Ethan Cumbler, MD

The combination of decreasing hospital lengths of stay and increasing age and comorbidity of the United States population is a principal driver of the increased use of postacute care in the US.^1-3 Postacute care refers to care in long-term acute care hospitals, inpatient rehabilitation facilities, skilled nursing facilities (SNFs), and care provided by home health agencies after an acute hospitalization. In 2016, 43% of Medicare beneficiaries received postacute care after hospital discharge at the cost of $60 billion annually; nearly half of these received care in an SNF.⁴ Increasing recognition of the significant cost and poor outcomes of postacute care led to payment reforms, such as bundled payments, that incentivized less expensive forms of postacute care and improvements in outcomes.^5-9 Early evaluations suggested that hospitals are sensitive to these reforms and responded by significantly decreasing SNF utilization.^10,11 It remains unclear whether this was safe and effective.

In this context, increased attention to how hospital clinicians and hospitalized patients decide whether to use postacute care (and what form to use) is appropriate since the effect of payment reforms could negatively impact vulnerable populations of older adults without adequate protection.¹² Suboptimal decision-making can drive both overuse and inappropriate underuse of this expensive medical resource. Initial evidence suggests that patients and clinicians are poorly equipped to make high-quality decisions about postacute care, with significant deficits in both the decision-making process and content.^13-16 While these gaps are important to address, they may only be part of the problem. The fields of cognitive psychology and behavioral economics have revealed new insights into decision-making, demonstrating that people deviate from rational decision-making in predictable ways, termed decision heuristics, or cognitive biases.¹⁷ This growing field of research suggests heuristics or biases play important roles in decision-making and determining behavior, particularly in situations where there may be little information provided and the patient is stressed, tired, and ill—precisely like deciding on postacute care.¹⁸ However, it is currently unknown whether cognitive biases are at play when making hospital discharge decisions.

We sought to identify the most salient heuristics or cognitive biases patients may utilize when making decisions about postacute care at the end of their hospitalization and ways clinicians may contribute to these biases. The overall goal was to derive insights for improving postacute care decision-making.

METHODS

Study Design

We conducted a secondary analysis on interviews with hospital and SNF clinicians as well as patients and their caregivers who were either leaving the hospital for an SNF or newly arrived in an SNF from the hospital to understand if cognitive biases were present and how they manifested themselves in a real-world clinical context.¹⁹ These interviews were part of a larger qualitative study that sought to understand how clinicians, patients, and their caregivers made decisions about postacute care, particularly related to SNFs.^13,14 This study represents the analysis of all our interviews, specifically examining decision-making bias. Participating sites, clinical roles, and both patient and caregiver characteristics (Table 1) in our cohort have been previously described.^13,14

Analysis

We used a team-based approach to framework analysis, which has been used in other decision-making studies¹⁴, including those measuring cognitive bias.²⁰ A limitation in cognitive bias research is the lack of a standardized list or categorization of cognitive biases. We reviewed prior systematic^17,21 and narrative reviews^18,22, as well as prior studies describing examples of cognitive biases playing a role in decision-making about therapy²⁰ to construct a list of possible cognitive biases to evaluate and narrow these a priori to potential biases relevant to the decision about postacute care based on our prior work (Table 2).

We applied this framework to analyze transcripts through an iterative process of deductive coding and reviewing across four reviewers (ML, RA, AL, CL) and a hospitalist physician with expertise leading qualitative studies (REB).

Intercoder consensus was built through team discussion by resolving points of disagreement.²³ Consistency of coding was regularly checked by having more than one investigator code individual manuscripts and comparing coding, and discrepancies were resolved through team discussion. We triangulated the data (shared our preliminary results) using a larger study team, including an expert in behavioral economics (SRG), physicians at study sites (EC, RA), and an anthropologist with expertise in qualitative methods (CL). We did this to ensure credibility (to what extent the findings are credible or believable) and confirmability of findings (ensuring the findings are based on participant narratives rather than researcher biases).

RESULTS 

We reviewed a total of 105 interviews with 25 hospital clinicians, 20 SNF clinicians, 21 patients and 14 caregivers in the hospital, and 15 patients and 10 caregivers in the SNF setting (Table 1). We found authority bias/halo effect; default/status quo bias, anchoring bias, and framing was commonly present in decision-making about postacute care in a SNF, whereas there were few if any examples of ambiguity aversion, availability heuristic, confirmation bias, optimism bias, or false consensus effect (Table 2).

Authority Bias/Halo Effect

While most patients deferred to their inpatient teams when it came to decision-making, this effect seemed to differ across VA and non-VA settings. Veterans expressed a higher degree of potential authority bias regarding the VA as an institution, whereas older adults in non-VA settings saw physicians as the authority figure making decisions in their best interests.

Veterans expressed confidence in the VA regarding both whether to go to a SNF and where to go:

“The VA wouldn’t license [an SNF] if they didn’t have a good reputation for care, cleanliness, things of that nature” (Veteran, VA CLC)

“I just knew the VA would have my best interests at heart” (Veteran, VA CLC)

Their caregivers expressed similar confidence:

“I’m not gonna decide [on whether the patient they care for goes to postacute care], like I told you, that’s totally up to the VA. I have trust and faith in them…so wherever they send him, that’s where he’s going” (Caregiver, VA hospital)

In some cases, this perspective was closer to the halo effect: a positive experience with the care provider or the care team led the decision-makers to believe that their recommendations about postacute care would be similarly positive.

“I think we were very trusting in the sense that whatever happened the last time around, he survived it…they took care of him…he got back home, and he started his life again, you know, so why would we question what they’re telling us to do? (Caregiver, VA hospital)

In contrast to Veterans, non-Veteran patients seemed to experience authority bias when it came to the inpatient team.

“Well, I’d like to know more about the PTs [Physical Therapists] there, but I assume since they were recommended, they will be good.” (Patient, University hospital)

This perspective was especially apparent when it came to physicians:

“The level of trust that they [patients] put in their doctor is gonna outweigh what anyone else would say.” (Clinical liaison, SNF)

“[In response to a question about influences on the decision to go to rehab] I don’t…that’s not my decision to make, that’s the doctor’s decision.” (Patient, University hospital)

“They said so…[the doctor] said I needed to go to rehab, so I guess I do because it’s the doctor’s decision.” (Patient, University hospital)

Default/Status quo Bias

In a related way, patients and caregivers with exposure to a SNF seemed to default to the same SNF with which they had previous experience. This bias seems to be primarily related to knowing what to expect.

“He thinks it’s [a particular SNF] the right place for him now…he was there before and he knew, again, it was the right place for him to be” (Caregiver, VA hospital)

“It’s the only one I’ve ever been in…but they have a lot of activities; you have a lot of freedom, staff was good” (Patient, VA hospital)

“I’ve been [to this SNF] before and I kind of know what the program involves…so it was kind of like going home, not, going home is the wrong way to put it…I mean coming here is like something I know, you know, I didn’t need anybody to explain it to me.” (Patient, VA hospital)

“Anybody that’s been to [SNF], that would be their choice to go back to, and I guess I must’ve liked it that first time because I asked to go back again.” (Patient, University hospital)

Anchoring Bias

While anchoring bias was less frequent, it came up in two domains: first, related to costs of care, and second, related to facility characteristics. Costs came up most frequently for Veterans who preferred to move their care to the VA for cost reasons, which appeared in these cases to overshadow other considerations:

“I kept emphasizing that the VA could do all the same things at a lot more reasonable price. The whole purpose of having the VA is for the Veteran, so that…we can get the healthcare that we need at a more reasonable [sic] or a reasonable price.” (Veteran, CLC)

“I think the CLC [VA SNF] is going to take care of her probably the same way any other facility of its type would, unless she were in a private facility, but you know, that costs a lot more money.” (Caregiver, VA hospital)

Patients occasionally had striking responses to particular characteristics of SNFs, regardless of whether this was a central feature or related to their rehabilitation:

“The social worker comes and talks to me about the nursing home where cats are running around, you know, to infect my leg or spin their little cat hairs into my lungs and make my asthma worse…I’m going to have to beg the nurses or the aides or the family or somebody to clean the cat…” (Veteran, VA hospital)

Framing

Framing was the strongest theme among clinician interviews in our sample. Clinicians most frequently described the SNF as a place where patients could recover function (a positive frame), explaining risks (eg, rehospitalization) associated with alternative postacute care options besides the SNF in great detail.

“Aside from explaining the benefits of going and…having that 24-hour care, having the therapies provided to them [the patients], talking about them getting stronger, phrasing it in such a way that patients sometimes are more agreeable, like not calling it a skilled nursing facility, calling it a rehab you know, for them to get physically stronger so they can be the most independent that they can once they do go home, and also explaining … we think that this would be the best plan to prevent them from coming back to the hospital, so those are some of the things that we’ll mention to patients to try and educate them and get them to be agreeable for placement.” (Social worker, University hospital)

Clinicians avoided negative associations with “nursing home” (even though all SNFs are nursing homes) and tended to use more positive frames such as “rehabilitation facility.”

“Use the word rehab….we definitely use the word rehab, to get more therapy, to go home; it’s not a, we really emphasize it’s not a nursing home, it’s not to go to stay forever.” (Physical therapist, safety-net hospital)

Clinicians used a frame of “safety” when discussing the SNF and used a frame of “risk” when discussing alternative postacute care options such as returning home. We did not find examples of clinicians discussing similar risks in going to a SNF even for risks, such as falling, which exist in both settings.

“I’ve talked to them primarily on an avenue of safety because I think people want and they value independence, they value making sure they can get home, but you know, a lot of the times they understand safety is, it can be a concern and outlining that our goal is to make sure that they’re safe and they stay home, and I tend to broach the subject saying that our therapists believe that they might not be safe at home in the moment, but they have potential goals to be safe later on if we continue therapy. I really highlight safety being the major driver of our discussion.” (Physician, VA hospital)

In some cases, framing was so overt that other risk-mitigating options (eg, home healthcare) are not discussed.

“I definitely tend to explain the ideal first. I’m not going to bring up home care when we really think somebody should go to rehab, however, once people say I don’t want to do that, I’m not going, then that’s when I’m like OK, well, let’s talk to the doctors, but we can see about other supports in the home.” (Social worker, VA hospital)

DISCUSSION

In a large sample of patients and their caregivers, as well as multidisciplinary clinicians at three different hospitals and three SNFs, we found authority bias/halo effect and framing biases were most common and seemed most impactful. Default/status quo bias and anchoring bias were also present in decision-making about a SNF. The combination of authority bias/halo effect and framing biases could synergistically interact to augment the likelihood of patients accepting a SNF for postacute care. Patients who had been to a SNF before seemed more likely to choose the SNF they had experienced previously even if they had no other postacute care experiences, and could be highly influenced by isolated characteristics of that facility (such as the physical environment or cost of care).

It is important to mention that cognitive biases do not necessarily have a negative impact: indeed, as Kahneman and Tversky point out, these are useful heuristics from “fast” thinking that are often effective.²⁴ For example, clinicians may be trying to act in the best interests of the patient when framing the decision in terms of regaining function and averting loss of safety and independence. However, the evidence base regarding the outcomes of an SNF versus other postacute options is not robust, and this decision-making is complex. While this decision was most commonly framed in terms of rehabilitation and returning home, the fact that only about half of patients have returned to the community by 100 days⁴ was not discussed in any interview. In fact, initial evidence suggests replacing the SNF with home healthcare in patients with hip and knee arthroplasty may reduce costs without worsening clinical outcomes.⁶ However, across a broader population, SNFs significantly reduce 30-day readmissions when directly compared with home healthcare, but other clinical outcomes are similar.²⁵ This evidence suggests that the “right” postacute care option for an individual patient is not clear, highlighting a key role biases may play in decision-making. Further, the nebulous concept of “safety” could introduce potential disparities related to social determinants of health.¹² The observed inclination to accept an SNF with which the individual had prior experience may be influenced by the acceptability of this choice because of personal factors or prior research, even if it also represents a bias by limiting the consideration of current alternatives.

Our findings complement those of others in the literature which have also identified profound gaps in discharge decision-making among patients and clinicians,^13-16,26-31 though to our knowledge the role of cognitive biases in these decisions has not been explored. This study also addresses gaps in the cognitive bias literature, including the need for real-world data rather than hypothetical vignettes,¹⁷ and evaluation of treatment and management decisions rather than diagnoses, which have been more commonly studied.²¹

These findings have implications for both individual clinicians and healthcare institutions. In the immediate term, these findings may serve as a call to discharging clinicians to modulate language and “debias” their conversations with patients about care after discharge.^18,22 Shared decision-making requires an informed choice by patients based on their goals and values; framing a decision in a way that puts the clinician’s goals or values (eg, safety) ahead of patient values (eg, independence and autonomy) or limits disclosure (eg, a “rehab” is a nursing home) in the hope of influencing choice may be more consistent with framing bias and less with shared decision-making.¹⁴ Although controversy exists about the best way to “debias” oneself,³² self-awareness of bias is increasingly recognized across healthcare venues as critical to improving care for vulnerable populations.³³ The use of data rather than vignettes may be a useful debiasing strategy, although the limitations of currently available data (eg, capturing nursing home quality) are increasingly recognized.³⁴ From a policy and health system perspective, cognitive biases should be integrated into the development of decision aids to facilitate informed, shared, and high-quality decision-making that incorporates patient values, and perhaps “nudges” from behavioral economics to assist patients in choosing the right postdischarge care for them. Such nudges use principles of framing to influence care without restricting choice.³⁵ As the science informing best practice regarding postacute care improves, identifying the “right” postdischarge care may become easier and recommendations more evidence-based.³⁶

Strengths of the study include a large, diverse sample of patients, caregivers, and clinicians in both the hospital and SNF setting. Also, we used a team-based analysis with an experienced team and a deep knowledge of the data, including triangulation with clinicians to verify results. However, all hospitals and SNFs were located in a single metropolitan area, and responses may vary by region or population density. All three hospitals have housestaff teaching programs, and at the time of the interviews all three community SNFs were “five-star” facilities on the Nursing Home Compare website; results may be different at community hospitals or other SNFs. Hospitalists were the only physician group sampled in the hospital as they provide the majority of inpatient care to older adults; geriatricians, in particular, may have had different perspectives. Since we intended to explore whether cognitive biases were present overall, we did not evaluate whether cognitive biases differed by role or subgroup (by clinician type, patient, or caregiver), but this may be a promising area to explore in future work. Many cognitive biases have been described, and there are likely additional biases we did not identify. To confirm the generalizability of these findings, they should be studied in a larger, more generalizable sample of respondents in future work.

Cognitive biases play an important role in patient decision-making about postacute care, particularly regarding SNF care. As postacute care undergoes a transformation spurred by payment reforms, it is more important than ever to ensure that patients understand their choices at hospital discharge and can make a high-quality decision consistent with their goals.

References

1. Burke RE, Juarez-Colunga E, Levy C, Prochazka AV, Coleman EA, Ginde AA. Rise of post-acute care facilities as a discharge destination of US hospitalizations. JAMA Intern Med. 2015;175(2):295-296. https://doi.org/10.1001/jamainternmed.2014.6383.
2. Burke RE, Juarez-Colunga E, Levy C, Prochazka AV, Coleman EA, Ginde AA. Patient and hospitalization characteristics associated with increased postacute care facility discharges from US hospitals. Med Care. 2015;53(6):492-500. https://doi.org/10.1097/MLR.0000000000000359.
3. Werner RM, Konetzka RT. Trends in post-acute care use among medicare beneficiaries: 2000 to 2015. JAMA. 2018;319(15):1616-1617. https://doi.org/10.1001/jama.2018.2408.
4. Medicare Payment Advisory Commission June 2018 Report to Congress. http://www.medpac.gov/docs/default-source/reports/jun18_ch5_medpacreport_sec.pdf?sfvrsn=0. Accessed November 9, 2018.
5. Burke RE, Cumbler E, Coleman EA, Levy C. Post-acute care reform: implications and opportunities for hospitalists. J Hosp Med. 2017;12(1):46-51. https://doi.org/10.1002/jhm.2673.
6. Dummit LA, Kahvecioglu D, Marrufo G, et al. Association between hospital participation in a medicare bundled payment initiative and payments and quality outcomes for lower extremity joint replacement episodes. JAMA. 2016;316(12):1267-1278. https://doi.org/10.1001/jama.2016.12717.
7. Navathe AS, Troxel AB, Liao JM, et al. Cost of joint replacement using bundled payment models. JAMA Intern Med. 2017;177(2):214-222. https://doi.org/10.1001/jamainternmed.2016.8263.
8. Kennedy G, Lewis VA, Kundu S, Mousqués J, Colla CH. Accountable care organizations and post-acute care: a focus on preferred SNF networks. Med Care Res Rev MCRR. 2018;1077558718781117. https://doi.org/10.1177/1077558718781117.
9. Chandra A, Dalton MA, Holmes J. Large increases in spending on postacute care in Medicare point to the potential for cost savings in these settings. Health Aff Proj Hope. 2013;32(5):864-872. https://doi.org/10.1377/hlthaff.2012.1262.
10. McWilliams JM, Gilstrap LG, Stevenson DG, Chernew ME, Huskamp HA, Grabowski DC. Changes in postacute care in the Medicare shared savings program. JAMA Intern Med. 2017;177(4):518-526. https://doi.org/10.1001/jamainternmed.2016.9115.
11. Zhu JM, Patel V, Shea JA, Neuman MD, Werner RM. Hospitals using bundled payment report reducing skilled nursing facility use and improving care integration. Health Aff Proj Hope. 2018;37(8):1282-1289. https://doi.org/10.1377/hlthaff.2018.0257.
12. Burke RE, Ibrahim SA. Discharge destination and disparities in postoperative care. JAMA. 2018;319(16):1653-1654. https://doi.org/10.1001/jama.2017.21884.
13. Burke RE, Lawrence E, Ladebue A, et al. How hospital clinicians select patients for skilled nursing facilities. J Am Geriatr Soc. 2017;65(11):2466-2472. https://doi.org/10.1111/jgs.14954.
14. Burke RE, Jones J, Lawrence E, et al. Evaluating the quality of patient decision-making regarding post-acute care. J Gen Intern Med. 2018;33(5):678-684. https://doi.org/10.1007/s11606-017-4298-1.
15. Gadbois EA, Tyler DA, Mor V. Selecting a skilled nursing facility for postacute care: individual and family perspectives. J Am Geriatr Soc. 2017;65(11):2459-2465. https://doi.org/10.1111/jgs.14988.
16. Tyler DA, Gadbois EA, McHugh JP, Shield RR, Winblad U, Mor V. Patients are not given quality-of-care data about skilled nursing facilities when discharged from hospitals. Health Aff. 2017;36(8):1385-1391. https://doi.org/10.1377/hlthaff.2017.0155.
17. Blumenthal-Barby JS, Krieger H. Cognitive biases and heuristics in medical decision making: a critical review using a systematic search strategy. Med Decis Mak Int J Soc Med Decis Mak. 2015;35(4):539-557. https://doi.org/10.1177/0272989X14547740.
18. Croskerry P, Singhal G, Mamede S. Cognitive debiasing 1: origins of bias and theory of debiasing. BMJ Qual Saf. 2013;22 Suppl 2:ii58-ii64. https://doi.org/10.1136/bmjqs-2012-001712.
19. Hinds PS, Vogel RJ, Clarke-Steffen L. The possibilities and pitfalls of doing a secondary analysis of a qualitative data set. Qual Health Res. 1997;7(3):408-424. https://doi.org/10.1177/104973239700700306.
20. Magid M, Mcllvennan CK, Jones J, et al. Exploring cognitive bias in destination therapy left ventricular assist device decision making: a retrospective qualitative framework analysis. Am Heart J. 2016;180:64-73. https://doi.org/10.1016/j.ahj.2016.06.024.
21. Saposnik G, Redelmeier D, Ruff CC, Tobler PN. Cognitive biases associated with medical decisions: a systematic review. BMC Med Inform Decis Mak. 2016;16(1):138. https://doi.org/10.1186/s12911-016-0377-1.
22. Croskerry P, Singhal G, Mamede S. Cognitive debiasing 2: impediments to and strategies for change. BMJ Qual Saf. 2013;22 Suppl 2:ii65-ii72. https://doi.org/10.1136/bmjqs-2012-001713.
23. Bradley EH, Curry LA, Devers KJ. Qualitative data analysis for health services research: developing taxonomy, themes, and theory. Health Serv Res. 2007;42(4):1758-1772. https://doi.org/10.1111/j.1475-6773.2006.00684.x.
24. Thinking, Fast and Slow. Daniel Kahneman. Macmillan. US Macmillan. https://us.macmillan.com/thinkingfastandslow/danielkahneman/9780374533557. Accessed February 5, 2019.
25. Werner RM, Konetzka RT, Coe NB. Does type of post-acute care matter? The effect of hospital discharge to home with home health care versus to skilled nursing facility. JAMA Intern Med. In press.
26. Jones J, Lawrence E, Ladebue A, Leonard C, Ayele R, Burke RE. Nurses’ role in managing “The Fit” of older adults in skilled nursing facilities. J Gerontol Nurs. 2017;43(12):11-20. https://doi.org/10.3928/00989134-20171110-06.
27. Lawrence E, Casler J-J, Jones J, et al. Variability in skilled nursing facility screening and admission processes: implications for value-based purchasing. Health Care Manage Rev. 2018. https://doi.org/10.1097/HMR.0000000000000225.
28. Ayele R, Jones J, Ladebue A, et al. Perceived costs of care influence post-acute care choices by clinicians, patients, and caregivers. J Am Geriatr Soc. 2019. https://doi.org/10.1111/jgs.15768.
29. Sefcik JS, Nock RH, Flores EJ, et al. Patient preferences for information on post-acute care services. Res Gerontol Nurs. 2016;9(4):175-182. https://doi.org/10.3928/19404921-20160120-01.
30. Konetzka RT, Perraillon MC. Use of nursing home compare website appears limited by lack of awareness and initial mistrust of the data. Health Aff Proj Hope. 2016;35(4):706-713. https://doi.org/10.1377/hlthaff.2015.1377.
31. Schapira MM, Shea JA, Duey KA, Kleiman C, Werner RM. The nursing home compare report card: perceptions of residents and caregivers regarding quality ratings and nursing home choice. Health Serv Res. 2016;51 Suppl 2:1212-1228. https://doi.org/10.1111/1475-6773.12458.
32. Dhaliwal G. Premature closure? Not so fast. BMJ Qual Saf. 2017;26(2):87-89. https://doi.org/10.1136/bmjqs-2016-005267.
33. Masters C, Robinson D, Faulkner S, Patterson E, McIlraith T, Ansari A. Addressing biases in patient care with the 5Rs of cultural humility, a clinician coaching tool. J Gen Intern Med. 2019;34(4):627-630. https://doi.org/10.1007/s11606-018-4814-y.
34. Burke RE, Werner RM. Quality measurement and nursing homes: measuring what matters. BMJ Qual Saf. 2019;28(7);520-523. https://doi.org/10.1136/bmjqs-2019-009447.
35. Patel MS, Volpp KG, Asch DA. Nudge units to improve the delivery of health care. N Engl J Med. 2018;378(3):214-216. https://doi.org/10.1056/NEJMp1712984.
36. Jenq GY, Tinetti ME. Post–acute care: who belongs where? JAMA Intern Med. 2015;175(2):296-297. https://doi.org/10.1001/jamainternmed.2014.4298.

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¹Center for Health Equity Research and Promotion (CHERP); Corporal Crescenz VA Medical Center, Philadelphia, Pennsylvania;²Hospital Medicine Section, Division of General Internal Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania; ³Center of Innovation for Veteran-Centered and Value-Driven Care; Denver VA Medical Center, Aurora, Colorado; ⁴Division of Hospital Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado; ⁵Department of Medicine, Denver Health and Hospital Authority, Denver, Colorado.

Disclosures

Dr. Burke is funded by a VA HSR&D Career Development Award, Dr. Greysen is funded by NIA K23 (AG045338). The authors have no conflicts of interest relevant to the presented work. All views are those of the authors and not necessarily those of the US Department of Veterans Affairs.

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Robert E Burke, MD, MS

Chelsea Leonard, PhD

Marcie Lee, MA, MPH

Roman Ayele, PhD, MPH

Ethan Cumbler, MD

Rebecca Allyn, MD

S Ryan Greysen, MD, MHS, MA

Author(s)

Robert E Burke, MD, MS

Chelsea Leonard, PhD

Marcie Lee, MA, MPH

Roman Ayele, PhD, MPH

Ethan Cumbler, MD

Rebecca Allyn, MD

S Ryan Greysen, MD, MHS, MA

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METHODS

Study Design

Analysis

RESULTS 

Authority Bias/Halo Effect

Veterans expressed confidence in the VA regarding both whether to go to a SNF and where to go:

Their caregivers expressed similar confidence:

In contrast to Veterans, non-Veteran patients seemed to experience authority bias when it came to the inpatient team.

“Well, I’d like to know more about the PTs [Physical Therapists] there, but I assume since they were recommended, they will be good.” (Patient, University hospital)

This perspective was especially apparent when it came to physicians:

Default/Status quo Bias

Anchoring Bias

Patients occasionally had striking responses to particular characteristics of SNFs, regardless of whether this was a central feature or related to their rehabilitation:

Framing

Clinicians avoided negative associations with “nursing home” (even though all SNFs are nursing homes) and tended to use more positive frames such as “rehabilitation facility.”

In some cases, framing was so overt that other risk-mitigating options (eg, home healthcare) are not discussed.

DISCUSSION

METHODS

Study Design

Analysis

RESULTS 

Authority Bias/Halo Effect

Veterans expressed confidence in the VA regarding both whether to go to a SNF and where to go:

Their caregivers expressed similar confidence:

In contrast to Veterans, non-Veteran patients seemed to experience authority bias when it came to the inpatient team.

“Well, I’d like to know more about the PTs [Physical Therapists] there, but I assume since they were recommended, they will be good.” (Patient, University hospital)

This perspective was especially apparent when it came to physicians:

Default/Status quo Bias

Anchoring Bias

Patients occasionally had striking responses to particular characteristics of SNFs, regardless of whether this was a central feature or related to their rehabilitation:

Framing

Clinicians avoided negative associations with “nursing home” (even though all SNFs are nursing homes) and tended to use more positive frames such as “rehabilitation facility.”

In some cases, framing was so overt that other risk-mitigating options (eg, home healthcare) are not discussed.

DISCUSSION

References

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Corresponding Author

Robert E Burke, MD, MS

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Robert E. Burke MD, MS; E-mail: Robert.Burke2@uphs.upenn.edu; Telephone: 215-573-3205; Twitter: @BBurkeMD

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Random Drug Testing of Physicians: A Complex Issue Framed in 7 Questions

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Author(s)

Ethan Cumbler, MD

Jean S. Kutner, MD, MPSH

Should physicians be subject to random drug testing? It’s a controversial topic. One in 10 Americans suffer from a drug use disorder at some point in their lives.¹ Although physicians engaging in drug diversion is very rare, we recognize, in the context of rising rates of opiate use, that drug misuse and addiction can involve physicians.^2,3 When it occurs, addiction can drive behaviors that endanger both clinicians and patients. Media reports on drug diversion describe an anesthesiologist who died of overdose from diverted fentanyl and a surgical technician with HIV who used and replaced opioids in the operating room, resulting in thousands of patients needing to be tested for infection.⁴ Multiple outbreaks of hepatitis C involving more than a dozen hospitals in eight states were traced to a single health care provider diverting narcotics.⁵ An investigation of outbreaks at various medical centers in the United States over a 10-year period identified nearly 30,000 patients that were potentially exposed and more than 100 iatrogenic infections.⁶

The profession of medicine holds a special place in the esteem of the public, with healthcare providers being among the most trusted professions. Patients rely on us to keep them safe when they are at their most vulnerable. This trust is predicated on the belief that the profession of medicine will self-regulate. Drug diversion by clinicians is a violation of this trust.

Our hospital utilizes existing structures to address substance use disorder; such structures include regular education on recognizing impairment for the medical staff, an impaired clinician policy for suspicion of impairment, and a state physician health program that provides nonpunitive evaluation and treatment for substance use by clinicians. In response to the imperative to mitigate the potential for drug diversion, our health system undertook a number of additional initiatives. These initiatives, included inventory control and tracking of controlled substances, and random testing and trigger-based audits of returned medications to ensure the entire amount had been accounted for. As part of this system-wide initiative, UCHealth began random drug testing of employees in safety-sensitive positions (for whom impairment would represent the potential for harm to others). Medical staff are not employees of the health system and were not initially subject to testing. The key questions at the time included the following:

Is our organization doing everything possible to prevent drug diversion?
If nurses and other staff are subject to random drug testing, why would physicians be exempt?

The University of Colorado Hospital (UCH) is the academic medical center within UCHealth. The structure of the relationship between the hospital and its medical staff requires the question of drug testing for physicians to be addressed by the UCH Medical Board (Medical Executive Committee). Medical staff leadership and key opinion leaders were engaged in the process of considering random drug testing of the medical staff. In the process, medical staff leadership raised additional questions about the process of decision making:

“How should this issue be handled in the context of physician autonomy?”
“How do we assure the concerns of the medical staff are heard and addressed?”

The guiding principles considered by the medical staff leadership in the implementation of random drug testing included the following: (1) as a matter of medical professionalism, for random drug testing to be implemented, the medical staff must elect to submit to mandatory testing; (2) the random drug testing program must be designed to minimize harm; and (3) the process for random drug testing program design needs to engage front-line clinicians. This resulted in a series of communications, meetings, and outreach to groups within the medical staff.

From front-line medical staff members, we heard overwhelming consensus for the moral case to prevent patient harm resulting from drug diversion, our professional duty to address the issue, and the need to maintain public trust in the institution of medicine. At the same time, medical staff members often expressed skepticism regarding the efficacy of random drug testing as a tactic, concerns about operational implementation, and fears regarding the unintended consequences:

How strong is the evidence that random drug testing prevents drug diversion?
How can we be confident that false-positive tests will not cause innocent clinicians to be incorrectly accused of drug use?

The efficacy of random drug testing in preventing drug diversion is not settled. The discussion of how to proceed in the absence of well-designed studies on the tactic was robust. One common principle we heard from members of the medical staff was that our response be driven by an authentic organizational desire to reduce patient harm. They expressed that the process of testing needs to respect the boundaries between work and home life and to avoid the disruption of clinical responsibilities. Whether targeting testing to “higher risk” groups of clinicians is appropriate and whether or not alcohol and/or marijuana would be tested came up often.

Other concerns expressed also included the intrusion of the institution into the private medical conditions of the medical staff members, breach of confidentiality, or accessibility of the information obtained as a result of the program for unrelated legal proceedings. One of the most prominent fears expressed was the possible impact of false-positive tests on the clinicians’ careers.

Following the listening tour by the medical staff and hospital leadership and extensive discussions, the Medical Board voted to approve a policy to implement random drug testing. The deliberative process lasted for approximately eight months. We sought input from other healthcare systems, such as the Veterans Administration and Cleveland Clinic, that conduct random drug tests on employed physicians. A physician from Massachusetts General Hospital who led the 2004 implementation of random drug testing for anesthesiologists was invited to come to Colorado to give grand rounds about the experience in his department and answer questions about the implementation of random drug testing at a Medical Board meeting.⁷ The policy went into effect January 2017.

The design of the program sought to explicitly address the issues raised by the front-line clinicians. In the interest of equity, all specialties, including Radiology and Pathology, are subject to testing. Medical staff are selected for testing using a random number generator and retained in the random selection pool at all times, regardless of previous selection for testing. Consistent with the underlying objective of identifying drug diversion, testing is limited to drugs at higher risk for diversion (eg, amphetamine, barbiturate, benzodiazepine, butorphanol, cocaine metabolite, fentanyl, ketamine, meperidine, methadone, nalbuphine, opiates, oxycodone, and tramadol). Although alcohol and marijuana are substances of abuse, they are not substances of healthcare diversion and thus are excluded from random drug testing (although included in testing for impairment). Random drug testing is conducted only for medical staff who are onsite and providing clinical services. The individuals selected for random drug testing are notified by Employee Health, or their clinical supervisor, to present to Employee Health that day to provide a urine sample. The involvement of the clinical supervisor in specific departments and the flexibility in time of presentation was implemented to address the concerns of the medical staff regarding harm from the disruption of acute patient care.

To address the concern regarding false-positive tests, an external medical laboratory that performs testing compliant with Substance Abuse and Mental Health Services and governmental standards is used. Samples are split providing the ability to perform independent testing of two samples. The thresholds are set to minimize false-positive tests. Positive results are sent to an independent medical review officer who confidentially contacts the medical staff member to assess for valid prescriptions to explain the test results. Unexplained positive test results trigger the testing of the second half of the split sample.

To address issues of dignity, privacy, and confidentiality, Employee Health discretely oversees the urine collection. The test results are not part of the individual’s medical record. Only the coordinator for random drug testing in Human Resources compliance can access the test results, which are stored in a separate, secure database. The medical review officer shares no information about the medical staff members’ medical conditions. A positive drug assay attributable to a valid medical explanation is reported as a negative test.

Positive test results, which would be reported to the President of the Medical Staff, would trigger further investigation, potential Medical Board action consistent with medical staff bylaws, and reporting to licensing bodies as appropriate. We recognize that most addiction is not associated with diversion, and all individuals struggling with substance use need support. The medical staff and hospital leadership committed through this process to connecting medical staff members who are identified by random drug testing to help for substance use disorder, starting with the State Physician Health Program.

The Medical Executive Committees of all hospitals within UCHealth have also approved random drug testing of medical staff. We are not the first healthcare organization to tackle the potential for drug diversion by healthcare workers. To our knowledge, we are the largest health system to have nonemployed medical staff leadership vote for the entire medical staff to be subject to random drug testing. Along the journey, the approach of random drug testing for physicians was vigorously debated. In this regard, we proffer one final question:

How would you have voted?

Disclosures

The authors have nothing to disclose.

References

1. Grant BF, Saha TD, Ruan WJ, et al. Epidemiology of DSM-5 drug use disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions-III. JAMA Psychiatry. 2016;73(1):39-47. doi: 10.1001/jamapsychiatry.2015.2132. PubMed
2. Oreskovich MR, Shanafelt T, Dyrbye LN, et al. The prevalence of substance use disorders in American physicians. Am J Addict. 2015;24(1):30-38. doi: 10.1111/ajad.12173. PubMed
3. Hughes PH, Brandenburg N, Baldwin DC Jr., et al. Prevalence of substance use among US physicians. JAMA. 1992;267(17):2333-2339. doi:10.1001/jama.1992.03480170059029. PubMed
4. Olinger D, Osher CN. Denver Post- Drug-addicted, dangerous and licensed for the operating room. https://www.denverpost.com/2016/04/23/drug-addicted-dangerous-and-licensed-for-the-operating-room/ Published April 23, 2016. Updated June 2, 2016. Accessed June 7, 2018.
5. Federal Bureau of Investigations. Press Release. Former Employee of Exeter Hospital Pleads Guilty to Charges Related to Multi-State Hepatitis C Outbreak. https://archives.fbi.gov/archives/boston/press-releases/2013/former-employee-of-exeter-hospital-pleads-guilty-to-charges-related-to-multi-state-hepatitis-c-outbreak. Accessed June 7, 2018.
6. Schaefer MK, Perz JF. Outbreaks of infections associated with drug diversion by US healthcare personnel. Mayo Clin Proc. 2014;89(7):878-887. doi: 10.1016/j.mayocp.2014.04.007. PubMed
7. Fitzsimons MG, Baker K, Malhotra R, Gottlieb A, Lowenstein E, Zapol WM. Reducing the incidence of substance use disorders in anesthesiology residents: 13 years of comprehensive urine drug screening. Anesthesiology. 2018;129:821-828. doi: 10.1097/ALN.0000000000002348. In press. PubMed

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Jean S. Kutner, MD, MPSH

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Is our organization doing everything possible to prevent drug diversion?
If nurses and other staff are subject to random drug testing, why would physicians be exempt?

“How should this issue be handled in the context of physician autonomy?”
“How do we assure the concerns of the medical staff are heard and addressed?”

How strong is the evidence that random drug testing prevents drug diversion?
How can we be confident that false-positive tests will not cause innocent clinicians to be incorrectly accused of drug use?

How would you have voted?

Disclosures

The authors have nothing to disclose.

Is our organization doing everything possible to prevent drug diversion?
If nurses and other staff are subject to random drug testing, why would physicians be exempt?

“How should this issue be handled in the context of physician autonomy?”
“How do we assure the concerns of the medical staff are heard and addressed?”

How strong is the evidence that random drug testing prevents drug diversion?
How can we be confident that false-positive tests will not cause innocent clinicians to be incorrectly accused of drug use?

How would you have voted?

Disclosures

The authors have nothing to disclose.

References

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Post–acute care reform: Implications and opportunities for hospitalists

Author(s)

Robert E. Burke, MD, MS

Ethan Cumbler, MD

Eric A. Coleman, MPH

Cari Levy, PhD

The landscape of post–acute care (PAC), which is predominantly provided by inpatient rehabilitation facilities (IRFs), skilled nursing facilities (SNFs), and home healthcare (HHC) providers, is rapidly changing. As hospitalizations shorten, PAC utilization is rising, resulting in rapidly increasing costs.^1-5 However, patient outcomes in PAC are characterized by high rates of readmission and low rates of return to the community.^6,7 Emerging evidence suggests these outcomes could be substantially improved through use of better in-hospital and transitional care processes.^8-10

Legislators took notice of the spiraling costs, potential quality concerns, and undesirable patient outcomes in PAC. Provisions in the Patient Protection and Affordable Care Act of 2010 (ACA), the Protecting Access to Medicare Act of 2014 (PAMA), and the Improving Medicare Post–Acute Care Transformation (IMPACT) Act of 2014 affect patient selection, payment, and quality measurement in PAC. As older adults are increasingly being cared for by hospitalists,¹¹ hospitalists must be aware of the implications of these reforms.

IMPLICATIONS FOR HOSPITALISTS

Choosing Patients Wisely for PAC

Because PAC-related decision making is not standardized, referral rates vary significantly.¹² The variability in PAC use accounts for 79% of all regional variation in Medicare spending in the United States.^13,14 Compared with other physicians, hospitalists are more likely to use PAC¹⁵ but typically receive little exposure to PAC during training.¹⁶

The IMPACT Act proposes 2 major changes to patient selection: a uniform assessment tool for patients being discharged to PAC and “site-neutral” payments for PAC. Starting in 2018, the Continuity Assessment Record and Evaluation (CARE) tool must be completed before a hospital discharge in order to better match PAC resources to patient needs. The current 26-page CARE tool includes questions about demographics and home support, medical complexity, physical function, cognitive status, and “transition items,” including discharge plans and advance directives. In pilot testing, significant amounts of missing data and average completion times of up to 60 minutes raised concerns about feasibility.¹⁷ CARE tool assessments accurately predicted what form of PAC patients actually received, but further testing is planned to validate whether the type of PAC selected was optimal for patient outcomes.. A plan for using CARE tool assessments to determine site-neutral payments is due to Congress by 2020. In the site-neutral payment system, the PAC provider will be reimbursed according to patient needs (identified by the CARE tool), regardless of PAC setting—a radical change from the current system, in which IRF, SNF, and HHC episodes show major differences in median costs (Table 1).¹⁸

Hospitalists may be concerned that use of the CARE tool will supplant clinical judgment about patients’ PAC needs. The burden of completing the CARE tool could inadvertently reduce the amount of attention hospitalists give to other aspects of a safe discharge rather than lead to the improvement desired.^19-21 Hospitalists will benefit from developing interdisciplinary, iterative workflows to complete the tool, improving accuracy and reducing the burden.

A potential unintended consequence of the site-neutral payment system may be increased difficulty discharging elderly patients who have limited rehabilitation potential but are lacking sufficient social support to return home. In the current system, these patients are commonly discharged to SNFs as a bridge to long-term nursing home care. Hospitalists will need to become increasingly familiar with novel alternatives to nursing home–based care, such as home-based primary care, medical foster homes, and Medicare/Medicaid’s Program of All-Inclusive Care of the Elderly (PACE).^22-25

Choosing PAC Providers Wisely

Medicare’s Nursing Home Compare tool (https://www.medicare.gov/nursinghomecompare/search.html) provides a “5-star” system for rating SNFs on several quality metrics; these metrics, however, are not correlated with readmission or mortality rates.^26,27 Improving quality measurement in PAC and tying payment to quality and outcomes are major emphases of the IMPACT Act and PAMA, respectively. PAC providers must publicly report an expanded list of quality measures and outcomes by 2018. In 2017, SNFs will begin reporting rates of “potentially preventable” readmissions, and starting in 2019 they will face penalties for having high
risk-adjusted rates.

These reforms coincide with an increased emphasis on hospitals and PAC providers sharing responsibility for costs and outcomes. One model of the Bundled Payments for Care Improvement (BPCI) initiative includes a single payment for an acute hospitalization and PAC up to 90 days after hospital discharge for select conditions. The Medicare Spending Per Beneficiary (MSPB) measure compares hospitals on their spending for Medicare beneficiaries from 3 days before hospital admission to 30 days after hospital discharge, and penalizes outliers with high costs.²⁸ PAC spending is the main driver of costs in both BPCI and MSPB.²⁹ One way that hospitals have responded to the BPCI is by drastically reducing their referrals to SNFs and increasing their referrals to HHC providers; unfortunately, this response has resulted in increases in post-discharge emergency department visits.^29,30 Taking a novel step in November 2015, the Centers for Medicare & Medicaid Services (CMS) ruled that hospitals in more than 67 metropolitan service areas will be involuntarily enrolled in the BPCI initiative, using elective lower extremity joint replacement as the sample condition.³¹ This ruling signaled that these reforms are not meant solely for “high-performing” hospital and PAC systems able to volunteer for novel models of payment.

These changes have direct implications for hospitalists. Bundled payments incentivize hospitalists to reduce hospital length of stay and choose PAC alternatives with lower costs. SNFs may start accepting fewer “high-risk” patients in order to avoid readmission penalties. Hospitals will need to identify and partner with high-performing PAC providers in their community to maximize outcomes for their patients. On their websites, the Society of Post-Acute and Long-Term Care Medicine (AMDA) lists its state chapters,³² and the National Association for Home Care & Hospice lists national HHC agencies.³³ Reviewing early lessons learned in the evaluation of PAC providers as potential hospital partners in Pioneer accountable care organizations may be helpful,³⁴ though the PAC cost savings in these organizations largely resulted from redirecting patients from SNFs to HHC providers.^35,36 In many markets, the relationships between hospitals and PAC providers may become more formalized, leading to vertical integration.³⁷ Hospitalists may increasingly be asked to work with, or even in, SNFs.³⁸ For hospitalists who begin working in PAC, the AMDA is developing an educational curriculum to maximize efficacy in a new practice setting.³⁹ In other markets, hospitals may turn to for-profit entities that provide “integrated post-acute care services,”⁴⁰ taking over PAC decision making from inpatient teams and sharing any resulting profits
from bundled payments.

OPPORTUNITIES FOR HOSPITALISTS

Improve Hospital and Transitional Care to Ensure Successful Early Outcomes in PAC

Payment reform ensures hospitalists will increasingly have a stake in these matters, as joint responsibility for costs and outcomes increases for patients discharged to PAC. Hospitalists play a major role in these outcomes by deciding when and where to discharge patients and ensuring that optimal transition-of-care processes are used.^8-10,41-45 Although no single intervention has been prospectively found to improve hospital-to-PAC transitional care outcomes, areas in need of improvement are known. Table 2 lists these within 9 of the Ideal Transition of Care Framework domains.^43,46

Advocate Patient-Centered PAC Placement That Maximizes Long-Term Outcomes

Payment reforms could reinforce the cynical view that the optimal PAC setting is the least costly one that avoids hospital readmission. This view does not incorporate evidence that, in some cases, placement in a more costly PAC setting results in better long-term outcomes (eg, community discharge rates).^47,48 It is also incongruent with a holistic view of the patient’s needs, particularly for patients who may otherwise be suitable for home-based PAC but have limited social support.⁴⁹ Finally, it does not acknowledge the reality that patients who are inadequately rehabilitated often transition to long-term nursing home care,⁵⁰ which could result in significant cost-shifting from Medicare to Medicaid, the predominant payer for long-term care.⁵¹ Given the extraordinary cost of long-term nursing home care, attending only to short-term costs and outcomes could increase national healthcare expenditures.

With most PAC-related decisions being made in the hospital, hospitalists find themselves at the center of a care team that must advocate the PAC that is best for the patient over the long term. This endeavor requires that hospitalists and others work for improvements in at least 3 aspects of in-hospital care. First, systems for accurately and reliably identifying patient factors that could substantially affect ability to rehabilitate (eg delirium) must be developed or enhanced.^52-54 Second, more formal evaluation of the ability of patients and their caregivers to succeed at home is needed.^55-60 Patients and caregivers may not understand their home needs without first “testing” the experience prior to discharge.⁶¹ Third, hospitalists must understand PAC in order to provide safe transitions.¹⁶ It is logistically challenging to expose practicing hospitalists to PAC, and it is unclear which exposures are most effective in improving decision making.⁶² An alternative approach that provides hospitalists with feedback about the short- and long-term outcomes of patients they have discharged to PAC may iteratively improve decision making. However, despite the high rate of discharges to PAC, there are anecdotal reports that few hospitalists receive feedback on patient outcomes.

As these reforms are tested and implemented, advocacy at regional and national levels is needed. The American Geriatrics Society (AGS), the AMDA, and the American Academy of Home Care Medicine all have well-developed advocacy platforms hospitalists can access.^63-65

Share Expertise to Improve Quality in a Constrained Environment

There are opportunities for synergy between robust quality improvement (QI) efforts in PAC (often as part of Quality Assurance and Performance Improvement programs) and similarly robust hospital QI efforts led by hospitalists.^66-70 These efforts have largely occurred in parallel, but now some important bridging QI interventions (eg, collaborative root cause analyses for patients readmitted after PAC) are starting at some sites, and these may drive improvement across the care spectrum.⁴⁵ The Society of Hospital Medicine, the AGS, and the AMDA have written White Papers on care transitions that may serve as starting points for
discussion.^41,71,72

CONCLUSION

PAC is rapidly changing in response to reform legislation that is intended to address poor outcomes and high costs. Hospitalists will increasingly feel the effects of these reforms in their day-to-day practices. To continue to deliver high-value care, hospitalists should review their in-hospital and transitional care practices and start building relationships with high-quality PAC providers in their community.

Disclosures: Dr. Burke was supported by a VA Health Services Research and Development Service career development award and by National Institute on Aging grant R03 AG050885. The funders had no role in the design, conduct, interpretation, or presentation of the data. The other authors have nothing to report. The views represented here are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs.

References

1. Kosecoff J, Kahn KL, Rogers WH, et al. Prospective payment system and impairment at discharge. The ‘quicker-and-sicker’ story revisited. JAMA. 1990;264(15):1980-1983. PubMed

2. Burke RE, Juarez-Colunga E, Levy C, Prochazka AV, Coleman EA, Ginde AA. Patient and hospitalization characteristics associated with increased postacute care facility discharges from US hospitals. Med Care. 2015;53(6):492-500. PubMed

3. Jones CD, Ginde AA, Burke RE, Wald HL, Masoudi FA, Boxer RS. Increasing home healthcare referrals upon discharge from U.S. hospitals: 2001-2012. J Am Geriatr Soc. 2015;63(6):1265-1266. PubMed

4. Burke RE, Juarez-Colunga E, Levy C, Prochazka AV, Coleman EA, Ginde AA. Rise of post-acute care facilities as a discharge destination of US hospitalizations. JAMA Intern Med. 2015;175(2):295-296. PubMed

5. Chandra A, Dalton MA, Holmes J. Large increases in spending on postacute care in Medicare point to the potential for cost savings in these settings. Health Aff (Millwood). 2013;32(5):864-872. PubMed

6. Mor V, Intrator O, Feng Z, Grabowski DC. The revolving door of rehospitalization from skilled nursing facilities. Health Aff (Millwood). 2010;29(1):57-64. PubMed

7. Kramer A, Fish R, Min S. Community Discharge and Rehospitalization Outcome Measures (Fiscal Year 2011): Final Report. Denver, CO: Providigm. http://67.59.137.244/documents/Apr13_CommunityDischarge_CONTRACTOR.pdf. Published April 15, 2013. Accessed March 24, 2016.

8. Burke RE, Whitfield EA, Hittle D, et al. Hospital readmission from post-acute care facilities: risk factors, timing, and outcomes. J Am Med Dir Assoc. 2016;17(3):249-255. PubMed

9. Levinson DR. Adverse Events in Skilled Nursing Facilities: National Incidence Among Medicare Beneficiaries. Washington, DC: Office of the Inspector General, US Dept of Health and Human Services. Report OEI-06-11-00370. http://oig.hhs.gov/oei/reports/oei-06-11-00370.pdf. Published February 2014. Accessed March 5, 2014.

10. Ouslander JG, Naharci I, Engstrom G, et al. Lessons learned from root cause analyses of transfers of skilled nursing facility (SNF) patients to acute hospitals: transfers rated as preventable versus nonpreventable by SNF staff. J Am Med Dir Assoc. 2016;17(7):596-601. PubMed

11. Kuo YF, Sharma G, Freeman JL, Goodwin JS. Growth in the care of older patients by hospitalists in the United States. N Engl J Med. 2009;360(11):1102-1112. PubMed

12. Kane RL. Finding the right level of posthospital care: “We didn’t realize there was any other option for him.” JAMA. 2011;305(3):284-293. PubMed

13. Newhouse JP, Garber AM. Geographic variation in health care spending in the United States: insights from an Institute of Medicine report. JAMA. 2013;310(12):1227-1228. PubMed

14. Kane RL, Lin WC, Blewett LA. Geographic variation in the use of post-acute care. Health Serv Res. 2002;37(3):667-682. PubMed

15. Kuo YF, Goodwin JS. Association of hospitalist care with medical utilization after discharge: evidence of cost shift from a cohort study. Ann Intern Med. 2011;155(3):152-159. PubMed

16. Ward KT, Eslami MS, Garcia MB, McCreath HE. Do internal medicine residents know enough about skilled nursing facilities to orchestrate a good care transition? J Am Med Dir Assoc. 2014;15(11):841-843. PubMed

17. Centers for Medicare & Medicaid Services. CARE Item Set and B-CARE. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/CARE-Item-Set-and-B-CARE.html. Published January 13, 2015. Accessed November 2, 2015.

18. Medicare Payment Advisory Commission. Report to the Congress: Medicare Payment Policy. Washington, DC: Medicare Payment Advisory Commission. http://medpac.gov/docs/default-source/reports/mar2015_entirereport_revised.pdf. Published March 13, 2015. Accessed December 8, 2015.

19. Block L, Morgan-Gouveia M, Levine RB, Cayea D. We could have done a better job: a qualitative study of medical student reflections on safe hospital discharge.
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20. Greysen SR, Schiliro D, Horwitz LI, Curry L, Bradley EH. “Out of sight, out of mind”: housestaff perceptions of quality-limiting factors in discharge care at teaching hospitals. J Hosp Med. 2012;7(5):376-381. PubMed

21. Halasyamani L, Kripalani S, Coleman E, et al. Transition of care for hospitalized elderly patients—development of a discharge checklist for hospitalists. J Hosp Med. 2006;1(6):354-360. PubMed

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24. Segelman M, Szydlowski J, Kinosian B, et al. Hospitalizations in the Program of All-Inclusive Care for the Elderly. J Am Geriatr Soc. 2014;62(2):320-324. PubMed

25. Manheim CE, Haverhals LM, Jones J, Levy CR. Allowing family to be family: end-of-life care in Veterans Affairs medical foster homes. J Soc Work End Life Palliat Care. 2016;12(1-2):104-125. PubMed

26. Neuman MD, Wirtalla C, Werner RM. Association between skilled nursing facility quality indicators and hospital readmissions. JAMA. 2014;312(15):1542-1551. PubMed

27. Unroe KT, Greiner MA, Colón-Emeric C, Peterson ED, Curtis LH. Associations between published quality ratings of skilled nursing facilities and outcomes of Medicare beneficiaries with heart failure. J Am Med Dir Assoc. 2012;13(2):
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28. Schumacher DN, Dobkin ED. Medicare spending per beneficiary. Health Aff (Millwood). 2014;33(10):1878. PubMed

29. Das A, Norton EC, Miller DC, Chen LM. Association of postdischarge spending and performance on new episode-based spending measure. JAMA Intern Med. 2016;176(1):117-119. PubMed

30. Jubelt LE, Goldfeld KS, Chung WY, Blecker SB, Horwitz LI. Changes in discharge location and readmission rates under Medicare bundled payment. JAMA Intern Med. 2016;176(1):115-117. PubMed

31. Federal Register: Medicare Program; Comprehensive Care for Joint Replacement Payment Model for Acute Care Hospitals Furnishing Lower Extremity Joint Replacement Services. https://www.gpo.gov/fdsys/pkg/FR-2015-11-24/pdf/2015-29438.pdf. Accessed June 20, 2016.

32. Society for Post-Acute and Long-Term Care Medicine. State chapters; AMDA state chapter network. http://www.paltc.org/state-chapters. Accessed June 6, 2016.

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34. Lage DE, Rusinak D, Carr D, Grabowski DC, Ackerly DC. Creating a network of high-quality skilled nursing facilities: preliminary data on the postacute care quality improvement experiences of an accountable care organization. J Am Geriatr Soc. 2015;63(4):804-808. PubMed

35. Nyweide DJ, Lee W, Cuerdon TT, et al. Association of Pioneer accountable care organizations vs traditional Medicare fee for service with spending, utilization, and patient experience. JAMA. 2015;313(21):2152-2161. PubMed

36. McWilliams JM, Chernew ME, Landon BE, Schwartz AL. Performance differences in year 1 of Pioneer accountable care organizations. N Engl J Med. 2015;372(20):1927-1936. PubMed

37. Afendulis CC, Kessler DP. Vertical integration and optimal reimbursement policy. Int J Health Care Finance Econ. 2011;11(3):165-179. PubMed

38. IPC Healthcare. Post-acute care services. http://www.ipchealthcare.com/advantage/post-acute-care. Accessed January 11, 2016.

39. Society for Post-Acute and Long-Term Care Medicine. Competencies curriculum for post-acute and long-term care medicine. http://www.paltc.org/competencies-curriculum-post-acute-and-long-term-care-medicine. Accessed May 26, 2016.

40. NaviHealth. Leading the way in a rapidly changing PAC marketplace. http://www.navihealth.us/home/solutions/services. Accessed January 11, 2016.

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