The Limited Academic Footprint of Hospital Medicine: Where Do We Go From Here?

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The Limited Academic Footprint of Hospital Medicine: Where Do We Go From Here?

What has been the scholarly output of academic hospital medicine faculty (AHMF) and what academic rank have they achieved at US academic medical centers (AMCs)? Sumarsono et al1 address these questions and add to the growing body of literature exposing the limited academic footprint of hospitalists.

The authors performed a cross-sectional analysis of AHMF affiliated with the top 25 internal medicine training programs (as determined by the physician networking service doximity.com) and used Scopus to determine number of publications, citations, and H-index (a metric of productivity) for each faculty member. They also evaluated predictors for promotion. In contrast, most prior research on this topic relies on data obtained by survey methodology.2-5

Among 1554 AHMF from 22 AMCs, 42 (2.7%) were full professors and 140 (9.0%) were associate professors. The number of publications per AHMF was noticeably low, with a mean of 6.3 and median of 0 (interquartile range, 0-4). The authors found that H-index, completion of chief residency, and graduation from a top 25 medical school were independently associated with promotion.

The authors only evaluated AHMF among the most academically rigorous AMCs, an approach that likely overestimates scholarly output of hospitalists across all US AMCs. Conversely, if we presume that promotion is more difficult at these major AMCs, the results may underestimate academic rank of AHMF nationally. Additionally, the authors did not distinguish faculty by tracks (eg, clinician-investigators, clinician-educators), which often have different criteria for academic promotion.

These findings are worrisomely consistent with prior reports, despite the tremendous expansion of the field.2-4 A 2008 survey of academic hospitalists found that 4% of respondents were full professors and 9% were associate professors, values nearly identical to the results in this current analysis,4 suggesting enduring barriers to academic advancement.

We are left with the following questions provoked by this body of literature: How can hospitalists increase their scholarly output and climb the promotional ladder? And how can we increase the academic footprint of hospital medicine? We recently proposed the following strategies based on a survey of academic groups participating in the Hospital Medicine Reengineering Network (HOMERuN) survey5: (1) expand hospital medicine research fellowships, which will provide graduates with research skills to justify dedicated time for research and aid their ability to obtain independent funding; (2) formalize mentorship between research faculty in hospital medicine and other internal medicine disciplines with robust track records for research; (3) invest in research infrastructure and data access within and between institutions; and (4) encourage hospital medicine group leaders to foster academic growth by incentivizing faculty to perform research, present their work at national conferences, and publish manuscripts with their findings.

Although an increase in scholarly output should contribute to higher academic rank, hospitalists routinely make other invaluable contributions beyond clinical care to AMCs, including medical education, hospital leadership, quality improvement, clinical innovation, and social justice advocacy. Also, hospitalists are increasingly disseminating their contributions via newer mediums (eg, social media, podcasts) that arguably have greater reach than traditional scholarship outlets. We believe that promotion committees should update their criteria to reflect the evolution of academic contribution and integrate these within traditional promotion pathways.

Finally, we must address federal funding mechanisms, which currently favor specialty-specific funding over funding that would be more applicable to hospital medicine researchers. Funding agencies are largely specialty- or disease-specific, with limited options for broader-based research.6 Additionally, grant-review committees are largely comprised of specialists, with few generalists and fewer hospitalists. These limitations make it difficult to “argue” the necessity of hospital medicine research. One concrete step would be for the National Institutes of Health (NIH) to create an Office for Hospital Medicine Research, analogous to the Office of Emergency Care Research, which works across NIH institutes and centers to foster research and research training for the emergency setting.

With these strategies, we are hopeful that hospital medicine will continue to expand its academic footprint and be recognized for its ever-growing contributions to the practice of medicine.

References

1. Sumarsono A, Keshvani N, Saleh SN, et al. Scholarly productivity and rank in academic hospital medicine. J Hosp Med. 2021;16(9):545-548. https://doi.org/10.12788/jhm.3631
2. Chopra V, Burden M, Jones CD, et al. State of research in adult hospital medicine: results of a national survey. J Hosp Med. 2019;14(4):207-211. https://doi.org/10.12788/jhm.3136
3. Miller CS, Fogerty RL, Gann J, et al, the Society of General Internal Medicine Membership Committee. The growth of hospitalists and the future of the society of general internal medicine: results from the 2014 membership survey. J Gen Intern Med. 2017;32(11):1179-1185. https://doi.org/10.1007/s11606-017-4126-7
4. Reid MB, Misky GJ, Harrison RA, Sharpe B, Auerbach A, Glasheen JJ. Mentorship, productivity, and promotion among academic hospitalists. J Gen Intern Med. 2012;27(1):23-27. https://doi.org/10.1007/s11606-011-1892-5
5. Shannon EM, Chopra V, Greysen SR, et al. Dearth of hospitalist investigators in academic medicine: a call to action. J Hosp Med. 2021;16(3):189-191. https://doi.org/10.12788/jhm.3536
6. Levinson W, Linzer M. What is an academic general internist? Career options and training pathways. JAMA. 2002;288(16):2045-2048. https://doi.org/10.1001/jama.288.16.2045

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1Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts; 2Harvard Medical School, Boston, Massachusetts; 3Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, Massachusetts.

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What has been the scholarly output of academic hospital medicine faculty (AHMF) and what academic rank have they achieved at US academic medical centers (AMCs)? Sumarsono et al1 address these questions and add to the growing body of literature exposing the limited academic footprint of hospitalists.

The authors performed a cross-sectional analysis of AHMF affiliated with the top 25 internal medicine training programs (as determined by the physician networking service doximity.com) and used Scopus to determine number of publications, citations, and H-index (a metric of productivity) for each faculty member. They also evaluated predictors for promotion. In contrast, most prior research on this topic relies on data obtained by survey methodology.2-5

Among 1554 AHMF from 22 AMCs, 42 (2.7%) were full professors and 140 (9.0%) were associate professors. The number of publications per AHMF was noticeably low, with a mean of 6.3 and median of 0 (interquartile range, 0-4). The authors found that H-index, completion of chief residency, and graduation from a top 25 medical school were independently associated with promotion.

The authors only evaluated AHMF among the most academically rigorous AMCs, an approach that likely overestimates scholarly output of hospitalists across all US AMCs. Conversely, if we presume that promotion is more difficult at these major AMCs, the results may underestimate academic rank of AHMF nationally. Additionally, the authors did not distinguish faculty by tracks (eg, clinician-investigators, clinician-educators), which often have different criteria for academic promotion.

These findings are worrisomely consistent with prior reports, despite the tremendous expansion of the field.2-4 A 2008 survey of academic hospitalists found that 4% of respondents were full professors and 9% were associate professors, values nearly identical to the results in this current analysis,4 suggesting enduring barriers to academic advancement.

We are left with the following questions provoked by this body of literature: How can hospitalists increase their scholarly output and climb the promotional ladder? And how can we increase the academic footprint of hospital medicine? We recently proposed the following strategies based on a survey of academic groups participating in the Hospital Medicine Reengineering Network (HOMERuN) survey5: (1) expand hospital medicine research fellowships, which will provide graduates with research skills to justify dedicated time for research and aid their ability to obtain independent funding; (2) formalize mentorship between research faculty in hospital medicine and other internal medicine disciplines with robust track records for research; (3) invest in research infrastructure and data access within and between institutions; and (4) encourage hospital medicine group leaders to foster academic growth by incentivizing faculty to perform research, present their work at national conferences, and publish manuscripts with their findings.

Although an increase in scholarly output should contribute to higher academic rank, hospitalists routinely make other invaluable contributions beyond clinical care to AMCs, including medical education, hospital leadership, quality improvement, clinical innovation, and social justice advocacy. Also, hospitalists are increasingly disseminating their contributions via newer mediums (eg, social media, podcasts) that arguably have greater reach than traditional scholarship outlets. We believe that promotion committees should update their criteria to reflect the evolution of academic contribution and integrate these within traditional promotion pathways.

Finally, we must address federal funding mechanisms, which currently favor specialty-specific funding over funding that would be more applicable to hospital medicine researchers. Funding agencies are largely specialty- or disease-specific, with limited options for broader-based research.6 Additionally, grant-review committees are largely comprised of specialists, with few generalists and fewer hospitalists. These limitations make it difficult to “argue” the necessity of hospital medicine research. One concrete step would be for the National Institutes of Health (NIH) to create an Office for Hospital Medicine Research, analogous to the Office of Emergency Care Research, which works across NIH institutes and centers to foster research and research training for the emergency setting.

With these strategies, we are hopeful that hospital medicine will continue to expand its academic footprint and be recognized for its ever-growing contributions to the practice of medicine.

What has been the scholarly output of academic hospital medicine faculty (AHMF) and what academic rank have they achieved at US academic medical centers (AMCs)? Sumarsono et al1 address these questions and add to the growing body of literature exposing the limited academic footprint of hospitalists.

The authors performed a cross-sectional analysis of AHMF affiliated with the top 25 internal medicine training programs (as determined by the physician networking service doximity.com) and used Scopus to determine number of publications, citations, and H-index (a metric of productivity) for each faculty member. They also evaluated predictors for promotion. In contrast, most prior research on this topic relies on data obtained by survey methodology.2-5

Among 1554 AHMF from 22 AMCs, 42 (2.7%) were full professors and 140 (9.0%) were associate professors. The number of publications per AHMF was noticeably low, with a mean of 6.3 and median of 0 (interquartile range, 0-4). The authors found that H-index, completion of chief residency, and graduation from a top 25 medical school were independently associated with promotion.

The authors only evaluated AHMF among the most academically rigorous AMCs, an approach that likely overestimates scholarly output of hospitalists across all US AMCs. Conversely, if we presume that promotion is more difficult at these major AMCs, the results may underestimate academic rank of AHMF nationally. Additionally, the authors did not distinguish faculty by tracks (eg, clinician-investigators, clinician-educators), which often have different criteria for academic promotion.

These findings are worrisomely consistent with prior reports, despite the tremendous expansion of the field.2-4 A 2008 survey of academic hospitalists found that 4% of respondents were full professors and 9% were associate professors, values nearly identical to the results in this current analysis,4 suggesting enduring barriers to academic advancement.

We are left with the following questions provoked by this body of literature: How can hospitalists increase their scholarly output and climb the promotional ladder? And how can we increase the academic footprint of hospital medicine? We recently proposed the following strategies based on a survey of academic groups participating in the Hospital Medicine Reengineering Network (HOMERuN) survey5: (1) expand hospital medicine research fellowships, which will provide graduates with research skills to justify dedicated time for research and aid their ability to obtain independent funding; (2) formalize mentorship between research faculty in hospital medicine and other internal medicine disciplines with robust track records for research; (3) invest in research infrastructure and data access within and between institutions; and (4) encourage hospital medicine group leaders to foster academic growth by incentivizing faculty to perform research, present their work at national conferences, and publish manuscripts with their findings.

Although an increase in scholarly output should contribute to higher academic rank, hospitalists routinely make other invaluable contributions beyond clinical care to AMCs, including medical education, hospital leadership, quality improvement, clinical innovation, and social justice advocacy. Also, hospitalists are increasingly disseminating their contributions via newer mediums (eg, social media, podcasts) that arguably have greater reach than traditional scholarship outlets. We believe that promotion committees should update their criteria to reflect the evolution of academic contribution and integrate these within traditional promotion pathways.

Finally, we must address federal funding mechanisms, which currently favor specialty-specific funding over funding that would be more applicable to hospital medicine researchers. Funding agencies are largely specialty- or disease-specific, with limited options for broader-based research.6 Additionally, grant-review committees are largely comprised of specialists, with few generalists and fewer hospitalists. These limitations make it difficult to “argue” the necessity of hospital medicine research. One concrete step would be for the National Institutes of Health (NIH) to create an Office for Hospital Medicine Research, analogous to the Office of Emergency Care Research, which works across NIH institutes and centers to foster research and research training for the emergency setting.

With these strategies, we are hopeful that hospital medicine will continue to expand its academic footprint and be recognized for its ever-growing contributions to the practice of medicine.

References

1. Sumarsono A, Keshvani N, Saleh SN, et al. Scholarly productivity and rank in academic hospital medicine. J Hosp Med. 2021;16(9):545-548. https://doi.org/10.12788/jhm.3631
2. Chopra V, Burden M, Jones CD, et al. State of research in adult hospital medicine: results of a national survey. J Hosp Med. 2019;14(4):207-211. https://doi.org/10.12788/jhm.3136
3. Miller CS, Fogerty RL, Gann J, et al, the Society of General Internal Medicine Membership Committee. The growth of hospitalists and the future of the society of general internal medicine: results from the 2014 membership survey. J Gen Intern Med. 2017;32(11):1179-1185. https://doi.org/10.1007/s11606-017-4126-7
4. Reid MB, Misky GJ, Harrison RA, Sharpe B, Auerbach A, Glasheen JJ. Mentorship, productivity, and promotion among academic hospitalists. J Gen Intern Med. 2012;27(1):23-27. https://doi.org/10.1007/s11606-011-1892-5
5. Shannon EM, Chopra V, Greysen SR, et al. Dearth of hospitalist investigators in academic medicine: a call to action. J Hosp Med. 2021;16(3):189-191. https://doi.org/10.12788/jhm.3536
6. Levinson W, Linzer M. What is an academic general internist? Career options and training pathways. JAMA. 2002;288(16):2045-2048. https://doi.org/10.1001/jama.288.16.2045

References

1. Sumarsono A, Keshvani N, Saleh SN, et al. Scholarly productivity and rank in academic hospital medicine. J Hosp Med. 2021;16(9):545-548. https://doi.org/10.12788/jhm.3631
2. Chopra V, Burden M, Jones CD, et al. State of research in adult hospital medicine: results of a national survey. J Hosp Med. 2019;14(4):207-211. https://doi.org/10.12788/jhm.3136
3. Miller CS, Fogerty RL, Gann J, et al, the Society of General Internal Medicine Membership Committee. The growth of hospitalists and the future of the society of general internal medicine: results from the 2014 membership survey. J Gen Intern Med. 2017;32(11):1179-1185. https://doi.org/10.1007/s11606-017-4126-7
4. Reid MB, Misky GJ, Harrison RA, Sharpe B, Auerbach A, Glasheen JJ. Mentorship, productivity, and promotion among academic hospitalists. J Gen Intern Med. 2012;27(1):23-27. https://doi.org/10.1007/s11606-011-1892-5
5. Shannon EM, Chopra V, Greysen SR, et al. Dearth of hospitalist investigators in academic medicine: a call to action. J Hosp Med. 2021;16(3):189-191. https://doi.org/10.12788/jhm.3536
6. Levinson W, Linzer M. What is an academic general internist? Career options and training pathways. JAMA. 2002;288(16):2045-2048. https://doi.org/10.1001/jama.288.16.2045

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Dearth of Hospitalist Investigators in Academic Medicine: A Call to Action

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Dearth of Hospitalist Investigators in Academic Medicine: A Call to Action

In their report celebrating the increase in the number of hospitalists from a few hundred in the 1990s to more than 50,000 in 2016, Drs Robert Wachter and Lee Goldman also noted the stunted growth of productive hospital medicine research programs, which presents a challenge to academic credibility in hospital medicine.1 Given the substantial increase in the number of hospitalists over the past two decades, we surveyed adult academic hospital medicine groups to quantify the number of hospitalist clinician investigators and identify gaps in resources for researchers. The number of clinician investigators supported at academic medical centers (AMCs) remains disturbingly low despite the rapid growth of our specialty. Some programs also reported a lack of access to fundamental research services. We report selected results from our survey and provide recommendations to support and facilitate the development of clinician investigators in hospital medicine.

DEARTH OF CLINICIAN INVESTIGATORS IN HOSPITAL MEDICINE

We performed a survey of hospital medicine programs at AMCs in the United States through the Hospital Medicine Reengineering Network (HOMERuN), a hospital medicine research collaborative that facilitates and conducts multisite research studies.2 The purpose of this survey was to obtain a profile of adult academic hospital medicine groups. Surveys were distributed via email to directors and/or senior leaders of each hospital medicine group between January and August 2019. In the survey, a clinician investigator was defined as “faculty whose primary nonclinical focus is scientific papers and grant writing.”

We received responses from 43 of the 86 invitees (50%), each of whom represented a unique hospital medicine group; 41 of the representatives responded to the questions concerning available research services. Collectively, these 43 programs represented 2,503 hospitalists. There were 79 clinician investigators reported among all surveyed hospital medicine groups (3.1% of all hospitalists). The median number of clinician investigators per hospital medicine group was 0 (range 0-12) (Appendix Figure 1), and 22 of 43 (51.2%) hospital medicine groups reported having no clinician investigators. Two of the hospital medicine groups, however, reported having 12 clinician investigators at their respective institutions, comprising nearly one third of the total number of clinician investigators reported in the survey.

Many of the programs reported lack of access to resources such as research assistants (56.1%) and dedicated research fellowships (53.7%) (Appendix Figure 2). A number of groups reported a need for more support for various junior faculty development activities, including research mentoring (53.5%), networking with other researchers (60.5%), and access to clinical data from multiple sites (62.8%).

One of the limitations of this survey was the manner in which the participating hospital medicine groups were chosen. Selection was based on groups affiliated with HOMERuN; among those chosen were highly visible US AMCs, including 70% of the top 20 AMCs based on National Institutes of Health (NIH) funding.3 Therefore, our results likely overestimate the research presence of hospital medicine across all AMCs in the United States.

LACK OF GROWTH OVER TIME: CONTEXTUALIZATION AND IMPLICATIONS

Despite the substantial growth of hospital medicine over the past 2 decades, there has been no proportional increase in the number of hospitalist clinician investigators, with earlier surveys also demonstrating low numbers.4,5 Along with the survey by Chopra and colleagues published in 2019,6 our survey provides an additional contemporary appraisal of research activities for adult academic hospital medicine groups. In the survey by Chopra et al, only 54% (15 of 28) of responding programs reported having any faculty with research as their major activity (ie, >50% effort), and 3% of total faculty reported having funding for >50% effort toward research.6 Our study expands upon these findings by providing more detailed data on the number of clinician investigators per hospital medicine group. Results of our survey showed a concentration of hospitalists within a small number of programs, which may have contributed to the observed lack of growth. We also expand on prior work by identifying a lack of resources and services to support hospitalist researchers.

The findings of our survey have important implications for the field of hospital medicine. Without a critical mass of hospitalist clinician investigators, the quality of research that addresses important questions in our field will suffer. It will also limit academic credibility of the field, as well as individual academic achievement; previous studies have consistently demonstrated that few hospitalists at AMCs achieve the rank of associate or full professor.5-9

POTENTIAL EXPLANATIONS FOR LACK OF RESEARCH GROWTH

The results of our study additionally offer possible explanations for the dearth of clinician investigators in hospital medicine. The limited access to research resources and fellowship training identified in our survey are critical domains that must be addressed in order to develop successful academic hospital medicine programs.4,6,8,10

Regarding dedicated hospital medicine research fellowships, there are only a handful across the country. The small number of existing research fellowships only have one or two fellows per year, and these positions often go unfilled because of a lack of applicants and lower salaries compared to full-time clinical positions.11 The lack of applicants for adult hospital medicine fellowship positions is also integrally linked to board certification requirements. Unlike pediatric hospital medicine where additional fellowship training is required to become board-certified, no such fellowship is required in adult hospital medicine. In pediatrics, this requirement has led to a rapid increase in the number of fellowships with scholarly work requirements (more than 60 fellowships, plus additional programs in development) and greater standardization among training experiences.12,13

The lack of fellowship applicants may also stem from the fact that many trainees are not aware of a potential career as a hospitalist clinician investigator due to limited exposure to this career at most AMCs. Our results revealed that nearly half of sites in our survey had zero clinician investigators, depriving trainees at these programs of role models and thus perpetuating a negative feedback loop. Lastly, although unfilled fellowship positions may indicate that demand is a larger problem than supply, it is also true that fellowship programs generate their own demand through recruitment efforts and the gradual establishment of a positive reputation.

Another potential explanation could relate to the development of hospital medicine in response to rising clinical demands at hospitals: compared with other medical specialties, AMCs may regard hospitalists as being clinicians first and academicians second.1,7,10 Also, hospitalists may be perceived as being beholden to hospitals and less engaged with their surrounding communities than other general medicine fields. With a small footprint in health equity research, academic hospital medicine may be less of a draw to generalists interested in pursuing this area of research. Further, there are very few underrepresented in medicine (URiM) hospital medicine research faculty.5

Another challenge to the career development of hospitalist researchers is the lack of available funding for the type of research typically conducted by hospitalists (eg, rigorous quality improvement implementation and evaluation, optimizing best evidence-based care delivery models, evaluation of patient safety in the hospital setting). As hospitalists tend to be system-level thinkers, this lack of funding may steer potential researchers away from externally funded research careers and into hospital operations and quality improvement positions. Also, unlike other medical specialties, there is no dedicated NIH funding source for hospital medicine research (eg, cardiology and the National Heart, Lung, and Blood Institute), placing hospitalists at a disadvantage in seeking funding compared to subspecialists.

STRATEGIES TO ENHANCE RESEARCH PRESENCE

We recommend several approaches—ones that should be pursued simultaneously—to increase the number of clinician investigators in hospital medicine. First, hospital medicine groups and their respective divisions, departments, and hospitals should allocate funding to support research resources; this includes investing in research assistants, data analysts, statisticians, and administrative support. Through the funding of such research infrastructure programs, AMCs could incentivize hospitalists to research best approaches to improve the value of healthcare delivery, ultimately leading to cost savings.

With 60% of respondents identifying the need for improved access to data across multiple sites, our survey also emphasizes the requirement for further collaboration among hospital medicine groups. Such collaboration could lead to high-powered observational studies and the evaluation of interventions across multiple sites, thus improving the generalizability of study findings.

The Society of Hospital Medicine (SHM) and its research committee can continue to expand the research footprint of hospital medicine. To date, the committee has achieved this by highlighting hospitalist research activity at the SHM Annual Conference Scientific Abstract and Poster Competition and developing a visiting professorship exchange program. In addition to these efforts, SHM could foster collaboration and networking between institutions, as well as take advantage of the current political push for expanded Medicare access by lobbying for robust funding for the Agency for Healthcare Research and Quality, which could provide more opportunities for hospitalists to study the effects of healthcare policy reform on the delivery of inpatient care.

Another strategy to increase the number of hospitalist clinician investigators is to expand hospital medicine research fellowships and recruit trainees for these programs. Fellowships could be internally funded wherein a fellow’s clinical productivity is used to offset the costs associated with obtaining advanced degrees. As an incentive to encourage applicants to temporarily forego a full-time clinical salary during fellowship, hospital medicine groups could offer expanded moonlighting opportunities and contribute to repayment of medical school loans. Hospital medicine groups should also advocate for NIH-funded T32 or K12 training grants for hospital medicine. (There are, however, challenges with this approach because the number of T32 spots per NIH institute is usually fixed). The success of academic emergency medicine offers a precedent for such efforts: After the development of a K12 research training program in emergency medicine, the number of NIH-sponsored principal investigators in this specialty increased by 40% in 6 years.14 Additionally, now that fellowships are required for the pediatric hospital medicine clinician investigators, it would be revealing to track the growth of this workforce.12,13

Structured and formalized mentorship is an essential part of the development of clinician investigators in hospital medicine.4,7,8,10 One successful strategy for mentorship has been the partnering of hospital medicine groups with faculty of general internal medicine and other subspecialty divisions with robust research programs.7,8,15 In addition to developing sustainable mentorship programs, hospital medicine researchers must increase their visibility to trainees. Therefore, it is essential that the majority of academic hospital medicine groups not only hire clinician investigators but also invest in their development, rather than rely on the few programs that have several such faculty members. With this strategy, we could dramatically increase the number of hospitalist clinician investigators from a diverse background of training institutions.

SHM could also play a greater role in organizing events for networking and mentoring for trainees and medical students interested in pursuing a career in hospital medicine research. It is also critically important that hospital medicine groups actively recruit, retain, and develop URiM hospital medicine research faculty in order to attract talented researchers and actively participate in the necessary effort to mitigate the inequities prevalent throughout our healthcare system.

CONCLUSION

Despite the growth of hospital medicine over the past decade, there remains a dearth of hospitalist clinician investigators at major AMCs in the United States. This may be due in part to lack of research resources and mentorship within hospital medicine groups. We believe that investment in these resources, expanded funding opportunities, mentorship development, research fellowship programs, and greater exposure of trainees to hospitalist researchers are solutions that should be strongly considered to develop hospitalist clinician investigators.

Acknowledgments

The authors thank HOMERuN executive committee members, including Grant Fletcher, MD, James Harrison, PhD, BSC, MPH, Peter K. Lindenauer, MD, Melissa Mattison, MD, David Meltzer, MD, PhD, Joshua Metlay, MD, PhD, Jennifer Myers, MD, Sumant Ranji, MD, Gregory Ruhnke, MD, MPH, Edmondo Robinson, MD, MBA, and Neil Sehgal, MPH PhD, for their assistance in developing the survey. They also thank Tiffany Lee, MA, for her project management assistance for HOMERuN.

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References

1. Wachter RM, Goldman L. Zero to 50,000 – The 20th anniversary of the hospitalist. N Engl J Med. 2016;375(11):1009-1011. https://doi.org/10.1056/NEJMp1607958
2. Auerbach AD, Patel MS, Metlay JP, et al. The Hospital Medicine Reengineering Network (HOMERuN): a learning organization focused on improving hospital care. Acad Med. 2014;89(3):415-420. https://doi.org/10.1097/acm.0000000000000139
3. Roskoski R Jr, Parslow TG. Ranking Tables of NIH funding to US medical schools in 2019. Blue Ridge Institute for Medical Research. Published 2020. Updated July 14, 2020. Accessed July 30, 2020. http://www.brimr.org/NIH_Awards/2019/NIH_Awards_2019.htm
4. Reid MB, Misky GJ, Harrison RA, Sharpe B, Auerbach A, Glasheen JJ. Mentorship, productivity, and promotion among academic hospitalists. J Gen Intern Med. 2012;27(1):23-27. https://doi.org/10.1007/s11606-011-1892-5
5. Miller CS, Fogerty RL, Gann J, Bruti CP, Klein R; The Society of General Internal Medicine Membership Committee. The growth of hospitalists and the future of the society of general internal medicine: results from the 2014 membership survey. J Gen Intern Med. 2017;32(11):1179-1185. https://doi.org/10.1007/s11606-017-4126-7
6. Chopra V, Burden M, Jones CD, et al; Society of Hospital Medicine Research Committee. State of research in adult hospital medicine: results of a national survey. J Hosp Med. 2019;14(4):207-211. https://doi.org/10.12788/jhm.3136
7. Seymann GB, Southern W, Burger A, et al. Features of successful academic hospitalist programs: insights from the SCHOLAR (SuCcessful HOspitaLists in academics and research) project. J Hosp Med. 2016;11(10):708-713. https://doi.org/10.1002/jhm.2603
8. Harrison R, Hunter AJ, Sharpe B, Auerbach AD. Survey of US academic hospitalist leaders about mentorship and academic activities in hospitalist groups. J Hosp Med. 2011;6(1):5-9. https://doi.org/10.1002/jhm.836
9. Dang Do AN, Munchhof AM, Terry C, Emmett T, Kara A. Research and publication trends in hospital medicine. J Hosp Med. 2014;9(3):148-154. https://doi.org/10.1002/jhm.2148
10. Sehgal NL, Sharpe BA, Auerbach AA, Wachter RM. Investing in the future: building an academic hospitalist faculty development program. J Hosp Med. 2011;6(3):161-166. https://doi.org/10.1002/jhm.845
11. Ranji SR, Rosenman DJ, Amin AN, Kripalani S. Hospital medicine fellowships: works in progress. Am J Med. 2006;119(1):72.e1-72.e7. https://doi.org/10.1016/j.amjmed.2005.07.061
12. Shah NH, Rhim HJ, Maniscalco J, Wilson K, Rassbach C. The current state of pediatric hospital medicine fellowships: a survey of program directors. J Hosp Med. 2016;11(5):324-328. https://doi.org/10.1002/jhm.2571
13. Jerardi KE, Fisher E, Rassbach C, et al; Council of Pediatric Hospital Medicine Fellowship Directors. Development of a curricular framework for pediatric hospital medicine fellowships. Pediatrics. 2017;140(1):e20170698. https://doi.org/10.1542/peds.2017-0698
14. Lewis RJ, Neumar RW. Research in emergency medicine: building the investigator pipeline. Ann Emerg Med. 2018;72(6):691-695. https://doi.org/10.1016/j.annemergmed.2018.10.019
15. Flanders SA, Kaufman SR, Nallamothu BK, Saint S. The University of Michigan Specialist-Hospitalist Allied Research Program: jumpstarting hospital medicine research. J Hosp Med. 2008;3(4):308-313. https://doi.org/10.1002/jhm.342

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1Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, Massachusetts; 2Harvard Medical School, Boston, Massachusetts; 3Division of Hospital Medicine, University of Michigan Medicine, Ann Arbor, Michigan; 4Section of Hospital Medicine, Division of General Internal Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; 5Leonard Davis Institute of Health Economics, The Wharton School at the University of Pennsylvania, Philadelphia, Pennsylvania; 6Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts; 7Section of Hospital Medicine, Division of General Internal Medicine and Public Health, Vanderbilt University, Nashville, Tennessee; 8Center for Clinical Quality and Implementation Research, Vanderbilt University, Nashville, Tennessee; 9Division of Hospital Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois; 10Geriatric Research Education and Clinical Center, VA Tennessee Valley, Nashville, Tennessee; 11Center for Health Services Research, University of Kentucky, Lexington, Kentucky; 12Division of Hospital Medicine, University of California San Francisco, San Francisco, California.

Disclosures

Dr Schnipper was the recipient of an investigator-initiated grant from Mallinckrodt Pharmaceuticals regarding postsurgical opioid-related adverse drug events, outside of the submitted work. The other authors have nothing to disclose.

Funding

Dr Herzig reports receiving grant support from the Agency for Healthcare Research and Quality, outside of the submitted work. Dr Vasilevskis is the recipient of a National Institutes of Health grant, outside of the submitted work. He and Dr Chopra are US government employees and participated in creation of this paper as part of their official duties.

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1Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, Massachusetts; 2Harvard Medical School, Boston, Massachusetts; 3Division of Hospital Medicine, University of Michigan Medicine, Ann Arbor, Michigan; 4Section of Hospital Medicine, Division of General Internal Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; 5Leonard Davis Institute of Health Economics, The Wharton School at the University of Pennsylvania, Philadelphia, Pennsylvania; 6Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts; 7Section of Hospital Medicine, Division of General Internal Medicine and Public Health, Vanderbilt University, Nashville, Tennessee; 8Center for Clinical Quality and Implementation Research, Vanderbilt University, Nashville, Tennessee; 9Division of Hospital Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois; 10Geriatric Research Education and Clinical Center, VA Tennessee Valley, Nashville, Tennessee; 11Center for Health Services Research, University of Kentucky, Lexington, Kentucky; 12Division of Hospital Medicine, University of California San Francisco, San Francisco, California.

Disclosures

Dr Schnipper was the recipient of an investigator-initiated grant from Mallinckrodt Pharmaceuticals regarding postsurgical opioid-related adverse drug events, outside of the submitted work. The other authors have nothing to disclose.

Funding

Dr Herzig reports receiving grant support from the Agency for Healthcare Research and Quality, outside of the submitted work. Dr Vasilevskis is the recipient of a National Institutes of Health grant, outside of the submitted work. He and Dr Chopra are US government employees and participated in creation of this paper as part of their official duties.

Author and Disclosure Information

1Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, Massachusetts; 2Harvard Medical School, Boston, Massachusetts; 3Division of Hospital Medicine, University of Michigan Medicine, Ann Arbor, Michigan; 4Section of Hospital Medicine, Division of General Internal Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; 5Leonard Davis Institute of Health Economics, The Wharton School at the University of Pennsylvania, Philadelphia, Pennsylvania; 6Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts; 7Section of Hospital Medicine, Division of General Internal Medicine and Public Health, Vanderbilt University, Nashville, Tennessee; 8Center for Clinical Quality and Implementation Research, Vanderbilt University, Nashville, Tennessee; 9Division of Hospital Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois; 10Geriatric Research Education and Clinical Center, VA Tennessee Valley, Nashville, Tennessee; 11Center for Health Services Research, University of Kentucky, Lexington, Kentucky; 12Division of Hospital Medicine, University of California San Francisco, San Francisco, California.

Disclosures

Dr Schnipper was the recipient of an investigator-initiated grant from Mallinckrodt Pharmaceuticals regarding postsurgical opioid-related adverse drug events, outside of the submitted work. The other authors have nothing to disclose.

Funding

Dr Herzig reports receiving grant support from the Agency for Healthcare Research and Quality, outside of the submitted work. Dr Vasilevskis is the recipient of a National Institutes of Health grant, outside of the submitted work. He and Dr Chopra are US government employees and participated in creation of this paper as part of their official duties.

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In their report celebrating the increase in the number of hospitalists from a few hundred in the 1990s to more than 50,000 in 2016, Drs Robert Wachter and Lee Goldman also noted the stunted growth of productive hospital medicine research programs, which presents a challenge to academic credibility in hospital medicine.1 Given the substantial increase in the number of hospitalists over the past two decades, we surveyed adult academic hospital medicine groups to quantify the number of hospitalist clinician investigators and identify gaps in resources for researchers. The number of clinician investigators supported at academic medical centers (AMCs) remains disturbingly low despite the rapid growth of our specialty. Some programs also reported a lack of access to fundamental research services. We report selected results from our survey and provide recommendations to support and facilitate the development of clinician investigators in hospital medicine.

DEARTH OF CLINICIAN INVESTIGATORS IN HOSPITAL MEDICINE

We performed a survey of hospital medicine programs at AMCs in the United States through the Hospital Medicine Reengineering Network (HOMERuN), a hospital medicine research collaborative that facilitates and conducts multisite research studies.2 The purpose of this survey was to obtain a profile of adult academic hospital medicine groups. Surveys were distributed via email to directors and/or senior leaders of each hospital medicine group between January and August 2019. In the survey, a clinician investigator was defined as “faculty whose primary nonclinical focus is scientific papers and grant writing.”

We received responses from 43 of the 86 invitees (50%), each of whom represented a unique hospital medicine group; 41 of the representatives responded to the questions concerning available research services. Collectively, these 43 programs represented 2,503 hospitalists. There were 79 clinician investigators reported among all surveyed hospital medicine groups (3.1% of all hospitalists). The median number of clinician investigators per hospital medicine group was 0 (range 0-12) (Appendix Figure 1), and 22 of 43 (51.2%) hospital medicine groups reported having no clinician investigators. Two of the hospital medicine groups, however, reported having 12 clinician investigators at their respective institutions, comprising nearly one third of the total number of clinician investigators reported in the survey.

Many of the programs reported lack of access to resources such as research assistants (56.1%) and dedicated research fellowships (53.7%) (Appendix Figure 2). A number of groups reported a need for more support for various junior faculty development activities, including research mentoring (53.5%), networking with other researchers (60.5%), and access to clinical data from multiple sites (62.8%).

One of the limitations of this survey was the manner in which the participating hospital medicine groups were chosen. Selection was based on groups affiliated with HOMERuN; among those chosen were highly visible US AMCs, including 70% of the top 20 AMCs based on National Institutes of Health (NIH) funding.3 Therefore, our results likely overestimate the research presence of hospital medicine across all AMCs in the United States.

LACK OF GROWTH OVER TIME: CONTEXTUALIZATION AND IMPLICATIONS

Despite the substantial growth of hospital medicine over the past 2 decades, there has been no proportional increase in the number of hospitalist clinician investigators, with earlier surveys also demonstrating low numbers.4,5 Along with the survey by Chopra and colleagues published in 2019,6 our survey provides an additional contemporary appraisal of research activities for adult academic hospital medicine groups. In the survey by Chopra et al, only 54% (15 of 28) of responding programs reported having any faculty with research as their major activity (ie, >50% effort), and 3% of total faculty reported having funding for >50% effort toward research.6 Our study expands upon these findings by providing more detailed data on the number of clinician investigators per hospital medicine group. Results of our survey showed a concentration of hospitalists within a small number of programs, which may have contributed to the observed lack of growth. We also expand on prior work by identifying a lack of resources and services to support hospitalist researchers.

The findings of our survey have important implications for the field of hospital medicine. Without a critical mass of hospitalist clinician investigators, the quality of research that addresses important questions in our field will suffer. It will also limit academic credibility of the field, as well as individual academic achievement; previous studies have consistently demonstrated that few hospitalists at AMCs achieve the rank of associate or full professor.5-9

POTENTIAL EXPLANATIONS FOR LACK OF RESEARCH GROWTH

The results of our study additionally offer possible explanations for the dearth of clinician investigators in hospital medicine. The limited access to research resources and fellowship training identified in our survey are critical domains that must be addressed in order to develop successful academic hospital medicine programs.4,6,8,10

Regarding dedicated hospital medicine research fellowships, there are only a handful across the country. The small number of existing research fellowships only have one or two fellows per year, and these positions often go unfilled because of a lack of applicants and lower salaries compared to full-time clinical positions.11 The lack of applicants for adult hospital medicine fellowship positions is also integrally linked to board certification requirements. Unlike pediatric hospital medicine where additional fellowship training is required to become board-certified, no such fellowship is required in adult hospital medicine. In pediatrics, this requirement has led to a rapid increase in the number of fellowships with scholarly work requirements (more than 60 fellowships, plus additional programs in development) and greater standardization among training experiences.12,13

The lack of fellowship applicants may also stem from the fact that many trainees are not aware of a potential career as a hospitalist clinician investigator due to limited exposure to this career at most AMCs. Our results revealed that nearly half of sites in our survey had zero clinician investigators, depriving trainees at these programs of role models and thus perpetuating a negative feedback loop. Lastly, although unfilled fellowship positions may indicate that demand is a larger problem than supply, it is also true that fellowship programs generate their own demand through recruitment efforts and the gradual establishment of a positive reputation.

Another potential explanation could relate to the development of hospital medicine in response to rising clinical demands at hospitals: compared with other medical specialties, AMCs may regard hospitalists as being clinicians first and academicians second.1,7,10 Also, hospitalists may be perceived as being beholden to hospitals and less engaged with their surrounding communities than other general medicine fields. With a small footprint in health equity research, academic hospital medicine may be less of a draw to generalists interested in pursuing this area of research. Further, there are very few underrepresented in medicine (URiM) hospital medicine research faculty.5

Another challenge to the career development of hospitalist researchers is the lack of available funding for the type of research typically conducted by hospitalists (eg, rigorous quality improvement implementation and evaluation, optimizing best evidence-based care delivery models, evaluation of patient safety in the hospital setting). As hospitalists tend to be system-level thinkers, this lack of funding may steer potential researchers away from externally funded research careers and into hospital operations and quality improvement positions. Also, unlike other medical specialties, there is no dedicated NIH funding source for hospital medicine research (eg, cardiology and the National Heart, Lung, and Blood Institute), placing hospitalists at a disadvantage in seeking funding compared to subspecialists.

STRATEGIES TO ENHANCE RESEARCH PRESENCE

We recommend several approaches—ones that should be pursued simultaneously—to increase the number of clinician investigators in hospital medicine. First, hospital medicine groups and their respective divisions, departments, and hospitals should allocate funding to support research resources; this includes investing in research assistants, data analysts, statisticians, and administrative support. Through the funding of such research infrastructure programs, AMCs could incentivize hospitalists to research best approaches to improve the value of healthcare delivery, ultimately leading to cost savings.

With 60% of respondents identifying the need for improved access to data across multiple sites, our survey also emphasizes the requirement for further collaboration among hospital medicine groups. Such collaboration could lead to high-powered observational studies and the evaluation of interventions across multiple sites, thus improving the generalizability of study findings.

The Society of Hospital Medicine (SHM) and its research committee can continue to expand the research footprint of hospital medicine. To date, the committee has achieved this by highlighting hospitalist research activity at the SHM Annual Conference Scientific Abstract and Poster Competition and developing a visiting professorship exchange program. In addition to these efforts, SHM could foster collaboration and networking between institutions, as well as take advantage of the current political push for expanded Medicare access by lobbying for robust funding for the Agency for Healthcare Research and Quality, which could provide more opportunities for hospitalists to study the effects of healthcare policy reform on the delivery of inpatient care.

Another strategy to increase the number of hospitalist clinician investigators is to expand hospital medicine research fellowships and recruit trainees for these programs. Fellowships could be internally funded wherein a fellow’s clinical productivity is used to offset the costs associated with obtaining advanced degrees. As an incentive to encourage applicants to temporarily forego a full-time clinical salary during fellowship, hospital medicine groups could offer expanded moonlighting opportunities and contribute to repayment of medical school loans. Hospital medicine groups should also advocate for NIH-funded T32 or K12 training grants for hospital medicine. (There are, however, challenges with this approach because the number of T32 spots per NIH institute is usually fixed). The success of academic emergency medicine offers a precedent for such efforts: After the development of a K12 research training program in emergency medicine, the number of NIH-sponsored principal investigators in this specialty increased by 40% in 6 years.14 Additionally, now that fellowships are required for the pediatric hospital medicine clinician investigators, it would be revealing to track the growth of this workforce.12,13

Structured and formalized mentorship is an essential part of the development of clinician investigators in hospital medicine.4,7,8,10 One successful strategy for mentorship has been the partnering of hospital medicine groups with faculty of general internal medicine and other subspecialty divisions with robust research programs.7,8,15 In addition to developing sustainable mentorship programs, hospital medicine researchers must increase their visibility to trainees. Therefore, it is essential that the majority of academic hospital medicine groups not only hire clinician investigators but also invest in their development, rather than rely on the few programs that have several such faculty members. With this strategy, we could dramatically increase the number of hospitalist clinician investigators from a diverse background of training institutions.

SHM could also play a greater role in organizing events for networking and mentoring for trainees and medical students interested in pursuing a career in hospital medicine research. It is also critically important that hospital medicine groups actively recruit, retain, and develop URiM hospital medicine research faculty in order to attract talented researchers and actively participate in the necessary effort to mitigate the inequities prevalent throughout our healthcare system.

CONCLUSION

Despite the growth of hospital medicine over the past decade, there remains a dearth of hospitalist clinician investigators at major AMCs in the United States. This may be due in part to lack of research resources and mentorship within hospital medicine groups. We believe that investment in these resources, expanded funding opportunities, mentorship development, research fellowship programs, and greater exposure of trainees to hospitalist researchers are solutions that should be strongly considered to develop hospitalist clinician investigators.

Acknowledgments

The authors thank HOMERuN executive committee members, including Grant Fletcher, MD, James Harrison, PhD, BSC, MPH, Peter K. Lindenauer, MD, Melissa Mattison, MD, David Meltzer, MD, PhD, Joshua Metlay, MD, PhD, Jennifer Myers, MD, Sumant Ranji, MD, Gregory Ruhnke, MD, MPH, Edmondo Robinson, MD, MBA, and Neil Sehgal, MPH PhD, for their assistance in developing the survey. They also thank Tiffany Lee, MA, for her project management assistance for HOMERuN.

In their report celebrating the increase in the number of hospitalists from a few hundred in the 1990s to more than 50,000 in 2016, Drs Robert Wachter and Lee Goldman also noted the stunted growth of productive hospital medicine research programs, which presents a challenge to academic credibility in hospital medicine.1 Given the substantial increase in the number of hospitalists over the past two decades, we surveyed adult academic hospital medicine groups to quantify the number of hospitalist clinician investigators and identify gaps in resources for researchers. The number of clinician investigators supported at academic medical centers (AMCs) remains disturbingly low despite the rapid growth of our specialty. Some programs also reported a lack of access to fundamental research services. We report selected results from our survey and provide recommendations to support and facilitate the development of clinician investigators in hospital medicine.

DEARTH OF CLINICIAN INVESTIGATORS IN HOSPITAL MEDICINE

We performed a survey of hospital medicine programs at AMCs in the United States through the Hospital Medicine Reengineering Network (HOMERuN), a hospital medicine research collaborative that facilitates and conducts multisite research studies.2 The purpose of this survey was to obtain a profile of adult academic hospital medicine groups. Surveys were distributed via email to directors and/or senior leaders of each hospital medicine group between January and August 2019. In the survey, a clinician investigator was defined as “faculty whose primary nonclinical focus is scientific papers and grant writing.”

We received responses from 43 of the 86 invitees (50%), each of whom represented a unique hospital medicine group; 41 of the representatives responded to the questions concerning available research services. Collectively, these 43 programs represented 2,503 hospitalists. There were 79 clinician investigators reported among all surveyed hospital medicine groups (3.1% of all hospitalists). The median number of clinician investigators per hospital medicine group was 0 (range 0-12) (Appendix Figure 1), and 22 of 43 (51.2%) hospital medicine groups reported having no clinician investigators. Two of the hospital medicine groups, however, reported having 12 clinician investigators at their respective institutions, comprising nearly one third of the total number of clinician investigators reported in the survey.

Many of the programs reported lack of access to resources such as research assistants (56.1%) and dedicated research fellowships (53.7%) (Appendix Figure 2). A number of groups reported a need for more support for various junior faculty development activities, including research mentoring (53.5%), networking with other researchers (60.5%), and access to clinical data from multiple sites (62.8%).

One of the limitations of this survey was the manner in which the participating hospital medicine groups were chosen. Selection was based on groups affiliated with HOMERuN; among those chosen were highly visible US AMCs, including 70% of the top 20 AMCs based on National Institutes of Health (NIH) funding.3 Therefore, our results likely overestimate the research presence of hospital medicine across all AMCs in the United States.

LACK OF GROWTH OVER TIME: CONTEXTUALIZATION AND IMPLICATIONS

Despite the substantial growth of hospital medicine over the past 2 decades, there has been no proportional increase in the number of hospitalist clinician investigators, with earlier surveys also demonstrating low numbers.4,5 Along with the survey by Chopra and colleagues published in 2019,6 our survey provides an additional contemporary appraisal of research activities for adult academic hospital medicine groups. In the survey by Chopra et al, only 54% (15 of 28) of responding programs reported having any faculty with research as their major activity (ie, >50% effort), and 3% of total faculty reported having funding for >50% effort toward research.6 Our study expands upon these findings by providing more detailed data on the number of clinician investigators per hospital medicine group. Results of our survey showed a concentration of hospitalists within a small number of programs, which may have contributed to the observed lack of growth. We also expand on prior work by identifying a lack of resources and services to support hospitalist researchers.

The findings of our survey have important implications for the field of hospital medicine. Without a critical mass of hospitalist clinician investigators, the quality of research that addresses important questions in our field will suffer. It will also limit academic credibility of the field, as well as individual academic achievement; previous studies have consistently demonstrated that few hospitalists at AMCs achieve the rank of associate or full professor.5-9

POTENTIAL EXPLANATIONS FOR LACK OF RESEARCH GROWTH

The results of our study additionally offer possible explanations for the dearth of clinician investigators in hospital medicine. The limited access to research resources and fellowship training identified in our survey are critical domains that must be addressed in order to develop successful academic hospital medicine programs.4,6,8,10

Regarding dedicated hospital medicine research fellowships, there are only a handful across the country. The small number of existing research fellowships only have one or two fellows per year, and these positions often go unfilled because of a lack of applicants and lower salaries compared to full-time clinical positions.11 The lack of applicants for adult hospital medicine fellowship positions is also integrally linked to board certification requirements. Unlike pediatric hospital medicine where additional fellowship training is required to become board-certified, no such fellowship is required in adult hospital medicine. In pediatrics, this requirement has led to a rapid increase in the number of fellowships with scholarly work requirements (more than 60 fellowships, plus additional programs in development) and greater standardization among training experiences.12,13

The lack of fellowship applicants may also stem from the fact that many trainees are not aware of a potential career as a hospitalist clinician investigator due to limited exposure to this career at most AMCs. Our results revealed that nearly half of sites in our survey had zero clinician investigators, depriving trainees at these programs of role models and thus perpetuating a negative feedback loop. Lastly, although unfilled fellowship positions may indicate that demand is a larger problem than supply, it is also true that fellowship programs generate their own demand through recruitment efforts and the gradual establishment of a positive reputation.

Another potential explanation could relate to the development of hospital medicine in response to rising clinical demands at hospitals: compared with other medical specialties, AMCs may regard hospitalists as being clinicians first and academicians second.1,7,10 Also, hospitalists may be perceived as being beholden to hospitals and less engaged with their surrounding communities than other general medicine fields. With a small footprint in health equity research, academic hospital medicine may be less of a draw to generalists interested in pursuing this area of research. Further, there are very few underrepresented in medicine (URiM) hospital medicine research faculty.5

Another challenge to the career development of hospitalist researchers is the lack of available funding for the type of research typically conducted by hospitalists (eg, rigorous quality improvement implementation and evaluation, optimizing best evidence-based care delivery models, evaluation of patient safety in the hospital setting). As hospitalists tend to be system-level thinkers, this lack of funding may steer potential researchers away from externally funded research careers and into hospital operations and quality improvement positions. Also, unlike other medical specialties, there is no dedicated NIH funding source for hospital medicine research (eg, cardiology and the National Heart, Lung, and Blood Institute), placing hospitalists at a disadvantage in seeking funding compared to subspecialists.

STRATEGIES TO ENHANCE RESEARCH PRESENCE

We recommend several approaches—ones that should be pursued simultaneously—to increase the number of clinician investigators in hospital medicine. First, hospital medicine groups and their respective divisions, departments, and hospitals should allocate funding to support research resources; this includes investing in research assistants, data analysts, statisticians, and administrative support. Through the funding of such research infrastructure programs, AMCs could incentivize hospitalists to research best approaches to improve the value of healthcare delivery, ultimately leading to cost savings.

With 60% of respondents identifying the need for improved access to data across multiple sites, our survey also emphasizes the requirement for further collaboration among hospital medicine groups. Such collaboration could lead to high-powered observational studies and the evaluation of interventions across multiple sites, thus improving the generalizability of study findings.

The Society of Hospital Medicine (SHM) and its research committee can continue to expand the research footprint of hospital medicine. To date, the committee has achieved this by highlighting hospitalist research activity at the SHM Annual Conference Scientific Abstract and Poster Competition and developing a visiting professorship exchange program. In addition to these efforts, SHM could foster collaboration and networking between institutions, as well as take advantage of the current political push for expanded Medicare access by lobbying for robust funding for the Agency for Healthcare Research and Quality, which could provide more opportunities for hospitalists to study the effects of healthcare policy reform on the delivery of inpatient care.

Another strategy to increase the number of hospitalist clinician investigators is to expand hospital medicine research fellowships and recruit trainees for these programs. Fellowships could be internally funded wherein a fellow’s clinical productivity is used to offset the costs associated with obtaining advanced degrees. As an incentive to encourage applicants to temporarily forego a full-time clinical salary during fellowship, hospital medicine groups could offer expanded moonlighting opportunities and contribute to repayment of medical school loans. Hospital medicine groups should also advocate for NIH-funded T32 or K12 training grants for hospital medicine. (There are, however, challenges with this approach because the number of T32 spots per NIH institute is usually fixed). The success of academic emergency medicine offers a precedent for such efforts: After the development of a K12 research training program in emergency medicine, the number of NIH-sponsored principal investigators in this specialty increased by 40% in 6 years.14 Additionally, now that fellowships are required for the pediatric hospital medicine clinician investigators, it would be revealing to track the growth of this workforce.12,13

Structured and formalized mentorship is an essential part of the development of clinician investigators in hospital medicine.4,7,8,10 One successful strategy for mentorship has been the partnering of hospital medicine groups with faculty of general internal medicine and other subspecialty divisions with robust research programs.7,8,15 In addition to developing sustainable mentorship programs, hospital medicine researchers must increase their visibility to trainees. Therefore, it is essential that the majority of academic hospital medicine groups not only hire clinician investigators but also invest in their development, rather than rely on the few programs that have several such faculty members. With this strategy, we could dramatically increase the number of hospitalist clinician investigators from a diverse background of training institutions.

SHM could also play a greater role in organizing events for networking and mentoring for trainees and medical students interested in pursuing a career in hospital medicine research. It is also critically important that hospital medicine groups actively recruit, retain, and develop URiM hospital medicine research faculty in order to attract talented researchers and actively participate in the necessary effort to mitigate the inequities prevalent throughout our healthcare system.

CONCLUSION

Despite the growth of hospital medicine over the past decade, there remains a dearth of hospitalist clinician investigators at major AMCs in the United States. This may be due in part to lack of research resources and mentorship within hospital medicine groups. We believe that investment in these resources, expanded funding opportunities, mentorship development, research fellowship programs, and greater exposure of trainees to hospitalist researchers are solutions that should be strongly considered to develop hospitalist clinician investigators.

Acknowledgments

The authors thank HOMERuN executive committee members, including Grant Fletcher, MD, James Harrison, PhD, BSC, MPH, Peter K. Lindenauer, MD, Melissa Mattison, MD, David Meltzer, MD, PhD, Joshua Metlay, MD, PhD, Jennifer Myers, MD, Sumant Ranji, MD, Gregory Ruhnke, MD, MPH, Edmondo Robinson, MD, MBA, and Neil Sehgal, MPH PhD, for their assistance in developing the survey. They also thank Tiffany Lee, MA, for her project management assistance for HOMERuN.

References

1. Wachter RM, Goldman L. Zero to 50,000 – The 20th anniversary of the hospitalist. N Engl J Med. 2016;375(11):1009-1011. https://doi.org/10.1056/NEJMp1607958
2. Auerbach AD, Patel MS, Metlay JP, et al. The Hospital Medicine Reengineering Network (HOMERuN): a learning organization focused on improving hospital care. Acad Med. 2014;89(3):415-420. https://doi.org/10.1097/acm.0000000000000139
3. Roskoski R Jr, Parslow TG. Ranking Tables of NIH funding to US medical schools in 2019. Blue Ridge Institute for Medical Research. Published 2020. Updated July 14, 2020. Accessed July 30, 2020. http://www.brimr.org/NIH_Awards/2019/NIH_Awards_2019.htm
4. Reid MB, Misky GJ, Harrison RA, Sharpe B, Auerbach A, Glasheen JJ. Mentorship, productivity, and promotion among academic hospitalists. J Gen Intern Med. 2012;27(1):23-27. https://doi.org/10.1007/s11606-011-1892-5
5. Miller CS, Fogerty RL, Gann J, Bruti CP, Klein R; The Society of General Internal Medicine Membership Committee. The growth of hospitalists and the future of the society of general internal medicine: results from the 2014 membership survey. J Gen Intern Med. 2017;32(11):1179-1185. https://doi.org/10.1007/s11606-017-4126-7
6. Chopra V, Burden M, Jones CD, et al; Society of Hospital Medicine Research Committee. State of research in adult hospital medicine: results of a national survey. J Hosp Med. 2019;14(4):207-211. https://doi.org/10.12788/jhm.3136
7. Seymann GB, Southern W, Burger A, et al. Features of successful academic hospitalist programs: insights from the SCHOLAR (SuCcessful HOspitaLists in academics and research) project. J Hosp Med. 2016;11(10):708-713. https://doi.org/10.1002/jhm.2603
8. Harrison R, Hunter AJ, Sharpe B, Auerbach AD. Survey of US academic hospitalist leaders about mentorship and academic activities in hospitalist groups. J Hosp Med. 2011;6(1):5-9. https://doi.org/10.1002/jhm.836
9. Dang Do AN, Munchhof AM, Terry C, Emmett T, Kara A. Research and publication trends in hospital medicine. J Hosp Med. 2014;9(3):148-154. https://doi.org/10.1002/jhm.2148
10. Sehgal NL, Sharpe BA, Auerbach AA, Wachter RM. Investing in the future: building an academic hospitalist faculty development program. J Hosp Med. 2011;6(3):161-166. https://doi.org/10.1002/jhm.845
11. Ranji SR, Rosenman DJ, Amin AN, Kripalani S. Hospital medicine fellowships: works in progress. Am J Med. 2006;119(1):72.e1-72.e7. https://doi.org/10.1016/j.amjmed.2005.07.061
12. Shah NH, Rhim HJ, Maniscalco J, Wilson K, Rassbach C. The current state of pediatric hospital medicine fellowships: a survey of program directors. J Hosp Med. 2016;11(5):324-328. https://doi.org/10.1002/jhm.2571
13. Jerardi KE, Fisher E, Rassbach C, et al; Council of Pediatric Hospital Medicine Fellowship Directors. Development of a curricular framework for pediatric hospital medicine fellowships. Pediatrics. 2017;140(1):e20170698. https://doi.org/10.1542/peds.2017-0698
14. Lewis RJ, Neumar RW. Research in emergency medicine: building the investigator pipeline. Ann Emerg Med. 2018;72(6):691-695. https://doi.org/10.1016/j.annemergmed.2018.10.019
15. Flanders SA, Kaufman SR, Nallamothu BK, Saint S. The University of Michigan Specialist-Hospitalist Allied Research Program: jumpstarting hospital medicine research. J Hosp Med. 2008;3(4):308-313. https://doi.org/10.1002/jhm.342

References

1. Wachter RM, Goldman L. Zero to 50,000 – The 20th anniversary of the hospitalist. N Engl J Med. 2016;375(11):1009-1011. https://doi.org/10.1056/NEJMp1607958
2. Auerbach AD, Patel MS, Metlay JP, et al. The Hospital Medicine Reengineering Network (HOMERuN): a learning organization focused on improving hospital care. Acad Med. 2014;89(3):415-420. https://doi.org/10.1097/acm.0000000000000139
3. Roskoski R Jr, Parslow TG. Ranking Tables of NIH funding to US medical schools in 2019. Blue Ridge Institute for Medical Research. Published 2020. Updated July 14, 2020. Accessed July 30, 2020. http://www.brimr.org/NIH_Awards/2019/NIH_Awards_2019.htm
4. Reid MB, Misky GJ, Harrison RA, Sharpe B, Auerbach A, Glasheen JJ. Mentorship, productivity, and promotion among academic hospitalists. J Gen Intern Med. 2012;27(1):23-27. https://doi.org/10.1007/s11606-011-1892-5
5. Miller CS, Fogerty RL, Gann J, Bruti CP, Klein R; The Society of General Internal Medicine Membership Committee. The growth of hospitalists and the future of the society of general internal medicine: results from the 2014 membership survey. J Gen Intern Med. 2017;32(11):1179-1185. https://doi.org/10.1007/s11606-017-4126-7
6. Chopra V, Burden M, Jones CD, et al; Society of Hospital Medicine Research Committee. State of research in adult hospital medicine: results of a national survey. J Hosp Med. 2019;14(4):207-211. https://doi.org/10.12788/jhm.3136
7. Seymann GB, Southern W, Burger A, et al. Features of successful academic hospitalist programs: insights from the SCHOLAR (SuCcessful HOspitaLists in academics and research) project. J Hosp Med. 2016;11(10):708-713. https://doi.org/10.1002/jhm.2603
8. Harrison R, Hunter AJ, Sharpe B, Auerbach AD. Survey of US academic hospitalist leaders about mentorship and academic activities in hospitalist groups. J Hosp Med. 2011;6(1):5-9. https://doi.org/10.1002/jhm.836
9. Dang Do AN, Munchhof AM, Terry C, Emmett T, Kara A. Research and publication trends in hospital medicine. J Hosp Med. 2014;9(3):148-154. https://doi.org/10.1002/jhm.2148
10. Sehgal NL, Sharpe BA, Auerbach AA, Wachter RM. Investing in the future: building an academic hospitalist faculty development program. J Hosp Med. 2011;6(3):161-166. https://doi.org/10.1002/jhm.845
11. Ranji SR, Rosenman DJ, Amin AN, Kripalani S. Hospital medicine fellowships: works in progress. Am J Med. 2006;119(1):72.e1-72.e7. https://doi.org/10.1016/j.amjmed.2005.07.061
12. Shah NH, Rhim HJ, Maniscalco J, Wilson K, Rassbach C. The current state of pediatric hospital medicine fellowships: a survey of program directors. J Hosp Med. 2016;11(5):324-328. https://doi.org/10.1002/jhm.2571
13. Jerardi KE, Fisher E, Rassbach C, et al; Council of Pediatric Hospital Medicine Fellowship Directors. Development of a curricular framework for pediatric hospital medicine fellowships. Pediatrics. 2017;140(1):e20170698. https://doi.org/10.1542/peds.2017-0698
14. Lewis RJ, Neumar RW. Research in emergency medicine: building the investigator pipeline. Ann Emerg Med. 2018;72(6):691-695. https://doi.org/10.1016/j.annemergmed.2018.10.019
15. Flanders SA, Kaufman SR, Nallamothu BK, Saint S. The University of Michigan Specialist-Hospitalist Allied Research Program: jumpstarting hospital medicine research. J Hosp Med. 2008;3(4):308-313. https://doi.org/10.1002/jhm.342

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Evan Michael Shannon, MD, MPH; Email: eshannon2@bwh.harvard.edu; Twitter: @EMShan_MD.
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Interhospital Transfer: Transfer Processes and Patient Outcomes

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The transfer of patients between acute care hospitals (interhospital transfer [IHT]) occurs regularly among patients with a variety of diagnoses, in theory, to gain access to unique specialty services and/or a higher level of care, among other reasons.1,2

However, the practice of IHT is variable and nonstandardized,3,4 and existing data largely suggests that transferred patients experience worse outcomes, including longer length of stay, higher hospitalization costs, longer ICU time, and greater mortality, even with rigorous adjustment for confounding by indication.5,6 Though there are many possible reasons for these findings, existing literature suggests that there may be aspects of the transfer process itself which contribute to these outcomes.2,6,7

Understanding which aspects of the transfer process contribute to poor patient outcomes is a key first step toward the development of targeted quality improvement initiatives to improve this process of care. In this study, we aim to examine the association between select characteristics of the transfer process, including the timing of transfer and workload of the admitting physician team, and clinical outcomes among patients undergoing IHT.

METHODS

Data and Study Population

We performed a retrospective analysis of patients ≥age 18 years who transferred to Brigham and Women’s Hospital (BWH), a 777-bed tertiary care hospital, from another acute care hospital between January 2005, and September 2013. Dates of inclusion were purposefully chosen prior to BWH implementation of a new electronic health records system to avoid potential information bias. As at most academic medical centers, night coverage at BWH differs by service and includes a combination of long-call admitting teams and night float coverage. On weekends, many services are less well staffed, and some procedures may only be available if needed emergently. Some services have caps on the daily number of admissions or total patient census, but none have caps on the number of discharges per day. Patients were excluded from analysis if they left BWH against medical advice, were transferred from closely affiliated hospitals with shared personnel and electronic health records (Brigham and Women’s Faulkner Hospital, Dana Farber Cancer Institute), transferred from inpatient psychiatric or inpatient hospice facilities, or transferred to obstetrics or nursery services. Data were obtained from administrative sources and the research patient data repository (RPDR), a centralized clinical data repository that gathers data from various hospital legacy systems and stores them in one data warehouse.8 Our study was approved by the Partners Institutional Review Board (IRB) with a waiver of patient consent.

Transfer Process Characteristics

Predictors included select characteristics of the transfer process, including (1) Day of week of transfer, dichotomized into Friday through Sunday (“weekend”), versus Monday through Thursday (“weekday”);9 Friday was included with “weekend” given the suggestion of increased volume of transfers in advance of the weekend; (2) Time of arrival of the transferred patient, categorized into “daytime” (7 am-5 pm), “evening” (5 pm -10 pm), and “nighttime” (10 pm -7 am), with daytime as the reference group; (3) Admitting team “busyness” on day of patient transfer, defined as the total number of additional patient admissions and patient discharges performed by the admitting team on the calendar day of patient arrival, as has been used in prior research,10 and categorized into quartiles with lowest quartile as the reference group. Service-specific quartiles were calculated and used for stratified analyses (described below); and (4) “Time delay” between patient acceptance for transfer and patient arrival at BWH, categorized into 0-12 hours, 12-24 hours, 24-48 hours, and >48 hours, with 12-24 hours as the reference group (anticipating that time delay of 0-12 hours would be reflective of “sicker” patients in need of expedited transfer).

 

 

Outcomes

Outcomes included transfer to the intensive care unit (ICU) within 48 hours of arrival and 30-day mortality from date of index admission.5,6

Patient Characteristics

Covariates for adjustment included: patient age, sex, race, Elixhauser comorbidity score,11 Diagnosis-Related Group (DRG)-weight, insurance status, year of admission, number of preadmission medications, and service of admission.

Statistical Analyses

We used descriptive statistics to display baseline characteristics and performed a series of univariable and multivariable logistic regression models to obtain the adjusted odds of each transfer process characteristic on each outcome, adjusting for all covariates (proc logistic, SAS Statistical Software, Cary, North Carolina). For analyses of ICU transfer within 48 hours of arrival, all patients initially admitted to the ICU at time of transfer were excluded.

In the secondary analyses, we used a combined day-of-week and time-of-day variable (ie, Monday day, Monday evening, Monday night, Tuesday day, and so on, with Monday day as the reference group) to obtain a more detailed evaluation of timing of transfer on patient outcomes. We also performed stratified analyses to evaluate each transfer process characteristic on adjusted odds of 30-day mortality stratified by service of admission (ie, at the time of transfer to BWH), adjusting for all covariates. For all analyses, two-sided P values < .05 were considered significant.

RESULTS

Overall, 24,352 patients met our inclusion criteria and underwent IHT, of whom 2,174 (8.9%) died within 30 days. Of the 22,910 transferred patients originally admitted to a non-ICU service, 5,464 (23.8%) underwent ICU transfer within 48 hours of arrival. Cohort characteristics are shown in Table 1.

mueller0666-0408e_t1.jpg

Multivariable regression analyses demonstrated no significant association between weekend (versus weekday) transfer or increased time delay between patient acceptance and arrival (>48 hours) and adjusted odds of ICU transfer within 48 hours or 30-day mortality. However, they did demonstrate that nighttime (versus daytime) transfer was associated with greater adjusted odds of both ICU transfer and 30-day mortality. Increased admitting team busyness was associated with lower adjusted odds of ICU transfer but was not significantly associated with adjusted odds of 30-day mortality (Table 2). As expected, decreased time delay between patient acceptance and arrival (0-12 hours) was associated with increased adjusted odds of both ICU transfer (adjusted OR 2.68; 95% CI 2.29, 3.15) and 30-day mortality (adjusted OR 1.25; 95% CI 1.03, 1.53) compared with 12-24 hours (results not shown). Time delay >48 hours was not associated with either outcome.

Regression analyses with the combined day/time variable demonstrated that compared with Monday daytime transfer, Sunday night transfer was significantly associated with increased adjusted odds of 30-day mortality, and Friday night transfer was associated with a trend toward increased 30-day mortality (adjusted OR [aOR] 1.88; 95% CI 1.25, 2.82, and aOR 1.43; 95% CI 0.99, 2.06, respectively). We also found that all nighttime transfers (ie, Monday through Sunday night) were associated with increased adjusted odds of ICU transfer within 48 hours (as compared with Monday daytime transfer). Other days/time analyses were not significant.

Univariable and multivariable analyses stratified by service were performed (Appendix). Multivariable stratified analyses demonstrated that weekend transfer, nighttime transfer, and increased admitting team busyness were associated with increased adjusted odds of 30-day mortality among cardiothoracic (CT) and gastrointestinal (GI) surgical service patients. Increased admitting team busyness was also associated with increased mortality among ICU service patients but was associated with decreased mortality among cardiology service patients. An increased time delay between patient acceptance and arrival was associated with decreased mortality among CT and GI surgical service patients (Figure; Appendix). Other adjusted stratified outcomes were not significant.

mueller0666-0408e_t2.jpg

 

 

DISCUSSION

In this study of 24,352 patients undergoing IHT, we found no significant association between weekend transfer or increased time delay between transfer acceptance and arrival and patient outcomes in the cohort as a whole; but we found that nighttime transfer is associated with increased adjusted odds of both ICU transfer within 48 hours and 30-day mortality. Our analyses combining day-of-week and time-of-day demonstrate that Sunday night transfer is particularly associated with increased adjusted odds of 30-day mortality (as compared with Monday daytime transfer), and show a trend toward increased mortality with Friday night transfers. These detailed analyses otherwise reinforce that nighttime transfer across all nights of the week is associated with increased adjusted odds of ICU transfer within 48 hours. We also found that increased admitting team busyness on the day of patient transfer is associated with decreased odds of ICU transfer, though this may solely be reflective of higher turnover services (ie, cardiology) caring for lower acuity patients, as suggested by secondary analyses stratified by service. In addition, secondary analyses demonstrated differential associations between weekend transfers, nighttime transfers, and increased team busyness on the odds of 30-day mortality based on service of transfer. These analyses showed that patients transferred to higher acuity services requiring procedural care, including CT surgery, GI surgery, and Medical ICU, do worse under all three circumstances as compared with patients transferred to other services. Secondary analyses also demonstrated that increased time delay between patient acceptance and arrival is inversely associated with 30-day mortality among CT and GI surgery service patients, likely reflecting lower acuity patients (ie, less sick patients are less rapidly transferred).

There are several possible explanations for these findings. Patients transferred to surgical services at night may reflect a more urgent need for surgery and include a sicker cohort of patients, possibly explaining these findings. Alternatively, or in addition, both weekend and nighttime hospital admission expose patients to similar potential risks, ie, limited resources available during off-peak hours. Our findings could, therefore, reflect the possibility that patients transferred to higher acuity services in need of procedural care are most vulnerable to off-peak timing of transfer. Similar data looking at patients admitted through the emergency room (ER) find the strongest effect of off-peak admissions on patients in need of procedures, including GI hemorrhage,12 atrial fibrillation13 and acute myocardial infarction (AMI),14 arguably because of the limited availability of necessary interventions. Patients undergoing IHT are a sicker cohort of patients than those admitted through the ER, and, therefore, may be even more vulnerable to these issues.3,5 This is supported by our findings that Sunday night transfers (and trend toward Friday night transfers) are associated with greater mortality compared with Monday daytime transfers, when at-the-ready resources and/or specialty personnel may be less available (Sunday night), and delays until receipt of necessary procedures may be longer (Friday night). Though we did not observe similar results among cardiology service transfers, as may be expected based on existing literature,13,14 this subset of patients includes more heterogeneous diagnoses, (ie, not solely those that require acute intervention) and exhibited a low level of acuity (low Elixhauser score and DRG-weight, data not shown).

mueller0666-0408e_f1.jpg


We also found that increased admitting team busyness on the day of patient transfer is associated with increased odds of 30-day mortality among CT surgery, GI surgery, and ICU service transfers. As above, there are several possible explanations for this finding. It is possible that among these services, only the sickest/neediest patients are accepted for transfer when teams are busiest, explaining our findings. Though this explanation is possible, the measure of team “busyness” includes patient discharge, thereby increasing, not decreasing, availability for incoming patients, making this explanation less likely. Alternatively, it is possible that this finding is reflective of reverse causation, ie, that teams have less ability to discharge/admit new patients when caring for particularly sick/unstable patient transfers, though this assumes that transferred patients arrive earlier in the day, (eg, in time to influence discharge decisions), which infrequently occurs (Table 1). Lastly, it is possible that this subset of patients will be more vulnerable to the workload of the team that is caring for them at the time of their arrival. With high patient turnover (admissions/discharges), the time allocated to each patient’s care may be diminished (ie, “work compression,” trying to do the same amount of work in less time), and may result in decreased time to care for the transferred patient. This has been shown to influence patient outcomes at the time of patient discharge.10

In trying to understand why we observed an inverse relationship between admitting team busyness and odds of ICU transfer within 48 hours, we believe this finding is largely driven by cardiology service transfers, which comprise the highest volume of transferred patients in our cohort (Table 1), and are low acuity patients. Within this population of patients, admitting team busyness is likely a surrogate variable for high turnover/low acuity. This idea is supported by our findings that admitting team busyness is associated with decreased adjusted odds of 30-day mortality in this group (and only in this group).

Similarly, our observed inverse relationship between increased time delay and 30-day mortality among CT and GI surgical service patients is also likely reflective of lower acuity patients. We anticipated that decreased time delay (0-12 hours) would be reflective of greater patient acuity (supported by our findings that decreased time delay is associated with increased odds of ICU transfer and 30-day mortality). However, our findings also suggest that increased time delay (>48 hours) is similarly representative of lower patient acuity and therefore an imperfect measure of discontinuity and/or harmful delays in care during IHT (see limitations below).

Our study is subject to several limitations. This is a single site study; given known variation in transfer practices between hospitals,3 it is possible that our findings are not generalizable. However, given similar existing data on patients admitted through the ER, it is likely our findings may be reflective of IHT to similar tertiary referral hospitals. Second, although we adjusted for patient characteristics, there remains the possibility of unmeasured confounding and other bias that account for our results, as discussed. Third, although the definition of “busyness” used in this study was chosen based on prior data demonstrating an effect on patient outcomes,10 we did not include other measures of busyness that may influence outcomes of transferred patients such as overall team census or hospital busyness. However, the workload associated with a high volume of patient admissions and discharges is arguably a greater reflection of “work compression” for the admitting team compared with overall team census, which may reflect a more static workload with less impact on the care of a newly transferred patient. Also, although hospital census may influence the ability to transfer (ie, lower volume of transferred patients during times of high hospital census), this likely has less of an impact on the direct care of transferred patients than the admitting team’s workload. It is more likely that it would serve as a confounder (eg, sicker patients are accepted for transfer despite high hospital census, while lower risk patients are not).

Nevertheless, future studies should further evaluate the association with other measures of busyness/workload and outcomes of transferred patients. Lastly, though we anticipated time delay between transfer acceptance and arrival would be correlated with patient acuity, we hypothesized that longer delay might affect patient continuity and communication and impact patient outcomes. However, our results demonstrate that our measurement of this variable was unsuccessful in unraveling patient acuity from our intended evaluation of these vulnerable aspects of IHT. It is likely that a more detailed evaluation is required to explore potential challenges more fully that may occur with greater time delays (eg, suboptimal communication regarding changes in clinical status during this time period, delays in treatment). Similarly, though our study evaluates the association between nighttime and weekend transfer (and the interaction between these) with patient outcomes, we did not evaluate other intermediate outcomes that may be more affected by the timing of transfer, such as diagnostic errors or delays in procedural care, which warrant further investigation. We do not directly examine the underlying reasons that explain our observed associations, and thus more research is needed to identify these as well as design and evaluate solutions.

Collectively, our findings suggest that high acuity patients in need of procedural care experience worse outcomes during off-peak times of transfer, and during times of high care-team workload. Though further research is needed to identify underlying reasons to explain our findings, both the timing of patient transfer (when modifiable) and workload of the team caring for the patient on arrival may serve as potential targets for interventions to improve the quality and safety of IHT for patients at greatest risk.

 

 

Disclosures

Dr. Mueller and Dr. Schnipper have nothing to disclose. Ms. Fiskio has nothing to disclose. Dr. Schnipper is the recipient of grant funding from Mallinckrodt Pharmaceuticals to conduct an investigator-initiated study of predictors and impact of opioid-related adverse drug events.

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References

1. Iwashyna TJ. The incomplete infrastructure for interhospital patient transfer. Crit Care Med. 2 012;40(8):2470-2478. https://doi.org/10.1097/CCM.0b013e318254516f.
2. Mueller SK, Shannon E, Dalal A, Schnipper JL, Dykes P. Patient and physician experience with interhospital transfer: a qualitative study. J Patient Saf. 2018. https://doi.org/10.1097/PTS.0000000000000501
3. Mueller SK, Zheng J, Orav EJ, Schnipper JL. Rates, predictors and variability of interhospital transfers: a national evaluation. J Hosp Med. 2017;12(6):435-442.https://doi.org/10.12788/jhm.2747.
4. Bosk EA, Veinot T, Iwashyna TJ. Which patients and where: a qualitative study of patient transfers from community hospitals. Med Care. 2011;49(6):592-598. https://doi.org/10.1097/MLR.0b013e31820fb71b.
5. Sokol-Hessner L, White AA, Davis KF, Herzig SJ, Hohmann SF. Interhospital transfer patients discharged by academic hospitalists and general internists: characteristics and outcomes. J Hosp Med. 2016;11(4):245-50. https://doi.org/10.1002/jhm.2515.
6. Mueller S, Zheng J, Orav EJP, Schnipper JL. Inter-hospital transfer and patient outcomes: a retrospective cohort study. BMJ Qual Saf. 2018. https://doi.org/10.1136/bmjqs-2018-008087.
7. Mueller SK, Schnipper JL. Physician perspectives on interhospital transfers. J Patient Saf. 2016. https://doi.org/10.1097/PTS.0000000000000312.
8. Research Patient Data Registry (RPDR). http://rc.partners.org/rpdr. Accessed April 20, 2018.
9. Bell CM, Redelmeier DA. Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663-668. https://doi.org/10.1056/NEJMsa003376
10. Mueller SK, Donze J, Schnipper JL. Intern workload and discontinuity of care on 30-day readmission. Am J Med. 2013;126(1):81-88. https://doi.org/10.1016/j.amjmed.2012.09.003.
11. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27. PubMed
12. Ananthakrishnan AN, McGinley EL, Saeian K. Outcomes of weekend admissions for upper gastrointestinal hemorrhage: a nationwide analysis. Clin Gastroenterol Hepatol. 2009;7(3):296-302e1. https://doi.org/10.1016/j.cgh.2008.08.013.
13. Deshmukh A, Pant S, Kumar G, Bursac Z, Paydak H, Mehta JL. Comparison of outcomes of weekend versus weekday admissions for atrial fibrillation. Am J Cardiol. 2012;110(2):208-211. https://doi.org/10.1016/j.amjcard.2012.03.011.
14. Clarke MS, Wills RA, Bowman RV, et al. Exploratory study of the ‘weekend effect’ for acute medical admissions to public hospitals in Queensland, Australia. Intern Med J. 2010;40(11):777-783. https://doi.org/-10.1111/j.1445-5994.2009.02067.x.

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Related Articles

The transfer of patients between acute care hospitals (interhospital transfer [IHT]) occurs regularly among patients with a variety of diagnoses, in theory, to gain access to unique specialty services and/or a higher level of care, among other reasons.1,2

However, the practice of IHT is variable and nonstandardized,3,4 and existing data largely suggests that transferred patients experience worse outcomes, including longer length of stay, higher hospitalization costs, longer ICU time, and greater mortality, even with rigorous adjustment for confounding by indication.5,6 Though there are many possible reasons for these findings, existing literature suggests that there may be aspects of the transfer process itself which contribute to these outcomes.2,6,7

Understanding which aspects of the transfer process contribute to poor patient outcomes is a key first step toward the development of targeted quality improvement initiatives to improve this process of care. In this study, we aim to examine the association between select characteristics of the transfer process, including the timing of transfer and workload of the admitting physician team, and clinical outcomes among patients undergoing IHT.

METHODS

Data and Study Population

We performed a retrospective analysis of patients ≥age 18 years who transferred to Brigham and Women’s Hospital (BWH), a 777-bed tertiary care hospital, from another acute care hospital between January 2005, and September 2013. Dates of inclusion were purposefully chosen prior to BWH implementation of a new electronic health records system to avoid potential information bias. As at most academic medical centers, night coverage at BWH differs by service and includes a combination of long-call admitting teams and night float coverage. On weekends, many services are less well staffed, and some procedures may only be available if needed emergently. Some services have caps on the daily number of admissions or total patient census, but none have caps on the number of discharges per day. Patients were excluded from analysis if they left BWH against medical advice, were transferred from closely affiliated hospitals with shared personnel and electronic health records (Brigham and Women’s Faulkner Hospital, Dana Farber Cancer Institute), transferred from inpatient psychiatric or inpatient hospice facilities, or transferred to obstetrics or nursery services. Data were obtained from administrative sources and the research patient data repository (RPDR), a centralized clinical data repository that gathers data from various hospital legacy systems and stores them in one data warehouse.8 Our study was approved by the Partners Institutional Review Board (IRB) with a waiver of patient consent.

Transfer Process Characteristics

Predictors included select characteristics of the transfer process, including (1) Day of week of transfer, dichotomized into Friday through Sunday (“weekend”), versus Monday through Thursday (“weekday”);9 Friday was included with “weekend” given the suggestion of increased volume of transfers in advance of the weekend; (2) Time of arrival of the transferred patient, categorized into “daytime” (7 am-5 pm), “evening” (5 pm -10 pm), and “nighttime” (10 pm -7 am), with daytime as the reference group; (3) Admitting team “busyness” on day of patient transfer, defined as the total number of additional patient admissions and patient discharges performed by the admitting team on the calendar day of patient arrival, as has been used in prior research,10 and categorized into quartiles with lowest quartile as the reference group. Service-specific quartiles were calculated and used for stratified analyses (described below); and (4) “Time delay” between patient acceptance for transfer and patient arrival at BWH, categorized into 0-12 hours, 12-24 hours, 24-48 hours, and >48 hours, with 12-24 hours as the reference group (anticipating that time delay of 0-12 hours would be reflective of “sicker” patients in need of expedited transfer).

 

 

Outcomes

Outcomes included transfer to the intensive care unit (ICU) within 48 hours of arrival and 30-day mortality from date of index admission.5,6

Patient Characteristics

Covariates for adjustment included: patient age, sex, race, Elixhauser comorbidity score,11 Diagnosis-Related Group (DRG)-weight, insurance status, year of admission, number of preadmission medications, and service of admission.

Statistical Analyses

We used descriptive statistics to display baseline characteristics and performed a series of univariable and multivariable logistic regression models to obtain the adjusted odds of each transfer process characteristic on each outcome, adjusting for all covariates (proc logistic, SAS Statistical Software, Cary, North Carolina). For analyses of ICU transfer within 48 hours of arrival, all patients initially admitted to the ICU at time of transfer were excluded.

In the secondary analyses, we used a combined day-of-week and time-of-day variable (ie, Monday day, Monday evening, Monday night, Tuesday day, and so on, with Monday day as the reference group) to obtain a more detailed evaluation of timing of transfer on patient outcomes. We also performed stratified analyses to evaluate each transfer process characteristic on adjusted odds of 30-day mortality stratified by service of admission (ie, at the time of transfer to BWH), adjusting for all covariates. For all analyses, two-sided P values < .05 were considered significant.

RESULTS

Overall, 24,352 patients met our inclusion criteria and underwent IHT, of whom 2,174 (8.9%) died within 30 days. Of the 22,910 transferred patients originally admitted to a non-ICU service, 5,464 (23.8%) underwent ICU transfer within 48 hours of arrival. Cohort characteristics are shown in Table 1.

mueller0666-0408e_t1.jpg

Multivariable regression analyses demonstrated no significant association between weekend (versus weekday) transfer or increased time delay between patient acceptance and arrival (>48 hours) and adjusted odds of ICU transfer within 48 hours or 30-day mortality. However, they did demonstrate that nighttime (versus daytime) transfer was associated with greater adjusted odds of both ICU transfer and 30-day mortality. Increased admitting team busyness was associated with lower adjusted odds of ICU transfer but was not significantly associated with adjusted odds of 30-day mortality (Table 2). As expected, decreased time delay between patient acceptance and arrival (0-12 hours) was associated with increased adjusted odds of both ICU transfer (adjusted OR 2.68; 95% CI 2.29, 3.15) and 30-day mortality (adjusted OR 1.25; 95% CI 1.03, 1.53) compared with 12-24 hours (results not shown). Time delay >48 hours was not associated with either outcome.

Regression analyses with the combined day/time variable demonstrated that compared with Monday daytime transfer, Sunday night transfer was significantly associated with increased adjusted odds of 30-day mortality, and Friday night transfer was associated with a trend toward increased 30-day mortality (adjusted OR [aOR] 1.88; 95% CI 1.25, 2.82, and aOR 1.43; 95% CI 0.99, 2.06, respectively). We also found that all nighttime transfers (ie, Monday through Sunday night) were associated with increased adjusted odds of ICU transfer within 48 hours (as compared with Monday daytime transfer). Other days/time analyses were not significant.

Univariable and multivariable analyses stratified by service were performed (Appendix). Multivariable stratified analyses demonstrated that weekend transfer, nighttime transfer, and increased admitting team busyness were associated with increased adjusted odds of 30-day mortality among cardiothoracic (CT) and gastrointestinal (GI) surgical service patients. Increased admitting team busyness was also associated with increased mortality among ICU service patients but was associated with decreased mortality among cardiology service patients. An increased time delay between patient acceptance and arrival was associated with decreased mortality among CT and GI surgical service patients (Figure; Appendix). Other adjusted stratified outcomes were not significant.

mueller0666-0408e_t2.jpg

 

 

DISCUSSION

In this study of 24,352 patients undergoing IHT, we found no significant association between weekend transfer or increased time delay between transfer acceptance and arrival and patient outcomes in the cohort as a whole; but we found that nighttime transfer is associated with increased adjusted odds of both ICU transfer within 48 hours and 30-day mortality. Our analyses combining day-of-week and time-of-day demonstrate that Sunday night transfer is particularly associated with increased adjusted odds of 30-day mortality (as compared with Monday daytime transfer), and show a trend toward increased mortality with Friday night transfers. These detailed analyses otherwise reinforce that nighttime transfer across all nights of the week is associated with increased adjusted odds of ICU transfer within 48 hours. We also found that increased admitting team busyness on the day of patient transfer is associated with decreased odds of ICU transfer, though this may solely be reflective of higher turnover services (ie, cardiology) caring for lower acuity patients, as suggested by secondary analyses stratified by service. In addition, secondary analyses demonstrated differential associations between weekend transfers, nighttime transfers, and increased team busyness on the odds of 30-day mortality based on service of transfer. These analyses showed that patients transferred to higher acuity services requiring procedural care, including CT surgery, GI surgery, and Medical ICU, do worse under all three circumstances as compared with patients transferred to other services. Secondary analyses also demonstrated that increased time delay between patient acceptance and arrival is inversely associated with 30-day mortality among CT and GI surgery service patients, likely reflecting lower acuity patients (ie, less sick patients are less rapidly transferred).

There are several possible explanations for these findings. Patients transferred to surgical services at night may reflect a more urgent need for surgery and include a sicker cohort of patients, possibly explaining these findings. Alternatively, or in addition, both weekend and nighttime hospital admission expose patients to similar potential risks, ie, limited resources available during off-peak hours. Our findings could, therefore, reflect the possibility that patients transferred to higher acuity services in need of procedural care are most vulnerable to off-peak timing of transfer. Similar data looking at patients admitted through the emergency room (ER) find the strongest effect of off-peak admissions on patients in need of procedures, including GI hemorrhage,12 atrial fibrillation13 and acute myocardial infarction (AMI),14 arguably because of the limited availability of necessary interventions. Patients undergoing IHT are a sicker cohort of patients than those admitted through the ER, and, therefore, may be even more vulnerable to these issues.3,5 This is supported by our findings that Sunday night transfers (and trend toward Friday night transfers) are associated with greater mortality compared with Monday daytime transfers, when at-the-ready resources and/or specialty personnel may be less available (Sunday night), and delays until receipt of necessary procedures may be longer (Friday night). Though we did not observe similar results among cardiology service transfers, as may be expected based on existing literature,13,14 this subset of patients includes more heterogeneous diagnoses, (ie, not solely those that require acute intervention) and exhibited a low level of acuity (low Elixhauser score and DRG-weight, data not shown).

mueller0666-0408e_f1.jpg


We also found that increased admitting team busyness on the day of patient transfer is associated with increased odds of 30-day mortality among CT surgery, GI surgery, and ICU service transfers. As above, there are several possible explanations for this finding. It is possible that among these services, only the sickest/neediest patients are accepted for transfer when teams are busiest, explaining our findings. Though this explanation is possible, the measure of team “busyness” includes patient discharge, thereby increasing, not decreasing, availability for incoming patients, making this explanation less likely. Alternatively, it is possible that this finding is reflective of reverse causation, ie, that teams have less ability to discharge/admit new patients when caring for particularly sick/unstable patient transfers, though this assumes that transferred patients arrive earlier in the day, (eg, in time to influence discharge decisions), which infrequently occurs (Table 1). Lastly, it is possible that this subset of patients will be more vulnerable to the workload of the team that is caring for them at the time of their arrival. With high patient turnover (admissions/discharges), the time allocated to each patient’s care may be diminished (ie, “work compression,” trying to do the same amount of work in less time), and may result in decreased time to care for the transferred patient. This has been shown to influence patient outcomes at the time of patient discharge.10

In trying to understand why we observed an inverse relationship between admitting team busyness and odds of ICU transfer within 48 hours, we believe this finding is largely driven by cardiology service transfers, which comprise the highest volume of transferred patients in our cohort (Table 1), and are low acuity patients. Within this population of patients, admitting team busyness is likely a surrogate variable for high turnover/low acuity. This idea is supported by our findings that admitting team busyness is associated with decreased adjusted odds of 30-day mortality in this group (and only in this group).

Similarly, our observed inverse relationship between increased time delay and 30-day mortality among CT and GI surgical service patients is also likely reflective of lower acuity patients. We anticipated that decreased time delay (0-12 hours) would be reflective of greater patient acuity (supported by our findings that decreased time delay is associated with increased odds of ICU transfer and 30-day mortality). However, our findings also suggest that increased time delay (>48 hours) is similarly representative of lower patient acuity and therefore an imperfect measure of discontinuity and/or harmful delays in care during IHT (see limitations below).

Our study is subject to several limitations. This is a single site study; given known variation in transfer practices between hospitals,3 it is possible that our findings are not generalizable. However, given similar existing data on patients admitted through the ER, it is likely our findings may be reflective of IHT to similar tertiary referral hospitals. Second, although we adjusted for patient characteristics, there remains the possibility of unmeasured confounding and other bias that account for our results, as discussed. Third, although the definition of “busyness” used in this study was chosen based on prior data demonstrating an effect on patient outcomes,10 we did not include other measures of busyness that may influence outcomes of transferred patients such as overall team census or hospital busyness. However, the workload associated with a high volume of patient admissions and discharges is arguably a greater reflection of “work compression” for the admitting team compared with overall team census, which may reflect a more static workload with less impact on the care of a newly transferred patient. Also, although hospital census may influence the ability to transfer (ie, lower volume of transferred patients during times of high hospital census), this likely has less of an impact on the direct care of transferred patients than the admitting team’s workload. It is more likely that it would serve as a confounder (eg, sicker patients are accepted for transfer despite high hospital census, while lower risk patients are not).

Nevertheless, future studies should further evaluate the association with other measures of busyness/workload and outcomes of transferred patients. Lastly, though we anticipated time delay between transfer acceptance and arrival would be correlated with patient acuity, we hypothesized that longer delay might affect patient continuity and communication and impact patient outcomes. However, our results demonstrate that our measurement of this variable was unsuccessful in unraveling patient acuity from our intended evaluation of these vulnerable aspects of IHT. It is likely that a more detailed evaluation is required to explore potential challenges more fully that may occur with greater time delays (eg, suboptimal communication regarding changes in clinical status during this time period, delays in treatment). Similarly, though our study evaluates the association between nighttime and weekend transfer (and the interaction between these) with patient outcomes, we did not evaluate other intermediate outcomes that may be more affected by the timing of transfer, such as diagnostic errors or delays in procedural care, which warrant further investigation. We do not directly examine the underlying reasons that explain our observed associations, and thus more research is needed to identify these as well as design and evaluate solutions.

Collectively, our findings suggest that high acuity patients in need of procedural care experience worse outcomes during off-peak times of transfer, and during times of high care-team workload. Though further research is needed to identify underlying reasons to explain our findings, both the timing of patient transfer (when modifiable) and workload of the team caring for the patient on arrival may serve as potential targets for interventions to improve the quality and safety of IHT for patients at greatest risk.

 

 

Disclosures

Dr. Mueller and Dr. Schnipper have nothing to disclose. Ms. Fiskio has nothing to disclose. Dr. Schnipper is the recipient of grant funding from Mallinckrodt Pharmaceuticals to conduct an investigator-initiated study of predictors and impact of opioid-related adverse drug events.

The transfer of patients between acute care hospitals (interhospital transfer [IHT]) occurs regularly among patients with a variety of diagnoses, in theory, to gain access to unique specialty services and/or a higher level of care, among other reasons.1,2

However, the practice of IHT is variable and nonstandardized,3,4 and existing data largely suggests that transferred patients experience worse outcomes, including longer length of stay, higher hospitalization costs, longer ICU time, and greater mortality, even with rigorous adjustment for confounding by indication.5,6 Though there are many possible reasons for these findings, existing literature suggests that there may be aspects of the transfer process itself which contribute to these outcomes.2,6,7

Understanding which aspects of the transfer process contribute to poor patient outcomes is a key first step toward the development of targeted quality improvement initiatives to improve this process of care. In this study, we aim to examine the association between select characteristics of the transfer process, including the timing of transfer and workload of the admitting physician team, and clinical outcomes among patients undergoing IHT.

METHODS

Data and Study Population

We performed a retrospective analysis of patients ≥age 18 years who transferred to Brigham and Women’s Hospital (BWH), a 777-bed tertiary care hospital, from another acute care hospital between January 2005, and September 2013. Dates of inclusion were purposefully chosen prior to BWH implementation of a new electronic health records system to avoid potential information bias. As at most academic medical centers, night coverage at BWH differs by service and includes a combination of long-call admitting teams and night float coverage. On weekends, many services are less well staffed, and some procedures may only be available if needed emergently. Some services have caps on the daily number of admissions or total patient census, but none have caps on the number of discharges per day. Patients were excluded from analysis if they left BWH against medical advice, were transferred from closely affiliated hospitals with shared personnel and electronic health records (Brigham and Women’s Faulkner Hospital, Dana Farber Cancer Institute), transferred from inpatient psychiatric or inpatient hospice facilities, or transferred to obstetrics or nursery services. Data were obtained from administrative sources and the research patient data repository (RPDR), a centralized clinical data repository that gathers data from various hospital legacy systems and stores them in one data warehouse.8 Our study was approved by the Partners Institutional Review Board (IRB) with a waiver of patient consent.

Transfer Process Characteristics

Predictors included select characteristics of the transfer process, including (1) Day of week of transfer, dichotomized into Friday through Sunday (“weekend”), versus Monday through Thursday (“weekday”);9 Friday was included with “weekend” given the suggestion of increased volume of transfers in advance of the weekend; (2) Time of arrival of the transferred patient, categorized into “daytime” (7 am-5 pm), “evening” (5 pm -10 pm), and “nighttime” (10 pm -7 am), with daytime as the reference group; (3) Admitting team “busyness” on day of patient transfer, defined as the total number of additional patient admissions and patient discharges performed by the admitting team on the calendar day of patient arrival, as has been used in prior research,10 and categorized into quartiles with lowest quartile as the reference group. Service-specific quartiles were calculated and used for stratified analyses (described below); and (4) “Time delay” between patient acceptance for transfer and patient arrival at BWH, categorized into 0-12 hours, 12-24 hours, 24-48 hours, and >48 hours, with 12-24 hours as the reference group (anticipating that time delay of 0-12 hours would be reflective of “sicker” patients in need of expedited transfer).

 

 

Outcomes

Outcomes included transfer to the intensive care unit (ICU) within 48 hours of arrival and 30-day mortality from date of index admission.5,6

Patient Characteristics

Covariates for adjustment included: patient age, sex, race, Elixhauser comorbidity score,11 Diagnosis-Related Group (DRG)-weight, insurance status, year of admission, number of preadmission medications, and service of admission.

Statistical Analyses

We used descriptive statistics to display baseline characteristics and performed a series of univariable and multivariable logistic regression models to obtain the adjusted odds of each transfer process characteristic on each outcome, adjusting for all covariates (proc logistic, SAS Statistical Software, Cary, North Carolina). For analyses of ICU transfer within 48 hours of arrival, all patients initially admitted to the ICU at time of transfer were excluded.

In the secondary analyses, we used a combined day-of-week and time-of-day variable (ie, Monday day, Monday evening, Monday night, Tuesday day, and so on, with Monday day as the reference group) to obtain a more detailed evaluation of timing of transfer on patient outcomes. We also performed stratified analyses to evaluate each transfer process characteristic on adjusted odds of 30-day mortality stratified by service of admission (ie, at the time of transfer to BWH), adjusting for all covariates. For all analyses, two-sided P values < .05 were considered significant.

RESULTS

Overall, 24,352 patients met our inclusion criteria and underwent IHT, of whom 2,174 (8.9%) died within 30 days. Of the 22,910 transferred patients originally admitted to a non-ICU service, 5,464 (23.8%) underwent ICU transfer within 48 hours of arrival. Cohort characteristics are shown in Table 1.

mueller0666-0408e_t1.jpg

Multivariable regression analyses demonstrated no significant association between weekend (versus weekday) transfer or increased time delay between patient acceptance and arrival (>48 hours) and adjusted odds of ICU transfer within 48 hours or 30-day mortality. However, they did demonstrate that nighttime (versus daytime) transfer was associated with greater adjusted odds of both ICU transfer and 30-day mortality. Increased admitting team busyness was associated with lower adjusted odds of ICU transfer but was not significantly associated with adjusted odds of 30-day mortality (Table 2). As expected, decreased time delay between patient acceptance and arrival (0-12 hours) was associated with increased adjusted odds of both ICU transfer (adjusted OR 2.68; 95% CI 2.29, 3.15) and 30-day mortality (adjusted OR 1.25; 95% CI 1.03, 1.53) compared with 12-24 hours (results not shown). Time delay >48 hours was not associated with either outcome.

Regression analyses with the combined day/time variable demonstrated that compared with Monday daytime transfer, Sunday night transfer was significantly associated with increased adjusted odds of 30-day mortality, and Friday night transfer was associated with a trend toward increased 30-day mortality (adjusted OR [aOR] 1.88; 95% CI 1.25, 2.82, and aOR 1.43; 95% CI 0.99, 2.06, respectively). We also found that all nighttime transfers (ie, Monday through Sunday night) were associated with increased adjusted odds of ICU transfer within 48 hours (as compared with Monday daytime transfer). Other days/time analyses were not significant.

Univariable and multivariable analyses stratified by service were performed (Appendix). Multivariable stratified analyses demonstrated that weekend transfer, nighttime transfer, and increased admitting team busyness were associated with increased adjusted odds of 30-day mortality among cardiothoracic (CT) and gastrointestinal (GI) surgical service patients. Increased admitting team busyness was also associated with increased mortality among ICU service patients but was associated with decreased mortality among cardiology service patients. An increased time delay between patient acceptance and arrival was associated with decreased mortality among CT and GI surgical service patients (Figure; Appendix). Other adjusted stratified outcomes were not significant.

mueller0666-0408e_t2.jpg

 

 

DISCUSSION

In this study of 24,352 patients undergoing IHT, we found no significant association between weekend transfer or increased time delay between transfer acceptance and arrival and patient outcomes in the cohort as a whole; but we found that nighttime transfer is associated with increased adjusted odds of both ICU transfer within 48 hours and 30-day mortality. Our analyses combining day-of-week and time-of-day demonstrate that Sunday night transfer is particularly associated with increased adjusted odds of 30-day mortality (as compared with Monday daytime transfer), and show a trend toward increased mortality with Friday night transfers. These detailed analyses otherwise reinforce that nighttime transfer across all nights of the week is associated with increased adjusted odds of ICU transfer within 48 hours. We also found that increased admitting team busyness on the day of patient transfer is associated with decreased odds of ICU transfer, though this may solely be reflective of higher turnover services (ie, cardiology) caring for lower acuity patients, as suggested by secondary analyses stratified by service. In addition, secondary analyses demonstrated differential associations between weekend transfers, nighttime transfers, and increased team busyness on the odds of 30-day mortality based on service of transfer. These analyses showed that patients transferred to higher acuity services requiring procedural care, including CT surgery, GI surgery, and Medical ICU, do worse under all three circumstances as compared with patients transferred to other services. Secondary analyses also demonstrated that increased time delay between patient acceptance and arrival is inversely associated with 30-day mortality among CT and GI surgery service patients, likely reflecting lower acuity patients (ie, less sick patients are less rapidly transferred).

There are several possible explanations for these findings. Patients transferred to surgical services at night may reflect a more urgent need for surgery and include a sicker cohort of patients, possibly explaining these findings. Alternatively, or in addition, both weekend and nighttime hospital admission expose patients to similar potential risks, ie, limited resources available during off-peak hours. Our findings could, therefore, reflect the possibility that patients transferred to higher acuity services in need of procedural care are most vulnerable to off-peak timing of transfer. Similar data looking at patients admitted through the emergency room (ER) find the strongest effect of off-peak admissions on patients in need of procedures, including GI hemorrhage,12 atrial fibrillation13 and acute myocardial infarction (AMI),14 arguably because of the limited availability of necessary interventions. Patients undergoing IHT are a sicker cohort of patients than those admitted through the ER, and, therefore, may be even more vulnerable to these issues.3,5 This is supported by our findings that Sunday night transfers (and trend toward Friday night transfers) are associated with greater mortality compared with Monday daytime transfers, when at-the-ready resources and/or specialty personnel may be less available (Sunday night), and delays until receipt of necessary procedures may be longer (Friday night). Though we did not observe similar results among cardiology service transfers, as may be expected based on existing literature,13,14 this subset of patients includes more heterogeneous diagnoses, (ie, not solely those that require acute intervention) and exhibited a low level of acuity (low Elixhauser score and DRG-weight, data not shown).

mueller0666-0408e_f1.jpg


We also found that increased admitting team busyness on the day of patient transfer is associated with increased odds of 30-day mortality among CT surgery, GI surgery, and ICU service transfers. As above, there are several possible explanations for this finding. It is possible that among these services, only the sickest/neediest patients are accepted for transfer when teams are busiest, explaining our findings. Though this explanation is possible, the measure of team “busyness” includes patient discharge, thereby increasing, not decreasing, availability for incoming patients, making this explanation less likely. Alternatively, it is possible that this finding is reflective of reverse causation, ie, that teams have less ability to discharge/admit new patients when caring for particularly sick/unstable patient transfers, though this assumes that transferred patients arrive earlier in the day, (eg, in time to influence discharge decisions), which infrequently occurs (Table 1). Lastly, it is possible that this subset of patients will be more vulnerable to the workload of the team that is caring for them at the time of their arrival. With high patient turnover (admissions/discharges), the time allocated to each patient’s care may be diminished (ie, “work compression,” trying to do the same amount of work in less time), and may result in decreased time to care for the transferred patient. This has been shown to influence patient outcomes at the time of patient discharge.10

In trying to understand why we observed an inverse relationship between admitting team busyness and odds of ICU transfer within 48 hours, we believe this finding is largely driven by cardiology service transfers, which comprise the highest volume of transferred patients in our cohort (Table 1), and are low acuity patients. Within this population of patients, admitting team busyness is likely a surrogate variable for high turnover/low acuity. This idea is supported by our findings that admitting team busyness is associated with decreased adjusted odds of 30-day mortality in this group (and only in this group).

Similarly, our observed inverse relationship between increased time delay and 30-day mortality among CT and GI surgical service patients is also likely reflective of lower acuity patients. We anticipated that decreased time delay (0-12 hours) would be reflective of greater patient acuity (supported by our findings that decreased time delay is associated with increased odds of ICU transfer and 30-day mortality). However, our findings also suggest that increased time delay (>48 hours) is similarly representative of lower patient acuity and therefore an imperfect measure of discontinuity and/or harmful delays in care during IHT (see limitations below).

Our study is subject to several limitations. This is a single site study; given known variation in transfer practices between hospitals,3 it is possible that our findings are not generalizable. However, given similar existing data on patients admitted through the ER, it is likely our findings may be reflective of IHT to similar tertiary referral hospitals. Second, although we adjusted for patient characteristics, there remains the possibility of unmeasured confounding and other bias that account for our results, as discussed. Third, although the definition of “busyness” used in this study was chosen based on prior data demonstrating an effect on patient outcomes,10 we did not include other measures of busyness that may influence outcomes of transferred patients such as overall team census or hospital busyness. However, the workload associated with a high volume of patient admissions and discharges is arguably a greater reflection of “work compression” for the admitting team compared with overall team census, which may reflect a more static workload with less impact on the care of a newly transferred patient. Also, although hospital census may influence the ability to transfer (ie, lower volume of transferred patients during times of high hospital census), this likely has less of an impact on the direct care of transferred patients than the admitting team’s workload. It is more likely that it would serve as a confounder (eg, sicker patients are accepted for transfer despite high hospital census, while lower risk patients are not).

Nevertheless, future studies should further evaluate the association with other measures of busyness/workload and outcomes of transferred patients. Lastly, though we anticipated time delay between transfer acceptance and arrival would be correlated with patient acuity, we hypothesized that longer delay might affect patient continuity and communication and impact patient outcomes. However, our results demonstrate that our measurement of this variable was unsuccessful in unraveling patient acuity from our intended evaluation of these vulnerable aspects of IHT. It is likely that a more detailed evaluation is required to explore potential challenges more fully that may occur with greater time delays (eg, suboptimal communication regarding changes in clinical status during this time period, delays in treatment). Similarly, though our study evaluates the association between nighttime and weekend transfer (and the interaction between these) with patient outcomes, we did not evaluate other intermediate outcomes that may be more affected by the timing of transfer, such as diagnostic errors or delays in procedural care, which warrant further investigation. We do not directly examine the underlying reasons that explain our observed associations, and thus more research is needed to identify these as well as design and evaluate solutions.

Collectively, our findings suggest that high acuity patients in need of procedural care experience worse outcomes during off-peak times of transfer, and during times of high care-team workload. Though further research is needed to identify underlying reasons to explain our findings, both the timing of patient transfer (when modifiable) and workload of the team caring for the patient on arrival may serve as potential targets for interventions to improve the quality and safety of IHT for patients at greatest risk.

 

 

Disclosures

Dr. Mueller and Dr. Schnipper have nothing to disclose. Ms. Fiskio has nothing to disclose. Dr. Schnipper is the recipient of grant funding from Mallinckrodt Pharmaceuticals to conduct an investigator-initiated study of predictors and impact of opioid-related adverse drug events.

References

1. Iwashyna TJ. The incomplete infrastructure for interhospital patient transfer. Crit Care Med. 2 012;40(8):2470-2478. https://doi.org/10.1097/CCM.0b013e318254516f.
2. Mueller SK, Shannon E, Dalal A, Schnipper JL, Dykes P. Patient and physician experience with interhospital transfer: a qualitative study. J Patient Saf. 2018. https://doi.org/10.1097/PTS.0000000000000501
3. Mueller SK, Zheng J, Orav EJ, Schnipper JL. Rates, predictors and variability of interhospital transfers: a national evaluation. J Hosp Med. 2017;12(6):435-442.https://doi.org/10.12788/jhm.2747.
4. Bosk EA, Veinot T, Iwashyna TJ. Which patients and where: a qualitative study of patient transfers from community hospitals. Med Care. 2011;49(6):592-598. https://doi.org/10.1097/MLR.0b013e31820fb71b.
5. Sokol-Hessner L, White AA, Davis KF, Herzig SJ, Hohmann SF. Interhospital transfer patients discharged by academic hospitalists and general internists: characteristics and outcomes. J Hosp Med. 2016;11(4):245-50. https://doi.org/10.1002/jhm.2515.
6. Mueller S, Zheng J, Orav EJP, Schnipper JL. Inter-hospital transfer and patient outcomes: a retrospective cohort study. BMJ Qual Saf. 2018. https://doi.org/10.1136/bmjqs-2018-008087.
7. Mueller SK, Schnipper JL. Physician perspectives on interhospital transfers. J Patient Saf. 2016. https://doi.org/10.1097/PTS.0000000000000312.
8. Research Patient Data Registry (RPDR). http://rc.partners.org/rpdr. Accessed April 20, 2018.
9. Bell CM, Redelmeier DA. Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663-668. https://doi.org/10.1056/NEJMsa003376
10. Mueller SK, Donze J, Schnipper JL. Intern workload and discontinuity of care on 30-day readmission. Am J Med. 2013;126(1):81-88. https://doi.org/10.1016/j.amjmed.2012.09.003.
11. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27. PubMed
12. Ananthakrishnan AN, McGinley EL, Saeian K. Outcomes of weekend admissions for upper gastrointestinal hemorrhage: a nationwide analysis. Clin Gastroenterol Hepatol. 2009;7(3):296-302e1. https://doi.org/10.1016/j.cgh.2008.08.013.
13. Deshmukh A, Pant S, Kumar G, Bursac Z, Paydak H, Mehta JL. Comparison of outcomes of weekend versus weekday admissions for atrial fibrillation. Am J Cardiol. 2012;110(2):208-211. https://doi.org/10.1016/j.amjcard.2012.03.011.
14. Clarke MS, Wills RA, Bowman RV, et al. Exploratory study of the ‘weekend effect’ for acute medical admissions to public hospitals in Queensland, Australia. Intern Med J. 2010;40(11):777-783. https://doi.org/-10.1111/j.1445-5994.2009.02067.x.

References

1. Iwashyna TJ. The incomplete infrastructure for interhospital patient transfer. Crit Care Med. 2 012;40(8):2470-2478. https://doi.org/10.1097/CCM.0b013e318254516f.
2. Mueller SK, Shannon E, Dalal A, Schnipper JL, Dykes P. Patient and physician experience with interhospital transfer: a qualitative study. J Patient Saf. 2018. https://doi.org/10.1097/PTS.0000000000000501
3. Mueller SK, Zheng J, Orav EJ, Schnipper JL. Rates, predictors and variability of interhospital transfers: a national evaluation. J Hosp Med. 2017;12(6):435-442.https://doi.org/10.12788/jhm.2747.
4. Bosk EA, Veinot T, Iwashyna TJ. Which patients and where: a qualitative study of patient transfers from community hospitals. Med Care. 2011;49(6):592-598. https://doi.org/10.1097/MLR.0b013e31820fb71b.
5. Sokol-Hessner L, White AA, Davis KF, Herzig SJ, Hohmann SF. Interhospital transfer patients discharged by academic hospitalists and general internists: characteristics and outcomes. J Hosp Med. 2016;11(4):245-50. https://doi.org/10.1002/jhm.2515.
6. Mueller S, Zheng J, Orav EJP, Schnipper JL. Inter-hospital transfer and patient outcomes: a retrospective cohort study. BMJ Qual Saf. 2018. https://doi.org/10.1136/bmjqs-2018-008087.
7. Mueller SK, Schnipper JL. Physician perspectives on interhospital transfers. J Patient Saf. 2016. https://doi.org/10.1097/PTS.0000000000000312.
8. Research Patient Data Registry (RPDR). http://rc.partners.org/rpdr. Accessed April 20, 2018.
9. Bell CM, Redelmeier DA. Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663-668. https://doi.org/10.1056/NEJMsa003376
10. Mueller SK, Donze J, Schnipper JL. Intern workload and discontinuity of care on 30-day readmission. Am J Med. 2013;126(1):81-88. https://doi.org/10.1016/j.amjmed.2012.09.003.
11. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27. PubMed
12. Ananthakrishnan AN, McGinley EL, Saeian K. Outcomes of weekend admissions for upper gastrointestinal hemorrhage: a nationwide analysis. Clin Gastroenterol Hepatol. 2009;7(3):296-302e1. https://doi.org/10.1016/j.cgh.2008.08.013.
13. Deshmukh A, Pant S, Kumar G, Bursac Z, Paydak H, Mehta JL. Comparison of outcomes of weekend versus weekday admissions for atrial fibrillation. Am J Cardiol. 2012;110(2):208-211. https://doi.org/10.1016/j.amjcard.2012.03.011.
14. Clarke MS, Wills RA, Bowman RV, et al. Exploratory study of the ‘weekend effect’ for acute medical admissions to public hospitals in Queensland, Australia. Intern Med J. 2010;40(11):777-783. https://doi.org/-10.1111/j.1445-5994.2009.02067.x.

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