medicine (ABIM) Foundation’s Choosing Wisely initiative, several professional societies have recommended against routine laboratory testing of hospitalized adult patients.⁴

Excessive inpatient laboratory testing has been documented mostly among adult internal medicine (IM) patients with studies of drivers of unnecessary testing and efforts to reduce it conducted in IM settings.^{5, 6} Attitudes toward other issues related to testing overuse differ by specialty⁷ and are likely to similarly vary with regard to unnecessary laboratory testing. Understanding differences in attitudes by clinical specialty is critical for framing tailored approaches to reducing inappropriate care.

We performed a cross-sectional survey of a diverse group of hospital clinicians to describe attitudes and beliefs regarding laboratory testing and its overuse across clinical specialties (eg, medical, surgical, and pediatric). We hypothesized that attitudes toward the need for testing would differ across specialties.

Survey Development and Administration

The study was conducted at Memorial Sloan Kettering Cancer Center, a tertiary academic cancer hospital in New York City. The 12-item survey was adopted from a previously administered but not formally validated survey (Online-only Appendix).^5,8 The survey was pilot tested with 4 physicians, 3 NPs, 2 PAs, and 3 RNs and edited for content and clarity. All staff providers including NPs, PAs, RNs, and resident, fellow, and attending MDs working in the hospital during the 2-week survey period (November 2-15, 2015) were eligible to participate and were emailed a link to the survey. The email invitation was resent 3 times during the survey period. Participants who completed the survey received a coupon for a free coffee. The study was reviewed by the Institutional Review Board and exempted from ongoing oversight.

Measures

Demographic items included clinical specialty, provider type, and gender (Online-only Appendix). The remaining survey questions included the following categories:

1. Attitudes toward laboratory testing were evaluated by 3 items about accepted norms for lab testing and 2 items about fears (Table 2). Responses to these items used a 4-point Likert scale (strongly agree to strongly disagree).

2. Drivers contributing to unnecessary testing were evaluated by presenting a list of possible contributing factors (Table 2). Responses to these items used a 3-point Likert scale (contributes a lot, contributes a little, or does not contribute).

Analysis

We used univariate statistics to describe demographics and survey responses. We used the chi-square statistic to evaluate differences in attitudes and drivers by clinical specialty. We dichotomized responses regarding attitudes toward lab testing (“strongly agree” and “somewhat agree” vs. “somewhat disagree” and “strongly disagree.”) and beliefs regarding contributing drivers (“contributes a lot” vs all others). We grouped clinical specialty into medical/med-oncology, surgical, pediatric, and other (gynecological, critical care, and other).

We used logistic regression to explore the associations between attitudes/drivers and clinical specialty after adjusting for provider type, and report the overall P-value. We used pediatrics as the reference group to assess direct comparisons with each of the other specialties. We performed analyses with SAS statistical software, version 9.4 (SAS Institute, Cary, North Carolina) and considered P < .05 to be significant.

Among 1580 eligible participants, 837 (53%) completed surveys. Attending MD response rates ranged between 61% (surgical) to 86% (pediatric); rates were 59% for all trainees, 72% for PAs and 46% for RNs and NPs combined. Given privacy concerns, we were unable to collect detailed response rate information or any information about nonrespondents. The demographics are shown in Table 1.

Attitudes toward Laboratory Testing

The majority of respondents agreed that hospitalized patients should get daily labs (59%), testing on the discharge day (52%), and that daily testing generally enhances safety (55%; Table 2). Fewer pediatric and surgical clinicians endorsed that laboratory testing should be done daily (56% and 47% respectively) and enhances patient safety (46% and 47%). These differences were significant after adjusting for provider type. In addition, fewer pediatric providers endorsed the statement that daily laboratory testing helps avoid malpractice litigation. Overall, 68% of respondents agreed they would be comfortable with less testing.

Drivers Contributing to Unnecessary Laboratory Testing

The strongest drivers of unnecessary testing were seen as habit (94% responding “contributes a lot”) and institutional culture (89% responding “contributes a lot”; Table 2). After adjusting for provider type, significant differences were observed based on clinical specialty. In particular, pediatric specialists were less likely to endorse fear of litigation (P < .001) and more likely to endorse pressure from patient/family (P = .0003) compared to all other specialties (Table 2, odd ratios not shown).

Overuse of laboratory testing in hospitalized patients is widely recognized in IM and likely to be prevalent in other clinical specialties. Our study elucidated differences in attitudes toward unnecessary testing and self-identified drivers across specialties in a diverse group of clinical providers at an academic cancer center. We found differences based on clinical specialty, with those caring for pediatric and surgical patients less likely than others to believe that testing should be done daily and that daily testing enhances patient safety. Furthermore, comfort with less testing was highest among pediatric specialists. Habit and institutional culture were recognized broadly as the strongest drivers of laboratory testing overuse.

Our findings regarding differences based on clinical specialty are novel. Respondents caring for pediatric patients generally placed lower value on testing, and IM clinicians were the most likely to endorse daily testing and to believe that it enhances patient safety and helps avoid malpractice litigation. The difference between adult and pediatric clinicians is surprising given the fundamental similarities between these specialties.⁹ Although some resource use studies have described differences across specialties, none has examined differences in laboratory testing or examined the practice patterns of clinicians who are not physicians across specialties.¹⁰ Prior studies have documented the impact of training location on practice^11,12, suggesting the importance of the local training culture.¹³ As physician personalities vary across clinical specialties¹⁴ it is likely that culture varies as well. Specialty-specific cultures are likely to strongly influence attitudes and practice patterns and warrant further exploration.

Clinicians in our sample identified drivers of unnecessary laboratory testing that were consistent with other studies, most frequently endorsing habit, followed by culture, discomfort with not knowing, and concern that someone will ask for the results.^5,15 Previous studies have focused on IM and have not included nonphysicians or compared attitudes across specialties. We found that the largest differences in drivers by specialty were related to malpractice concerns and the perception of pressure from patients or families. The low endorsement of defensive medicine among clinicians serving pediatric populations may imply that interventions to reduce unnecessary care in hospitalized children may not need to address malpractice fear. In contrast, clinicians from pediatrics identified family pressure as a greater driver of unnecessary testing. Efforts to reduce unnecessary laboratory testing in pediatrics will need to address parent expectations.

Our findings have implications for efforts to reduce unnecessary testing. Culture, identified as a key driver of testing, reflects leadership priorities, institutional history, and other factors and is difficult to specifically target. Habit, the other most-endorsed driver, is a more promising target for quality improvement interventions, particularly those addressing care processes (eg, electronic ordering). Discomfort with not knowing and fear of being asked are drivers that might be influenced by better communication about information expectations by supervising physicians and hospital administration. Lastly, education about the potential harms of excessive testing may facilitate more targeted efforts to reduce testing overuse.

Our study has important limitations. The cancer focus of the center may have influenced provider attitudes and practices. Attitudes may differ at community centers, though important differences regarding routine laboratory testing are unlikely. Second, although our sample was large, our response rate was modest at 53% and as low as 46% among RNs and NPs and we have no information regarding nonresponders. This response rate, though, was comparable to response rates seen in other large surveys.^5,15 In addition, our results reflect clinician self-report; perceptions of necessity and the true need for testing may vary across specialties and the true subconscious drivers of behavior may differ. However, differences across specialties are likely to be valid even if there are other factors at play. Self assessment of unnecessary testing may also underestimate prevalence of the problem. Finally, our findings related to drivers of unnecessary testing are descriptive rather than quantitative given the lack of validated scales.

In conclusion, we evaluated attitudes toward routine laboratory testing in hospitalized patients in clinicians across specialties and found important differences. These findings speak to the diversity of cultures of medical care even within a single institution and point to the importance of studying attitudes about overused services across clinical specialties. In particular, as medical fields beyond IM increasingly recognize the importance of reducing medical overuse both in and out of the hospital, our findings highlight the importance of elucidating specialty-specific attitudes to optimize interventions to address unnecessary testing.

Disclosures

Mr. Husain, Ms. Gennarelli, Ms. White⁴, Mr. Masciale, MA⁵, and Dr. Roman, MD, have nothing to disclose. The work of Dr. Roman and Dr. Korenstein on this project was supported, in part, by a Cancer Center Support Grant from the National Cancer Institute to Memorial Sloan Kettering Cancer Center (P30 CA008748)

Routine laboratory testing in hospitalized patients is common, with a high prevalence of unnecessary tests that do not contribute to patient management.¹ Excessive laboratory testing of hospitalized patients can contribute to anemia² and may cause patient discomfort, additional unnecessary testing resulting from false positive results, and higher out-of-pocket patient costs. Excessive testing can impact hospital budgets both directly (though direct costs are often low) and indirectly through costly downstream services and prolonged hospital stay.³ As part of the American Board of Internal Medicine (ABIM) Foundation’s Choosing Wisely initiative, several professional societies have recommended against routine laboratory testing of hospitalized adult patients.⁴

Excessive inpatient laboratory testing has been documented mostly among adult internal medicine (IM) patients with studies of drivers of unnecessary testing and efforts to reduce it conducted in IM settings.^{5, 6} Attitudes toward other issues related to testing overuse differ by specialty⁷ and are likely to similarly vary with regard to unnecessary laboratory testing. Understanding differences in attitudes by clinical specialty is critical for framing tailored approaches to reducing inappropriate care.

We performed a cross-sectional survey of a diverse group of hospital clinicians to describe attitudes and beliefs regarding laboratory testing and its overuse across clinical specialties (eg, medical, surgical, and pediatric). We hypothesized that attitudes toward the need for testing would differ across specialties.

Survey Development and Administration

The study was conducted at Memorial Sloan Kettering Cancer Center, a tertiary academic cancer hospital in New York City. The 12-item survey was adopted from a previously administered but not formally validated survey (Online-only Appendix).^5,8 The survey was pilot tested with 4 physicians, 3 NPs, 2 PAs, and 3 RNs and edited for content and clarity. All staff providers including NPs, PAs, RNs, and resident, fellow, and attending MDs working in the hospital during the 2-week survey period (November 2-15, 2015) were eligible to participate and were emailed a link to the survey. The email invitation was resent 3 times during the survey period. Participants who completed the survey received a coupon for a free coffee. The study was reviewed by the Institutional Review Board and exempted from ongoing oversight.

Measures

Demographic items included clinical specialty, provider type, and gender (Online-only Appendix). The remaining survey questions included the following categories:

1. Attitudes toward laboratory testing were evaluated by 3 items about accepted norms for lab testing and 2 items about fears (Table 2). Responses to these items used a 4-point Likert scale (strongly agree to strongly disagree).

2. Drivers contributing to unnecessary testing were evaluated by presenting a list of possible contributing factors (Table 2). Responses to these items used a 3-point Likert scale (contributes a lot, contributes a little, or does not contribute).

Analysis

We used univariate statistics to describe demographics and survey responses. We used the chi-square statistic to evaluate differences in attitudes and drivers by clinical specialty. We dichotomized responses regarding attitudes toward lab testing (“strongly agree” and “somewhat agree” vs. “somewhat disagree” and “strongly disagree.”) and beliefs regarding contributing drivers (“contributes a lot” vs all others). We grouped clinical specialty into medical/med-oncology, surgical, pediatric, and other (gynecological, critical care, and other).

We used logistic regression to explore the associations between attitudes/drivers and clinical specialty after adjusting for provider type, and report the overall P-value. We used pediatrics as the reference group to assess direct comparisons with each of the other specialties. We performed analyses with SAS statistical software, version 9.4 (SAS Institute, Cary, North Carolina) and considered P < .05 to be significant.

Among 1580 eligible participants, 837 (53%) completed surveys. Attending MD response rates ranged between 61% (surgical) to 86% (pediatric); rates were 59% for all trainees, 72% for PAs and 46% for RNs and NPs combined. Given privacy concerns, we were unable to collect detailed response rate information or any information about nonrespondents. The demographics are shown in Table 1.

Attitudes toward Laboratory Testing

The majority of respondents agreed that hospitalized patients should get daily labs (59%), testing on the discharge day (52%), and that daily testing generally enhances safety (55%; Table 2). Fewer pediatric and surgical clinicians endorsed that laboratory testing should be done daily (56% and 47% respectively) and enhances patient safety (46% and 47%). These differences were significant after adjusting for provider type. In addition, fewer pediatric providers endorsed the statement that daily laboratory testing helps avoid malpractice litigation. Overall, 68% of respondents agreed they would be comfortable with less testing.

Drivers Contributing to Unnecessary Laboratory Testing

The strongest drivers of unnecessary testing were seen as habit (94% responding “contributes a lot”) and institutional culture (89% responding “contributes a lot”; Table 2). After adjusting for provider type, significant differences were observed based on clinical specialty. In particular, pediatric specialists were less likely to endorse fear of litigation (P < .001) and more likely to endorse pressure from patient/family (P = .0003) compared to all other specialties (Table 2, odd ratios not shown).

Overuse of laboratory testing in hospitalized patients is widely recognized in IM and likely to be prevalent in other clinical specialties. Our study elucidated differences in attitudes toward unnecessary testing and self-identified drivers across specialties in a diverse group of clinical providers at an academic cancer center. We found differences based on clinical specialty, with those caring for pediatric and surgical patients less likely than others to believe that testing should be done daily and that daily testing enhances patient safety. Furthermore, comfort with less testing was highest among pediatric specialists. Habit and institutional culture were recognized broadly as the strongest drivers of laboratory testing overuse.

Our findings regarding differences based on clinical specialty are novel. Respondents caring for pediatric patients generally placed lower value on testing, and IM clinicians were the most likely to endorse daily testing and to believe that it enhances patient safety and helps avoid malpractice litigation. The difference between adult and pediatric clinicians is surprising given the fundamental similarities between these specialties.⁹ Although some resource use studies have described differences across specialties, none has examined differences in laboratory testing or examined the practice patterns of clinicians who are not physicians across specialties.¹⁰ Prior studies have documented the impact of training location on practice^11,12, suggesting the importance of the local training culture.¹³ As physician personalities vary across clinical specialties¹⁴ it is likely that culture varies as well. Specialty-specific cultures are likely to strongly influence attitudes and practice patterns and warrant further exploration.

Clinicians in our sample identified drivers of unnecessary laboratory testing that were consistent with other studies, most frequently endorsing habit, followed by culture, discomfort with not knowing, and concern that someone will ask for the results.^5,15 Previous studies have focused on IM and have not included nonphysicians or compared attitudes across specialties. We found that the largest differences in drivers by specialty were related to malpractice concerns and the perception of pressure from patients or families. The low endorsement of defensive medicine among clinicians serving pediatric populations may imply that interventions to reduce unnecessary care in hospitalized children may not need to address malpractice fear. In contrast, clinicians from pediatrics identified family pressure as a greater driver of unnecessary testing. Efforts to reduce unnecessary laboratory testing in pediatrics will need to address parent expectations.

Our findings have implications for efforts to reduce unnecessary testing. Culture, identified as a key driver of testing, reflects leadership priorities, institutional history, and other factors and is difficult to specifically target. Habit, the other most-endorsed driver, is a more promising target for quality improvement interventions, particularly those addressing care processes (eg, electronic ordering). Discomfort with not knowing and fear of being asked are drivers that might be influenced by better communication about information expectations by supervising physicians and hospital administration. Lastly, education about the potential harms of excessive testing may facilitate more targeted efforts to reduce testing overuse.

Our study has important limitations. The cancer focus of the center may have influenced provider attitudes and practices. Attitudes may differ at community centers, though important differences regarding routine laboratory testing are unlikely. Second, although our sample was large, our response rate was modest at 53% and as low as 46% among RNs and NPs and we have no information regarding nonresponders. This response rate, though, was comparable to response rates seen in other large surveys.^5,15 In addition, our results reflect clinician self-report; perceptions of necessity and the true need for testing may vary across specialties and the true subconscious drivers of behavior may differ. However, differences across specialties are likely to be valid even if there are other factors at play. Self assessment of unnecessary testing may also underestimate prevalence of the problem. Finally, our findings related to drivers of unnecessary testing are descriptive rather than quantitative given the lack of validated scales.

In conclusion, we evaluated attitudes toward routine laboratory testing in hospitalized patients in clinicians across specialties and found important differences. These findings speak to the diversity of cultures of medical care even within a single institution and point to the importance of studying attitudes about overused services across clinical specialties. In particular, as medical fields beyond IM increasingly recognize the importance of reducing medical overuse both in and out of the hospital, our findings highlight the importance of elucidating specialty-specific attitudes to optimize interventions to address unnecessary testing.

Disclosures

Mr. Husain, Ms. Gennarelli, Ms. White⁴, Mr. Masciale, MA⁵, and Dr. Roman, MD, have nothing to disclose. The work of Dr. Roman and Dr. Korenstein on this project was supported, in part, by a Cancer Center Support Grant from the National Cancer Institute to Memorial Sloan Kettering Cancer Center (P30 CA008748)

Routine laboratory testing in hospitalized patients is common, with a high prevalence of unnecessary tests that do not contribute to patient management.¹ Excessive laboratory testing of hospitalized patients can contribute to anemia² and may cause patient discomfort, additional unnecessary testing resulting from false positive results, and higher out-of-pocket patient costs. Excessive testing can impact hospital budgets both directly (though direct costs are often low) and indirectly through costly downstream services and prolonged hospital stay.³ As part of the American Board of Internal Medicine (ABIM) Foundation’s Choosing Wisely initiative, several professional societies have recommended against routine laboratory testing of hospitalized adult patients.⁴

Excessive inpatient laboratory testing has been documented mostly among adult internal medicine (IM) patients with studies of drivers of unnecessary testing and efforts to reduce it conducted in IM settings.^{5, 6} Attitudes toward other issues related to testing overuse differ by specialty⁷ and are likely to similarly vary with regard to unnecessary laboratory testing. Understanding differences in attitudes by clinical specialty is critical for framing tailored approaches to reducing inappropriate care.

We performed a cross-sectional survey of a diverse group of hospital clinicians to describe attitudes and beliefs regarding laboratory testing and its overuse across clinical specialties (eg, medical, surgical, and pediatric). We hypothesized that attitudes toward the need for testing would differ across specialties.

Survey Development and Administration

The study was conducted at Memorial Sloan Kettering Cancer Center, a tertiary academic cancer hospital in New York City. The 12-item survey was adopted from a previously administered but not formally validated survey (Online-only Appendix).^5,8 The survey was pilot tested with 4 physicians, 3 NPs, 2 PAs, and 3 RNs and edited for content and clarity. All staff providers including NPs, PAs, RNs, and resident, fellow, and attending MDs working in the hospital during the 2-week survey period (November 2-15, 2015) were eligible to participate and were emailed a link to the survey. The email invitation was resent 3 times during the survey period. Participants who completed the survey received a coupon for a free coffee. The study was reviewed by the Institutional Review Board and exempted from ongoing oversight.

Measures

Demographic items included clinical specialty, provider type, and gender (Online-only Appendix). The remaining survey questions included the following categories:

1. Attitudes toward laboratory testing were evaluated by 3 items about accepted norms for lab testing and 2 items about fears (Table 2). Responses to these items used a 4-point Likert scale (strongly agree to strongly disagree).

2. Drivers contributing to unnecessary testing were evaluated by presenting a list of possible contributing factors (Table 2). Responses to these items used a 3-point Likert scale (contributes a lot, contributes a little, or does not contribute).

Analysis

We used univariate statistics to describe demographics and survey responses. We used the chi-square statistic to evaluate differences in attitudes and drivers by clinical specialty. We dichotomized responses regarding attitudes toward lab testing (“strongly agree” and “somewhat agree” vs. “somewhat disagree” and “strongly disagree.”) and beliefs regarding contributing drivers (“contributes a lot” vs all others). We grouped clinical specialty into medical/med-oncology, surgical, pediatric, and other (gynecological, critical care, and other).

We used logistic regression to explore the associations between attitudes/drivers and clinical specialty after adjusting for provider type, and report the overall P-value. We used pediatrics as the reference group to assess direct comparisons with each of the other specialties. We performed analyses with SAS statistical software, version 9.4 (SAS Institute, Cary, North Carolina) and considered P < .05 to be significant.

Among 1580 eligible participants, 837 (53%) completed surveys. Attending MD response rates ranged between 61% (surgical) to 86% (pediatric); rates were 59% for all trainees, 72% for PAs and 46% for RNs and NPs combined. Given privacy concerns, we were unable to collect detailed response rate information or any information about nonrespondents. The demographics are shown in Table 1.

Attitudes toward Laboratory Testing

The majority of respondents agreed that hospitalized patients should get daily labs (59%), testing on the discharge day (52%), and that daily testing generally enhances safety (55%; Table 2). Fewer pediatric and surgical clinicians endorsed that laboratory testing should be done daily (56% and 47% respectively) and enhances patient safety (46% and 47%). These differences were significant after adjusting for provider type. In addition, fewer pediatric providers endorsed the statement that daily laboratory testing helps avoid malpractice litigation. Overall, 68% of respondents agreed they would be comfortable with less testing.

Drivers Contributing to Unnecessary Laboratory Testing

The strongest drivers of unnecessary testing were seen as habit (94% responding “contributes a lot”) and institutional culture (89% responding “contributes a lot”; Table 2). After adjusting for provider type, significant differences were observed based on clinical specialty. In particular, pediatric specialists were less likely to endorse fear of litigation (P < .001) and more likely to endorse pressure from patient/family (P = .0003) compared to all other specialties (Table 2, odd ratios not shown).

Overuse of laboratory testing in hospitalized patients is widely recognized in IM and likely to be prevalent in other clinical specialties. Our study elucidated differences in attitudes toward unnecessary testing and self-identified drivers across specialties in a diverse group of clinical providers at an academic cancer center. We found differences based on clinical specialty, with those caring for pediatric and surgical patients less likely than others to believe that testing should be done daily and that daily testing enhances patient safety. Furthermore, comfort with less testing was highest among pediatric specialists. Habit and institutional culture were recognized broadly as the strongest drivers of laboratory testing overuse.

Our findings regarding differences based on clinical specialty are novel. Respondents caring for pediatric patients generally placed lower value on testing, and IM clinicians were the most likely to endorse daily testing and to believe that it enhances patient safety and helps avoid malpractice litigation. The difference between adult and pediatric clinicians is surprising given the fundamental similarities between these specialties.⁹ Although some resource use studies have described differences across specialties, none has examined differences in laboratory testing or examined the practice patterns of clinicians who are not physicians across specialties.¹⁰ Prior studies have documented the impact of training location on practice^11,12, suggesting the importance of the local training culture.¹³ As physician personalities vary across clinical specialties¹⁴ it is likely that culture varies as well. Specialty-specific cultures are likely to strongly influence attitudes and practice patterns and warrant further exploration.

Clinicians in our sample identified drivers of unnecessary laboratory testing that were consistent with other studies, most frequently endorsing habit, followed by culture, discomfort with not knowing, and concern that someone will ask for the results.^5,15 Previous studies have focused on IM and have not included nonphysicians or compared attitudes across specialties. We found that the largest differences in drivers by specialty were related to malpractice concerns and the perception of pressure from patients or families. The low endorsement of defensive medicine among clinicians serving pediatric populations may imply that interventions to reduce unnecessary care in hospitalized children may not need to address malpractice fear. In contrast, clinicians from pediatrics identified family pressure as a greater driver of unnecessary testing. Efforts to reduce unnecessary laboratory testing in pediatrics will need to address parent expectations.

Our findings have implications for efforts to reduce unnecessary testing. Culture, identified as a key driver of testing, reflects leadership priorities, institutional history, and other factors and is difficult to specifically target. Habit, the other most-endorsed driver, is a more promising target for quality improvement interventions, particularly those addressing care processes (eg, electronic ordering). Discomfort with not knowing and fear of being asked are drivers that might be influenced by better communication about information expectations by supervising physicians and hospital administration. Lastly, education about the potential harms of excessive testing may facilitate more targeted efforts to reduce testing overuse.

Our study has important limitations. The cancer focus of the center may have influenced provider attitudes and practices. Attitudes may differ at community centers, though important differences regarding routine laboratory testing are unlikely. Second, although our sample was large, our response rate was modest at 53% and as low as 46% among RNs and NPs and we have no information regarding nonresponders. This response rate, though, was comparable to response rates seen in other large surveys.^5,15 In addition, our results reflect clinician self-report; perceptions of necessity and the true need for testing may vary across specialties and the true subconscious drivers of behavior may differ. However, differences across specialties are likely to be valid even if there are other factors at play. Self assessment of unnecessary testing may also underestimate prevalence of the problem. Finally, our findings related to drivers of unnecessary testing are descriptive rather than quantitative given the lack of validated scales.

In conclusion, we evaluated attitudes toward routine laboratory testing in hospitalized patients in clinicians across specialties and found important differences. These findings speak to the diversity of cultures of medical care even within a single institution and point to the importance of studying attitudes about overused services across clinical specialties. In particular, as medical fields beyond IM increasingly recognize the importance of reducing medical overuse both in and out of the hospital, our findings highlight the importance of elucidating specialty-specific attitudes to optimize interventions to address unnecessary testing.

Disclosures

Mr. Husain, Ms. Gennarelli, Ms. White⁴, Mr. Masciale, MA⁵, and Dr. Roman, MD, have nothing to disclose. The work of Dr. Roman and Dr. Korenstein on this project was supported, in part, by a Cancer Center Support Grant from the National Cancer Institute to Memorial Sloan Kettering Cancer Center (P30 CA008748)

Although Staphylococcus aureus pneumonia is common in children with cystic fibrosis and those with healthcare-associated infections (eg, ventilator-associated pneumonia),^1,2 S. aureus is an uncommon cause of community-acquired pneumonia in children. In recent years, concerns have arisen about the increasing frequency and severity of staphylococcal pneumonia, largely fueled by the emergence of community-associated methicillin-resistant S. aureus (MRSA).^3,4 Thus, therapy with clindamycin or vancomycin, both active against MRSA, has been recommended when S. aureus is suspected.⁵ Given the lack of rapid and sensitive approaches to the detection of the etiologies of pneumonia, antibiotic selection is most often empirical, contributing to overuse of anti-MRSA antibiotics. In addition, resistance against these antibiotics, especially clindamycin, has been increasing.^6,7

A better understanding of the likelihood of staphylococcal pneumonia would help to optimize empirical antibiotic selection, allowing for judicious use of antistaphylococcal antibiotics, while also avoiding poor outcomes due to delays in effective treatment when S. aureus is present.⁸ Using data from a multicenter, population-based study of pneumonia hospitalizations in children, we sought to describe the prevalence, clinical characteristics, and in-hospital outcomes of staphylococcal pneumonia and the prevalence of antistaphylococcal antibiotic use.

The Etiology of Pneumonia in the Community (EPIC) study was a prospective, active, population-based surveillance study of pneumonia hospitalizations among children (age <18 years) conducted between 2010 and 2012 at three children’s hospitals, including two in Tennessee and one in Utah.⁹ Children hospitalized with clinical evidence of pneumonia and radiographic evidence confirmed by a blinded review by study radiologists were enrolled. Etiologic assessments included blood analysis for bacterial culture, serology for eight respiratory viruses, pneumococcal and group A streptococcal polymerase chain reaction (PCR), and naso/oro-pharyngeal swabs for PCR for 13 respiratory viruses, Mycoplasma pneumoniae, and Chlamydophila pneumoniae. Data from other clinical specimens (pleural fluid, high-quality endotracheal aspirate, or quantified bronchoalveolar lavage fluid) were also recorded. For this study, we included only children with at least one bacterial culture and complete information about antibiotic use. Those with confirmed fungal pneumonia were excluded. Additional details regarding the study population and methods have been published previously.⁹

Staphylococcal pneumonia was defined based on the detection of S. aureus by culture (any site) or PCR (pleural fluid only), regardless of codetection of other pathogens. Antibiotic susceptibility profiles were used to classify S. aureus isolates as MRSA or methicillin-sensitive S. aureus (MSSA). The remaining children were classified as nonstaphylococcal pneumonia including children with other bacterial pathogens detected (classified as other bacterial pneumonia, excludes atypical bacteria), atypical bacteria, viruses, and no pathogens detected.

Use of anti-MRSA antibiotics (vancomycin, clindamycin, linezolid, doxycycline, and trimethoprim-sulfamethoxazole) and any antistaphylococcal antibiotics (anti-MRSA agents plus oxacillin, nafcillin, and cefazolin) during and after the first two calendar days of admission was identified by medical record review.

Descriptive statistics included number (%) and median (interquartile range, [IQR]) for categorical and continuous variables, respectively. Baseline clinical characteristics and outcomes were compared between children with staphylococcal versus nonstaphylococcal pneumonia, those with staphylococcal versus other bacterial pneumonia, and those with MRSA versus MSSA pneumonia using Wilcoxon rank-sum and Pearson’s chi-square tests where appropriate. To account for multiple comparisons, we used a Bonferroni corrected P value threshold of <.001 to determine statistical significance.

Of the 2,358 children enrolled in the EPIC study hospitalized with radiographically confirmed pneumonia, 2,146 (91.0%) had ≥1 bacterial culture obtained. Two children with Histoplasma capsulatum fungal infection and six children with incomplete antibiotic utilization data were excluded, yielding a final study population of 2,138 children. Among these, blood samples were obtained from 2,134 (>99%) children for culture, pleural fluid from 87 (4%) children, bronchoalveolar lavage fluid from 31 (1%) children, and endotracheal aspirate from 80 (4%) children. Across all culture types, there were 2,332 initial cultures; 2,150 (92%) were collected within the first 24 hours.

Staphylococcal pneumonia was detected in 23 of the 2,138 children (1% [95% CI 0.7, 1.6]; 17 MRSA, 6 MSSA). Of these, 6/23 (26%) had bacteremia, 12/23 (52%) had a positive pleural fluid, and 9/23 (39%) had a positive culture from bronchoalveolar lavage fluid or endotracheal aspirate; 4/23 (17%) children had S. aureus detected from more than one site. Three children (13%) with S. aureus had a viral codetection, including two with influenza.

Compared with children with nonstaphylococcal pneumonia, those with staphylococcal pneumonia were more likely to have a parapneumonic effusion (78% vs 12%, P < .001), but less likely to have cough (78% vs 95%, P < .001). Other baseline characteristics were similar between the two groups. Children with staphylococcal pneumonia had more adverse outcomes than those without (Table), including longer median length of stay (10 vs 3 days, P < .001), more frequent admission to intensive care (83% vs 21%, P < .001), and more frequent invasive mechanical ventilation (65% vs 7%, P < .001). Similar findings were noted when staphylococcal pneumonia was compared with pneumonia caused due to other bacterial pathogens (n = 124). There were no significant differences in baseline characteristics or clinical course between children with MRSA and MSSA pneumonia, although the numbers were small. Overall, S. aureus was detected in 18/267 (7%) children with parapneumonic effusion and 19/462 (4%) children admitted to intensive care. Importantly, there were no confirmed S. aureus cases among children with less severe pneumonia, defined as lacking both parapneumonic effusion and intensive care admission (n = 1,488).

In our large, population-based study of >2,000 children hospitalized with community-acquired pneumonia, S. aureus was identified in only 1% of children. Compared with children with other pneumonia etiologies, staphylococcal pneumonia was associated with increased disease severity. Among the small numbers studied, no differences in outcomes were found between children with MRSA and MSSA disease. Despite the low prevalence of staphylococcal pneumonia, almost 1 in 4 children received antistaphylococcal antibiotic therapy; anti-MRSA therapy was used almost exclusively.

The severity of staphylococcal pneumonia was striking, with >80% of children with S. aureus detected being admitted to intensive care, about 65% requiring invasive mechanical ventilation, and >75% with parapneumonic effusion. These findings are similar to those of prior retrospective studies.^4,10 The association between staphylococcal pneumonia and adverse outcomes underscores the importance of prompt institution of antimicrobial therapy targeting S. aureus in high-risk patients. This is noteworthy given recent epidemiological data demonstrating increases in MSSA relative to MRSA infections in children,⁶ and the known superiority of beta-lactam versus vancomycin for MSSA infections, including pneumonia.¹¹

Although detection of staphylococcal infection was rare, almost a quarter of children received antistaphylococcal therapy; nearly all of these children received anti-MRSA therapy. Confirming a bacterial etiology of pneumonia, however, is challenging. Given the severity associated with staphylococcal pneumonia, it is not surprising that use of antistaphylococcal therapy outpaced staphylococcal detections. Antistaphylococcal therapy was especially common in those with severe pneumonia, suggesting that disease severity is an important factor that influences initial antibiotic treatment decisions. Even so, two children with MRSA detected did not initially receive anti-MRSA therapy, highlighting the challenge of balancing judicious antibiotic selection along with ensuring effective treatment. Perhaps more striking is the finding that 16% of children received antistaphylococcal therapy beyond the first two days of hospitalization, presumably after the initial culture results were available. This suggests that clinicians are reluctant to stop antistaphylococcal therapy when the etiology is unknown, although certain features, such as negative cultures, rapid clinical improvement, and lack of risk factors for staphylococcal disease, may provide important clues to support de-escalation of empiric antibiotic therapy. It is also possible that some antibiotics with antistaphylococcal activity were used for alternative indications (eg, clindamycin for penicillin allergy or concern for aspiration pneumonia).

A simple strategy for tailoring antibiotic treatment is maximizing opportunities to identify a causative pathogen. Despite the very low yield of blood cultures in children with pneumonia overall, bacteremia is more common in children with severe pneumonia and those with parapneumonic effusion, especially when cultures are obtained prior to antibiotic use.^12,13 Similarly, obtaining pleural fluid is often therapeutic and significantly improves the chances of identifying a bacterial pathogen.¹⁴ Moreover, at least one study suggests that S. aureus is much less likely in cases of culture-negative parapneumonic effusions.¹⁵ Institutional guidelines, order sets, and antimicrobial stewardship teams are also effective strategies that can facilitate judicious antibiotic use. In particular, stewardship experts can be very useful in assisting clinicians around de-escalation of therapy.¹⁶ Use of procalcitonin, a biomarker associated with bacterial infections,¹⁷ and prognostic tools to identify risk for adverse outcomes,¹⁸ may also inform treatment decisions and are deserving of further study.

Our study must be considered in the light of its strengths and limitations. Analysis was derived from a population-based surveillance study of community-acquired pneumonia hospitalizations in three children’s hospitals and may not be generalizable to other settings. Nevertheless, the antibiotic-prescribing practices identified in our study are consistent with those from a larger network of children’s hospitals in the United States.¹⁹ The relatively small number of children with S. aureus identified limited our ability to control for potential confounding factors. Some cases of staphylococcal pneumonia may not have been identified. All study children, however, were prospectively enrolled and had samples systematically collected and tested for etiology, likely leading to few cases of misclassification for this pathogen.

Our study demonstrates a very low prevalence of S. aureus detection among children hospitalized with pneumonia and highlights the association between staphylococcal disease and adverse in-hospital outcomes. We also document important discrepancies between disease prevalence and utilization of antistaphylococcal therapy, especially anti-MRSA therapy. Improved approaches are needed to minimize overuse of antistaphylococcal antibiotics while also ensuring adequate therapy for those who need it.

Disclosures

Drs. Zhu, Edwards, Self, Ampofo, Arnold, McCullers, and Williams report grants from the Centers for Disease Control and Prevention during the conduct of the study. Ms. Frush has nothing to disclose. Dr. Jain has nothing to disclose. Dr. Grijalva reports other from Merck, grants and other from Sanofi, other from Pfizer, grants from CDC, grants from AHRQ, grants from NIH, and grants from Campbell Alliance, outside the submitted work. Dr. Self reports grants from CDC, during the conduct of the study; personal fees from Cempra Pharmaceuticals, grants and personal fees from Ferring Pharmaceuticals, personal fees from BioTest AG, personal fees from Abbott Point of Care, personal fees from Gilead Pharmaceuticals, personal fees from Pfizer, grants from Merck, outside the submitted work. Dr. Thomsen has nothing to disclose. Dr. Ampofo reports grants from CDC, during the conduct of the study; other from GlaxoSmithKline, other from Cubist Pharmaceuticals outside the submitted work; and KA collaborate with BioFire Diagnostics, Inc. (formerly Idaho Technology, Inc.) on several NIH grants. Dr. Pavia reports grants from NAID/NIH, grants from NAID/NIH, grants from CDC, personal fees from WebMD, personal fees from Antimicrobial Therapy Inc., outside the submitted work.

Funding

This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K23AI104779 to D.J.W. and Award 1K23AI113150 to I.P.T., the National Institute of General Medical Sciences under Award K23GM110469 to W.H.S., and the Agency for Healthcare Research and Quality under Award R03HS022342 to C.G.G. The EPIC study was supported by the Influenza Division in the National Center for Immunizations and Respiratory Diseases at the Centers for Disease Control and Prevention through cooperative agreements with each study site and was based on a competitive research funding opportunity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute of Allergy and Infectious Diseases, the National Institute of General Medical Sciences, the Agency for Healthcare Research and Quality, or the Centers for Disease Control and Prevention.

Although Staphylococcus aureus pneumonia is common in children with cystic fibrosis and those with healthcare-associated infections (eg, ventilator-associated pneumonia),^1,2 S. aureus is an uncommon cause of community-acquired pneumonia in children. In recent years, concerns have arisen about the increasing frequency and severity of staphylococcal pneumonia, largely fueled by the emergence of community-associated methicillin-resistant S. aureus (MRSA).^3,4 Thus, therapy with clindamycin or vancomycin, both active against MRSA, has been recommended when S. aureus is suspected.⁵ Given the lack of rapid and sensitive approaches to the detection of the etiologies of pneumonia, antibiotic selection is most often empirical, contributing to overuse of anti-MRSA antibiotics. In addition, resistance against these antibiotics, especially clindamycin, has been increasing.^6,7

A better understanding of the likelihood of staphylococcal pneumonia would help to optimize empirical antibiotic selection, allowing for judicious use of antistaphylococcal antibiotics, while also avoiding poor outcomes due to delays in effective treatment when S. aureus is present.⁸ Using data from a multicenter, population-based study of pneumonia hospitalizations in children, we sought to describe the prevalence, clinical characteristics, and in-hospital outcomes of staphylococcal pneumonia and the prevalence of antistaphylococcal antibiotic use.

The Etiology of Pneumonia in the Community (EPIC) study was a prospective, active, population-based surveillance study of pneumonia hospitalizations among children (age <18 years) conducted between 2010 and 2012 at three children’s hospitals, including two in Tennessee and one in Utah.⁹ Children hospitalized with clinical evidence of pneumonia and radiographic evidence confirmed by a blinded review by study radiologists were enrolled. Etiologic assessments included blood analysis for bacterial culture, serology for eight respiratory viruses, pneumococcal and group A streptococcal polymerase chain reaction (PCR), and naso/oro-pharyngeal swabs for PCR for 13 respiratory viruses, Mycoplasma pneumoniae, and Chlamydophila pneumoniae. Data from other clinical specimens (pleural fluid, high-quality endotracheal aspirate, or quantified bronchoalveolar lavage fluid) were also recorded. For this study, we included only children with at least one bacterial culture and complete information about antibiotic use. Those with confirmed fungal pneumonia were excluded. Additional details regarding the study population and methods have been published previously.⁹

Staphylococcal pneumonia was defined based on the detection of S. aureus by culture (any site) or PCR (pleural fluid only), regardless of codetection of other pathogens. Antibiotic susceptibility profiles were used to classify S. aureus isolates as MRSA or methicillin-sensitive S. aureus (MSSA). The remaining children were classified as nonstaphylococcal pneumonia including children with other bacterial pathogens detected (classified as other bacterial pneumonia, excludes atypical bacteria), atypical bacteria, viruses, and no pathogens detected.

Use of anti-MRSA antibiotics (vancomycin, clindamycin, linezolid, doxycycline, and trimethoprim-sulfamethoxazole) and any antistaphylococcal antibiotics (anti-MRSA agents plus oxacillin, nafcillin, and cefazolin) during and after the first two calendar days of admission was identified by medical record review.

Descriptive statistics included number (%) and median (interquartile range, [IQR]) for categorical and continuous variables, respectively. Baseline clinical characteristics and outcomes were compared between children with staphylococcal versus nonstaphylococcal pneumonia, those with staphylococcal versus other bacterial pneumonia, and those with MRSA versus MSSA pneumonia using Wilcoxon rank-sum and Pearson’s chi-square tests where appropriate. To account for multiple comparisons, we used a Bonferroni corrected P value threshold of <.001 to determine statistical significance.

Of the 2,358 children enrolled in the EPIC study hospitalized with radiographically confirmed pneumonia, 2,146 (91.0%) had ≥1 bacterial culture obtained. Two children with Histoplasma capsulatum fungal infection and six children with incomplete antibiotic utilization data were excluded, yielding a final study population of 2,138 children. Among these, blood samples were obtained from 2,134 (>99%) children for culture, pleural fluid from 87 (4%) children, bronchoalveolar lavage fluid from 31 (1%) children, and endotracheal aspirate from 80 (4%) children. Across all culture types, there were 2,332 initial cultures; 2,150 (92%) were collected within the first 24 hours.

Staphylococcal pneumonia was detected in 23 of the 2,138 children (1% [95% CI 0.7, 1.6]; 17 MRSA, 6 MSSA). Of these, 6/23 (26%) had bacteremia, 12/23 (52%) had a positive pleural fluid, and 9/23 (39%) had a positive culture from bronchoalveolar lavage fluid or endotracheal aspirate; 4/23 (17%) children had S. aureus detected from more than one site. Three children (13%) with S. aureus had a viral codetection, including two with influenza.

Compared with children with nonstaphylococcal pneumonia, those with staphylococcal pneumonia were more likely to have a parapneumonic effusion (78% vs 12%, P < .001), but less likely to have cough (78% vs 95%, P < .001). Other baseline characteristics were similar between the two groups. Children with staphylococcal pneumonia had more adverse outcomes than those without (Table), including longer median length of stay (10 vs 3 days, P < .001), more frequent admission to intensive care (83% vs 21%, P < .001), and more frequent invasive mechanical ventilation (65% vs 7%, P < .001). Similar findings were noted when staphylococcal pneumonia was compared with pneumonia caused due to other bacterial pathogens (n = 124). There were no significant differences in baseline characteristics or clinical course between children with MRSA and MSSA pneumonia, although the numbers were small. Overall, S. aureus was detected in 18/267 (7%) children with parapneumonic effusion and 19/462 (4%) children admitted to intensive care. Importantly, there were no confirmed S. aureus cases among children with less severe pneumonia, defined as lacking both parapneumonic effusion and intensive care admission (n = 1,488).

In our large, population-based study of >2,000 children hospitalized with community-acquired pneumonia, S. aureus was identified in only 1% of children. Compared with children with other pneumonia etiologies, staphylococcal pneumonia was associated with increased disease severity. Among the small numbers studied, no differences in outcomes were found between children with MRSA and MSSA disease. Despite the low prevalence of staphylococcal pneumonia, almost 1 in 4 children received antistaphylococcal antibiotic therapy; anti-MRSA therapy was used almost exclusively.

The severity of staphylococcal pneumonia was striking, with >80% of children with S. aureus detected being admitted to intensive care, about 65% requiring invasive mechanical ventilation, and >75% with parapneumonic effusion. These findings are similar to those of prior retrospective studies.^4,10 The association between staphylococcal pneumonia and adverse outcomes underscores the importance of prompt institution of antimicrobial therapy targeting S. aureus in high-risk patients. This is noteworthy given recent epidemiological data demonstrating increases in MSSA relative to MRSA infections in children,⁶ and the known superiority of beta-lactam versus vancomycin for MSSA infections, including pneumonia.¹¹

Although detection of staphylococcal infection was rare, almost a quarter of children received antistaphylococcal therapy; nearly all of these children received anti-MRSA therapy. Confirming a bacterial etiology of pneumonia, however, is challenging. Given the severity associated with staphylococcal pneumonia, it is not surprising that use of antistaphylococcal therapy outpaced staphylococcal detections. Antistaphylococcal therapy was especially common in those with severe pneumonia, suggesting that disease severity is an important factor that influences initial antibiotic treatment decisions. Even so, two children with MRSA detected did not initially receive anti-MRSA therapy, highlighting the challenge of balancing judicious antibiotic selection along with ensuring effective treatment. Perhaps more striking is the finding that 16% of children received antistaphylococcal therapy beyond the first two days of hospitalization, presumably after the initial culture results were available. This suggests that clinicians are reluctant to stop antistaphylococcal therapy when the etiology is unknown, although certain features, such as negative cultures, rapid clinical improvement, and lack of risk factors for staphylococcal disease, may provide important clues to support de-escalation of empiric antibiotic therapy. It is also possible that some antibiotics with antistaphylococcal activity were used for alternative indications (eg, clindamycin for penicillin allergy or concern for aspiration pneumonia).

A simple strategy for tailoring antibiotic treatment is maximizing opportunities to identify a causative pathogen. Despite the very low yield of blood cultures in children with pneumonia overall, bacteremia is more common in children with severe pneumonia and those with parapneumonic effusion, especially when cultures are obtained prior to antibiotic use.^12,13 Similarly, obtaining pleural fluid is often therapeutic and significantly improves the chances of identifying a bacterial pathogen.¹⁴ Moreover, at least one study suggests that S. aureus is much less likely in cases of culture-negative parapneumonic effusions.¹⁵ Institutional guidelines, order sets, and antimicrobial stewardship teams are also effective strategies that can facilitate judicious antibiotic use. In particular, stewardship experts can be very useful in assisting clinicians around de-escalation of therapy.¹⁶ Use of procalcitonin, a biomarker associated with bacterial infections,¹⁷ and prognostic tools to identify risk for adverse outcomes,¹⁸ may also inform treatment decisions and are deserving of further study.

Our study must be considered in the light of its strengths and limitations. Analysis was derived from a population-based surveillance study of community-acquired pneumonia hospitalizations in three children’s hospitals and may not be generalizable to other settings. Nevertheless, the antibiotic-prescribing practices identified in our study are consistent with those from a larger network of children’s hospitals in the United States.¹⁹ The relatively small number of children with S. aureus identified limited our ability to control for potential confounding factors. Some cases of staphylococcal pneumonia may not have been identified. All study children, however, were prospectively enrolled and had samples systematically collected and tested for etiology, likely leading to few cases of misclassification for this pathogen.

Our study demonstrates a very low prevalence of S. aureus detection among children hospitalized with pneumonia and highlights the association between staphylococcal disease and adverse in-hospital outcomes. We also document important discrepancies between disease prevalence and utilization of antistaphylococcal therapy, especially anti-MRSA therapy. Improved approaches are needed to minimize overuse of antistaphylococcal antibiotics while also ensuring adequate therapy for those who need it.

Disclosures

Drs. Zhu, Edwards, Self, Ampofo, Arnold, McCullers, and Williams report grants from the Centers for Disease Control and Prevention during the conduct of the study. Ms. Frush has nothing to disclose. Dr. Jain has nothing to disclose. Dr. Grijalva reports other from Merck, grants and other from Sanofi, other from Pfizer, grants from CDC, grants from AHRQ, grants from NIH, and grants from Campbell Alliance, outside the submitted work. Dr. Self reports grants from CDC, during the conduct of the study; personal fees from Cempra Pharmaceuticals, grants and personal fees from Ferring Pharmaceuticals, personal fees from BioTest AG, personal fees from Abbott Point of Care, personal fees from Gilead Pharmaceuticals, personal fees from Pfizer, grants from Merck, outside the submitted work. Dr. Thomsen has nothing to disclose. Dr. Ampofo reports grants from CDC, during the conduct of the study; other from GlaxoSmithKline, other from Cubist Pharmaceuticals outside the submitted work; and KA collaborate with BioFire Diagnostics, Inc. (formerly Idaho Technology, Inc.) on several NIH grants. Dr. Pavia reports grants from NAID/NIH, grants from NAID/NIH, grants from CDC, personal fees from WebMD, personal fees from Antimicrobial Therapy Inc., outside the submitted work.

Funding

This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K23AI104779 to D.J.W. and Award 1K23AI113150 to I.P.T., the National Institute of General Medical Sciences under Award K23GM110469 to W.H.S., and the Agency for Healthcare Research and Quality under Award R03HS022342 to C.G.G. The EPIC study was supported by the Influenza Division in the National Center for Immunizations and Respiratory Diseases at the Centers for Disease Control and Prevention through cooperative agreements with each study site and was based on a competitive research funding opportunity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute of Allergy and Infectious Diseases, the National Institute of General Medical Sciences, the Agency for Healthcare Research and Quality, or the Centers for Disease Control and Prevention.

Although Staphylococcus aureus pneumonia is common in children with cystic fibrosis and those with healthcare-associated infections (eg, ventilator-associated pneumonia),^1,2 S. aureus is an uncommon cause of community-acquired pneumonia in children. In recent years, concerns have arisen about the increasing frequency and severity of staphylococcal pneumonia, largely fueled by the emergence of community-associated methicillin-resistant S. aureus (MRSA).^3,4 Thus, therapy with clindamycin or vancomycin, both active against MRSA, has been recommended when S. aureus is suspected.⁵ Given the lack of rapid and sensitive approaches to the detection of the etiologies of pneumonia, antibiotic selection is most often empirical, contributing to overuse of anti-MRSA antibiotics. In addition, resistance against these antibiotics, especially clindamycin, has been increasing.^6,7

A better understanding of the likelihood of staphylococcal pneumonia would help to optimize empirical antibiotic selection, allowing for judicious use of antistaphylococcal antibiotics, while also avoiding poor outcomes due to delays in effective treatment when S. aureus is present.⁸ Using data from a multicenter, population-based study of pneumonia hospitalizations in children, we sought to describe the prevalence, clinical characteristics, and in-hospital outcomes of staphylococcal pneumonia and the prevalence of antistaphylococcal antibiotic use.

The Etiology of Pneumonia in the Community (EPIC) study was a prospective, active, population-based surveillance study of pneumonia hospitalizations among children (age <18 years) conducted between 2010 and 2012 at three children’s hospitals, including two in Tennessee and one in Utah.⁹ Children hospitalized with clinical evidence of pneumonia and radiographic evidence confirmed by a blinded review by study radiologists were enrolled. Etiologic assessments included blood analysis for bacterial culture, serology for eight respiratory viruses, pneumococcal and group A streptococcal polymerase chain reaction (PCR), and naso/oro-pharyngeal swabs for PCR for 13 respiratory viruses, Mycoplasma pneumoniae, and Chlamydophila pneumoniae. Data from other clinical specimens (pleural fluid, high-quality endotracheal aspirate, or quantified bronchoalveolar lavage fluid) were also recorded. For this study, we included only children with at least one bacterial culture and complete information about antibiotic use. Those with confirmed fungal pneumonia were excluded. Additional details regarding the study population and methods have been published previously.⁹

Staphylococcal pneumonia was defined based on the detection of S. aureus by culture (any site) or PCR (pleural fluid only), regardless of codetection of other pathogens. Antibiotic susceptibility profiles were used to classify S. aureus isolates as MRSA or methicillin-sensitive S. aureus (MSSA). The remaining children were classified as nonstaphylococcal pneumonia including children with other bacterial pathogens detected (classified as other bacterial pneumonia, excludes atypical bacteria), atypical bacteria, viruses, and no pathogens detected.

Use of anti-MRSA antibiotics (vancomycin, clindamycin, linezolid, doxycycline, and trimethoprim-sulfamethoxazole) and any antistaphylococcal antibiotics (anti-MRSA agents plus oxacillin, nafcillin, and cefazolin) during and after the first two calendar days of admission was identified by medical record review.

Descriptive statistics included number (%) and median (interquartile range, [IQR]) for categorical and continuous variables, respectively. Baseline clinical characteristics and outcomes were compared between children with staphylococcal versus nonstaphylococcal pneumonia, those with staphylococcal versus other bacterial pneumonia, and those with MRSA versus MSSA pneumonia using Wilcoxon rank-sum and Pearson’s chi-square tests where appropriate. To account for multiple comparisons, we used a Bonferroni corrected P value threshold of <.001 to determine statistical significance.

Of the 2,358 children enrolled in the EPIC study hospitalized with radiographically confirmed pneumonia, 2,146 (91.0%) had ≥1 bacterial culture obtained. Two children with Histoplasma capsulatum fungal infection and six children with incomplete antibiotic utilization data were excluded, yielding a final study population of 2,138 children. Among these, blood samples were obtained from 2,134 (>99%) children for culture, pleural fluid from 87 (4%) children, bronchoalveolar lavage fluid from 31 (1%) children, and endotracheal aspirate from 80 (4%) children. Across all culture types, there were 2,332 initial cultures; 2,150 (92%) were collected within the first 24 hours.

Staphylococcal pneumonia was detected in 23 of the 2,138 children (1% [95% CI 0.7, 1.6]; 17 MRSA, 6 MSSA). Of these, 6/23 (26%) had bacteremia, 12/23 (52%) had a positive pleural fluid, and 9/23 (39%) had a positive culture from bronchoalveolar lavage fluid or endotracheal aspirate; 4/23 (17%) children had S. aureus detected from more than one site. Three children (13%) with S. aureus had a viral codetection, including two with influenza.

Compared with children with nonstaphylococcal pneumonia, those with staphylococcal pneumonia were more likely to have a parapneumonic effusion (78% vs 12%, P < .001), but less likely to have cough (78% vs 95%, P < .001). Other baseline characteristics were similar between the two groups. Children with staphylococcal pneumonia had more adverse outcomes than those without (Table), including longer median length of stay (10 vs 3 days, P < .001), more frequent admission to intensive care (83% vs 21%, P < .001), and more frequent invasive mechanical ventilation (65% vs 7%, P < .001). Similar findings were noted when staphylococcal pneumonia was compared with pneumonia caused due to other bacterial pathogens (n = 124). There were no significant differences in baseline characteristics or clinical course between children with MRSA and MSSA pneumonia, although the numbers were small. Overall, S. aureus was detected in 18/267 (7%) children with parapneumonic effusion and 19/462 (4%) children admitted to intensive care. Importantly, there were no confirmed S. aureus cases among children with less severe pneumonia, defined as lacking both parapneumonic effusion and intensive care admission (n = 1,488).

In our large, population-based study of >2,000 children hospitalized with community-acquired pneumonia, S. aureus was identified in only 1% of children. Compared with children with other pneumonia etiologies, staphylococcal pneumonia was associated with increased disease severity. Among the small numbers studied, no differences in outcomes were found between children with MRSA and MSSA disease. Despite the low prevalence of staphylococcal pneumonia, almost 1 in 4 children received antistaphylococcal antibiotic therapy; anti-MRSA therapy was used almost exclusively.

The severity of staphylococcal pneumonia was striking, with >80% of children with S. aureus detected being admitted to intensive care, about 65% requiring invasive mechanical ventilation, and >75% with parapneumonic effusion. These findings are similar to those of prior retrospective studies.^4,10 The association between staphylococcal pneumonia and adverse outcomes underscores the importance of prompt institution of antimicrobial therapy targeting S. aureus in high-risk patients. This is noteworthy given recent epidemiological data demonstrating increases in MSSA relative to MRSA infections in children,⁶ and the known superiority of beta-lactam versus vancomycin for MSSA infections, including pneumonia.¹¹

Although detection of staphylococcal infection was rare, almost a quarter of children received antistaphylococcal therapy; nearly all of these children received anti-MRSA therapy. Confirming a bacterial etiology of pneumonia, however, is challenging. Given the severity associated with staphylococcal pneumonia, it is not surprising that use of antistaphylococcal therapy outpaced staphylococcal detections. Antistaphylococcal therapy was especially common in those with severe pneumonia, suggesting that disease severity is an important factor that influences initial antibiotic treatment decisions. Even so, two children with MRSA detected did not initially receive anti-MRSA therapy, highlighting the challenge of balancing judicious antibiotic selection along with ensuring effective treatment. Perhaps more striking is the finding that 16% of children received antistaphylococcal therapy beyond the first two days of hospitalization, presumably after the initial culture results were available. This suggests that clinicians are reluctant to stop antistaphylococcal therapy when the etiology is unknown, although certain features, such as negative cultures, rapid clinical improvement, and lack of risk factors for staphylococcal disease, may provide important clues to support de-escalation of empiric antibiotic therapy. It is also possible that some antibiotics with antistaphylococcal activity were used for alternative indications (eg, clindamycin for penicillin allergy or concern for aspiration pneumonia).

A simple strategy for tailoring antibiotic treatment is maximizing opportunities to identify a causative pathogen. Despite the very low yield of blood cultures in children with pneumonia overall, bacteremia is more common in children with severe pneumonia and those with parapneumonic effusion, especially when cultures are obtained prior to antibiotic use.^12,13 Similarly, obtaining pleural fluid is often therapeutic and significantly improves the chances of identifying a bacterial pathogen.¹⁴ Moreover, at least one study suggests that S. aureus is much less likely in cases of culture-negative parapneumonic effusions.¹⁵ Institutional guidelines, order sets, and antimicrobial stewardship teams are also effective strategies that can facilitate judicious antibiotic use. In particular, stewardship experts can be very useful in assisting clinicians around de-escalation of therapy.¹⁶ Use of procalcitonin, a biomarker associated with bacterial infections,¹⁷ and prognostic tools to identify risk for adverse outcomes,¹⁸ may also inform treatment decisions and are deserving of further study.

Our study must be considered in the light of its strengths and limitations. Analysis was derived from a population-based surveillance study of community-acquired pneumonia hospitalizations in three children’s hospitals and may not be generalizable to other settings. Nevertheless, the antibiotic-prescribing practices identified in our study are consistent with those from a larger network of children’s hospitals in the United States.¹⁹ The relatively small number of children with S. aureus identified limited our ability to control for potential confounding factors. Some cases of staphylococcal pneumonia may not have been identified. All study children, however, were prospectively enrolled and had samples systematically collected and tested for etiology, likely leading to few cases of misclassification for this pathogen.

Our study demonstrates a very low prevalence of S. aureus detection among children hospitalized with pneumonia and highlights the association between staphylococcal disease and adverse in-hospital outcomes. We also document important discrepancies between disease prevalence and utilization of antistaphylococcal therapy, especially anti-MRSA therapy. Improved approaches are needed to minimize overuse of antistaphylococcal antibiotics while also ensuring adequate therapy for those who need it.

Disclosures

Drs. Zhu, Edwards, Self, Ampofo, Arnold, McCullers, and Williams report grants from the Centers for Disease Control and Prevention during the conduct of the study. Ms. Frush has nothing to disclose. Dr. Jain has nothing to disclose. Dr. Grijalva reports other from Merck, grants and other from Sanofi, other from Pfizer, grants from CDC, grants from AHRQ, grants from NIH, and grants from Campbell Alliance, outside the submitted work. Dr. Self reports grants from CDC, during the conduct of the study; personal fees from Cempra Pharmaceuticals, grants and personal fees from Ferring Pharmaceuticals, personal fees from BioTest AG, personal fees from Abbott Point of Care, personal fees from Gilead Pharmaceuticals, personal fees from Pfizer, grants from Merck, outside the submitted work. Dr. Thomsen has nothing to disclose. Dr. Ampofo reports grants from CDC, during the conduct of the study; other from GlaxoSmithKline, other from Cubist Pharmaceuticals outside the submitted work; and KA collaborate with BioFire Diagnostics, Inc. (formerly Idaho Technology, Inc.) on several NIH grants. Dr. Pavia reports grants from NAID/NIH, grants from NAID/NIH, grants from CDC, personal fees from WebMD, personal fees from Antimicrobial Therapy Inc., outside the submitted work.

Funding

This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K23AI104779 to D.J.W. and Award 1K23AI113150 to I.P.T., the National Institute of General Medical Sciences under Award K23GM110469 to W.H.S., and the Agency for Healthcare Research and Quality under Award R03HS022342 to C.G.G. The EPIC study was supported by the Influenza Division in the National Center for Immunizations and Respiratory Diseases at the Centers for Disease Control and Prevention through cooperative agreements with each study site and was based on a competitive research funding opportunity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute of Allergy and Infectious Diseases, the National Institute of General Medical Sciences, the Agency for Healthcare Research and Quality, or the Centers for Disease Control and Prevention.

In recent years, hospitals and health systems have engaged in considerable efforts to reduce readmissions, in part due to financial incentives from the Medicare Hospital Readmission Reduction Program.^1,2 Though efforts to improve transitions of care for all patients are laudable, risk for readmission is not distributed equally; a small subset of patients accounts for a disproportionate number of hospital readmissions.³ This phenomenon of frequently hospitalized patients is similar to that seen in other populations in which a small proportion of patients account for a majority of healthcare utilization.^3,4

Recognizing that the current system of healthcare delivery does not meet the needs of this population, healthcare organizations have begun to implement interventions that supplement or redesign the system of care for frequently hospitalized patients.^5-7 Descriptive reviews of ambulatory "high-need, high-cost" patients emphasize complex case management and interdisciplinary, team-based care.^8,9 Prior systematic reviews of studies aimed at patients with high use of emergency care demonstrate improvements in social outcomes such as homelessness but mixed results in reducing emergency department (ED) use.¹⁰ However, we were unable to identify any prior reviews that evaluated interventions intended specifically for patients with frequent hospital admissions. Our objective in this systematic review was to characterize interventions for frequently admitted patients and determine whether these interventions decrease use of healthcare resources, improve health outcomes, and/or reduce costs.

Literature Search

We registered our study protocol in the PROSPERO database. A librarian (L.O.) collaboratively developed the search strategies with other review authors (A.G., B.H., N.N.) and in January 2018 ran searches on "super users," "high utilizers," and similar terms in the following databases: PubMed MEDLINE, Embase (embase.com), and Cochrane Central Register of Controlled Trials (CENTRAL) on the Wiley platform. The complete search strategies used are available in Appendix A.  

We attempted to discover additional studies by searching the reference lists of key publications and contacted authors of relevant abstracts to determine whether studies had been published or were planned for peer-reviewed publication. We also contacted authors of included studies to locate additional studies meeting inclusion criteria.

Data Collection Process

Studies were eligible for inclusion in our review if they were (1) published in a peer-reviewed source, (2) defined a study population of patients frequently admitted to inpatient medical services, (3) evaluated an intervention targeting frequently hospitalized patients, and (4) included patients who were >18 years old and (5) admitted as inpatients on medical services. Of note, studies with patients admitted to psychiatric, obstetric, or surgical wards were not included, as the authors did not define these as "general medicine" units. Studies focused solely on an ambulatory population were similarly excluded. Given the heterogeneity of how studies defined frequently hospitalized patients, we did not establish a prespecified number of admissions for inclusion to ensure that we did not exclude interventions not meeting a strict set of criteria. The goal was not to examine interventions to reduce all readmissions, but rather, to look at patients who were recurrently hospitalized. Thus, patients had to be repeatedly admitted, but we let the studies define that usage explicitly.  

Two members of a four-physician team (A.G., B.H., K.O., and N.N.) screened all initial results for eligibility through title and abstract review; potentially relevant articles were retained for full-text review to assess each study's eligibility. If a study's abstract did not clearly indicate whether inclusion criteria were met, we retained the article for full-text review. Two team members (A.G. and B.H.) independently reviewed the full text of each selected article to determine final inclusion in the study. The previously described inclusion criteria were again applied, and a final set of articles was identified for data extraction. Disagreements regarding inclusion in the final review (such as whether a study measured medical or psychiatric hospitalizations) were resolved through discussion among the entire four-physician review team to achieve consensus or, when required, by contacting authors of individual studies.  

Data Abstraction and Risk of Bias Assessment

After selecting the final set of articles, we abstracted data using a tool developed by the Cochrane Effective Practice and Organization of Care Group.¹¹ We then compiled study-level data into a single database for reporting. Extracted elements included study design, setting, patient characteristics, inclusion and exclusion criteria, control group identification, outcome measures, results, and length of follow-up. We also extracted individual characteristics of each intervention, including common intervention elements such as intervention setting, use of health information technology resources, and whether programs developed interdisciplinary care plans. We assessed the risk of bias of each study and the quality of studies using the Downs and Black Scale.^12,13 Two team members (A.G. and B.H.) independently assessed the risk of bias for all nine studies, and differences were resolved by consensus. Due to the variation in the outcomes used, we were unable to conduct a meta-analysis.

Search Results

We found a total of 4,762 references in the three databases. After de-duplication using the EndNote software, there were 3,314 references to screen. We identified 116 studies for full-text review. Of those, we selected nine studies that met the criteria for this study (Figure). The most common reason for exclusion of an article for full-text review was that the patients studied were not defined as high utilizers of inpatient resources and were instead high-utilizers of ambulatory or emergency care (32 studies). We identified five of the included studies through the primary search and four through review of the references of the included papers.

Study Designs and  Included Studies

Of the nine included studies, three were randomized controlled trials, three were controlled retrospective cohort studies, and three were uncontrolled pre-post studies. The key characteristics of each study are described in Table 1.^14-22 The included studies had different definitions for patients who were high utilizers of hospital care. Eight used a "threshold" model that predicted future admissions using past patterns; these studies included patients with at least two admissions over a period of 6 to 12 months, although many had higher thresholds. Zulman et al. used a prediction algorithm to identify patients at risk of future admission. Four studies also included some measure of medical complexity, such as a certain number of chronic medical conditions;^14,17,18,22  in contrast, Sledge et al. excluded the most complex and high-cost patients.²⁰

All studies measured hospital admissions as a primary or a secondary outcome (Table 1). Although all studies demonstrated a reduction in hospital admissions following implementation, those with the greatest reductions did not have a control group.^14,15,17 All three randomized controlled trials showed equal reductions in admission rates between the intervention and control groups.^18,20,22 Among those specifically examining readmissions to the hospital, similar trends emerged, although one study (Plant et al.) found a nonsignificant decrease in hospital readmissions (17% reduction in 24 months, P = .07).¹⁸

In the secondary outcome analysis, six of the nine studies found nonsignificant reductions in ED admissions (Table 1). Four studies measured costs to the hospital or the local hospital system, though none examined costs to patients or payors. Studies estimated cost differently, including the use of estimated hospital costs,^17,20 "facility patient costs" at the VA,²² and a combination of inpatient and ED costs.¹⁹ The latter study (Shah et al., which implemented complex case management services) was the only one to find a statistically significant decrease in mean cost per year pre- and postintervention ($20,298 versus $7,053, P < .001).¹⁹

Only one study measured the quality of life, finding no significant change in summary scores after the intervention compared with controls (93.4 versus 92, P = .32).21 Another study conducted at a VA clinic network found no difference in a patient activation scale following the intervention but found significantly increased satisfaction with overall VA care (3.16 versus 2.90, P = .04).²²

Intervention Characteristics

Intervention characteristics are summarized in Table 2. Although there was heterogeneity in study interventions, we identified common themes. Five of the nine interventions^14-17,22 consisted of interdisciplinary teams that included community health workers, nurses, social workers, and physicians. Physicians were not included on every team; three interventions used them in direct care roles while two others contained physicians as advisors or in indirect roles. Intervention teams also had a variable level of involvement in a patient's care. Mercer et al. developed care plans for patients without physical interaction,¹⁷ whereas Zulman et al. recruited patients to a separate, intensive outpatient clinic outside the usual VA care team structure.²²

The majority of interventions added direct services or support - most commonly, a social worker - to usual care processes. Patient panel sizes were relatively small, with most of the teams recruiting fewer than 150 patients per interdisciplinary team (range, 25-251). There was variation in the length of intervention, from 35 days of case management following hospital discharge to one year of intensive social work support to others of an indefinite length.^15,17,22
Additional common themes included caring for patients across settings and incorporating information technology (IT) into workflows. Four interventions reported either interacting with patients in multiple settings, such as the hospital, clinic, and day hospital, ED, at home, or in the community.^14,19,21,22 Two others^16,20 interacted with patients only in the clinic but expanded the scope of a "traditional" primary care practice to include open scheduling, flexible appointment times, interdisciplinary visits, or outreach. In addition, IT resources assisted seven of the nine interventions, most commonly by identifying eligible patients via an electronic data tracking system or by automated alerts when their patients arrived at affiliated care locations. 

Risk of Study Bias

We systematically assessed the risk of bias of the nine included studies (Appendix B). Using the scale published by Downs and Black, a point-based scale in which a score of 18 denotes a high-quality study, the studies in this review scored 15.55 on average (range 6-22, standard deviation [SD] 5.0). Four of the nine studies met the benchmark for high quality.^12,13,18-22 The risk of bias was highest for measures of internal validity and confounding (range 0-5, mean 2.83, SD 1.94). The risk of bias was lowest for reporting measures (range 0-13, mean 7.40, SD 3.43).

Overall, studies reported mixed results related to readmissions and hospital utilization. While low-quality studies found reductions in hospital use over time, higher quality studies found similar reductions in utilization between the intervention and control groups. Johnson et al. showed that frequent hospitalization rates in a cohort of high-utilizer patients declined naturally over the course of 1-2 years; only 10% of individuals in the initial cohort remained "chronically hospitalized."⁶ Thus, expanding on these findings, the decline in hospitalizations over time as observed in some of the studies included in this review may be due to study patients being identified during a "spike" in utilization, which naturally decreases as the underlying medical or social factors driving rehospitalization resolve. Alternatively, reduction in hospitalizations may represent patients choosing to pursue care at other neighboring hospitals.²³ No study included in our review evaluated healthcare use at institutions other than their study hospital or health system.

A striking theme of this review was the heterogeneity in each study's patient population. Thresholds for "high utilizers" varied from two hospital admissions in six months to two to three admissions in 30 days, to a combination of ED and hospital admissions, and to the use of predictive algorithms. A standard "case definition" for this population could guide future research, enabling comparison of outcomes across settings. Thus, we propose that future studies use three or more hospital admissions within six months when evaluating interventions targeting "high utilizer" patients. Although patients with one prior hospitalization in the past year are at elevated risk of rehospitalization,² we feel that a higher "threshold" for this population will identify those at the highest strata of risk. Although predictive models may be better than "threshold" models, more work in validating these tools needs to be done before these can be put to use across settings.

In contrast to interventions designed to reduce readmissions for heart failure, pneumonia, or other diagnoses, frequently admitted patients do not encompass one disease or pathology pattern. Rinehart et al., in a study characterizing frequently admitted patients across a health system, identified five "subgroups" of patients, including those with (1) unstable housing, (2) comorbid medical and psychiatric illness, (3) severe complex medical illness, (4) dual-diagnosis psychiatric illness and substance abuse, and (5) a combination of medical and psychosocial barriers.25 In light of this population's heterogeneity, interventions may need to be flexible and tailored to the needs of individual patients, while simultaneously accounting for the capabilities and priorities of the health system. More specific and standardized interventions, targeting more homogenous groups, may be appropriate for populations defined according to pathology (such as heart failure or sickle cell disease).²⁷

The components of interventions used for frequently hospitalized patients were diverse. Although most of the studies used interdisciplinary teams, they focused their efforts in a variety of settings, often crossing modern "boundaries of care" by providing direct or indirect input on care across healthcare settings. Care fragmentation probably plays an important role in the risk for readmissions in this population;9 as such, interventions that address factors across the continuum of care may be more likely to succeed.²¹ Notably, six of nine studies were conducted at academic medical centers and an additional one at a VA facility affiliated with an academic center. Only two were located at community-based clinical networks, indicating a theoretical potential for publication bias as academic centers may be more likely to study and publish their work. There may be successful interventions that have not been formally studied or published in the peer-reviewed literature.

The breadth of the outcome measures in the included studies raises questions about what metrics should define success. Although all the studies looked at hospital utilization and readmission, measure definitions varied. Importantly, a minority of studies investigated quality of life and patient satisfaction, outcomes that may ultimately provide a more fertile ground for inquiry and intervention. Two studies looked at quality of life as an outcome,^19,22 but only one found that patients reported increased satisfaction despite showing nonsignificant reductions in hospital use.²² As shown in multiple prior studies, patient engagement is associated with increased satisfaction and can be associated with lower healthcare costs.^26,27 Hibbard et al. have demonstrated that patient activation is a specific component of patient engagement and inversely impacts healthcare cost, with lower levels of patient activation showing increased costs in comparison to those patients more engaged in their own care.²⁷ By focusing on changing patients' perceptions about their own health and involvement in their own care team as a partner, programs may be able to make a greater impact.  

Our systematic review has several limitations. Although we used a search strategy designed to identify all relevant studies, reviewed the references of included studies, and contacted the authors, we identified only nine studies meeting our inclusion criteria. Four of the nine studies were identified from a manual review of references of the included studies, suggesting the possibility of a suboptimal search strategy. Although the inclusion of articles that appear in a check of reference lists is a valid step in the systematic review article acquisition process, we conducted a post hoc investigation of alternate search strategies. We checked the titles, abstracts, and subject headings of the four articles found by reference review to determine whether the original search could have been improved. An analysis of the articles revealed that the terminology used was not consistent with the super user/utilizer terminology we were operating under, and that the four articles used terms such as "high risk" and "complex patients," which are more generic than our targeted terms. Only on a careful read of the abstracts and full-text did we find that these articles were useful to the study. Adjusting the original search to include these general terms would have resulted in an unwieldy set of results; hence, we felt it best to adhere to our original search strategy.

Additional limitations include that only four of the nine included studies were at low risk of bias. In addition to limitations based on study design and small sample sizes, the interventions were often limited to a short period. In light of the multiple factors that contribute to frequent hospitalizations, some of which cannot be addressed quickly, studies to evaluate interventions for longer durations are warranted.  

We found mixed results for the effect of interventions on outcomes for frequently hospitalized patients. While low-quality studies found reductions in hospital use over time, higher quality studies generally found similar reductions in utilization between the intervention and control groups. The range of definitions, interventions, and outcomes used for frequently hospitalized patients is partly explained by the heterogeneity of the population. More rigorous studies using multifaceted interventions that adapt to patients' unique needs should be conducted to assess the effect on outcomes relevant to both providers and patients.

Acknowledgments

The authors would like the thank Dr. Luke Hansen, Dr. Margaret Chapman, and McKay Barra for their support and contributions to this paper and to Northwestern Memorial Hospital's CHAMP (Complex High Admission Management Program).

Disclosures

The authors have nothing to disclose.

Funding

The authors received no funding from external or internal sources for the completion of this project.

In recent years, hospitals and health systems have engaged in considerable efforts to reduce readmissions, in part due to financial incentives from the Medicare Hospital Readmission Reduction Program.^1,2 Though efforts to improve transitions of care for all patients are laudable, risk for readmission is not distributed equally; a small subset of patients accounts for a disproportionate number of hospital readmissions.³ This phenomenon of frequently hospitalized patients is similar to that seen in other populations in which a small proportion of patients account for a majority of healthcare utilization.^3,4

Recognizing that the current system of healthcare delivery does not meet the needs of this population, healthcare organizations have begun to implement interventions that supplement or redesign the system of care for frequently hospitalized patients.^5-7 Descriptive reviews of ambulatory "high-need, high-cost" patients emphasize complex case management and interdisciplinary, team-based care.^8,9 Prior systematic reviews of studies aimed at patients with high use of emergency care demonstrate improvements in social outcomes such as homelessness but mixed results in reducing emergency department (ED) use.¹⁰ However, we were unable to identify any prior reviews that evaluated interventions intended specifically for patients with frequent hospital admissions. Our objective in this systematic review was to characterize interventions for frequently admitted patients and determine whether these interventions decrease use of healthcare resources, improve health outcomes, and/or reduce costs.

Literature Search

We registered our study protocol in the PROSPERO database. A librarian (L.O.) collaboratively developed the search strategies with other review authors (A.G., B.H., N.N.) and in January 2018 ran searches on "super users," "high utilizers," and similar terms in the following databases: PubMed MEDLINE, Embase (embase.com), and Cochrane Central Register of Controlled Trials (CENTRAL) on the Wiley platform. The complete search strategies used are available in Appendix A.  

We attempted to discover additional studies by searching the reference lists of key publications and contacted authors of relevant abstracts to determine whether studies had been published or were planned for peer-reviewed publication. We also contacted authors of included studies to locate additional studies meeting inclusion criteria.

Data Collection Process

Studies were eligible for inclusion in our review if they were (1) published in a peer-reviewed source, (2) defined a study population of patients frequently admitted to inpatient medical services, (3) evaluated an intervention targeting frequently hospitalized patients, and (4) included patients who were >18 years old and (5) admitted as inpatients on medical services. Of note, studies with patients admitted to psychiatric, obstetric, or surgical wards were not included, as the authors did not define these as "general medicine" units. Studies focused solely on an ambulatory population were similarly excluded. Given the heterogeneity of how studies defined frequently hospitalized patients, we did not establish a prespecified number of admissions for inclusion to ensure that we did not exclude interventions not meeting a strict set of criteria. The goal was not to examine interventions to reduce all readmissions, but rather, to look at patients who were recurrently hospitalized. Thus, patients had to be repeatedly admitted, but we let the studies define that usage explicitly.  

Two members of a four-physician team (A.G., B.H., K.O., and N.N.) screened all initial results for eligibility through title and abstract review; potentially relevant articles were retained for full-text review to assess each study's eligibility. If a study's abstract did not clearly indicate whether inclusion criteria were met, we retained the article for full-text review. Two team members (A.G. and B.H.) independently reviewed the full text of each selected article to determine final inclusion in the study. The previously described inclusion criteria were again applied, and a final set of articles was identified for data extraction. Disagreements regarding inclusion in the final review (such as whether a study measured medical or psychiatric hospitalizations) were resolved through discussion among the entire four-physician review team to achieve consensus or, when required, by contacting authors of individual studies.  

Data Abstraction and Risk of Bias Assessment

After selecting the final set of articles, we abstracted data using a tool developed by the Cochrane Effective Practice and Organization of Care Group.¹¹ We then compiled study-level data into a single database for reporting. Extracted elements included study design, setting, patient characteristics, inclusion and exclusion criteria, control group identification, outcome measures, results, and length of follow-up. We also extracted individual characteristics of each intervention, including common intervention elements such as intervention setting, use of health information technology resources, and whether programs developed interdisciplinary care plans. We assessed the risk of bias of each study and the quality of studies using the Downs and Black Scale.^12,13 Two team members (A.G. and B.H.) independently assessed the risk of bias for all nine studies, and differences were resolved by consensus. Due to the variation in the outcomes used, we were unable to conduct a meta-analysis.

Search Results

We found a total of 4,762 references in the three databases. After de-duplication using the EndNote software, there were 3,314 references to screen. We identified 116 studies for full-text review. Of those, we selected nine studies that met the criteria for this study (Figure). The most common reason for exclusion of an article for full-text review was that the patients studied were not defined as high utilizers of inpatient resources and were instead high-utilizers of ambulatory or emergency care (32 studies). We identified five of the included studies through the primary search and four through review of the references of the included papers.

Study Designs and  Included Studies

Of the nine included studies, three were randomized controlled trials, three were controlled retrospective cohort studies, and three were uncontrolled pre-post studies. The key characteristics of each study are described in Table 1.^14-22 The included studies had different definitions for patients who were high utilizers of hospital care. Eight used a "threshold" model that predicted future admissions using past patterns; these studies included patients with at least two admissions over a period of 6 to 12 months, although many had higher thresholds. Zulman et al. used a prediction algorithm to identify patients at risk of future admission. Four studies also included some measure of medical complexity, such as a certain number of chronic medical conditions;^14,17,18,22  in contrast, Sledge et al. excluded the most complex and high-cost patients.²⁰

All studies measured hospital admissions as a primary or a secondary outcome (Table 1). Although all studies demonstrated a reduction in hospital admissions following implementation, those with the greatest reductions did not have a control group.^14,15,17 All three randomized controlled trials showed equal reductions in admission rates between the intervention and control groups.^18,20,22 Among those specifically examining readmissions to the hospital, similar trends emerged, although one study (Plant et al.) found a nonsignificant decrease in hospital readmissions (17% reduction in 24 months, P = .07).¹⁸

In the secondary outcome analysis, six of the nine studies found nonsignificant reductions in ED admissions (Table 1). Four studies measured costs to the hospital or the local hospital system, though none examined costs to patients or payors. Studies estimated cost differently, including the use of estimated hospital costs,^17,20 "facility patient costs" at the VA,²² and a combination of inpatient and ED costs.¹⁹ The latter study (Shah et al., which implemented complex case management services) was the only one to find a statistically significant decrease in mean cost per year pre- and postintervention ($20,298 versus $7,053, P < .001).¹⁹

Only one study measured the quality of life, finding no significant change in summary scores after the intervention compared with controls (93.4 versus 92, P = .32).21 Another study conducted at a VA clinic network found no difference in a patient activation scale following the intervention but found significantly increased satisfaction with overall VA care (3.16 versus 2.90, P = .04).²²

Intervention Characteristics

Intervention characteristics are summarized in Table 2. Although there was heterogeneity in study interventions, we identified common themes. Five of the nine interventions^14-17,22 consisted of interdisciplinary teams that included community health workers, nurses, social workers, and physicians. Physicians were not included on every team; three interventions used them in direct care roles while two others contained physicians as advisors or in indirect roles. Intervention teams also had a variable level of involvement in a patient's care. Mercer et al. developed care plans for patients without physical interaction,¹⁷ whereas Zulman et al. recruited patients to a separate, intensive outpatient clinic outside the usual VA care team structure.²²

The majority of interventions added direct services or support - most commonly, a social worker - to usual care processes. Patient panel sizes were relatively small, with most of the teams recruiting fewer than 150 patients per interdisciplinary team (range, 25-251). There was variation in the length of intervention, from 35 days of case management following hospital discharge to one year of intensive social work support to others of an indefinite length.^15,17,22
Additional common themes included caring for patients across settings and incorporating information technology (IT) into workflows. Four interventions reported either interacting with patients in multiple settings, such as the hospital, clinic, and day hospital, ED, at home, or in the community.^14,19,21,22 Two others^16,20 interacted with patients only in the clinic but expanded the scope of a "traditional" primary care practice to include open scheduling, flexible appointment times, interdisciplinary visits, or outreach. In addition, IT resources assisted seven of the nine interventions, most commonly by identifying eligible patients via an electronic data tracking system or by automated alerts when their patients arrived at affiliated care locations. 

Risk of Study Bias

We systematically assessed the risk of bias of the nine included studies (Appendix B). Using the scale published by Downs and Black, a point-based scale in which a score of 18 denotes a high-quality study, the studies in this review scored 15.55 on average (range 6-22, standard deviation [SD] 5.0). Four of the nine studies met the benchmark for high quality.^12,13,18-22 The risk of bias was highest for measures of internal validity and confounding (range 0-5, mean 2.83, SD 1.94). The risk of bias was lowest for reporting measures (range 0-13, mean 7.40, SD 3.43).

Overall, studies reported mixed results related to readmissions and hospital utilization. While low-quality studies found reductions in hospital use over time, higher quality studies found similar reductions in utilization between the intervention and control groups. Johnson et al. showed that frequent hospitalization rates in a cohort of high-utilizer patients declined naturally over the course of 1-2 years; only 10% of individuals in the initial cohort remained "chronically hospitalized."⁶ Thus, expanding on these findings, the decline in hospitalizations over time as observed in some of the studies included in this review may be due to study patients being identified during a "spike" in utilization, which naturally decreases as the underlying medical or social factors driving rehospitalization resolve. Alternatively, reduction in hospitalizations may represent patients choosing to pursue care at other neighboring hospitals.²³ No study included in our review evaluated healthcare use at institutions other than their study hospital or health system.

A striking theme of this review was the heterogeneity in each study's patient population. Thresholds for "high utilizers" varied from two hospital admissions in six months to two to three admissions in 30 days, to a combination of ED and hospital admissions, and to the use of predictive algorithms. A standard "case definition" for this population could guide future research, enabling comparison of outcomes across settings. Thus, we propose that future studies use three or more hospital admissions within six months when evaluating interventions targeting "high utilizer" patients. Although patients with one prior hospitalization in the past year are at elevated risk of rehospitalization,² we feel that a higher "threshold" for this population will identify those at the highest strata of risk. Although predictive models may be better than "threshold" models, more work in validating these tools needs to be done before these can be put to use across settings.

In contrast to interventions designed to reduce readmissions for heart failure, pneumonia, or other diagnoses, frequently admitted patients do not encompass one disease or pathology pattern. Rinehart et al., in a study characterizing frequently admitted patients across a health system, identified five "subgroups" of patients, including those with (1) unstable housing, (2) comorbid medical and psychiatric illness, (3) severe complex medical illness, (4) dual-diagnosis psychiatric illness and substance abuse, and (5) a combination of medical and psychosocial barriers.25 In light of this population's heterogeneity, interventions may need to be flexible and tailored to the needs of individual patients, while simultaneously accounting for the capabilities and priorities of the health system. More specific and standardized interventions, targeting more homogenous groups, may be appropriate for populations defined according to pathology (such as heart failure or sickle cell disease).²⁷

The components of interventions used for frequently hospitalized patients were diverse. Although most of the studies used interdisciplinary teams, they focused their efforts in a variety of settings, often crossing modern "boundaries of care" by providing direct or indirect input on care across healthcare settings. Care fragmentation probably plays an important role in the risk for readmissions in this population;9 as such, interventions that address factors across the continuum of care may be more likely to succeed.²¹ Notably, six of nine studies were conducted at academic medical centers and an additional one at a VA facility affiliated with an academic center. Only two were located at community-based clinical networks, indicating a theoretical potential for publication bias as academic centers may be more likely to study and publish their work. There may be successful interventions that have not been formally studied or published in the peer-reviewed literature.

The breadth of the outcome measures in the included studies raises questions about what metrics should define success. Although all the studies looked at hospital utilization and readmission, measure definitions varied. Importantly, a minority of studies investigated quality of life and patient satisfaction, outcomes that may ultimately provide a more fertile ground for inquiry and intervention. Two studies looked at quality of life as an outcome,^19,22 but only one found that patients reported increased satisfaction despite showing nonsignificant reductions in hospital use.²² As shown in multiple prior studies, patient engagement is associated with increased satisfaction and can be associated with lower healthcare costs.^26,27 Hibbard et al. have demonstrated that patient activation is a specific component of patient engagement and inversely impacts healthcare cost, with lower levels of patient activation showing increased costs in comparison to those patients more engaged in their own care.²⁷ By focusing on changing patients' perceptions about their own health and involvement in their own care team as a partner, programs may be able to make a greater impact.  

Our systematic review has several limitations. Although we used a search strategy designed to identify all relevant studies, reviewed the references of included studies, and contacted the authors, we identified only nine studies meeting our inclusion criteria. Four of the nine studies were identified from a manual review of references of the included studies, suggesting the possibility of a suboptimal search strategy. Although the inclusion of articles that appear in a check of reference lists is a valid step in the systematic review article acquisition process, we conducted a post hoc investigation of alternate search strategies. We checked the titles, abstracts, and subject headings of the four articles found by reference review to determine whether the original search could have been improved. An analysis of the articles revealed that the terminology used was not consistent with the super user/utilizer terminology we were operating under, and that the four articles used terms such as "high risk" and "complex patients," which are more generic than our targeted terms. Only on a careful read of the abstracts and full-text did we find that these articles were useful to the study. Adjusting the original search to include these general terms would have resulted in an unwieldy set of results; hence, we felt it best to adhere to our original search strategy.

Additional limitations include that only four of the nine included studies were at low risk of bias. In addition to limitations based on study design and small sample sizes, the interventions were often limited to a short period. In light of the multiple factors that contribute to frequent hospitalizations, some of which cannot be addressed quickly, studies to evaluate interventions for longer durations are warranted.  

We found mixed results for the effect of interventions on outcomes for frequently hospitalized patients. While low-quality studies found reductions in hospital use over time, higher quality studies generally found similar reductions in utilization between the intervention and control groups. The range of definitions, interventions, and outcomes used for frequently hospitalized patients is partly explained by the heterogeneity of the population. More rigorous studies using multifaceted interventions that adapt to patients' unique needs should be conducted to assess the effect on outcomes relevant to both providers and patients.

Acknowledgments

The authors would like the thank Dr. Luke Hansen, Dr. Margaret Chapman, and McKay Barra for their support and contributions to this paper and to Northwestern Memorial Hospital's CHAMP (Complex High Admission Management Program).

Disclosures

The authors have nothing to disclose.

Funding

The authors received no funding from external or internal sources for the completion of this project.

In recent years, hospitals and health systems have engaged in considerable efforts to reduce readmissions, in part due to financial incentives from the Medicare Hospital Readmission Reduction Program.^1,2 Though efforts to improve transitions of care for all patients are laudable, risk for readmission is not distributed equally; a small subset of patients accounts for a disproportionate number of hospital readmissions.³ This phenomenon of frequently hospitalized patients is similar to that seen in other populations in which a small proportion of patients account for a majority of healthcare utilization.^3,4

Recognizing that the current system of healthcare delivery does not meet the needs of this population, healthcare organizations have begun to implement interventions that supplement or redesign the system of care for frequently hospitalized patients.^5-7 Descriptive reviews of ambulatory "high-need, high-cost" patients emphasize complex case management and interdisciplinary, team-based care.^8,9 Prior systematic reviews of studies aimed at patients with high use of emergency care demonstrate improvements in social outcomes such as homelessness but mixed results in reducing emergency department (ED) use.¹⁰ However, we were unable to identify any prior reviews that evaluated interventions intended specifically for patients with frequent hospital admissions. Our objective in this systematic review was to characterize interventions for frequently admitted patients and determine whether these interventions decrease use of healthcare resources, improve health outcomes, and/or reduce costs.

Literature Search

We registered our study protocol in the PROSPERO database. A librarian (L.O.) collaboratively developed the search strategies with other review authors (A.G., B.H., N.N.) and in January 2018 ran searches on "super users," "high utilizers," and similar terms in the following databases: PubMed MEDLINE, Embase (embase.com), and Cochrane Central Register of Controlled Trials (CENTRAL) on the Wiley platform. The complete search strategies used are available in Appendix A.  

We attempted to discover additional studies by searching the reference lists of key publications and contacted authors of relevant abstracts to determine whether studies had been published or were planned for peer-reviewed publication. We also contacted authors of included studies to locate additional studies meeting inclusion criteria.

Data Collection Process

Studies were eligible for inclusion in our review if they were (1) published in a peer-reviewed source, (2) defined a study population of patients frequently admitted to inpatient medical services, (3) evaluated an intervention targeting frequently hospitalized patients, and (4) included patients who were >18 years old and (5) admitted as inpatients on medical services. Of note, studies with patients admitted to psychiatric, obstetric, or surgical wards were not included, as the authors did not define these as "general medicine" units. Studies focused solely on an ambulatory population were similarly excluded. Given the heterogeneity of how studies defined frequently hospitalized patients, we did not establish a prespecified number of admissions for inclusion to ensure that we did not exclude interventions not meeting a strict set of criteria. The goal was not to examine interventions to reduce all readmissions, but rather, to look at patients who were recurrently hospitalized. Thus, patients had to be repeatedly admitted, but we let the studies define that usage explicitly.  

Two members of a four-physician team (A.G., B.H., K.O., and N.N.) screened all initial results for eligibility through title and abstract review; potentially relevant articles were retained for full-text review to assess each study's eligibility. If a study's abstract did not clearly indicate whether inclusion criteria were met, we retained the article for full-text review. Two team members (A.G. and B.H.) independently reviewed the full text of each selected article to determine final inclusion in the study. The previously described inclusion criteria were again applied, and a final set of articles was identified for data extraction. Disagreements regarding inclusion in the final review (such as whether a study measured medical or psychiatric hospitalizations) were resolved through discussion among the entire four-physician review team to achieve consensus or, when required, by contacting authors of individual studies.  

Data Abstraction and Risk of Bias Assessment

After selecting the final set of articles, we abstracted data using a tool developed by the Cochrane Effective Practice and Organization of Care Group.¹¹ We then compiled study-level data into a single database for reporting. Extracted elements included study design, setting, patient characteristics, inclusion and exclusion criteria, control group identification, outcome measures, results, and length of follow-up. We also extracted individual characteristics of each intervention, including common intervention elements such as intervention setting, use of health information technology resources, and whether programs developed interdisciplinary care plans. We assessed the risk of bias of each study and the quality of studies using the Downs and Black Scale.^12,13 Two team members (A.G. and B.H.) independently assessed the risk of bias for all nine studies, and differences were resolved by consensus. Due to the variation in the outcomes used, we were unable to conduct a meta-analysis.

Search Results

We found a total of 4,762 references in the three databases. After de-duplication using the EndNote software, there were 3,314 references to screen. We identified 116 studies for full-text review. Of those, we selected nine studies that met the criteria for this study (Figure). The most common reason for exclusion of an article for full-text review was that the patients studied were not defined as high utilizers of inpatient resources and were instead high-utilizers of ambulatory or emergency care (32 studies). We identified five of the included studies through the primary search and four through review of the references of the included papers.

Study Designs and  Included Studies

Of the nine included studies, three were randomized controlled trials, three were controlled retrospective cohort studies, and three were uncontrolled pre-post studies. The key characteristics of each study are described in Table 1.^14-22 The included studies had different definitions for patients who were high utilizers of hospital care. Eight used a "threshold" model that predicted future admissions using past patterns; these studies included patients with at least two admissions over a period of 6 to 12 months, although many had higher thresholds. Zulman et al. used a prediction algorithm to identify patients at risk of future admission. Four studies also included some measure of medical complexity, such as a certain number of chronic medical conditions;^14,17,18,22  in contrast, Sledge et al. excluded the most complex and high-cost patients.²⁰

All studies measured hospital admissions as a primary or a secondary outcome (Table 1). Although all studies demonstrated a reduction in hospital admissions following implementation, those with the greatest reductions did not have a control group.^14,15,17 All three randomized controlled trials showed equal reductions in admission rates between the intervention and control groups.^18,20,22 Among those specifically examining readmissions to the hospital, similar trends emerged, although one study (Plant et al.) found a nonsignificant decrease in hospital readmissions (17% reduction in 24 months, P = .07).¹⁸

In the secondary outcome analysis, six of the nine studies found nonsignificant reductions in ED admissions (Table 1). Four studies measured costs to the hospital or the local hospital system, though none examined costs to patients or payors. Studies estimated cost differently, including the use of estimated hospital costs,^17,20 "facility patient costs" at the VA,²² and a combination of inpatient and ED costs.¹⁹ The latter study (Shah et al., which implemented complex case management services) was the only one to find a statistically significant decrease in mean cost per year pre- and postintervention ($20,298 versus $7,053, P < .001).¹⁹

Only one study measured the quality of life, finding no significant change in summary scores after the intervention compared with controls (93.4 versus 92, P = .32).21 Another study conducted at a VA clinic network found no difference in a patient activation scale following the intervention but found significantly increased satisfaction with overall VA care (3.16 versus 2.90, P = .04).²²

Intervention Characteristics

Intervention characteristics are summarized in Table 2. Although there was heterogeneity in study interventions, we identified common themes. Five of the nine interventions^14-17,22 consisted of interdisciplinary teams that included community health workers, nurses, social workers, and physicians. Physicians were not included on every team; three interventions used them in direct care roles while two others contained physicians as advisors or in indirect roles. Intervention teams also had a variable level of involvement in a patient's care. Mercer et al. developed care plans for patients without physical interaction,¹⁷ whereas Zulman et al. recruited patients to a separate, intensive outpatient clinic outside the usual VA care team structure.²²

The majority of interventions added direct services or support - most commonly, a social worker - to usual care processes. Patient panel sizes were relatively small, with most of the teams recruiting fewer than 150 patients per interdisciplinary team (range, 25-251). There was variation in the length of intervention, from 35 days of case management following hospital discharge to one year of intensive social work support to others of an indefinite length.^15,17,22
Additional common themes included caring for patients across settings and incorporating information technology (IT) into workflows. Four interventions reported either interacting with patients in multiple settings, such as the hospital, clinic, and day hospital, ED, at home, or in the community.^14,19,21,22 Two others^16,20 interacted with patients only in the clinic but expanded the scope of a "traditional" primary care practice to include open scheduling, flexible appointment times, interdisciplinary visits, or outreach. In addition, IT resources assisted seven of the nine interventions, most commonly by identifying eligible patients via an electronic data tracking system or by automated alerts when their patients arrived at affiliated care locations. 

Risk of Study Bias

We systematically assessed the risk of bias of the nine included studies (Appendix B). Using the scale published by Downs and Black, a point-based scale in which a score of 18 denotes a high-quality study, the studies in this review scored 15.55 on average (range 6-22, standard deviation [SD] 5.0). Four of the nine studies met the benchmark for high quality.^12,13,18-22 The risk of bias was highest for measures of internal validity and confounding (range 0-5, mean 2.83, SD 1.94). The risk of bias was lowest for reporting measures (range 0-13, mean 7.40, SD 3.43).

Overall, studies reported mixed results related to readmissions and hospital utilization. While low-quality studies found reductions in hospital use over time, higher quality studies found similar reductions in utilization between the intervention and control groups. Johnson et al. showed that frequent hospitalization rates in a cohort of high-utilizer patients declined naturally over the course of 1-2 years; only 10% of individuals in the initial cohort remained "chronically hospitalized."⁶ Thus, expanding on these findings, the decline in hospitalizations over time as observed in some of the studies included in this review may be due to study patients being identified during a "spike" in utilization, which naturally decreases as the underlying medical or social factors driving rehospitalization resolve. Alternatively, reduction in hospitalizations may represent patients choosing to pursue care at other neighboring hospitals.²³ No study included in our review evaluated healthcare use at institutions other than their study hospital or health system.

A striking theme of this review was the heterogeneity in each study's patient population. Thresholds for "high utilizers" varied from two hospital admissions in six months to two to three admissions in 30 days, to a combination of ED and hospital admissions, and to the use of predictive algorithms. A standard "case definition" for this population could guide future research, enabling comparison of outcomes across settings. Thus, we propose that future studies use three or more hospital admissions within six months when evaluating interventions targeting "high utilizer" patients. Although patients with one prior hospitalization in the past year are at elevated risk of rehospitalization,² we feel that a higher "threshold" for this population will identify those at the highest strata of risk. Although predictive models may be better than "threshold" models, more work in validating these tools needs to be done before these can be put to use across settings.

In contrast to interventions designed to reduce readmissions for heart failure, pneumonia, or other diagnoses, frequently admitted patients do not encompass one disease or pathology pattern. Rinehart et al., in a study characterizing frequently admitted patients across a health system, identified five "subgroups" of patients, including those with (1) unstable housing, (2) comorbid medical and psychiatric illness, (3) severe complex medical illness, (4) dual-diagnosis psychiatric illness and substance abuse, and (5) a combination of medical and psychosocial barriers.25 In light of this population's heterogeneity, interventions may need to be flexible and tailored to the needs of individual patients, while simultaneously accounting for the capabilities and priorities of the health system. More specific and standardized interventions, targeting more homogenous groups, may be appropriate for populations defined according to pathology (such as heart failure or sickle cell disease).²⁷

The components of interventions used for frequently hospitalized patients were diverse. Although most of the studies used interdisciplinary teams, they focused their efforts in a variety of settings, often crossing modern "boundaries of care" by providing direct or indirect input on care across healthcare settings. Care fragmentation probably plays an important role in the risk for readmissions in this population;9 as such, interventions that address factors across the continuum of care may be more likely to succeed.²¹ Notably, six of nine studies were conducted at academic medical centers and an additional one at a VA facility affiliated with an academic center. Only two were located at community-based clinical networks, indicating a theoretical potential for publication bias as academic centers may be more likely to study and publish their work. There may be successful interventions that have not been formally studied or published in the peer-reviewed literature.

The breadth of the outcome measures in the included studies raises questions about what metrics should define success. Although all the studies looked at hospital utilization and readmission, measure definitions varied. Importantly, a minority of studies investigated quality of life and patient satisfaction, outcomes that may ultimately provide a more fertile ground for inquiry and intervention. Two studies looked at quality of life as an outcome,^19,22 but only one found that patients reported increased satisfaction despite showing nonsignificant reductions in hospital use.²² As shown in multiple prior studies, patient engagement is associated with increased satisfaction and can be associated with lower healthcare costs.^26,27 Hibbard et al. have demonstrated that patient activation is a specific component of patient engagement and inversely impacts healthcare cost, with lower levels of patient activation showing increased costs in comparison to those patients more engaged in their own care.²⁷ By focusing on changing patients' perceptions about their own health and involvement in their own care team as a partner, programs may be able to make a greater impact.  

Our systematic review has several limitations. Although we used a search strategy designed to identify all relevant studies, reviewed the references of included studies, and contacted the authors, we identified only nine studies meeting our inclusion criteria. Four of the nine studies were identified from a manual review of references of the included studies, suggesting the possibility of a suboptimal search strategy. Although the inclusion of articles that appear in a check of reference lists is a valid step in the systematic review article acquisition process, we conducted a post hoc investigation of alternate search strategies. We checked the titles, abstracts, and subject headings of the four articles found by reference review to determine whether the original search could have been improved. An analysis of the articles revealed that the terminology used was not consistent with the super user/utilizer terminology we were operating under, and that the four articles used terms such as "high risk" and "complex patients," which are more generic than our targeted terms. Only on a careful read of the abstracts and full-text did we find that these articles were useful to the study. Adjusting the original search to include these general terms would have resulted in an unwieldy set of results; hence, we felt it best to adhere to our original search strategy.

Additional limitations include that only four of the nine included studies were at low risk of bias. In addition to limitations based on study design and small sample sizes, the interventions were often limited to a short period. In light of the multiple factors that contribute to frequent hospitalizations, some of which cannot be addressed quickly, studies to evaluate interventions for longer durations are warranted.  

We found mixed results for the effect of interventions on outcomes for frequently hospitalized patients. While low-quality studies found reductions in hospital use over time, higher quality studies generally found similar reductions in utilization between the intervention and control groups. The range of definitions, interventions, and outcomes used for frequently hospitalized patients is partly explained by the heterogeneity of the population. More rigorous studies using multifaceted interventions that adapt to patients' unique needs should be conducted to assess the effect on outcomes relevant to both providers and patients.

Acknowledgments

The authors would like the thank Dr. Luke Hansen, Dr. Margaret Chapman, and McKay Barra for their support and contributions to this paper and to Northwestern Memorial Hospital's CHAMP (Complex High Admission Management Program).

Disclosures

The authors have nothing to disclose.

Funding

The authors received no funding from external or internal sources for the completion of this project.

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

A 67-year-old man is hospitalized with community-acquired pneumonia. He has a history of hypertension and is prescribed two antihypertensive medications (amlodipine and chlorthalidone) as an outpatient. On the evening of hospital day two, he is found to have a blood pressure of 192/95 on a scheduled vital signs check. He reports no symptoms other than cough, which is not new or worsening. The covering hospitalist reviews the documented blood pressures since admission and notes that many have been elevated despite continuation of his home regimen. The patient's nurse inquires about treating the patient with additional "as-needed" antihypertensive medications.  

Hypertensive crises are common in hospitalized patients, with approximately one in seven patients experiencing an episode of hypertensive emergency and/or hypertensive urgency.¹ Hypertensive emergency is typically defined as (1) a systolic blood pressure &#8805;180 mm Hg and/or a diastolic blood pressure &#8805;120 mm Hg with (2) evidence of new or worsening end-organ damage. The organs most commonly affected by severe hypertension are the brain (headache, confusion, stroke), heart (chest pain, myocardial infarction, pulmonary edema), large blood vessels (aortic dissection), and kidneys (acute hypertensive nephrosclerosis).² With hypertensive urgency, patients experience similarly elevated blood pressure but have no symptoms or signs suggesting acute end-organ damage. Acute treatment with intravenous (IV) or immediate-acting oral medications is common; a single-center study showed that 7.4% of hospitalized patients had an order for "as needed" IV hydralazine or labetalol, with 60.3% receiving at least one dose.³ Among internal medicine and family medicine trainees in one survey, nearly half reported that they would use IV medications in a scenario where an inpatient had an asymptomatic blood pressure above 180 mm Hg.⁴

Treating patients with hypertensive urgency is based on an assumption: If one does not treat immediately, something bad (ie, end-organ damage) will occur over the next few hours. Data from the 1930s showed that patients with untreated hypertensive emergency had a one-year mortality rate >79% and a median survival of 10.4 months.⁵ More recent studies suggest that the in-hospital and one-year mortality for those with hypertensive emergency are 13% and 39%, respectively.⁶ These data demonstrate that patients with hypertensive emergency are at risk in both the short- and long-term.
Patients with hypertensive urgency are also at increased risk for long-term morbidity and mortality. The one-year mortality for those experiencing an episode of hypertensive urgency is approximately 9%.6 Given the concerns about poor outcomes, it remains a common practice in many facilities to acutely lower the blood pressure in patients with hypertensive urgency. This is highlighted by recommendations of a commonly used point-of-care medical resource, which suggests that "potential legal ramifications partially motivate lowering the blood pressure over several hours."⁷

Concerns regarding overtreatment of hypertensive urgency relate to overestimated rates of hypertensive complications, the pathophysiology of hypertension itself, and the potential for adverse events related to treatment. Given that there are few trials examining hospitalized patients with hypertensive urgency, much of the data supporting a conservative approach are drawn from studies of outpatients or emergency department patients. In addition, there is little data suggesting that outcomes are different for patients presenting with a chief complaint of hypertensive urgency and those presenting with an alternate diagnosis but who are found to have blood pressures that meet the threshold for diagnosis of hypertensive urgency.

The landmark 1967 Veterans Affairs Cooperative Trial demonstrated the long-term benefits of treating patients with chronic hypertensive urgency.⁸ Importantly though, benefits accrued over a period of months to years, not hours. The time to the first adverse event in the placebo arm was two months, suggesting that even those with blood pressures chronically in the range of hypertensive urgency are unlikely to experience hyperacute (ie, within hours) events, even without treatment.  

A more recent study, conducted by Patel et al., examined 58,836 patients seen in outpatient clinics and found to have blood pressures meeting the criteria for hypertensive urgency.⁹ This study included patients whose primary issue was hypertensive urgency and patients in whom the diagnosis was secondary. A total of 426 patients were referred to the hospital and only 100 (0.17%) were subsequently admitted. At seven days, the rates of the primary outcome (a composite of myocardial infarction, stroke, and/or transient ischemic attack) were 0.1% in those sent home and 0.5% in those sent to the hospital. In those patients with a systolic blood pressure &#8805;220 mm Hg, two out of 977 (0.2%) of those sent home and zero out of 81 of those sent to the hospital experienced the primary outcome. These data reinforce the message that, in patients with hypertensive urgency, rates of adverse events at seven days are low, even with extreme blood pressure elevation.  

The human body has adapted to withstand wide variations in blood pressure.¹⁰ For example, through arteriolar constriction and reflex vasodilation, cerebral autoregulation maintains a constant cerebral blood flow within a wide range of perfusion pressures, ensuring that the brain is protected from higher mean arterial pressures.¹¹ While this process is protective, over time the autoregulatory system becomes impaired, especially in patients with cerebrovascular disease. This places patients at risk for cerebral and/or cardiac ischemia with even slight drops in perfusion pressure.^12,13 Indeed, in assessing treatment-related adverse events in a series of patients treated with intravenous nicardipine or nitroprusside for hypertensive emergency, Brooks and colleagues reported that 57% (27 of 47) of patients had overly large reductions in blood pressure (>25% reduction in mean arterial pressure) within the first 30 minutes of treatment.¹⁴ Two patients had acute ischemic events attributed to treatment with antihypertensive medications. Myocardial infarction and stroke have both been reported,¹² and medication classes such as calcium channel blockers (sublingual nifedipine in particular), beta-blockers (eg, labetolol), angiotensin-converting-enzyme inhibitors (eg, captopril), and clonidine have all been implicated in treatment-related adverse events.^12,15-17 Another potential issue derives from the observation that blood pressures obtained in the hospital setting are often inaccurate, owing to inappropriate patient preparation, faulty equipment, and inadequate training of staff obtaining the measurement.¹⁸

National guidelines support a cautious approach to the treatment of hypertensive urgency. The seventh Report of the Joint National Committee on Detection, Evaluation, and Treatment of Hypertension, published in 2003, noted that "patients with markedly elevated BP but without acute target-organ damage usually do not require hospitalization, but they should receive immediate combination oral antihypertensive therapy" and that "there is no evidence to suggest that failure to aggressively lower BP in the [emergency department] is associated with any increased short-term risk to the patient who presents with severe hypertension." JNC 7 also laments contemporary terminology: "Unfortunately, the term 'urgency' has led to overly aggressive management of many patients with severe, uncomplicated hypertension. Aggressive dosing with intravenous drugs or even oral agents, to rapidly lower BP is not without risk."¹⁹ The most recent JNC guideline does not comment on hypertensive urgency,²⁰ and the 2017 American College of Cardiology/American Heart Association Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults argues that, "¬there is no indication for referral to the emergency department, immediate reduction in BP in the emergency department, or hospitalization for [patients with hypertensive urgency]."²¹

After it is confirmed that a patient has no end-organ damage (ie, the patient has hypertensive urgency, not emergency), treatable causes of hypertension should be assessed. In hospitalized patients, these include missed or held doses of outpatient medications, pain, nausea, alcohol and/or benzodiazepine withdrawal, delirium, and obstructive sleep apnea.²² If no remediable cause is identified, patients should be allowed to rest for at least 30 minutes without the administration of additional antihypertensive medications, after which time the blood pressure should be measured using the correct technique.2 Clinical trials have shown that rest is effective at lowering blood pressure in patients with hypertensive urgency.^23,24 One study initially treated 549 emergency department patients with a 30-minute rest period, after which time 32% of patients had responded (defined as a SBP <180 mm Hg and DBP <110 mm Hg, with at least a 20 mm Hg reduction in baseline SBP and/or a 10 mm Hg reduction in DBP).²³ Another study randomized 138 patients with hypertensive urgency to either rest or active treatment with telmisartan. Blood pressures were checked every 30 minutes for four hours. The primary endpoint (reduction of MAP of 10%-35%) was similar in both groups (68.5% in the rest group and 69.1% in the telmisartan group).²⁴ Even if rest is ineffective, the risk-benefit ratio of acutely lowering blood pressure will typically favor withholding acute treatment in asymptomatic patients. If blood pressure remains consistently elevated, augmentation of the home regimen (eg, increasing the dose of their next scheduled antihypertensive) of oral medications may be warranted. Though not all agree with management of antihypertensives in hospitalized patients,²⁵ acute hospitalizations afford an opportunity to modify and observe chronic hypertension.²⁶

• Ensure that patients do not have symptoms and/or signs of end-organ damage. This can be done with a brief review of systems and a physical examination. In select cases, an electrocardiogram and a chest x-ray may be warranted.
• Search for common causes of treatable hypertension in hospitalized patients; these include pain, nausea, withdrawal syndromes, and holding of usual antihypertensive medications.
• In those patients without symptoms and/or signs of end-organ damage, allow rest, followed by reassessment.
• Do not administer intravenous or immediate-acting oral antihypertensive medications to acutely lower blood pressure. Instead, address the issues raised in Recommendation #2 and consider modifying the chronic oral antihypertensive regimen in patients who are uncontrolled as outpatients or who are not treated as outpatients. Coordinate early postdischarge follow-up for repeat blood pressure evaluation and continued modification of a patient's chronic antihypertensive regimen.

Although patients with hypertensive urgency are often treated with medications to acutely lower their blood pressure, there is no evidence to support this practice, and a strong pathophysiologic basis suggests that harm may result. The patient in the case described above should be allowed to rest for at least 30 minutes, with reevaluation of his blood pressure. If it remains elevated and no treatable secondary causes are found, the treating hospitalist should consider altering his chronic antihypertensive regimen to promote long-term blood pressure control.

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

Disclosures

The authors have no conflicts of interest.
 

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

A 67-year-old man is hospitalized with community-acquired pneumonia. He has a history of hypertension and is prescribed two antihypertensive medications (amlodipine and chlorthalidone) as an outpatient. On the evening of hospital day two, he is found to have a blood pressure of 192/95 on a scheduled vital signs check. He reports no symptoms other than cough, which is not new or worsening. The covering hospitalist reviews the documented blood pressures since admission and notes that many have been elevated despite continuation of his home regimen. The patient's nurse inquires about treating the patient with additional "as-needed" antihypertensive medications.  

Hypertensive crises are common in hospitalized patients, with approximately one in seven patients experiencing an episode of hypertensive emergency and/or hypertensive urgency.¹ Hypertensive emergency is typically defined as (1) a systolic blood pressure &#8805;180 mm Hg and/or a diastolic blood pressure &#8805;120 mm Hg with (2) evidence of new or worsening end-organ damage. The organs most commonly affected by severe hypertension are the brain (headache, confusion, stroke), heart (chest pain, myocardial infarction, pulmonary edema), large blood vessels (aortic dissection), and kidneys (acute hypertensive nephrosclerosis).² With hypertensive urgency, patients experience similarly elevated blood pressure but have no symptoms or signs suggesting acute end-organ damage. Acute treatment with intravenous (IV) or immediate-acting oral medications is common; a single-center study showed that 7.4% of hospitalized patients had an order for "as needed" IV hydralazine or labetalol, with 60.3% receiving at least one dose.³ Among internal medicine and family medicine trainees in one survey, nearly half reported that they would use IV medications in a scenario where an inpatient had an asymptomatic blood pressure above 180 mm Hg.⁴

Treating patients with hypertensive urgency is based on an assumption: If one does not treat immediately, something bad (ie, end-organ damage) will occur over the next few hours. Data from the 1930s showed that patients with untreated hypertensive emergency had a one-year mortality rate >79% and a median survival of 10.4 months.⁵ More recent studies suggest that the in-hospital and one-year mortality for those with hypertensive emergency are 13% and 39%, respectively.⁶ These data demonstrate that patients with hypertensive emergency are at risk in both the short- and long-term.
Patients with hypertensive urgency are also at increased risk for long-term morbidity and mortality. The one-year mortality for those experiencing an episode of hypertensive urgency is approximately 9%.6 Given the concerns about poor outcomes, it remains a common practice in many facilities to acutely lower the blood pressure in patients with hypertensive urgency. This is highlighted by recommendations of a commonly used point-of-care medical resource, which suggests that "potential legal ramifications partially motivate lowering the blood pressure over several hours."⁷

Concerns regarding overtreatment of hypertensive urgency relate to overestimated rates of hypertensive complications, the pathophysiology of hypertension itself, and the potential for adverse events related to treatment. Given that there are few trials examining hospitalized patients with hypertensive urgency, much of the data supporting a conservative approach are drawn from studies of outpatients or emergency department patients. In addition, there is little data suggesting that outcomes are different for patients presenting with a chief complaint of hypertensive urgency and those presenting with an alternate diagnosis but who are found to have blood pressures that meet the threshold for diagnosis of hypertensive urgency.

The landmark 1967 Veterans Affairs Cooperative Trial demonstrated the long-term benefits of treating patients with chronic hypertensive urgency.⁸ Importantly though, benefits accrued over a period of months to years, not hours. The time to the first adverse event in the placebo arm was two months, suggesting that even those with blood pressures chronically in the range of hypertensive urgency are unlikely to experience hyperacute (ie, within hours) events, even without treatment.  

A more recent study, conducted by Patel et al., examined 58,836 patients seen in outpatient clinics and found to have blood pressures meeting the criteria for hypertensive urgency.⁹ This study included patients whose primary issue was hypertensive urgency and patients in whom the diagnosis was secondary. A total of 426 patients were referred to the hospital and only 100 (0.17%) were subsequently admitted. At seven days, the rates of the primary outcome (a composite of myocardial infarction, stroke, and/or transient ischemic attack) were 0.1% in those sent home and 0.5% in those sent to the hospital. In those patients with a systolic blood pressure &#8805;220 mm Hg, two out of 977 (0.2%) of those sent home and zero out of 81 of those sent to the hospital experienced the primary outcome. These data reinforce the message that, in patients with hypertensive urgency, rates of adverse events at seven days are low, even with extreme blood pressure elevation.  

The human body has adapted to withstand wide variations in blood pressure.¹⁰ For example, through arteriolar constriction and reflex vasodilation, cerebral autoregulation maintains a constant cerebral blood flow within a wide range of perfusion pressures, ensuring that the brain is protected from higher mean arterial pressures.¹¹ While this process is protective, over time the autoregulatory system becomes impaired, especially in patients with cerebrovascular disease. This places patients at risk for cerebral and/or cardiac ischemia with even slight drops in perfusion pressure.^12,13 Indeed, in assessing treatment-related adverse events in a series of patients treated with intravenous nicardipine or nitroprusside for hypertensive emergency, Brooks and colleagues reported that 57% (27 of 47) of patients had overly large reductions in blood pressure (>25% reduction in mean arterial pressure) within the first 30 minutes of treatment.¹⁴ Two patients had acute ischemic events attributed to treatment with antihypertensive medications. Myocardial infarction and stroke have both been reported,¹² and medication classes such as calcium channel blockers (sublingual nifedipine in particular), beta-blockers (eg, labetolol), angiotensin-converting-enzyme inhibitors (eg, captopril), and clonidine have all been implicated in treatment-related adverse events.^12,15-17 Another potential issue derives from the observation that blood pressures obtained in the hospital setting are often inaccurate, owing to inappropriate patient preparation, faulty equipment, and inadequate training of staff obtaining the measurement.¹⁸

National guidelines support a cautious approach to the treatment of hypertensive urgency. The seventh Report of the Joint National Committee on Detection, Evaluation, and Treatment of Hypertension, published in 2003, noted that "patients with markedly elevated BP but without acute target-organ damage usually do not require hospitalization, but they should receive immediate combination oral antihypertensive therapy" and that "there is no evidence to suggest that failure to aggressively lower BP in the [emergency department] is associated with any increased short-term risk to the patient who presents with severe hypertension." JNC 7 also laments contemporary terminology: "Unfortunately, the term 'urgency' has led to overly aggressive management of many patients with severe, uncomplicated hypertension. Aggressive dosing with intravenous drugs or even oral agents, to rapidly lower BP is not without risk."¹⁹ The most recent JNC guideline does not comment on hypertensive urgency,²⁰ and the 2017 American College of Cardiology/American Heart Association Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults argues that, "¬there is no indication for referral to the emergency department, immediate reduction in BP in the emergency department, or hospitalization for [patients with hypertensive urgency]."²¹

After it is confirmed that a patient has no end-organ damage (ie, the patient has hypertensive urgency, not emergency), treatable causes of hypertension should be assessed. In hospitalized patients, these include missed or held doses of outpatient medications, pain, nausea, alcohol and/or benzodiazepine withdrawal, delirium, and obstructive sleep apnea.²² If no remediable cause is identified, patients should be allowed to rest for at least 30 minutes without the administration of additional antihypertensive medications, after which time the blood pressure should be measured using the correct technique.2 Clinical trials have shown that rest is effective at lowering blood pressure in patients with hypertensive urgency.^23,24 One study initially treated 549 emergency department patients with a 30-minute rest period, after which time 32% of patients had responded (defined as a SBP <180 mm Hg and DBP <110 mm Hg, with at least a 20 mm Hg reduction in baseline SBP and/or a 10 mm Hg reduction in DBP).²³ Another study randomized 138 patients with hypertensive urgency to either rest or active treatment with telmisartan. Blood pressures were checked every 30 minutes for four hours. The primary endpoint (reduction of MAP of 10%-35%) was similar in both groups (68.5% in the rest group and 69.1% in the telmisartan group).²⁴ Even if rest is ineffective, the risk-benefit ratio of acutely lowering blood pressure will typically favor withholding acute treatment in asymptomatic patients. If blood pressure remains consistently elevated, augmentation of the home regimen (eg, increasing the dose of their next scheduled antihypertensive) of oral medications may be warranted. Though not all agree with management of antihypertensives in hospitalized patients,²⁵ acute hospitalizations afford an opportunity to modify and observe chronic hypertension.²⁶

• Ensure that patients do not have symptoms and/or signs of end-organ damage. This can be done with a brief review of systems and a physical examination. In select cases, an electrocardiogram and a chest x-ray may be warranted.
• Search for common causes of treatable hypertension in hospitalized patients; these include pain, nausea, withdrawal syndromes, and holding of usual antihypertensive medications.
• In those patients without symptoms and/or signs of end-organ damage, allow rest, followed by reassessment.
• Do not administer intravenous or immediate-acting oral antihypertensive medications to acutely lower blood pressure. Instead, address the issues raised in Recommendation #2 and consider modifying the chronic oral antihypertensive regimen in patients who are uncontrolled as outpatients or who are not treated as outpatients. Coordinate early postdischarge follow-up for repeat blood pressure evaluation and continued modification of a patient's chronic antihypertensive regimen.

Although patients with hypertensive urgency are often treated with medications to acutely lower their blood pressure, there is no evidence to support this practice, and a strong pathophysiologic basis suggests that harm may result. The patient in the case described above should be allowed to rest for at least 30 minutes, with reevaluation of his blood pressure. If it remains elevated and no treatable secondary causes are found, the treating hospitalist should consider altering his chronic antihypertensive regimen to promote long-term blood pressure control.

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

Disclosures

The authors have no conflicts of interest.
 

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

A 67-year-old man is hospitalized with community-acquired pneumonia. He has a history of hypertension and is prescribed two antihypertensive medications (amlodipine and chlorthalidone) as an outpatient. On the evening of hospital day two, he is found to have a blood pressure of 192/95 on a scheduled vital signs check. He reports no symptoms other than cough, which is not new or worsening. The covering hospitalist reviews the documented blood pressures since admission and notes that many have been elevated despite continuation of his home regimen. The patient's nurse inquires about treating the patient with additional "as-needed" antihypertensive medications.  

Hypertensive crises are common in hospitalized patients, with approximately one in seven patients experiencing an episode of hypertensive emergency and/or hypertensive urgency.¹ Hypertensive emergency is typically defined as (1) a systolic blood pressure &#8805;180 mm Hg and/or a diastolic blood pressure &#8805;120 mm Hg with (2) evidence of new or worsening end-organ damage. The organs most commonly affected by severe hypertension are the brain (headache, confusion, stroke), heart (chest pain, myocardial infarction, pulmonary edema), large blood vessels (aortic dissection), and kidneys (acute hypertensive nephrosclerosis).² With hypertensive urgency, patients experience similarly elevated blood pressure but have no symptoms or signs suggesting acute end-organ damage. Acute treatment with intravenous (IV) or immediate-acting oral medications is common; a single-center study showed that 7.4% of hospitalized patients had an order for "as needed" IV hydralazine or labetalol, with 60.3% receiving at least one dose.³ Among internal medicine and family medicine trainees in one survey, nearly half reported that they would use IV medications in a scenario where an inpatient had an asymptomatic blood pressure above 180 mm Hg.⁴

Treating patients with hypertensive urgency is based on an assumption: If one does not treat immediately, something bad (ie, end-organ damage) will occur over the next few hours. Data from the 1930s showed that patients with untreated hypertensive emergency had a one-year mortality rate >79% and a median survival of 10.4 months.⁵ More recent studies suggest that the in-hospital and one-year mortality for those with hypertensive emergency are 13% and 39%, respectively.⁶ These data demonstrate that patients with hypertensive emergency are at risk in both the short- and long-term.
Patients with hypertensive urgency are also at increased risk for long-term morbidity and mortality. The one-year mortality for those experiencing an episode of hypertensive urgency is approximately 9%.6 Given the concerns about poor outcomes, it remains a common practice in many facilities to acutely lower the blood pressure in patients with hypertensive urgency. This is highlighted by recommendations of a commonly used point-of-care medical resource, which suggests that "potential legal ramifications partially motivate lowering the blood pressure over several hours."⁷

Concerns regarding overtreatment of hypertensive urgency relate to overestimated rates of hypertensive complications, the pathophysiology of hypertension itself, and the potential for adverse events related to treatment. Given that there are few trials examining hospitalized patients with hypertensive urgency, much of the data supporting a conservative approach are drawn from studies of outpatients or emergency department patients. In addition, there is little data suggesting that outcomes are different for patients presenting with a chief complaint of hypertensive urgency and those presenting with an alternate diagnosis but who are found to have blood pressures that meet the threshold for diagnosis of hypertensive urgency.

The landmark 1967 Veterans Affairs Cooperative Trial demonstrated the long-term benefits of treating patients with chronic hypertensive urgency.⁸ Importantly though, benefits accrued over a period of months to years, not hours. The time to the first adverse event in the placebo arm was two months, suggesting that even those with blood pressures chronically in the range of hypertensive urgency are unlikely to experience hyperacute (ie, within hours) events, even without treatment.  

A more recent study, conducted by Patel et al., examined 58,836 patients seen in outpatient clinics and found to have blood pressures meeting the criteria for hypertensive urgency.⁹ This study included patients whose primary issue was hypertensive urgency and patients in whom the diagnosis was secondary. A total of 426 patients were referred to the hospital and only 100 (0.17%) were subsequently admitted. At seven days, the rates of the primary outcome (a composite of myocardial infarction, stroke, and/or transient ischemic attack) were 0.1% in those sent home and 0.5% in those sent to the hospital. In those patients with a systolic blood pressure &#8805;220 mm Hg, two out of 977 (0.2%) of those sent home and zero out of 81 of those sent to the hospital experienced the primary outcome. These data reinforce the message that, in patients with hypertensive urgency, rates of adverse events at seven days are low, even with extreme blood pressure elevation.  

The human body has adapted to withstand wide variations in blood pressure.¹⁰ For example, through arteriolar constriction and reflex vasodilation, cerebral autoregulation maintains a constant cerebral blood flow within a wide range of perfusion pressures, ensuring that the brain is protected from higher mean arterial pressures.¹¹ While this process is protective, over time the autoregulatory system becomes impaired, especially in patients with cerebrovascular disease. This places patients at risk for cerebral and/or cardiac ischemia with even slight drops in perfusion pressure.^12,13 Indeed, in assessing treatment-related adverse events in a series of patients treated with intravenous nicardipine or nitroprusside for hypertensive emergency, Brooks and colleagues reported that 57% (27 of 47) of patients had overly large reductions in blood pressure (>25% reduction in mean arterial pressure) within the first 30 minutes of treatment.¹⁴ Two patients had acute ischemic events attributed to treatment with antihypertensive medications. Myocardial infarction and stroke have both been reported,¹² and medication classes such as calcium channel blockers (sublingual nifedipine in particular), beta-blockers (eg, labetolol), angiotensin-converting-enzyme inhibitors (eg, captopril), and clonidine have all been implicated in treatment-related adverse events.^12,15-17 Another potential issue derives from the observation that blood pressures obtained in the hospital setting are often inaccurate, owing to inappropriate patient preparation, faulty equipment, and inadequate training of staff obtaining the measurement.¹⁸

National guidelines support a cautious approach to the treatment of hypertensive urgency. The seventh Report of the Joint National Committee on Detection, Evaluation, and Treatment of Hypertension, published in 2003, noted that "patients with markedly elevated BP but without acute target-organ damage usually do not require hospitalization, but they should receive immediate combination oral antihypertensive therapy" and that "there is no evidence to suggest that failure to aggressively lower BP in the [emergency department] is associated with any increased short-term risk to the patient who presents with severe hypertension." JNC 7 also laments contemporary terminology: "Unfortunately, the term 'urgency' has led to overly aggressive management of many patients with severe, uncomplicated hypertension. Aggressive dosing with intravenous drugs or even oral agents, to rapidly lower BP is not without risk."¹⁹ The most recent JNC guideline does not comment on hypertensive urgency,²⁰ and the 2017 American College of Cardiology/American Heart Association Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults argues that, "¬there is no indication for referral to the emergency department, immediate reduction in BP in the emergency department, or hospitalization for [patients with hypertensive urgency]."²¹

After it is confirmed that a patient has no end-organ damage (ie, the patient has hypertensive urgency, not emergency), treatable causes of hypertension should be assessed. In hospitalized patients, these include missed or held doses of outpatient medications, pain, nausea, alcohol and/or benzodiazepine withdrawal, delirium, and obstructive sleep apnea.²² If no remediable cause is identified, patients should be allowed to rest for at least 30 minutes without the administration of additional antihypertensive medications, after which time the blood pressure should be measured using the correct technique.2 Clinical trials have shown that rest is effective at lowering blood pressure in patients with hypertensive urgency.^23,24 One study initially treated 549 emergency department patients with a 30-minute rest period, after which time 32% of patients had responded (defined as a SBP <180 mm Hg and DBP <110 mm Hg, with at least a 20 mm Hg reduction in baseline SBP and/or a 10 mm Hg reduction in DBP).²³ Another study randomized 138 patients with hypertensive urgency to either rest or active treatment with telmisartan. Blood pressures were checked every 30 minutes for four hours. The primary endpoint (reduction of MAP of 10%-35%) was similar in both groups (68.5% in the rest group and 69.1% in the telmisartan group).²⁴ Even if rest is ineffective, the risk-benefit ratio of acutely lowering blood pressure will typically favor withholding acute treatment in asymptomatic patients. If blood pressure remains consistently elevated, augmentation of the home regimen (eg, increasing the dose of their next scheduled antihypertensive) of oral medications may be warranted. Though not all agree with management of antihypertensives in hospitalized patients,²⁵ acute hospitalizations afford an opportunity to modify and observe chronic hypertension.²⁶

• Ensure that patients do not have symptoms and/or signs of end-organ damage. This can be done with a brief review of systems and a physical examination. In select cases, an electrocardiogram and a chest x-ray may be warranted.
• Search for common causes of treatable hypertension in hospitalized patients; these include pain, nausea, withdrawal syndromes, and holding of usual antihypertensive medications.
• In those patients without symptoms and/or signs of end-organ damage, allow rest, followed by reassessment.
• Do not administer intravenous or immediate-acting oral antihypertensive medications to acutely lower blood pressure. Instead, address the issues raised in Recommendation #2 and consider modifying the chronic oral antihypertensive regimen in patients who are uncontrolled as outpatients or who are not treated as outpatients. Coordinate early postdischarge follow-up for repeat blood pressure evaluation and continued modification of a patient's chronic antihypertensive regimen.

Although patients with hypertensive urgency are often treated with medications to acutely lower their blood pressure, there is no evidence to support this practice, and a strong pathophysiologic basis suggests that harm may result. The patient in the case described above should be allowed to rest for at least 30 minutes, with reevaluation of his blood pressure. If it remains elevated and no treatable secondary causes are found, the treating hospitalist should consider altering his chronic antihypertensive regimen to promote long-term blood pressure control.

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

Disclosures

The authors have no conflicts of interest.
 

A 44-year-old previously healthy semiprofessional male athlete presented with five days of nausea, vomiting, and abdominal pain. He had also experienced several months of decreased energy and new episodes of constipation three weeks prior to presentation.

At this point, we do not have sufficient information to completely determine the cause of his abdominal symptoms. Common causes of abdominal pain and vomiting in adults of his age group include peptic ulcer disease, pancreatic or hepatobiliary track disorders, small or large bowel processes, appendicitis, or even renal pathology. Further characterization may be possible by describing the location and quality of pain and factors that might relieve or exacerbate his pain. Despite the ambiguity, multiple clues might allow us to narrow the broad differential diagnosis of abdominal pain. In a previously healthy, vigorous, middle-aged man with subacute abdominal pain associated with constipation, the differential diagnosis should include disease states that may cause a bowel obstruction; these states include inflammatory bowel disease (IBD), gastrointestinal malignancy, or peptic ulcer disease. Mechanical obstruction due to volvulus or intussusception would be less likely in his age group. Given his history of several months of fatigue and several weeks of constipation, he should be evaluated for metabolic causes of abdominal pain and constipation, such as hypothyroidism or hypercalcemia. In addition to basic laboratory and imaging studies, obtaining additional history regarding prior abdominal surgeries, medication use, alcohol intake, and family and travel history will be the key in directing the evaluation.

Six months prior to admission, the patient began to feel more fatigue and exercise intolerance, reduced sweating, increased cold intolerance, and increased presyncopal episodes. He was diagnosed with hypothyroidism (TSH 6.69 μIU/mL; free T4 not done) and initiated on levothyroxine. One month prior to presentation, he developed constipation, loss of taste, reduced appetite, and weight loss of 30 pounds. He developed blurry vision and photophobia. He also complained of erectile dysfunction, urinary hesitancy and straining, which were diagnosed as benign prostatic hypertrophy.

Given the addition of numerous historical features in a previously healthy man, it is important to strive for a parsimonious diagnosis to unify his seemingly disparate features. His fatigue, constipation, and cold intolerance are consistent with his diagnosis of hypothyroidism but are nonspecific. Whether the degree of hypothyroidism caused his symptoms or signs is doubtful. The constellation of symptoms and signs are more likely to be representative of a nonthyroidal illness. His abdominal pain, unexplained weight loss, and presyncopal episodes should raise consideration of adrenal insufficiency. The combination of hypothyroidism and adrenal insufficiency suggest the possibility of an autoimmune polyendocrine syndrome or other pituitary pathology. In this case, history of headache, dysgeusia, and visual disturbances might support the diagnosis of pituitary adenoma. A cosyntropin stimulation test could establish the diagnosis of adrenal insufficiency. A low ACTH level would establish a diagnosis of pituitary or hypothalamic hypofunction. If pituitary hypofunction is documented, then a brain MRI would be needed to confirm the diagnosis of pituitary adenoma.

His newly reported erectile dysfunction suggests the possibility of a psychiatric, neurologic, hormonal, or vascular process and should be explored further. Sexual dysfunction is also associated with adrenal insufficiency and hypopituitarism. However, the presence of suspected prostatic hypertrophy in a male competitive athlete in his forties also raises the question of exogenous androgen use.

His past medical history was notable for a two-year history of alopecia totalis, seasonal allergies, asthma, and a repaired congenital aortic web with known aortic insufficiency. He was married with two children, worked an office job, and had no history of injection drug use, blood transfusions, or multiple sexual partners. His family history was notable for hypothyroidism and asthma in several family members in addition to Crohn disease, celiac disease, diabetes, cardiovascular disease, and cancers of the breast and lung.

His past medical, surgical, and family history supports a diagnosis of autoimmune disease.  Although there is a personal and family history of atopic disorders, including allergic rhinitis and asthma, no association is found between atopy and autoimmunity. His family history of hypothyroidism, Crohn disease, and diabetes suggests a familial autoimmune genetic predisposition. His history of alopecia totalis in the setting of hypothyroidism and possible autoimmune adrenal insufficiency or autoimmune hypophysitis raises suspicion for the previously suggested diagnosis of polyglandular autoimmune syndrome, also known as autoimmune polyendocrine syndrome. Type I polyglandular autoimmune syndrome is associated with hypoparathyroidism and mucocutaneous candidiasis. In the absence of these symptoms, the patient more likely has type II polyglandular autoimmune syndrome. Type II syndrome is more prevalent and can occur in the setting of other nonendocrine autoimmune disorders, such as vitiligo, myasthenia gravis, or rheumatoid arthritis. Adrenal insufficiency can be the initial and most prominent manifestation of type II syndrome.

On physical exam, he was afebrile, with a heart rate of 68 beats per minute, respiratory rate of 16 breaths per minute, and normal oxygen saturation. His supine blood pressure and heart rate were 116/72 mm Hg and 66 beats per minute, respectively, and his standing blood pressure and heart rates were 80/48 mm Hg and 68 beats per minute respectively. He was thin, had diffuse scalp and body alopecia, and was ill-appearing with dry skin and dry mucous membranes. No evidence of Osler nodes, Janeway lesions, or splinter hemorrhages were found on cutaneous examination. No Roth spots or conjunctival hemorrhages were noted on ophthalmologic examination. He had both a 3/6 crescendo–decrescendo systolic murmur best heard at the right clavicle and radiated to the carotids and a 3/6 early diastolic decrescendo murmur best heard at the left sternal border. His abdomen was slightly protuberant, with reduced bowel sounds, hyperresonant to tympanitic on percussion, and a diffusely, moderately tender without peritoneal signs. Neurologic examination revealed 8 mm pupils with minimal response to light and accommodation. The remaining portions of his cranial nerve and complete neurologic examination were normal.

The presence of postural hypotension supports the previous suspicion of adrenal insufficiency, and the possibility of a pituitary or hypothalamic process remains. However, his dilated and minimally responsive pupils and potentially adynamic bowel are inconsistent with these diagnoses. Mydriasis and adynamic bowel in combination with orthostatic hypotension, dysgeusia, urinary retention, and erectile dysfunction are strongly suggestive of an autonomic process. Endocarditis is worth considering given his multisystem involvement, subacute decline, and known valve pathology. The absence of fever or stigmata of endocarditis make it difficult to explain his clinical syndrome. An echocardiogram would be reasonable for further assessment. At this point, it is prudent to explore his adrenal and pituitary function; if unrevealing, embark on an evaluation of his autonomic dysfunction.

Initial laboratory investigations were notable for mild normocytic anemia and hypoalbuminemia. His cosyntropin stimulation test was normal at 60 minutes. An abdominal CT scan demonstrated marked dilation in the small bowel loops (6 cm in caliber) with associated small bowel wall thickening and hyperemia. The echocardiogram was unrevealing and only confirmed the ongoing, progression of his known valve pathology without evidence of vegetation.

The above testing rules out primary adrenal insufficiency, but an appropriate response to the cosyntropin stimulation test does not rule out secondary, or pituitary, adrenal insufficiency. The echocardiogram and lack of other features make infective endocarditis unlikely. Thus, as mentioned, it is important now to commence a complete work-up of his probable dysautonomia to explain the majority of his features. Additionally, his hypothyroidism (if more than sick euthyroid syndrome), family history of autoimmune processes, and alopecia totalis all suggest the possibility of an immune-related syndrome. His CT scan revealed some thickened hyperemic bowel, which could suggest an IBD, such as Crohn disease; however, the absence of other signs, such as fever, diarrhea, or bloody stools, argues against this diagnosis. A syndrome that could unify his presentation is autoimmune autonomic ganglionopathy (AAG), a rare genetic autonomic system disorder that presents with pandysautonomia. The spectrum of autoimmunity was considered early in this case, but the differential diagnosis included more common conditions, such as adrenal insufficiency. Similarly, IBD remains a consideration. The serologic studies for IBD can be useful but they lack definitive diagnostic accuracy. Given that treatment for AAG differs from that for IBD, additional information will help guide the therapeutic approach. Anti-α3gnAChR antibodies, which are associated with AAG, should be checked.

His history of presyncope, anhidrosis, urinary retention, and ileus raised suspicion for pandysautonomia, as characterized by signs of sympathetic and parasympathetic dysfunction. The suspicion for pandysautonomia was confirmed via specialized autonomic testing, which included reduced heart rate variation on Valsalva and deep breathing maneuvers, orthostatic hypotension consistent autonomic insufficiency on Tilt table testing, and reduced sweat response to acetylcholine application (QSART test). The patient underwent further diagnostic serologic testing to differentiate causes of autonomic failure (Table 1). His personal and family history of autoimmunity led to the working diagnosis of AAG. Ultimate testing revealed high titers of autoantibodies, specifically anti-α3gnAChR (3.29 nmol/L, normal <0.02 nmol/L), directed against the ganglionic nicotinic acetylcholine receptor. This finding strongly supported the diagnosis of AAG.^1,4-7

He was initially treated empirically with intravenous immunoglobulin (IVIG) with minimal improvement. He received additional immunomodulating therapies including methylprednisolone, plasmapheresis, and rituximab but did not tolerate a trial of mycophenolate. Six weeks after therapy initiation, his antibody titers decreased to 0.89 nmol/L with associated clinical improvement. Ultimately, he was discharged from the hospital on day 73 with a feeding tube and supplemental total parenteral nutrition. Four months postdischarge, he had returned to his prediagnosis weight, had eased back into his prior activities, and was off supplemental nutrition. Over a year later, he completed a 10-month prednisone taper and continued to receive monthly IVIG infusions. His symptoms were well controlled, and he reported perspiration with exercise, good oral intake, no photophobia or orthostasis, and was able to return to work.

The clinical approach to dysautonomia is based on different etiologies: (1) those associated with neurodegenerative disorders; (2) those associated with peripheral neuropathies, and (3) isolated autonomic failure.² Thus, clinical history and physical examination can assist greatly in guiding the evaluation of patients. Neurodegenerative disorders (such as Parkinson disease), combined disorders (such as multiple-system atrophy), and acquired or familial processes were considered. Our patient had neither a personal or family history nor physical examination supporting a neurodegenerative disorder. Disorders of the peripheral nerves were considered and can broadly be categorized as chronic sensorimotor neuropathies, sensory ganglionopathies, distal painful neuropathies, and acute or subacute motor polyradiculopathies. During evaluation, no historical, physical examination, or laboratory findings supported diabetes, amyloidosis, heavy metals, Sjögren syndrome, paraneoplastic neuropathy, sodium channel disorders, infectious etiologies, or porphyria (Table 1). Thus, in the absence of supportive evidence for primary neurodegenerative disorders or peripheral neuropathies, his syndrome appeared most compatible with an isolated autonomic failure syndrome. The principal differential for this syndrome is pure autonomic failure versus an immune-mediated autonomic disorder, including paraneoplastic autoimmune neuropathy and AAG. The diagnosis of pure autonomic failure is made after there is no clear unifying syndrome after more than five years of investigation. After exploration, no evidence of malignancy was discovered on body cross sectional imaging, PET scanning, bone marrow biopsy, colonoscopy, or laboratory testing. Thus, positive serologic testing in the absence of an underlying malignancy suggests a diagnosis of AAG.

AAG was first described in 1969 and is a rare, acquired disorder characterized by combined failure of the parasympathetic, sympathetic, and enteric nervous systems. This disorder typically presents in young-to-middle aged patients but has been described in all age groups. It is more commonly seen in patients with coexistent autoimmune diseases and/or a history of familial autoimmunity. The onset of clinical AAG may be subacute (less than three months) or insidious (more than three months). Patients present with signs or symptoms of pandysautonomia, such as severe orthostatic hypotension, syncope, constipation and gastrointestinal dysmotility, urinary retention, fixed and dilated pupils, and dry mouth and eyes (Table 2). Up to 40% of patients with AAG may also have significant cognitive impairment.^3,4 Diagnosis relies on a combination of typical clinical features as discussed above and the exclusion of other diagnostic considerations. Diagnosis of AAG is aided by the presence of autoantibodies to ganglionic nicotinic acetylcholine receptors (gnAChR), particularly antiganglionic acetylcholine receptor α3 (anti-α3gAChR).¹ Anti-gnAChR antibodies are only present in about half of patients with AAG. Antibody titers are highest in subacute AAG (40%-50%)³ compared with chronic AAG (30%-40%) or paraneoplastic AAG (10%-20%).⁵ Anti-gnAChR antibodies are not specific to AAG and have been identified in low levels in up to 20% of patients with thymomas, postural orthostatic tachycardia syndrome, chronic idiopathic anhidrosis, idiopathic gastrointestinal dysmotility, Lambert–Eaton syndrome, and myasthenia gravis without thymoma.^1,5-7 These associations raise the question of shared pathology and perhaps a syndrome overlap. Individuals with seropositive AAG may also have other paraneoplastic antibodies, making it clinically indistinguishable from paraneoplastic autonomic neuropathy.^5,8 Although the autoantibody lacks sensitivity and is imperfectly specific, its presence supports a diagnosis of AAG. Anti-gnAChR antibodies have been shown to be pathological in rabbit and mouse models.⁴ In patients with AAG, higher autoantibody titers correlate with increased disease severity.^1,6,7 A decrease in autoantibody titers correlates with decreased disease severity.⁶ Case report series also described a distinct entity of seronegative AAG.^2,3 Maintaining a high clinical suspicion for AAG even with negative antibodies is important.

• Recognize the following signs and symptoms suggesting a dysautonomic syndrome: orthostasis, syncope, anhidrosis, xerophthalmia, xerostomia, impaired pupillary constriction, blurry vision, photophobia, erectile dysfunction, urinary retention, gastroparesis, constipation, neurogenic bowel obstruction, and dysgeusia.
• Recognize the clinical features, diagnostic approach, and management of autoimmune autonomic ganglionopathy.
• When faced with a complex clinical presentation, early application of the “law of parsimony” may help identify a unifying syndrome.

The authors wish to thank our Blinded Expert, Anthony Montanaro, MD, for his expertise and guidance during this process.

Disclosures

There are no known conflicts of interest.

A 44-year-old previously healthy semiprofessional male athlete presented with five days of nausea, vomiting, and abdominal pain. He had also experienced several months of decreased energy and new episodes of constipation three weeks prior to presentation.

At this point, we do not have sufficient information to completely determine the cause of his abdominal symptoms. Common causes of abdominal pain and vomiting in adults of his age group include peptic ulcer disease, pancreatic or hepatobiliary track disorders, small or large bowel processes, appendicitis, or even renal pathology. Further characterization may be possible by describing the location and quality of pain and factors that might relieve or exacerbate his pain. Despite the ambiguity, multiple clues might allow us to narrow the broad differential diagnosis of abdominal pain. In a previously healthy, vigorous, middle-aged man with subacute abdominal pain associated with constipation, the differential diagnosis should include disease states that may cause a bowel obstruction; these states include inflammatory bowel disease (IBD), gastrointestinal malignancy, or peptic ulcer disease. Mechanical obstruction due to volvulus or intussusception would be less likely in his age group. Given his history of several months of fatigue and several weeks of constipation, he should be evaluated for metabolic causes of abdominal pain and constipation, such as hypothyroidism or hypercalcemia. In addition to basic laboratory and imaging studies, obtaining additional history regarding prior abdominal surgeries, medication use, alcohol intake, and family and travel history will be the key in directing the evaluation.

Six months prior to admission, the patient began to feel more fatigue and exercise intolerance, reduced sweating, increased cold intolerance, and increased presyncopal episodes. He was diagnosed with hypothyroidism (TSH 6.69 μIU/mL; free T4 not done) and initiated on levothyroxine. One month prior to presentation, he developed constipation, loss of taste, reduced appetite, and weight loss of 30 pounds. He developed blurry vision and photophobia. He also complained of erectile dysfunction, urinary hesitancy and straining, which were diagnosed as benign prostatic hypertrophy.

Given the addition of numerous historical features in a previously healthy man, it is important to strive for a parsimonious diagnosis to unify his seemingly disparate features. His fatigue, constipation, and cold intolerance are consistent with his diagnosis of hypothyroidism but are nonspecific. Whether the degree of hypothyroidism caused his symptoms or signs is doubtful. The constellation of symptoms and signs are more likely to be representative of a nonthyroidal illness. His abdominal pain, unexplained weight loss, and presyncopal episodes should raise consideration of adrenal insufficiency. The combination of hypothyroidism and adrenal insufficiency suggest the possibility of an autoimmune polyendocrine syndrome or other pituitary pathology. In this case, history of headache, dysgeusia, and visual disturbances might support the diagnosis of pituitary adenoma. A cosyntropin stimulation test could establish the diagnosis of adrenal insufficiency. A low ACTH level would establish a diagnosis of pituitary or hypothalamic hypofunction. If pituitary hypofunction is documented, then a brain MRI would be needed to confirm the diagnosis of pituitary adenoma.

His newly reported erectile dysfunction suggests the possibility of a psychiatric, neurologic, hormonal, or vascular process and should be explored further. Sexual dysfunction is also associated with adrenal insufficiency and hypopituitarism. However, the presence of suspected prostatic hypertrophy in a male competitive athlete in his forties also raises the question of exogenous androgen use.

His past medical history was notable for a two-year history of alopecia totalis, seasonal allergies, asthma, and a repaired congenital aortic web with known aortic insufficiency. He was married with two children, worked an office job, and had no history of injection drug use, blood transfusions, or multiple sexual partners. His family history was notable for hypothyroidism and asthma in several family members in addition to Crohn disease, celiac disease, diabetes, cardiovascular disease, and cancers of the breast and lung.

His past medical, surgical, and family history supports a diagnosis of autoimmune disease.  Although there is a personal and family history of atopic disorders, including allergic rhinitis and asthma, no association is found between atopy and autoimmunity. His family history of hypothyroidism, Crohn disease, and diabetes suggests a familial autoimmune genetic predisposition. His history of alopecia totalis in the setting of hypothyroidism and possible autoimmune adrenal insufficiency or autoimmune hypophysitis raises suspicion for the previously suggested diagnosis of polyglandular autoimmune syndrome, also known as autoimmune polyendocrine syndrome. Type I polyglandular autoimmune syndrome is associated with hypoparathyroidism and mucocutaneous candidiasis. In the absence of these symptoms, the patient more likely has type II polyglandular autoimmune syndrome. Type II syndrome is more prevalent and can occur in the setting of other nonendocrine autoimmune disorders, such as vitiligo, myasthenia gravis, or rheumatoid arthritis. Adrenal insufficiency can be the initial and most prominent manifestation of type II syndrome.

On physical exam, he was afebrile, with a heart rate of 68 beats per minute, respiratory rate of 16 breaths per minute, and normal oxygen saturation. His supine blood pressure and heart rate were 116/72 mm Hg and 66 beats per minute, respectively, and his standing blood pressure and heart rates were 80/48 mm Hg and 68 beats per minute respectively. He was thin, had diffuse scalp and body alopecia, and was ill-appearing with dry skin and dry mucous membranes. No evidence of Osler nodes, Janeway lesions, or splinter hemorrhages were found on cutaneous examination. No Roth spots or conjunctival hemorrhages were noted on ophthalmologic examination. He had both a 3/6 crescendo–decrescendo systolic murmur best heard at the right clavicle and radiated to the carotids and a 3/6 early diastolic decrescendo murmur best heard at the left sternal border. His abdomen was slightly protuberant, with reduced bowel sounds, hyperresonant to tympanitic on percussion, and a diffusely, moderately tender without peritoneal signs. Neurologic examination revealed 8 mm pupils with minimal response to light and accommodation. The remaining portions of his cranial nerve and complete neurologic examination were normal.

The presence of postural hypotension supports the previous suspicion of adrenal insufficiency, and the possibility of a pituitary or hypothalamic process remains. However, his dilated and minimally responsive pupils and potentially adynamic bowel are inconsistent with these diagnoses. Mydriasis and adynamic bowel in combination with orthostatic hypotension, dysgeusia, urinary retention, and erectile dysfunction are strongly suggestive of an autonomic process. Endocarditis is worth considering given his multisystem involvement, subacute decline, and known valve pathology. The absence of fever or stigmata of endocarditis make it difficult to explain his clinical syndrome. An echocardiogram would be reasonable for further assessment. At this point, it is prudent to explore his adrenal and pituitary function; if unrevealing, embark on an evaluation of his autonomic dysfunction.

Initial laboratory investigations were notable for mild normocytic anemia and hypoalbuminemia. His cosyntropin stimulation test was normal at 60 minutes. An abdominal CT scan demonstrated marked dilation in the small bowel loops (6 cm in caliber) with associated small bowel wall thickening and hyperemia. The echocardiogram was unrevealing and only confirmed the ongoing, progression of his known valve pathology without evidence of vegetation.

The above testing rules out primary adrenal insufficiency, but an appropriate response to the cosyntropin stimulation test does not rule out secondary, or pituitary, adrenal insufficiency. The echocardiogram and lack of other features make infective endocarditis unlikely. Thus, as mentioned, it is important now to commence a complete work-up of his probable dysautonomia to explain the majority of his features. Additionally, his hypothyroidism (if more than sick euthyroid syndrome), family history of autoimmune processes, and alopecia totalis all suggest the possibility of an immune-related syndrome. His CT scan revealed some thickened hyperemic bowel, which could suggest an IBD, such as Crohn disease; however, the absence of other signs, such as fever, diarrhea, or bloody stools, argues against this diagnosis. A syndrome that could unify his presentation is autoimmune autonomic ganglionopathy (AAG), a rare genetic autonomic system disorder that presents with pandysautonomia. The spectrum of autoimmunity was considered early in this case, but the differential diagnosis included more common conditions, such as adrenal insufficiency. Similarly, IBD remains a consideration. The serologic studies for IBD can be useful but they lack definitive diagnostic accuracy. Given that treatment for AAG differs from that for IBD, additional information will help guide the therapeutic approach. Anti-α3gnAChR antibodies, which are associated with AAG, should be checked.

His history of presyncope, anhidrosis, urinary retention, and ileus raised suspicion for pandysautonomia, as characterized by signs of sympathetic and parasympathetic dysfunction. The suspicion for pandysautonomia was confirmed via specialized autonomic testing, which included reduced heart rate variation on Valsalva and deep breathing maneuvers, orthostatic hypotension consistent autonomic insufficiency on Tilt table testing, and reduced sweat response to acetylcholine application (QSART test). The patient underwent further diagnostic serologic testing to differentiate causes of autonomic failure (Table 1). His personal and family history of autoimmunity led to the working diagnosis of AAG. Ultimate testing revealed high titers of autoantibodies, specifically anti-α3gnAChR (3.29 nmol/L, normal <0.02 nmol/L), directed against the ganglionic nicotinic acetylcholine receptor. This finding strongly supported the diagnosis of AAG.^1,4-7

He was initially treated empirically with intravenous immunoglobulin (IVIG) with minimal improvement. He received additional immunomodulating therapies including methylprednisolone, plasmapheresis, and rituximab but did not tolerate a trial of mycophenolate. Six weeks after therapy initiation, his antibody titers decreased to 0.89 nmol/L with associated clinical improvement. Ultimately, he was discharged from the hospital on day 73 with a feeding tube and supplemental total parenteral nutrition. Four months postdischarge, he had returned to his prediagnosis weight, had eased back into his prior activities, and was off supplemental nutrition. Over a year later, he completed a 10-month prednisone taper and continued to receive monthly IVIG infusions. His symptoms were well controlled, and he reported perspiration with exercise, good oral intake, no photophobia or orthostasis, and was able to return to work.

The clinical approach to dysautonomia is based on different etiologies: (1) those associated with neurodegenerative disorders; (2) those associated with peripheral neuropathies, and (3) isolated autonomic failure.² Thus, clinical history and physical examination can assist greatly in guiding the evaluation of patients. Neurodegenerative disorders (such as Parkinson disease), combined disorders (such as multiple-system atrophy), and acquired or familial processes were considered. Our patient had neither a personal or family history nor physical examination supporting a neurodegenerative disorder. Disorders of the peripheral nerves were considered and can broadly be categorized as chronic sensorimotor neuropathies, sensory ganglionopathies, distal painful neuropathies, and acute or subacute motor polyradiculopathies. During evaluation, no historical, physical examination, or laboratory findings supported diabetes, amyloidosis, heavy metals, Sjögren syndrome, paraneoplastic neuropathy, sodium channel disorders, infectious etiologies, or porphyria (Table 1). Thus, in the absence of supportive evidence for primary neurodegenerative disorders or peripheral neuropathies, his syndrome appeared most compatible with an isolated autonomic failure syndrome. The principal differential for this syndrome is pure autonomic failure versus an immune-mediated autonomic disorder, including paraneoplastic autoimmune neuropathy and AAG. The diagnosis of pure autonomic failure is made after there is no clear unifying syndrome after more than five years of investigation. After exploration, no evidence of malignancy was discovered on body cross sectional imaging, PET scanning, bone marrow biopsy, colonoscopy, or laboratory testing. Thus, positive serologic testing in the absence of an underlying malignancy suggests a diagnosis of AAG.

AAG was first described in 1969 and is a rare, acquired disorder characterized by combined failure of the parasympathetic, sympathetic, and enteric nervous systems. This disorder typically presents in young-to-middle aged patients but has been described in all age groups. It is more commonly seen in patients with coexistent autoimmune diseases and/or a history of familial autoimmunity. The onset of clinical AAG may be subacute (less than three months) or insidious (more than three months). Patients present with signs or symptoms of pandysautonomia, such as severe orthostatic hypotension, syncope, constipation and gastrointestinal dysmotility, urinary retention, fixed and dilated pupils, and dry mouth and eyes (Table 2). Up to 40% of patients with AAG may also have significant cognitive impairment.^3,4 Diagnosis relies on a combination of typical clinical features as discussed above and the exclusion of other diagnostic considerations. Diagnosis of AAG is aided by the presence of autoantibodies to ganglionic nicotinic acetylcholine receptors (gnAChR), particularly antiganglionic acetylcholine receptor α3 (anti-α3gAChR).¹ Anti-gnAChR antibodies are only present in about half of patients with AAG. Antibody titers are highest in subacute AAG (40%-50%)³ compared with chronic AAG (30%-40%) or paraneoplastic AAG (10%-20%).⁵ Anti-gnAChR antibodies are not specific to AAG and have been identified in low levels in up to 20% of patients with thymomas, postural orthostatic tachycardia syndrome, chronic idiopathic anhidrosis, idiopathic gastrointestinal dysmotility, Lambert–Eaton syndrome, and myasthenia gravis without thymoma.^1,5-7 These associations raise the question of shared pathology and perhaps a syndrome overlap. Individuals with seropositive AAG may also have other paraneoplastic antibodies, making it clinically indistinguishable from paraneoplastic autonomic neuropathy.^5,8 Although the autoantibody lacks sensitivity and is imperfectly specific, its presence supports a diagnosis of AAG. Anti-gnAChR antibodies have been shown to be pathological in rabbit and mouse models.⁴ In patients with AAG, higher autoantibody titers correlate with increased disease severity.^1,6,7 A decrease in autoantibody titers correlates with decreased disease severity.⁶ Case report series also described a distinct entity of seronegative AAG.^2,3 Maintaining a high clinical suspicion for AAG even with negative antibodies is important.

• Recognize the following signs and symptoms suggesting a dysautonomic syndrome: orthostasis, syncope, anhidrosis, xerophthalmia, xerostomia, impaired pupillary constriction, blurry vision, photophobia, erectile dysfunction, urinary retention, gastroparesis, constipation, neurogenic bowel obstruction, and dysgeusia.
• Recognize the clinical features, diagnostic approach, and management of autoimmune autonomic ganglionopathy.
• When faced with a complex clinical presentation, early application of the “law of parsimony” may help identify a unifying syndrome.

The authors wish to thank our Blinded Expert, Anthony Montanaro, MD, for his expertise and guidance during this process.

Disclosures

There are no known conflicts of interest.

A 44-year-old previously healthy semiprofessional male athlete presented with five days of nausea, vomiting, and abdominal pain. He had also experienced several months of decreased energy and new episodes of constipation three weeks prior to presentation.

At this point, we do not have sufficient information to completely determine the cause of his abdominal symptoms. Common causes of abdominal pain and vomiting in adults of his age group include peptic ulcer disease, pancreatic or hepatobiliary track disorders, small or large bowel processes, appendicitis, or even renal pathology. Further characterization may be possible by describing the location and quality of pain and factors that might relieve or exacerbate his pain. Despite the ambiguity, multiple clues might allow us to narrow the broad differential diagnosis of abdominal pain. In a previously healthy, vigorous, middle-aged man with subacute abdominal pain associated with constipation, the differential diagnosis should include disease states that may cause a bowel obstruction; these states include inflammatory bowel disease (IBD), gastrointestinal malignancy, or peptic ulcer disease. Mechanical obstruction due to volvulus or intussusception would be less likely in his age group. Given his history of several months of fatigue and several weeks of constipation, he should be evaluated for metabolic causes of abdominal pain and constipation, such as hypothyroidism or hypercalcemia. In addition to basic laboratory and imaging studies, obtaining additional history regarding prior abdominal surgeries, medication use, alcohol intake, and family and travel history will be the key in directing the evaluation.

Six months prior to admission, the patient began to feel more fatigue and exercise intolerance, reduced sweating, increased cold intolerance, and increased presyncopal episodes. He was diagnosed with hypothyroidism (TSH 6.69 μIU/mL; free T4 not done) and initiated on levothyroxine. One month prior to presentation, he developed constipation, loss of taste, reduced appetite, and weight loss of 30 pounds. He developed blurry vision and photophobia. He also complained of erectile dysfunction, urinary hesitancy and straining, which were diagnosed as benign prostatic hypertrophy.

Given the addition of numerous historical features in a previously healthy man, it is important to strive for a parsimonious diagnosis to unify his seemingly disparate features. His fatigue, constipation, and cold intolerance are consistent with his diagnosis of hypothyroidism but are nonspecific. Whether the degree of hypothyroidism caused his symptoms or signs is doubtful. The constellation of symptoms and signs are more likely to be representative of a nonthyroidal illness. His abdominal pain, unexplained weight loss, and presyncopal episodes should raise consideration of adrenal insufficiency. The combination of hypothyroidism and adrenal insufficiency suggest the possibility of an autoimmune polyendocrine syndrome or other pituitary pathology. In this case, history of headache, dysgeusia, and visual disturbances might support the diagnosis of pituitary adenoma. A cosyntropin stimulation test could establish the diagnosis of adrenal insufficiency. A low ACTH level would establish a diagnosis of pituitary or hypothalamic hypofunction. If pituitary hypofunction is documented, then a brain MRI would be needed to confirm the diagnosis of pituitary adenoma.

His newly reported erectile dysfunction suggests the possibility of a psychiatric, neurologic, hormonal, or vascular process and should be explored further. Sexual dysfunction is also associated with adrenal insufficiency and hypopituitarism. However, the presence of suspected prostatic hypertrophy in a male competitive athlete in his forties also raises the question of exogenous androgen use.

His past medical history was notable for a two-year history of alopecia totalis, seasonal allergies, asthma, and a repaired congenital aortic web with known aortic insufficiency. He was married with two children, worked an office job, and had no history of injection drug use, blood transfusions, or multiple sexual partners. His family history was notable for hypothyroidism and asthma in several family members in addition to Crohn disease, celiac disease, diabetes, cardiovascular disease, and cancers of the breast and lung.

His past medical, surgical, and family history supports a diagnosis of autoimmune disease.  Although there is a personal and family history of atopic disorders, including allergic rhinitis and asthma, no association is found between atopy and autoimmunity. His family history of hypothyroidism, Crohn disease, and diabetes suggests a familial autoimmune genetic predisposition. His history of alopecia totalis in the setting of hypothyroidism and possible autoimmune adrenal insufficiency or autoimmune hypophysitis raises suspicion for the previously suggested diagnosis of polyglandular autoimmune syndrome, also known as autoimmune polyendocrine syndrome. Type I polyglandular autoimmune syndrome is associated with hypoparathyroidism and mucocutaneous candidiasis. In the absence of these symptoms, the patient more likely has type II polyglandular autoimmune syndrome. Type II syndrome is more prevalent and can occur in the setting of other nonendocrine autoimmune disorders, such as vitiligo, myasthenia gravis, or rheumatoid arthritis. Adrenal insufficiency can be the initial and most prominent manifestation of type II syndrome.

On physical exam, he was afebrile, with a heart rate of 68 beats per minute, respiratory rate of 16 breaths per minute, and normal oxygen saturation. His supine blood pressure and heart rate were 116/72 mm Hg and 66 beats per minute, respectively, and his standing blood pressure and heart rates were 80/48 mm Hg and 68 beats per minute respectively. He was thin, had diffuse scalp and body alopecia, and was ill-appearing with dry skin and dry mucous membranes. No evidence of Osler nodes, Janeway lesions, or splinter hemorrhages were found on cutaneous examination. No Roth spots or conjunctival hemorrhages were noted on ophthalmologic examination. He had both a 3/6 crescendo–decrescendo systolic murmur best heard at the right clavicle and radiated to the carotids and a 3/6 early diastolic decrescendo murmur best heard at the left sternal border. His abdomen was slightly protuberant, with reduced bowel sounds, hyperresonant to tympanitic on percussion, and a diffusely, moderately tender without peritoneal signs. Neurologic examination revealed 8 mm pupils with minimal response to light and accommodation. The remaining portions of his cranial nerve and complete neurologic examination were normal.

The presence of postural hypotension supports the previous suspicion of adrenal insufficiency, and the possibility of a pituitary or hypothalamic process remains. However, his dilated and minimally responsive pupils and potentially adynamic bowel are inconsistent with these diagnoses. Mydriasis and adynamic bowel in combination with orthostatic hypotension, dysgeusia, urinary retention, and erectile dysfunction are strongly suggestive of an autonomic process. Endocarditis is worth considering given his multisystem involvement, subacute decline, and known valve pathology. The absence of fever or stigmata of endocarditis make it difficult to explain his clinical syndrome. An echocardiogram would be reasonable for further assessment. At this point, it is prudent to explore his adrenal and pituitary function; if unrevealing, embark on an evaluation of his autonomic dysfunction.

Initial laboratory investigations were notable for mild normocytic anemia and hypoalbuminemia. His cosyntropin stimulation test was normal at 60 minutes. An abdominal CT scan demonstrated marked dilation in the small bowel loops (6 cm in caliber) with associated small bowel wall thickening and hyperemia. The echocardiogram was unrevealing and only confirmed the ongoing, progression of his known valve pathology without evidence of vegetation.

The above testing rules out primary adrenal insufficiency, but an appropriate response to the cosyntropin stimulation test does not rule out secondary, or pituitary, adrenal insufficiency. The echocardiogram and lack of other features make infective endocarditis unlikely. Thus, as mentioned, it is important now to commence a complete work-up of his probable dysautonomia to explain the majority of his features. Additionally, his hypothyroidism (if more than sick euthyroid syndrome), family history of autoimmune processes, and alopecia totalis all suggest the possibility of an immune-related syndrome. His CT scan revealed some thickened hyperemic bowel, which could suggest an IBD, such as Crohn disease; however, the absence of other signs, such as fever, diarrhea, or bloody stools, argues against this diagnosis. A syndrome that could unify his presentation is autoimmune autonomic ganglionopathy (AAG), a rare genetic autonomic system disorder that presents with pandysautonomia. The spectrum of autoimmunity was considered early in this case, but the differential diagnosis included more common conditions, such as adrenal insufficiency. Similarly, IBD remains a consideration. The serologic studies for IBD can be useful but they lack definitive diagnostic accuracy. Given that treatment for AAG differs from that for IBD, additional information will help guide the therapeutic approach. Anti-α3gnAChR antibodies, which are associated with AAG, should be checked.

His history of presyncope, anhidrosis, urinary retention, and ileus raised suspicion for pandysautonomia, as characterized by signs of sympathetic and parasympathetic dysfunction. The suspicion for pandysautonomia was confirmed via specialized autonomic testing, which included reduced heart rate variation on Valsalva and deep breathing maneuvers, orthostatic hypotension consistent autonomic insufficiency on Tilt table testing, and reduced sweat response to acetylcholine application (QSART test). The patient underwent further diagnostic serologic testing to differentiate causes of autonomic failure (Table 1). His personal and family history of autoimmunity led to the working diagnosis of AAG. Ultimate testing revealed high titers of autoantibodies, specifically anti-α3gnAChR (3.29 nmol/L, normal <0.02 nmol/L), directed against the ganglionic nicotinic acetylcholine receptor. This finding strongly supported the diagnosis of AAG.^1,4-7

He was initially treated empirically with intravenous immunoglobulin (IVIG) with minimal improvement. He received additional immunomodulating therapies including methylprednisolone, plasmapheresis, and rituximab but did not tolerate a trial of mycophenolate. Six weeks after therapy initiation, his antibody titers decreased to 0.89 nmol/L with associated clinical improvement. Ultimately, he was discharged from the hospital on day 73 with a feeding tube and supplemental total parenteral nutrition. Four months postdischarge, he had returned to his prediagnosis weight, had eased back into his prior activities, and was off supplemental nutrition. Over a year later, he completed a 10-month prednisone taper and continued to receive monthly IVIG infusions. His symptoms were well controlled, and he reported perspiration with exercise, good oral intake, no photophobia or orthostasis, and was able to return to work.

The clinical approach to dysautonomia is based on different etiologies: (1) those associated with neurodegenerative disorders; (2) those associated with peripheral neuropathies, and (3) isolated autonomic failure.² Thus, clinical history and physical examination can assist greatly in guiding the evaluation of patients. Neurodegenerative disorders (such as Parkinson disease), combined disorders (such as multiple-system atrophy), and acquired or familial processes were considered. Our patient had neither a personal or family history nor physical examination supporting a neurodegenerative disorder. Disorders of the peripheral nerves were considered and can broadly be categorized as chronic sensorimotor neuropathies, sensory ganglionopathies, distal painful neuropathies, and acute or subacute motor polyradiculopathies. During evaluation, no historical, physical examination, or laboratory findings supported diabetes, amyloidosis, heavy metals, Sjögren syndrome, paraneoplastic neuropathy, sodium channel disorders, infectious etiologies, or porphyria (Table 1). Thus, in the absence of supportive evidence for primary neurodegenerative disorders or peripheral neuropathies, his syndrome appeared most compatible with an isolated autonomic failure syndrome. The principal differential for this syndrome is pure autonomic failure versus an immune-mediated autonomic disorder, including paraneoplastic autoimmune neuropathy and AAG. The diagnosis of pure autonomic failure is made after there is no clear unifying syndrome after more than five years of investigation. After exploration, no evidence of malignancy was discovered on body cross sectional imaging, PET scanning, bone marrow biopsy, colonoscopy, or laboratory testing. Thus, positive serologic testing in the absence of an underlying malignancy suggests a diagnosis of AAG.

AAG was first described in 1969 and is a rare, acquired disorder characterized by combined failure of the parasympathetic, sympathetic, and enteric nervous systems. This disorder typically presents in young-to-middle aged patients but has been described in all age groups. It is more commonly seen in patients with coexistent autoimmune diseases and/or a history of familial autoimmunity. The onset of clinical AAG may be subacute (less than three months) or insidious (more than three months). Patients present with signs or symptoms of pandysautonomia, such as severe orthostatic hypotension, syncope, constipation and gastrointestinal dysmotility, urinary retention, fixed and dilated pupils, and dry mouth and eyes (Table 2). Up to 40% of patients with AAG may also have significant cognitive impairment.^3,4 Diagnosis relies on a combination of typical clinical features as discussed above and the exclusion of other diagnostic considerations. Diagnosis of AAG is aided by the presence of autoantibodies to ganglionic nicotinic acetylcholine receptors (gnAChR), particularly antiganglionic acetylcholine receptor α3 (anti-α3gAChR).¹ Anti-gnAChR antibodies are only present in about half of patients with AAG. Antibody titers are highest in subacute AAG (40%-50%)³ compared with chronic AAG (30%-40%) or paraneoplastic AAG (10%-20%).⁵ Anti-gnAChR antibodies are not specific to AAG and have been identified in low levels in up to 20% of patients with thymomas, postural orthostatic tachycardia syndrome, chronic idiopathic anhidrosis, idiopathic gastrointestinal dysmotility, Lambert–Eaton syndrome, and myasthenia gravis without thymoma.^1,5-7 These associations raise the question of shared pathology and perhaps a syndrome overlap. Individuals with seropositive AAG may also have other paraneoplastic antibodies, making it clinically indistinguishable from paraneoplastic autonomic neuropathy.^5,8 Although the autoantibody lacks sensitivity and is imperfectly specific, its presence supports a diagnosis of AAG. Anti-gnAChR antibodies have been shown to be pathological in rabbit and mouse models.⁴ In patients with AAG, higher autoantibody titers correlate with increased disease severity.^1,6,7 A decrease in autoantibody titers correlates with decreased disease severity.⁶ Case report series also described a distinct entity of seronegative AAG.^2,3 Maintaining a high clinical suspicion for AAG even with negative antibodies is important.

• Recognize the following signs and symptoms suggesting a dysautonomic syndrome: orthostasis, syncope, anhidrosis, xerophthalmia, xerostomia, impaired pupillary constriction, blurry vision, photophobia, erectile dysfunction, urinary retention, gastroparesis, constipation, neurogenic bowel obstruction, and dysgeusia.
• Recognize the clinical features, diagnostic approach, and management of autoimmune autonomic ganglionopathy.
• When faced with a complex clinical presentation, early application of the “law of parsimony” may help identify a unifying syndrome.

The authors wish to thank our Blinded Expert, Anthony Montanaro, MD, for his expertise and guidance during this process.

Disclosures

There are no known conflicts of interest.

Palliative care is an essential component of inpatient medicine. At its core, it is an interdisciplinary philosophy of care aiming to achieve the best quality of life for patients and families in the physical, psychosocial, and spiritual domains. With the aging population and growing complexity of hospitalized patients, inpatient palliative care needs are only projected to rise. However, a mismatch exists between the number of palliative care–trained physicians and the demand for such physicians. Currently, only 6,600 US physicians are board certified in palliative care – just 37% of the projected need.¹ These workforce shortages have serious implications. In fact, it is estimated that nearly 40% of all hospitalized patients who need palliative care go without it.²

Existing efforts to improve access to palliative care have largely focused on bolstering the palliative care workforce. One tactic particularly relevant to hospitalists centers on frontline physicians providing “primary” palliative care: basic symptom management, patient-centered communication, and goals of care assessment, regardless of the disease state.³ Such physicians constitute the base of today’s palliative care workforce model – a three-tiered pyramid built on clinician availability and skills. In this model, the second tier (“secondary” palliative care) includes physicians supported by a palliative care consultant or referral. The third level (“tertiary” palliative care) encompasses care provided directly by specialized palliative care teams, usually within academic medical centers (Figure).⁴

To better address the current palliative care access problem, we propose a new model: “The Palliative care Redistribution Integrated Service Model (PRISM; Figure 1).” Using the industrial engineering principle of “task shifting,” this approach leverages disciplinary diversity and shifts specific activities from more specialized to less specialized members.⁹ In this way, PRISM integrates hospital-based interdisciplinary teams across all tiers of palliative care delivery.

PRISM sheds a tier-based approach in favor of flexible, skill-based verticals that span all physician and nonphysician providers. By dividing the original pyramid into three domains – physical, psychosocial, and spiritual – providers with various spheres of expertise may serve patients on multiple tiers. For example, a bedside nurse may perform basic psychosocial assessment consistent with his or her training, while physicians may focus on code status or prescribe antiemetics or low-dose opiate monotherapy – skills they have refined during medical school. Analogously, secondary palliative care may be delivered by any provider with more advanced skills in communication or symptom management. In this way, we expand the pool of clinicians available to provide palliative care to include nurses, hospitalists, oncologists, intensivists, social workers, and chaplains and also recognize the diversity of skill sets within and between disciplines. Thus, a hospitalist may clarify the goals of care but may ask a social worker trained in psychosocial assessment for assistance with difficult family dynamics or a chaplain for spiritual needs. Interdisciplinary teamwork and cross-disciplinary communication – hallmarks of palliative care – are encouraged and valued. Furthermore, if providers feel uncomfortable providing a certain type of care, they can ask for assistance from more experienced providers within their discipline or outside of it. In rare cases, the most complex patients may be referred to specialist palliative care teams.

Inherent within PRISM is a recognition that all providers must have a basic palliative care skillset obtained through educational initiatives.⁷ Yet focusing solely on training the workforce as a strategy has and will continue to miss the mark. Rather, structural changes to the means of providing care are also needed. Within hospitals, these changes often rely heavily on hospitalists due to their central position in care delivery. In this way, hospitalists are well primed to be the agents of change in this model.

Since many hospitalized patients have unrecognized and underserved palliative care needs, a formal approach to assessment is needed. Lin et al. proposed criteria for a “sentinel hospitalization,” marking a major illness or transition in high-risk patients necessitating palliative interventions.¹⁰ Similar screening criteria have been validated among hospitalized oncology patients¹¹ and in critical care.¹² While checklists have been shown to help identify hospitalized patients with palliative care needs,¹³ their implementation has been slow, presumably because they are burdensome for busy providers to complete.

Technological automation may be a solution to the checklist conundrum. For example, if palliative care screening criteria could be automatically extracted from electronic health records, scoring systems could trigger hospitalists to consider the goals of care discussions or engage an interdisciplinary care team to fulfill a variety of needs. Frameworks for such scoring systems already exist and are familiar to most hospitalists. For example, admission order sets routinely calculate the Padua or Caprini score to facilitate decision-making for prophylaxis of deep vein thrombosis. An admission order set that screens and prompts decision-making around palliative care needs is thus feasible. One example is a hard stop for entering code status in the admission order set; in turn, this hard stop could also trigger providers to complete a “check-box” palliative care screening checklist. Automatic extraction of certain data from the record – such as age, prior code status, recent hospitalizations, or mobility scores – could auto-populate to facilitate decision-making. In turn, measuring the influence of such tools on access to palliative care, workflow, and capacity will be important, as most tools may not have quality or value intended.¹⁴

It is common for hospitalists to oversee care for 15-20 patients at a time. Thus, they may not have the time to meaningfully engage patients to assess palliative care needs. Creating designated hospitalist palliative care teams with enhanced interdisciplinary support for patients identified using sentinel hospitalization or checklist-based tools may help to solve this dilemma. These teams may also employ lower “caps,” freeing up time for critical discussions and planning around end of life. At the University of Michigan, we are planning just such an approach, a strategy which has the additional benefit of bypassing the binary “care versus no care” dilemma faced by patients choosing palliation. Rather, patients may continue to receive treatments congruent with the goals of care in such teams.

A call for health systems to develop and implement palliative care quality metrics has emerged. Given their role in quality improvement and health system reform, hospitalists are well positioned to shepherd this imperative. Creating incentives to screen inpatients for palliative care needs and develop new homes in which to care for these patients are but a few ways to help set the tone. Additionally, developing and sharing quality metrics and benchmarks currently captured in repositories such as the Palliative Care Quality Network, Global Palliative Care Quality Alliance, and Center to Advance Palliative Care can help to assess and continually improve care delivery. Creating and sharing dashboards from these metrics with all providers, regardless of discipline or training, will ensure accountability to deliver quality palliative care.

Many hospitalized patients do not receive appropriate attention to their palliative care needs. A new interdisciplinary workforce model that task shifts to physician and nonphysician providers and pairs system-level innovations and quality may solve this problem. Input and endorsement from a wide variety of disciplines (particularly our nonphysician colleagues) are needed to make PRISM operational. The proof of concept will lie in testing feasibility among key stakeholders and rigorously studying the proposed interventions. Through innovation in technology, workflow, and quality improvement, hospitalists are well poised to lead this change. After all, our patients deserve nothing less.

Disclosures

The authors have nothing to disclose.Funding: Dr. Abedini’s work is supported by the University of Michigan National Clinician Scholars Program at the Institute for Healthcare Policy and Innovation, as well as the Un

Palliative care is an essential component of inpatient medicine. At its core, it is an interdisciplinary philosophy of care aiming to achieve the best quality of life for patients and families in the physical, psychosocial, and spiritual domains. With the aging population and growing complexity of hospitalized patients, inpatient palliative care needs are only projected to rise. However, a mismatch exists between the number of palliative care–trained physicians and the demand for such physicians. Currently, only 6,600 US physicians are board certified in palliative care – just 37% of the projected need.¹ These workforce shortages have serious implications. In fact, it is estimated that nearly 40% of all hospitalized patients who need palliative care go without it.²

Existing efforts to improve access to palliative care have largely focused on bolstering the palliative care workforce. One tactic particularly relevant to hospitalists centers on frontline physicians providing “primary” palliative care: basic symptom management, patient-centered communication, and goals of care assessment, regardless of the disease state.³ Such physicians constitute the base of today’s palliative care workforce model – a three-tiered pyramid built on clinician availability and skills. In this model, the second tier (“secondary” palliative care) includes physicians supported by a palliative care consultant or referral. The third level (“tertiary” palliative care) encompasses care provided directly by specialized palliative care teams, usually within academic medical centers (Figure).⁴

To better address the current palliative care access problem, we propose a new model: “The Palliative care Redistribution Integrated Service Model (PRISM; Figure 1).” Using the industrial engineering principle of “task shifting,” this approach leverages disciplinary diversity and shifts specific activities from more specialized to less specialized members.⁹ In this way, PRISM integrates hospital-based interdisciplinary teams across all tiers of palliative care delivery.

PRISM sheds a tier-based approach in favor of flexible, skill-based verticals that span all physician and nonphysician providers. By dividing the original pyramid into three domains – physical, psychosocial, and spiritual – providers with various spheres of expertise may serve patients on multiple tiers. For example, a bedside nurse may perform basic psychosocial assessment consistent with his or her training, while physicians may focus on code status or prescribe antiemetics or low-dose opiate monotherapy – skills they have refined during medical school. Analogously, secondary palliative care may be delivered by any provider with more advanced skills in communication or symptom management. In this way, we expand the pool of clinicians available to provide palliative care to include nurses, hospitalists, oncologists, intensivists, social workers, and chaplains and also recognize the diversity of skill sets within and between disciplines. Thus, a hospitalist may clarify the goals of care but may ask a social worker trained in psychosocial assessment for assistance with difficult family dynamics or a chaplain for spiritual needs. Interdisciplinary teamwork and cross-disciplinary communication – hallmarks of palliative care – are encouraged and valued. Furthermore, if providers feel uncomfortable providing a certain type of care, they can ask for assistance from more experienced providers within their discipline or outside of it. In rare cases, the most complex patients may be referred to specialist palliative care teams.

Inherent within PRISM is a recognition that all providers must have a basic palliative care skillset obtained through educational initiatives.⁷ Yet focusing solely on training the workforce as a strategy has and will continue to miss the mark. Rather, structural changes to the means of providing care are also needed. Within hospitals, these changes often rely heavily on hospitalists due to their central position in care delivery. In this way, hospitalists are well primed to be the agents of change in this model.

Since many hospitalized patients have unrecognized and underserved palliative care needs, a formal approach to assessment is needed. Lin et al. proposed criteria for a “sentinel hospitalization,” marking a major illness or transition in high-risk patients necessitating palliative interventions.¹⁰ Similar screening criteria have been validated among hospitalized oncology patients¹¹ and in critical care.¹² While checklists have been shown to help identify hospitalized patients with palliative care needs,¹³ their implementation has been slow, presumably because they are burdensome for busy providers to complete.

Technological automation may be a solution to the checklist conundrum. For example, if palliative care screening criteria could be automatically extracted from electronic health records, scoring systems could trigger hospitalists to consider the goals of care discussions or engage an interdisciplinary care team to fulfill a variety of needs. Frameworks for such scoring systems already exist and are familiar to most hospitalists. For example, admission order sets routinely calculate the Padua or Caprini score to facilitate decision-making for prophylaxis of deep vein thrombosis. An admission order set that screens and prompts decision-making around palliative care needs is thus feasible. One example is a hard stop for entering code status in the admission order set; in turn, this hard stop could also trigger providers to complete a “check-box” palliative care screening checklist. Automatic extraction of certain data from the record – such as age, prior code status, recent hospitalizations, or mobility scores – could auto-populate to facilitate decision-making. In turn, measuring the influence of such tools on access to palliative care, workflow, and capacity will be important, as most tools may not have quality or value intended.¹⁴

It is common for hospitalists to oversee care for 15-20 patients at a time. Thus, they may not have the time to meaningfully engage patients to assess palliative care needs. Creating designated hospitalist palliative care teams with enhanced interdisciplinary support for patients identified using sentinel hospitalization or checklist-based tools may help to solve this dilemma. These teams may also employ lower “caps,” freeing up time for critical discussions and planning around end of life. At the University of Michigan, we are planning just such an approach, a strategy which has the additional benefit of bypassing the binary “care versus no care” dilemma faced by patients choosing palliation. Rather, patients may continue to receive treatments congruent with the goals of care in such teams.

A call for health systems to develop and implement palliative care quality metrics has emerged. Given their role in quality improvement and health system reform, hospitalists are well positioned to shepherd this imperative. Creating incentives to screen inpatients for palliative care needs and develop new homes in which to care for these patients are but a few ways to help set the tone. Additionally, developing and sharing quality metrics and benchmarks currently captured in repositories such as the Palliative Care Quality Network, Global Palliative Care Quality Alliance, and Center to Advance Palliative Care can help to assess and continually improve care delivery. Creating and sharing dashboards from these metrics with all providers, regardless of discipline or training, will ensure accountability to deliver quality palliative care.

Many hospitalized patients do not receive appropriate attention to their palliative care needs. A new interdisciplinary workforce model that task shifts to physician and nonphysician providers and pairs system-level innovations and quality may solve this problem. Input and endorsement from a wide variety of disciplines (particularly our nonphysician colleagues) are needed to make PRISM operational. The proof of concept will lie in testing feasibility among key stakeholders and rigorously studying the proposed interventions. Through innovation in technology, workflow, and quality improvement, hospitalists are well poised to lead this change. After all, our patients deserve nothing less.

Disclosures

The authors have nothing to disclose.Funding: Dr. Abedini’s work is supported by the University of Michigan National Clinician Scholars Program at the Institute for Healthcare Policy and Innovation, as well as the Un

Palliative care is an essential component of inpatient medicine. At its core, it is an interdisciplinary philosophy of care aiming to achieve the best quality of life for patients and families in the physical, psychosocial, and spiritual domains. With the aging population and growing complexity of hospitalized patients, inpatient palliative care needs are only projected to rise. However, a mismatch exists between the number of palliative care–trained physicians and the demand for such physicians. Currently, only 6,600 US physicians are board certified in palliative care – just 37% of the projected need.¹ These workforce shortages have serious implications. In fact, it is estimated that nearly 40% of all hospitalized patients who need palliative care go without it.²

Existing efforts to improve access to palliative care have largely focused on bolstering the palliative care workforce. One tactic particularly relevant to hospitalists centers on frontline physicians providing “primary” palliative care: basic symptom management, patient-centered communication, and goals of care assessment, regardless of the disease state.³ Such physicians constitute the base of today’s palliative care workforce model – a three-tiered pyramid built on clinician availability and skills. In this model, the second tier (“secondary” palliative care) includes physicians supported by a palliative care consultant or referral. The third level (“tertiary” palliative care) encompasses care provided directly by specialized palliative care teams, usually within academic medical centers (Figure).⁴

To better address the current palliative care access problem, we propose a new model: “The Palliative care Redistribution Integrated Service Model (PRISM; Figure 1).” Using the industrial engineering principle of “task shifting,” this approach leverages disciplinary diversity and shifts specific activities from more specialized to less specialized members.⁹ In this way, PRISM integrates hospital-based interdisciplinary teams across all tiers of palliative care delivery.

PRISM sheds a tier-based approach in favor of flexible, skill-based verticals that span all physician and nonphysician providers. By dividing the original pyramid into three domains – physical, psychosocial, and spiritual – providers with various spheres of expertise may serve patients on multiple tiers. For example, a bedside nurse may perform basic psychosocial assessment consistent with his or her training, while physicians may focus on code status or prescribe antiemetics or low-dose opiate monotherapy – skills they have refined during medical school. Analogously, secondary palliative care may be delivered by any provider with more advanced skills in communication or symptom management. In this way, we expand the pool of clinicians available to provide palliative care to include nurses, hospitalists, oncologists, intensivists, social workers, and chaplains and also recognize the diversity of skill sets within and between disciplines. Thus, a hospitalist may clarify the goals of care but may ask a social worker trained in psychosocial assessment for assistance with difficult family dynamics or a chaplain for spiritual needs. Interdisciplinary teamwork and cross-disciplinary communication – hallmarks of palliative care – are encouraged and valued. Furthermore, if providers feel uncomfortable providing a certain type of care, they can ask for assistance from more experienced providers within their discipline or outside of it. In rare cases, the most complex patients may be referred to specialist palliative care teams.

Inherent within PRISM is a recognition that all providers must have a basic palliative care skillset obtained through educational initiatives.⁷ Yet focusing solely on training the workforce as a strategy has and will continue to miss the mark. Rather, structural changes to the means of providing care are also needed. Within hospitals, these changes often rely heavily on hospitalists due to their central position in care delivery. In this way, hospitalists are well primed to be the agents of change in this model.

Since many hospitalized patients have unrecognized and underserved palliative care needs, a formal approach to assessment is needed. Lin et al. proposed criteria for a “sentinel hospitalization,” marking a major illness or transition in high-risk patients necessitating palliative interventions.¹⁰ Similar screening criteria have been validated among hospitalized oncology patients¹¹ and in critical care.¹² While checklists have been shown to help identify hospitalized patients with palliative care needs,¹³ their implementation has been slow, presumably because they are burdensome for busy providers to complete.

Technological automation may be a solution to the checklist conundrum. For example, if palliative care screening criteria could be automatically extracted from electronic health records, scoring systems could trigger hospitalists to consider the goals of care discussions or engage an interdisciplinary care team to fulfill a variety of needs. Frameworks for such scoring systems already exist and are familiar to most hospitalists. For example, admission order sets routinely calculate the Padua or Caprini score to facilitate decision-making for prophylaxis of deep vein thrombosis. An admission order set that screens and prompts decision-making around palliative care needs is thus feasible. One example is a hard stop for entering code status in the admission order set; in turn, this hard stop could also trigger providers to complete a “check-box” palliative care screening checklist. Automatic extraction of certain data from the record – such as age, prior code status, recent hospitalizations, or mobility scores – could auto-populate to facilitate decision-making. In turn, measuring the influence of such tools on access to palliative care, workflow, and capacity will be important, as most tools may not have quality or value intended.¹⁴

It is common for hospitalists to oversee care for 15-20 patients at a time. Thus, they may not have the time to meaningfully engage patients to assess palliative care needs. Creating designated hospitalist palliative care teams with enhanced interdisciplinary support for patients identified using sentinel hospitalization or checklist-based tools may help to solve this dilemma. These teams may also employ lower “caps,” freeing up time for critical discussions and planning around end of life. At the University of Michigan, we are planning just such an approach, a strategy which has the additional benefit of bypassing the binary “care versus no care” dilemma faced by patients choosing palliation. Rather, patients may continue to receive treatments congruent with the goals of care in such teams.

A call for health systems to develop and implement palliative care quality metrics has emerged. Given their role in quality improvement and health system reform, hospitalists are well positioned to shepherd this imperative. Creating incentives to screen inpatients for palliative care needs and develop new homes in which to care for these patients are but a few ways to help set the tone. Additionally, developing and sharing quality metrics and benchmarks currently captured in repositories such as the Palliative Care Quality Network, Global Palliative Care Quality Alliance, and Center to Advance Palliative Care can help to assess and continually improve care delivery. Creating and sharing dashboards from these metrics with all providers, regardless of discipline or training, will ensure accountability to deliver quality palliative care.

Many hospitalized patients do not receive appropriate attention to their palliative care needs. A new interdisciplinary workforce model that task shifts to physician and nonphysician providers and pairs system-level innovations and quality may solve this problem. Input and endorsement from a wide variety of disciplines (particularly our nonphysician colleagues) are needed to make PRISM operational. The proof of concept will lie in testing feasibility among key stakeholders and rigorously studying the proposed interventions. Through innovation in technology, workflow, and quality improvement, hospitalists are well poised to lead this change. After all, our patients deserve nothing less.

Disclosures

The authors have nothing to disclose.Funding: Dr. Abedini’s work is supported by the University of Michigan National Clinician Scholars Program at the Institute for Healthcare Policy and Innovation, as well as the Un

“Every system is perfectly designed to get the results it gets.”
—W. Edwards Deming inspired quote¹

The timing of patient discharge represents a Gordian knot in hospital operations. Moving the time of discharge to earlier in the day is a complex challenge that defies replicable solutions and is often a barrier to optimal throughput and patient experience. In this issue of the Journal of Hospital Medicine, Zoucha et al. identify that discharge orders are frequently delayed due to physicians caring for other patients, heterogeneity in physician rounding styles, and other intrinsic factors such as census size, rounding style, and teaching versus nonteaching services.² Some of these factors and their negative impact are consistent with the effect of higher hospitalist workload (census) when increasing length of stay that was identified by Elliott et al.³ Others, such as rounding style and balancing teaching and education, are a part of many hospitalist service operations. Other intrinsic factors identified by the authors include awaiting consultant recommendations, care completion by social workers, procedures, labs, radiology, therapy services, and home oxygen.

The authors, however, recognize hospitalist behaviors and hospital operations as intrinsic factors. This is significant because intrinsic factors are theoretically under the control of the hospital’s physicians, administration, and support services. They lend themselves to continuous improvement, re-engineering, and change management. They are a direct result of the people, processes, structure, and supporting information technology (IT).

The findings of this study contrast with the perceived dominance of extrinsic factors such as awaiting a ride, insurance authorization issues, or placement as the cause for discharge delays. Anecdotally, physicians and nurses in organizations often identify such extrinsic factors as causes of discharge delays before they call out intrinsic factors.

Frequently, the first reaction to managing complex intrinsic constraints is to add resources and complexity. Continuous improvement often reveals the culprit is poor design and waste found throughout the system. Zoucha et al. refer to LEAN successes by others⁴ as an example of how to approach these complex intrinsic issues. Increasing early discharge with improvement in length of stay and reducing or maintaining the readmission rate has been achieved using the Institute for Healthcare Improvement Model for Improvement,⁵ the Red/Yellow/Green Discharge Tool within the electronic medical record,⁶ and a comprehensive management plan.⁷ These examples were often accomplished through improving the deployment of existing resources and reducing wasted activity. New predictive tools using supervised machine learning can help identify appropriate patients for discharge earlier in the day.⁸ This approach is built on the concepts of “efficiency and communication as components of quality healthcare delivery.”⁶

Perhaps a practical reductionist approach is to start with the end in mind, and ask the question “what matters most?” Three key times occur in each discharge and the authors capture two of these: the discharge order time and discharge time. Not captured is the time the patient and family are told they are being discharged. It is against this backdrop that we can look at four perspectives: caregiver, organization, community, and the patient and family. “What matters most?” depends on the perspective of each one of the parties involved.

From the perspective of the caregivers (physicians and residents), the conclusions support prioritizing rounding on patients ready to discharge, lowering team census, and restructuring teaching rounds to drive earlier discharges. But only 7% of encounters prioritized patients ready for discharge first. Seventy-six percent prioritized sickest patients first (33%), room-by-room (27%), and newest patients (16%).² The authors emphasize that such an approach needs to be balanced against the needs of the entire team census to ensure optimal care for all patients. Team and individual hospitalist census and processes must be optimized to improve the efficiency and effectiveness of the work. For teaching services, the goal is to accomplish effective teaching while maintaining or improving throughput. When addressing optimal census, Wachter concludes “the right census number will be the one in a given setting that maximizes patient outcomes (and in a teaching hospital, educational outcomes as well), efficiency, and the satisfaction of both patients and clinicians, and does so in an economical way.”⁹

Healthcare is delivered by teams. As we look at supporting and structuring our hospitalist teams’ inpatient rounding we need to include the contributions of advanced practice professionals, pharmacists, nurses, care managers, social workers, and others. Achieving a team focus on a goal can be supported by number-by-time (n-by-T) target initiatives, which have been used successfully.^10,11 Team-based solutions must be developed to address these complex issues and in recognition of the need to distribute this responsibility across the system, not just depending on physician changes to ensure optimal outcomes.

The perspectives of organization and community have the common goals of delivering healthcare value (outcomes, quality, safety, and sustainability) and ensuring access. To achieve these, it is important to separate the discharge curve (by shifting these patients’ time of discharge to the left) from the arrival curve, which is more fixed. The organization and community benefit from reduced cost of care, improved value delivery, and better access to services. For hospitals and health systems facing high occupancy, this becomes important for access and serving the community, especially during the peak hours for admissions and discharges.

Against this backdrop is the most important perspective, which is that of the patients and families. What matters most to them? When does their clock start? For patients and families, we believe that their expectations begin when the physician or APP says, “you are doing well and we can get you home today.” In the current study, the median time to discharge from the discharge order for four of the five hospitals was about three hours.² It is reasonable to assume the time interval is on the order of four to six hours or more for many patients. Is this acceptable? We have little data to answer this question directly, and while the Hospital Consumers Assessment of Healthcare Providers and Systems (HCAHPS) survey asks select questions regarding the effectiveness of discharge information, it is silent on matters of discharge timeliness and expectations. While on the administrative side we often use readmission rates as a proxy for a safe and “effective” discharge, in reality, we lack meaningful patient-reported outcome measures to assess our effectiveness, which is a necessity for performance improvement.

The opportunities for improvement suggested by this study include restructuring rounding to prioritize discharges, managing census per provider, and rethinking resident education to accommodate both education and service. The authors’ approach includes identifying ways to improve the efficiency of the work through other team members (such as pharmacy techs for medication reconciliation) and balancing ancillary services support for all inpatient care and the outpatients they serve. Alternatively, tying incentives to the goal could be a convenient leadership response. The 2016 Society of Hospital Medicine State of Hospital Medicine Report notes that more than half (54%) of nonacademic hospitalist groups that treat adults have an incentive tied to early morning discharge orders or times. We believe that by keeping the patients and families at the center of this discussion, we are more likely to accomplish the goal of improved safety, efficiency, effectiveness, and patient experience.

The literature supports discharge delays as an international challenge with research on the topic in healthcare systems across the world.¹² This may be related to an aging population, improvements, and access to advanced healthcare, and the challenges of occupancy and capacity mismatches in many healthcare systems worldwide. The authors have identified important intrinsic factors for these throughput and discharge delays. The results beg the question, are we willing to do the redesign and behavior change in our delivery of healthcare and healthcare education to achieve a more optimized system of care delivery?

A now-retired Cleveland Clinic performance improvement engineer frequently referenced W. Edwards Deming on “what makes the biggest difference in improving internal service quality?” He distilled this to two axioms based on Deming’s work: reducing cycle time and reducing defects. Both must be accomplished from the customer’s (patient’s) perspective without tradeoffs between the two. Cycle time is the time to accomplish a completed process or action, such as patient discharge or LOS. Defects are all the waste or “impossible” challenges that contribute to the feeling of resignation that lead to people dismissing the possibility of improvement, stating “it is what it is.” The challenge in the service of our patients and families, organizations, and communities is to move this dialog forward to “it is what we make it.”¹³

When we tell the patient and family they are being discharged it should happen safely, efficiently, predictably, and with empathy. From the perspective of clinicians, it should be as easy as possible to consistently do the right thing and do the work to which they have dedicated themselves. For communities and organizations struggling with access, improving throughput is vital.

Disclosures

Neither author has any conflicts to disclose. There are no external funding sources for this manuscript.

“Every system is perfectly designed to get the results it gets.”
—W. Edwards Deming inspired quote¹

The timing of patient discharge represents a Gordian knot in hospital operations. Moving the time of discharge to earlier in the day is a complex challenge that defies replicable solutions and is often a barrier to optimal throughput and patient experience. In this issue of the Journal of Hospital Medicine, Zoucha et al. identify that discharge orders are frequently delayed due to physicians caring for other patients, heterogeneity in physician rounding styles, and other intrinsic factors such as census size, rounding style, and teaching versus nonteaching services.² Some of these factors and their negative impact are consistent with the effect of higher hospitalist workload (census) when increasing length of stay that was identified by Elliott et al.³ Others, such as rounding style and balancing teaching and education, are a part of many hospitalist service operations. Other intrinsic factors identified by the authors include awaiting consultant recommendations, care completion by social workers, procedures, labs, radiology, therapy services, and home oxygen.

The authors, however, recognize hospitalist behaviors and hospital operations as intrinsic factors. This is significant because intrinsic factors are theoretically under the control of the hospital’s physicians, administration, and support services. They lend themselves to continuous improvement, re-engineering, and change management. They are a direct result of the people, processes, structure, and supporting information technology (IT).

The findings of this study contrast with the perceived dominance of extrinsic factors such as awaiting a ride, insurance authorization issues, or placement as the cause for discharge delays. Anecdotally, physicians and nurses in organizations often identify such extrinsic factors as causes of discharge delays before they call out intrinsic factors.

Frequently, the first reaction to managing complex intrinsic constraints is to add resources and complexity. Continuous improvement often reveals the culprit is poor design and waste found throughout the system. Zoucha et al. refer to LEAN successes by others⁴ as an example of how to approach these complex intrinsic issues. Increasing early discharge with improvement in length of stay and reducing or maintaining the readmission rate has been achieved using the Institute for Healthcare Improvement Model for Improvement,⁵ the Red/Yellow/Green Discharge Tool within the electronic medical record,⁶ and a comprehensive management plan.⁷ These examples were often accomplished through improving the deployment of existing resources and reducing wasted activity. New predictive tools using supervised machine learning can help identify appropriate patients for discharge earlier in the day.⁸ This approach is built on the concepts of “efficiency and communication as components of quality healthcare delivery.”⁶

Perhaps a practical reductionist approach is to start with the end in mind, and ask the question “what matters most?” Three key times occur in each discharge and the authors capture two of these: the discharge order time and discharge time. Not captured is the time the patient and family are told they are being discharged. It is against this backdrop that we can look at four perspectives: caregiver, organization, community, and the patient and family. “What matters most?” depends on the perspective of each one of the parties involved.

From the perspective of the caregivers (physicians and residents), the conclusions support prioritizing rounding on patients ready to discharge, lowering team census, and restructuring teaching rounds to drive earlier discharges. But only 7% of encounters prioritized patients ready for discharge first. Seventy-six percent prioritized sickest patients first (33%), room-by-room (27%), and newest patients (16%).² The authors emphasize that such an approach needs to be balanced against the needs of the entire team census to ensure optimal care for all patients. Team and individual hospitalist census and processes must be optimized to improve the efficiency and effectiveness of the work. For teaching services, the goal is to accomplish effective teaching while maintaining or improving throughput. When addressing optimal census, Wachter concludes “the right census number will be the one in a given setting that maximizes patient outcomes (and in a teaching hospital, educational outcomes as well), efficiency, and the satisfaction of both patients and clinicians, and does so in an economical way.”⁹

Healthcare is delivered by teams. As we look at supporting and structuring our hospitalist teams’ inpatient rounding we need to include the contributions of advanced practice professionals, pharmacists, nurses, care managers, social workers, and others. Achieving a team focus on a goal can be supported by number-by-time (n-by-T) target initiatives, which have been used successfully.^10,11 Team-based solutions must be developed to address these complex issues and in recognition of the need to distribute this responsibility across the system, not just depending on physician changes to ensure optimal outcomes.

The perspectives of organization and community have the common goals of delivering healthcare value (outcomes, quality, safety, and sustainability) and ensuring access. To achieve these, it is important to separate the discharge curve (by shifting these patients’ time of discharge to the left) from the arrival curve, which is more fixed. The organization and community benefit from reduced cost of care, improved value delivery, and better access to services. For hospitals and health systems facing high occupancy, this becomes important for access and serving the community, especially during the peak hours for admissions and discharges.

Against this backdrop is the most important perspective, which is that of the patients and families. What matters most to them? When does their clock start? For patients and families, we believe that their expectations begin when the physician or APP says, “you are doing well and we can get you home today.” In the current study, the median time to discharge from the discharge order for four of the five hospitals was about three hours.² It is reasonable to assume the time interval is on the order of four to six hours or more for many patients. Is this acceptable? We have little data to answer this question directly, and while the Hospital Consumers Assessment of Healthcare Providers and Systems (HCAHPS) survey asks select questions regarding the effectiveness of discharge information, it is silent on matters of discharge timeliness and expectations. While on the administrative side we often use readmission rates as a proxy for a safe and “effective” discharge, in reality, we lack meaningful patient-reported outcome measures to assess our effectiveness, which is a necessity for performance improvement.

The opportunities for improvement suggested by this study include restructuring rounding to prioritize discharges, managing census per provider, and rethinking resident education to accommodate both education and service. The authors’ approach includes identifying ways to improve the efficiency of the work through other team members (such as pharmacy techs for medication reconciliation) and balancing ancillary services support for all inpatient care and the outpatients they serve. Alternatively, tying incentives to the goal could be a convenient leadership response. The 2016 Society of Hospital Medicine State of Hospital Medicine Report notes that more than half (54%) of nonacademic hospitalist groups that treat adults have an incentive tied to early morning discharge orders or times. We believe that by keeping the patients and families at the center of this discussion, we are more likely to accomplish the goal of improved safety, efficiency, effectiveness, and patient experience.

The literature supports discharge delays as an international challenge with research on the topic in healthcare systems across the world.¹² This may be related to an aging population, improvements, and access to advanced healthcare, and the challenges of occupancy and capacity mismatches in many healthcare systems worldwide. The authors have identified important intrinsic factors for these throughput and discharge delays. The results beg the question, are we willing to do the redesign and behavior change in our delivery of healthcare and healthcare education to achieve a more optimized system of care delivery?

A now-retired Cleveland Clinic performance improvement engineer frequently referenced W. Edwards Deming on “what makes the biggest difference in improving internal service quality?” He distilled this to two axioms based on Deming’s work: reducing cycle time and reducing defects. Both must be accomplished from the customer’s (patient’s) perspective without tradeoffs between the two. Cycle time is the time to accomplish a completed process or action, such as patient discharge or LOS. Defects are all the waste or “impossible” challenges that contribute to the feeling of resignation that lead to people dismissing the possibility of improvement, stating “it is what it is.” The challenge in the service of our patients and families, organizations, and communities is to move this dialog forward to “it is what we make it.”¹³

When we tell the patient and family they are being discharged it should happen safely, efficiently, predictably, and with empathy. From the perspective of clinicians, it should be as easy as possible to consistently do the right thing and do the work to which they have dedicated themselves. For communities and organizations struggling with access, improving throughput is vital.

Disclosures

Neither author has any conflicts to disclose. There are no external funding sources for this manuscript.

“Every system is perfectly designed to get the results it gets.”
—W. Edwards Deming inspired quote¹

The timing of patient discharge represents a Gordian knot in hospital operations. Moving the time of discharge to earlier in the day is a complex challenge that defies replicable solutions and is often a barrier to optimal throughput and patient experience. In this issue of the Journal of Hospital Medicine, Zoucha et al. identify that discharge orders are frequently delayed due to physicians caring for other patients, heterogeneity in physician rounding styles, and other intrinsic factors such as census size, rounding style, and teaching versus nonteaching services.² Some of these factors and their negative impact are consistent with the effect of higher hospitalist workload (census) when increasing length of stay that was identified by Elliott et al.³ Others, such as rounding style and balancing teaching and education, are a part of many hospitalist service operations. Other intrinsic factors identified by the authors include awaiting consultant recommendations, care completion by social workers, procedures, labs, radiology, therapy services, and home oxygen.

The authors, however, recognize hospitalist behaviors and hospital operations as intrinsic factors. This is significant because intrinsic factors are theoretically under the control of the hospital’s physicians, administration, and support services. They lend themselves to continuous improvement, re-engineering, and change management. They are a direct result of the people, processes, structure, and supporting information technology (IT).

The findings of this study contrast with the perceived dominance of extrinsic factors such as awaiting a ride, insurance authorization issues, or placement as the cause for discharge delays. Anecdotally, physicians and nurses in organizations often identify such extrinsic factors as causes of discharge delays before they call out intrinsic factors.

Frequently, the first reaction to managing complex intrinsic constraints is to add resources and complexity. Continuous improvement often reveals the culprit is poor design and waste found throughout the system. Zoucha et al. refer to LEAN successes by others⁴ as an example of how to approach these complex intrinsic issues. Increasing early discharge with improvement in length of stay and reducing or maintaining the readmission rate has been achieved using the Institute for Healthcare Improvement Model for Improvement,⁵ the Red/Yellow/Green Discharge Tool within the electronic medical record,⁶ and a comprehensive management plan.⁷ These examples were often accomplished through improving the deployment of existing resources and reducing wasted activity. New predictive tools using supervised machine learning can help identify appropriate patients for discharge earlier in the day.⁸ This approach is built on the concepts of “efficiency and communication as components of quality healthcare delivery.”⁶

Perhaps a practical reductionist approach is to start with the end in mind, and ask the question “what matters most?” Three key times occur in each discharge and the authors capture two of these: the discharge order time and discharge time. Not captured is the time the patient and family are told they are being discharged. It is against this backdrop that we can look at four perspectives: caregiver, organization, community, and the patient and family. “What matters most?” depends on the perspective of each one of the parties involved.

From the perspective of the caregivers (physicians and residents), the conclusions support prioritizing rounding on patients ready to discharge, lowering team census, and restructuring teaching rounds to drive earlier discharges. But only 7% of encounters prioritized patients ready for discharge first. Seventy-six percent prioritized sickest patients first (33%), room-by-room (27%), and newest patients (16%).² The authors emphasize that such an approach needs to be balanced against the needs of the entire team census to ensure optimal care for all patients. Team and individual hospitalist census and processes must be optimized to improve the efficiency and effectiveness of the work. For teaching services, the goal is to accomplish effective teaching while maintaining or improving throughput. When addressing optimal census, Wachter concludes “the right census number will be the one in a given setting that maximizes patient outcomes (and in a teaching hospital, educational outcomes as well), efficiency, and the satisfaction of both patients and clinicians, and does so in an economical way.”⁹

Healthcare is delivered by teams. As we look at supporting and structuring our hospitalist teams’ inpatient rounding we need to include the contributions of advanced practice professionals, pharmacists, nurses, care managers, social workers, and others. Achieving a team focus on a goal can be supported by number-by-time (n-by-T) target initiatives, which have been used successfully.^10,11 Team-based solutions must be developed to address these complex issues and in recognition of the need to distribute this responsibility across the system, not just depending on physician changes to ensure optimal outcomes.

The perspectives of organization and community have the common goals of delivering healthcare value (outcomes, quality, safety, and sustainability) and ensuring access. To achieve these, it is important to separate the discharge curve (by shifting these patients’ time of discharge to the left) from the arrival curve, which is more fixed. The organization and community benefit from reduced cost of care, improved value delivery, and better access to services. For hospitals and health systems facing high occupancy, this becomes important for access and serving the community, especially during the peak hours for admissions and discharges.

Against this backdrop is the most important perspective, which is that of the patients and families. What matters most to them? When does their clock start? For patients and families, we believe that their expectations begin when the physician or APP says, “you are doing well and we can get you home today.” In the current study, the median time to discharge from the discharge order for four of the five hospitals was about three hours.² It is reasonable to assume the time interval is on the order of four to six hours or more for many patients. Is this acceptable? We have little data to answer this question directly, and while the Hospital Consumers Assessment of Healthcare Providers and Systems (HCAHPS) survey asks select questions regarding the effectiveness of discharge information, it is silent on matters of discharge timeliness and expectations. While on the administrative side we often use readmission rates as a proxy for a safe and “effective” discharge, in reality, we lack meaningful patient-reported outcome measures to assess our effectiveness, which is a necessity for performance improvement.

The opportunities for improvement suggested by this study include restructuring rounding to prioritize discharges, managing census per provider, and rethinking resident education to accommodate both education and service. The authors’ approach includes identifying ways to improve the efficiency of the work through other team members (such as pharmacy techs for medication reconciliation) and balancing ancillary services support for all inpatient care and the outpatients they serve. Alternatively, tying incentives to the goal could be a convenient leadership response. The 2016 Society of Hospital Medicine State of Hospital Medicine Report notes that more than half (54%) of nonacademic hospitalist groups that treat adults have an incentive tied to early morning discharge orders or times. We believe that by keeping the patients and families at the center of this discussion, we are more likely to accomplish the goal of improved safety, efficiency, effectiveness, and patient experience.

The literature supports discharge delays as an international challenge with research on the topic in healthcare systems across the world.¹² This may be related to an aging population, improvements, and access to advanced healthcare, and the challenges of occupancy and capacity mismatches in many healthcare systems worldwide. The authors have identified important intrinsic factors for these throughput and discharge delays. The results beg the question, are we willing to do the redesign and behavior change in our delivery of healthcare and healthcare education to achieve a more optimized system of care delivery?

A now-retired Cleveland Clinic performance improvement engineer frequently referenced W. Edwards Deming on “what makes the biggest difference in improving internal service quality?” He distilled this to two axioms based on Deming’s work: reducing cycle time and reducing defects. Both must be accomplished from the customer’s (patient’s) perspective without tradeoffs between the two. Cycle time is the time to accomplish a completed process or action, such as patient discharge or LOS. Defects are all the waste or “impossible” challenges that contribute to the feeling of resignation that lead to people dismissing the possibility of improvement, stating “it is what it is.” The challenge in the service of our patients and families, organizations, and communities is to move this dialog forward to “it is what we make it.”¹³

When we tell the patient and family they are being discharged it should happen safely, efficiently, predictably, and with empathy. From the perspective of clinicians, it should be as easy as possible to consistently do the right thing and do the work to which they have dedicated themselves. For communities and organizations struggling with access, improving throughput is vital.

Disclosures

Neither author has any conflicts to disclose. There are no external funding sources for this manuscript.

One of the least taught yet most complicated tasks confronting new trainees is the bewildering process of discharging a patient. On an internal medicine service, this process can often resemble a Rube Goldberg machine, in which a “simple” task is accomplished through a series of interconnected, almost comically convoluted, yet separate steps that are triggered one after another and must be executed perfectly in sequence for success. It seems easy at first; just tap out a few sentences in the discharge paperwork, do a quick medication reconciliation, and a click of a button later, voila! The patient magically falls off the list and is on their merry way home. In reality, it only takes one wrench thrown into the Rube Goldberg machine to take down the whole operation. Much to the chagrin of internal medicine interns across the country, residents quickly learn that discharge planning is usually far from straightforward and that a myriad of obstacles (often dynamic and frustratingly unpredictable) can stand in the way of a successful discharge.

While some surgical services can streamline discharge processes to target defined lengths of stay based on a particular diagnosis, general medicine patients tend to have greater numbers of comorbid conditions, complex hospital courses, and wider variation in access to posthospital healthcare. In addition, there is very little formal instruction in transitions of care, and most residents identify direct patient care (learning by doing) as the primary mode of education.^1,2 Struggling through the process of finding an appropriate placement, ensuring adequate outpatient follow-up, and untangling a jumbled mess of a medication reconciliation is often the only way that housestaff learn the Sisyphean task of transitioning care out of the hospital. The unpredictability and intensity of patient care adds to the ever growing list of competing demands on the time and attention of residents. Attendings face pressure on all sides to not only provide exemplary patient care and an educational experience but also to optimize hospital throughput by discharging patients as soon as possible (and ideally before noon). No wonder that the discharge process can threaten to unravel at any time, with delays and complications in discharge metamorphosing into increased length of stay (LOS), poorer outcomes, and increased 30-day readmission rates. As on-the-ground providers, what realities do we face when challenging ourselves to discharge patients before noon, and what practical changes in our workflow can we make to reach this goal?

In this month’s Journal of Hospital Medicine, Zoucha et al. examine these questions in real time by identifying barriers preventing both “definite” and “possible” discharges at three representative time points over the course of randomly chosen weekdays. They surveyed both housestaff and attendings at five academic hospitals across the United States, and the majority of patients were cared for on teaching services.³ Reflecting the inherent differences in workflow between teaching and nonteaching services, delays in definite discharges on teaching services were most often hindered by completing rounds and the need to staff the patient with the attending, whereas nonresident services identified other patient-care-related (both urgent and nonurgent) issues to be the culprits. Late-afternoon discharges were delayed on teaching services due to outstanding paperwork and follow-up arrangements, both of which most senior residents are keenly aware of and make their best effort to complete ahead of time. Patients designated as “possible” discharges were awaiting clinical improvement and resolution of disposition issues dependent on social work and safe placement, which reasonably seemed independent of service type. These descriptive findings suggest that nonresident services are more efficient than resident teams, and we are keen to identify novel solutions, such as dedicated discharge coordinators,⁴ to facilitate the discharge process on resident teams without detracting from the educational value of the rotation.

Zoucha et al. also found that factors beyond our control (having a lower daily census, attending on a nonresident service) were significantly associated with both earlier discharge order entry times and the actual time of patient discharge.³ While it is tempting to foist the entirety of the blame on extrinsic factors such as discharge placement and insurance issues, the reality is there might be some workflow changes that could expedite the discharge process. The authors are correct to emphasize that rounding style, in which discharges are prioritized to be seen first, is a behavior modification worth targeting. The percentage of teams that routinely see discharges first is not well studied, as other factors, such as clinically unstable patients, new admissions from overnight, and even mundane characteristics such as geographic location in the hospital, can also compete for prioritization in rounding order. Given the authors’ findings, we are eager to see further work in this area as prioritization of discharges during rounds could conceivably be studied within the context of a randomized controlled trial. Other innovations in rounding styles such as rounding-in-flow⁵ (in which all tasks are completed for a single patient before rounding on the next patient) can also significantly reduce the time to discharge order placement.

With help from the Penn Medicine Center for Health Care Innovation, we are actively studying bottlenecks in the discharge process by developing an interactive platform focused on delivering real-time information to all members of the healthcare team. Rapid rounds are held every morning with the attending physician, floor nursing leadership, physical therapy, social worker, and case management to quickly identify pending tasks, anticipated disposition, and a target date of discharge. Efficiency is key, as each team is limited to approximately 5-10 minutes. Previous studies (mostly pre–post studies) have shown that this simple intervention significantly reduced LOS,^6,7 increased rates of discharge before noon,⁸ and was improved by electronic tracking tools.⁹ Our multidisciplinary rounds are unique in that information is then entered into an intuitive, web-based platform, which allows consolidation and analysis that permits generation of real-time statistics. By standardizing the discharge planning process, we hope to streamline a previously fragmented process and maximize the efficiency of hospital resource utilization.

Ultimately, high-quality care of complex patients on internal medicine services from admission to discharge requires hard work, smart utilization of resources, and a little bit of luck. There may not be a secret ingredient that guarantees perfectly efficient discharges 100% of the time, but this study inspires us to ponder additional approaches to this longstanding problem. The authors are to be congratulated for a rigorous study that illuminates where we as healthcare providers are able to realistically intervene to expedite the discharge process. First, having a lower census cap may not be possible in this era of maximal hospital usage, but this work suggests that thoughtful management of time on rounds may be a way to address the underlying problem. Secondly, the superior efficiency of nonteaching services may merely reflect the increased experience of the providers, and a realistic solution could be to implement a formal curriculum to educate housestaff about the discharge process, which would simultaneously address residency competency standards for transitions of care. Finally, the role of innovative informatics tools will surely open further avenues of investigation, as we continually evolve in response to intensifying standards of modern, efficient healthcare delivery in the 21^st century. It may not be possible to eliminate the complexity from this particular Rube Goldberg machine, but taking the steps above may allow us to implement as many fail-safes as we can.

Disclosures

The authors have nothing to disclose.

One of the least taught yet most complicated tasks confronting new trainees is the bewildering process of discharging a patient. On an internal medicine service, this process can often resemble a Rube Goldberg machine, in which a “simple” task is accomplished through a series of interconnected, almost comically convoluted, yet separate steps that are triggered one after another and must be executed perfectly in sequence for success. It seems easy at first; just tap out a few sentences in the discharge paperwork, do a quick medication reconciliation, and a click of a button later, voila! The patient magically falls off the list and is on their merry way home. In reality, it only takes one wrench thrown into the Rube Goldberg machine to take down the whole operation. Much to the chagrin of internal medicine interns across the country, residents quickly learn that discharge planning is usually far from straightforward and that a myriad of obstacles (often dynamic and frustratingly unpredictable) can stand in the way of a successful discharge.

While some surgical services can streamline discharge processes to target defined lengths of stay based on a particular diagnosis, general medicine patients tend to have greater numbers of comorbid conditions, complex hospital courses, and wider variation in access to posthospital healthcare. In addition, there is very little formal instruction in transitions of care, and most residents identify direct patient care (learning by doing) as the primary mode of education.^1,2 Struggling through the process of finding an appropriate placement, ensuring adequate outpatient follow-up, and untangling a jumbled mess of a medication reconciliation is often the only way that housestaff learn the Sisyphean task of transitioning care out of the hospital. The unpredictability and intensity of patient care adds to the ever growing list of competing demands on the time and attention of residents. Attendings face pressure on all sides to not only provide exemplary patient care and an educational experience but also to optimize hospital throughput by discharging patients as soon as possible (and ideally before noon). No wonder that the discharge process can threaten to unravel at any time, with delays and complications in discharge metamorphosing into increased length of stay (LOS), poorer outcomes, and increased 30-day readmission rates. As on-the-ground providers, what realities do we face when challenging ourselves to discharge patients before noon, and what practical changes in our workflow can we make to reach this goal?

In this month’s Journal of Hospital Medicine, Zoucha et al. examine these questions in real time by identifying barriers preventing both “definite” and “possible” discharges at three representative time points over the course of randomly chosen weekdays. They surveyed both housestaff and attendings at five academic hospitals across the United States, and the majority of patients were cared for on teaching services.³ Reflecting the inherent differences in workflow between teaching and nonteaching services, delays in definite discharges on teaching services were most often hindered by completing rounds and the need to staff the patient with the attending, whereas nonresident services identified other patient-care-related (both urgent and nonurgent) issues to be the culprits. Late-afternoon discharges were delayed on teaching services due to outstanding paperwork and follow-up arrangements, both of which most senior residents are keenly aware of and make their best effort to complete ahead of time. Patients designated as “possible” discharges were awaiting clinical improvement and resolution of disposition issues dependent on social work and safe placement, which reasonably seemed independent of service type. These descriptive findings suggest that nonresident services are more efficient than resident teams, and we are keen to identify novel solutions, such as dedicated discharge coordinators,⁴ to facilitate the discharge process on resident teams without detracting from the educational value of the rotation.

Zoucha et al. also found that factors beyond our control (having a lower daily census, attending on a nonresident service) were significantly associated with both earlier discharge order entry times and the actual time of patient discharge.³ While it is tempting to foist the entirety of the blame on extrinsic factors such as discharge placement and insurance issues, the reality is there might be some workflow changes that could expedite the discharge process. The authors are correct to emphasize that rounding style, in which discharges are prioritized to be seen first, is a behavior modification worth targeting. The percentage of teams that routinely see discharges first is not well studied, as other factors, such as clinically unstable patients, new admissions from overnight, and even mundane characteristics such as geographic location in the hospital, can also compete for prioritization in rounding order. Given the authors’ findings, we are eager to see further work in this area as prioritization of discharges during rounds could conceivably be studied within the context of a randomized controlled trial. Other innovations in rounding styles such as rounding-in-flow⁵ (in which all tasks are completed for a single patient before rounding on the next patient) can also significantly reduce the time to discharge order placement.

With help from the Penn Medicine Center for Health Care Innovation, we are actively studying bottlenecks in the discharge process by developing an interactive platform focused on delivering real-time information to all members of the healthcare team. Rapid rounds are held every morning with the attending physician, floor nursing leadership, physical therapy, social worker, and case management to quickly identify pending tasks, anticipated disposition, and a target date of discharge. Efficiency is key, as each team is limited to approximately 5-10 minutes. Previous studies (mostly pre–post studies) have shown that this simple intervention significantly reduced LOS,^6,7 increased rates of discharge before noon,⁸ and was improved by electronic tracking tools.⁹ Our multidisciplinary rounds are unique in that information is then entered into an intuitive, web-based platform, which allows consolidation and analysis that permits generation of real-time statistics. By standardizing the discharge planning process, we hope to streamline a previously fragmented process and maximize the efficiency of hospital resource utilization.

Ultimately, high-quality care of complex patients on internal medicine services from admission to discharge requires hard work, smart utilization of resources, and a little bit of luck. There may not be a secret ingredient that guarantees perfectly efficient discharges 100% of the time, but this study inspires us to ponder additional approaches to this longstanding problem. The authors are to be congratulated for a rigorous study that illuminates where we as healthcare providers are able to realistically intervene to expedite the discharge process. First, having a lower census cap may not be possible in this era of maximal hospital usage, but this work suggests that thoughtful management of time on rounds may be a way to address the underlying problem. Secondly, the superior efficiency of nonteaching services may merely reflect the increased experience of the providers, and a realistic solution could be to implement a formal curriculum to educate housestaff about the discharge process, which would simultaneously address residency competency standards for transitions of care. Finally, the role of innovative informatics tools will surely open further avenues of investigation, as we continually evolve in response to intensifying standards of modern, efficient healthcare delivery in the 21^st century. It may not be possible to eliminate the complexity from this particular Rube Goldberg machine, but taking the steps above may allow us to implement as many fail-safes as we can.

Disclosures

The authors have nothing to disclose.

One of the least taught yet most complicated tasks confronting new trainees is the bewildering process of discharging a patient. On an internal medicine service, this process can often resemble a Rube Goldberg machine, in which a “simple” task is accomplished through a series of interconnected, almost comically convoluted, yet separate steps that are triggered one after another and must be executed perfectly in sequence for success. It seems easy at first; just tap out a few sentences in the discharge paperwork, do a quick medication reconciliation, and a click of a button later, voila! The patient magically falls off the list and is on their merry way home. In reality, it only takes one wrench thrown into the Rube Goldberg machine to take down the whole operation. Much to the chagrin of internal medicine interns across the country, residents quickly learn that discharge planning is usually far from straightforward and that a myriad of obstacles (often dynamic and frustratingly unpredictable) can stand in the way of a successful discharge.

While some surgical services can streamline discharge processes to target defined lengths of stay based on a particular diagnosis, general medicine patients tend to have greater numbers of comorbid conditions, complex hospital courses, and wider variation in access to posthospital healthcare. In addition, there is very little formal instruction in transitions of care, and most residents identify direct patient care (learning by doing) as the primary mode of education.^1,2 Struggling through the process of finding an appropriate placement, ensuring adequate outpatient follow-up, and untangling a jumbled mess of a medication reconciliation is often the only way that housestaff learn the Sisyphean task of transitioning care out of the hospital. The unpredictability and intensity of patient care adds to the ever growing list of competing demands on the time and attention of residents. Attendings face pressure on all sides to not only provide exemplary patient care and an educational experience but also to optimize hospital throughput by discharging patients as soon as possible (and ideally before noon). No wonder that the discharge process can threaten to unravel at any time, with delays and complications in discharge metamorphosing into increased length of stay (LOS), poorer outcomes, and increased 30-day readmission rates. As on-the-ground providers, what realities do we face when challenging ourselves to discharge patients before noon, and what practical changes in our workflow can we make to reach this goal?

In this month’s Journal of Hospital Medicine, Zoucha et al. examine these questions in real time by identifying barriers preventing both “definite” and “possible” discharges at three representative time points over the course of randomly chosen weekdays. They surveyed both housestaff and attendings at five academic hospitals across the United States, and the majority of patients were cared for on teaching services.³ Reflecting the inherent differences in workflow between teaching and nonteaching services, delays in definite discharges on teaching services were most often hindered by completing rounds and the need to staff the patient with the attending, whereas nonresident services identified other patient-care-related (both urgent and nonurgent) issues to be the culprits. Late-afternoon discharges were delayed on teaching services due to outstanding paperwork and follow-up arrangements, both of which most senior residents are keenly aware of and make their best effort to complete ahead of time. Patients designated as “possible” discharges were awaiting clinical improvement and resolution of disposition issues dependent on social work and safe placement, which reasonably seemed independent of service type. These descriptive findings suggest that nonresident services are more efficient than resident teams, and we are keen to identify novel solutions, such as dedicated discharge coordinators,⁴ to facilitate the discharge process on resident teams without detracting from the educational value of the rotation.

Zoucha et al. also found that factors beyond our control (having a lower daily census, attending on a nonresident service) were significantly associated with both earlier discharge order entry times and the actual time of patient discharge.³ While it is tempting to foist the entirety of the blame on extrinsic factors such as discharge placement and insurance issues, the reality is there might be some workflow changes that could expedite the discharge process. The authors are correct to emphasize that rounding style, in which discharges are prioritized to be seen first, is a behavior modification worth targeting. The percentage of teams that routinely see discharges first is not well studied, as other factors, such as clinically unstable patients, new admissions from overnight, and even mundane characteristics such as geographic location in the hospital, can also compete for prioritization in rounding order. Given the authors’ findings, we are eager to see further work in this area as prioritization of discharges during rounds could conceivably be studied within the context of a randomized controlled trial. Other innovations in rounding styles such as rounding-in-flow⁵ (in which all tasks are completed for a single patient before rounding on the next patient) can also significantly reduce the time to discharge order placement.

With help from the Penn Medicine Center for Health Care Innovation, we are actively studying bottlenecks in the discharge process by developing an interactive platform focused on delivering real-time information to all members of the healthcare team. Rapid rounds are held every morning with the attending physician, floor nursing leadership, physical therapy, social worker, and case management to quickly identify pending tasks, anticipated disposition, and a target date of discharge. Efficiency is key, as each team is limited to approximately 5-10 minutes. Previous studies (mostly pre–post studies) have shown that this simple intervention significantly reduced LOS,^6,7 increased rates of discharge before noon,⁸ and was improved by electronic tracking tools.⁹ Our multidisciplinary rounds are unique in that information is then entered into an intuitive, web-based platform, which allows consolidation and analysis that permits generation of real-time statistics. By standardizing the discharge planning process, we hope to streamline a previously fragmented process and maximize the efficiency of hospital resource utilization.

Ultimately, high-quality care of complex patients on internal medicine services from admission to discharge requires hard work, smart utilization of resources, and a little bit of luck. There may not be a secret ingredient that guarantees perfectly efficient discharges 100% of the time, but this study inspires us to ponder additional approaches to this longstanding problem. The authors are to be congratulated for a rigorous study that illuminates where we as healthcare providers are able to realistically intervene to expedite the discharge process. First, having a lower census cap may not be possible in this era of maximal hospital usage, but this work suggests that thoughtful management of time on rounds may be a way to address the underlying problem. Secondly, the superior efficiency of nonteaching services may merely reflect the increased experience of the providers, and a realistic solution could be to implement a formal curriculum to educate housestaff about the discharge process, which would simultaneously address residency competency standards for transitions of care. Finally, the role of innovative informatics tools will surely open further avenues of investigation, as we continually evolve in response to intensifying standards of modern, efficient healthcare delivery in the 21^st century. It may not be possible to eliminate the complexity from this particular Rube Goldberg machine, but taking the steps above may allow us to implement as many fail-safes as we can.

Disclosures

The authors have nothing to disclose.