Challenges in Reducing Readmissions: Lessons from Leadership and Frontline Personnel at Eight Minority-Serving Hospitals

Abstract

Background:

Hospitals that serve minority patients have higher readmission rates than other hospitals and, as a result, receive higher penalties under the federal government’s Hospital Readmissions Reduction Program. A study was conducted to determine how minority-serving hospitals are responding to federal readmissions policy and whether they face specific challenges as they work to reduce readmissions.

Methods:

In-depth case studies were created for eight minority-serving hospitals, selected to reflect a range of geographies and sizes. Semistructured interviews with hospital leaders and frontline personnel focused on knowledge of readmission rates and prioritization of readmission reduction, strategies to reduce readmissions, barriers to reducing Readmissions, and opinions about federal readmissions policy.

Results:

Each hospital had only a general awareness of its performance on readmissions metrics but placed a high priority on reducing readmissions, largely spurred by federal readmissions policy. Respondents reported that socioeconomics, rather than race alone, was a key factor in readmissions reduction. The hospitals followed a similar progression in strategies to reduce readmissions—moving from working on the discharge process to creating customized approaches to transitional care to, finally, focusing more on building community supports and resources. Salient barriers to reducing readmission rates included scarce resources, the variety of patient needs, limited ability to influence care in the community, and a misalignment of financial incentives.

Conclusions:

Among eight hospitals serving a high proportion of minority patients, the findings uncovered the importance of addressing issues specific to the patient population and community and reaching outside the walls of the hospital to implement programs that improve outpatient access and management.

Early readmissions to hospitals occur frequently and are expensive and often avoidable.^1,2 The Affordable Care Act established the Hospital Readmissions Reduction Program (HRRP), the first nationwide effort in the United States to use financial incentives to reduce readmissions.³ Beginning with fiscal year (FY) 2013 (October 2012–September 2013) the Center for Medicare & Medicaid Services (CMS) tracks readmission rates for selected medical conditions and levies penalties against hospitals with higher than expected 30-day risk-adjusted readmission rates. However, little is known about how hospitals are responding to the program in terms of setting their strategic priorities and implementing new initiatives.

Of special interest, hospitals that serve a high proportion of minority patients tend to have high readmission rates⁴ and may be more likely to be penalized under the HRRP.⁵ Although some studies have shed light on the specific patient characteristics that may predict a higher risk of readmission,^4,6,7 hospital-based studies of strategies, challenges, and successes in reducing readmissions have not systematically examined minority-serving hospitals,^8–12 which may differ from other hospitals in important ways. These hospitals may also be particularly motivated to reduce readmissions because of incumbent financial penalties. Understanding the challenges faced by minority-serving hospitals and exploring the interventions that they are undertaking may enable the dissemination of these approaches to similar hospitals seeking to lower their rates of readmission and may help reduce racial disparities in this important health outcome. Further, given that minority-serving hospitals face significant penalties under current federal readmissions policy, understanding the issues that are most salient for these hospitals may help improve future policies. Accordingly, we conducted a series of detailed case studies to better understand how the HRRP has affected minority-serving hospitals, to learn more about the strategies they are employing to reduce readmissions, and to explore challenges specific to these hospitals in reducing readmission rates.

Methods

Site Selection

We conducted a qualitative study from September 2012 through April 2013. This study was approved by the Office of Human Research Administration at the Harvard School of Public Health. Our intent was to enroll eight hospitals into the study, with the methodological rationale that, on the basis of two previous studies of readmission strategies,^12,13 “saturation” is generally reached after a relatively small number in terms of identifying common, generalizable lessons. We selected participating institutions with a patient population greater than 50% black, as identified by Medicare inpatient data for all acute care hospitals in the United States from 2008 through 2010, the most recent data available at the time of study initiation. We identified hospitals that represented a range of readmission rates and other characteristics. We used the Medicare data to calculate a composite readmission rate for acute myocardial infarction, congestive heart failure, and pneumonia—the three conditions that are the focus of the HRRP. The American Hospital Association survey data were used to obtain information on hospitals’ size, teaching status, ownership, region, and location.¹⁴ Hospitals in the top quartile of the Disproportionate Share Hospital (DSH) index were considered to be safety-net hospitals, as has been done previously.^15,16 Four of the eight hospitals initially agreed. After each refusal we selected an alternate hospital and invited it to participate. Two sites refused because of inopportune timing or the belief that participation would not benefit them, and five sites did not respond to our solicitation. In total, we contacted 15 hospitals to achieve our target enrollment of 8.

Interviews

We developed a semistructured interview guide, shown in Appendix 1 (available in online article), to explore our study question. To inform the development of our instrument, we considered organizational change theory, in particular the concept of “rational models” that emphasize awareness of a problem or quality gap, identification of an action to solve the problem or narrow the gap, implementation of the action, and, finally, institutionalization, where all relevant parties accept the change.¹⁷ For each of these steps, we created a set of questions to help us understand hospitals’ progress in organizational change. For ease of presentation and conversation, we then sorted these questions into four main topical domains—knowledge of readmission rates and prioritization of readmission reduction, strategies to reduce readmissions, barriers to reducing readmissions, and opinions about federal readmissions policy.

We identified hospital leaders involved in quality initiatives and readmissions reduction programs. Two trained coauthors [K.E.J. or J.S.W, along with A.M.E or A.K.J.] spoke with at least one member of the hospital corporate suite (C-suite) leadership team (CEO, chief medical officer, chief quality officer, chief financial officer, chief nursing officer), frontline readmissions reduction staff (director of case management, director of care coordination, or equivalent), or clinical personnel (division chiefs, staff physicians, and nurse managers). Each participant provided informed consent and was informed about the confidentiality agreement associated with the project.

At least two members of the study team participated in all the interviews, which were audiorecorded. During the majority of the interviews, an investigator and a research assistant each took notes. When this was not feasible, only one set of notes was prepared, but both interviewers reviewed the notes for accuracy. In general, the notes were organized according to the domains described previously. Using a technique in which researchers verify study findings with members of the study, in a form of member checking, we validated our findings by sending a case study site summary to all the interviewees at each site for feedback.

Data Analysis

Although there is no universally accepted approach to qualitative data analysis, a rigorous approach can help to ensure the reliable discovery of emergent themes. The analysis used in this study roughly followed the method described by Miles and Huberman,¹⁸ which included a multistep, iterative process to ensure the quality of the data and the interpretation.

We analyzed the transcribed and summarized interviews using standard qualitative analysis techniques with a cross-case approach that relied on pattern-matching and explanation-building.¹⁹ The first analytic stage was familiarization, in which a review of a subset of the interviews early on was undertaken to immerse the researcher intellectually in the data and begin to list key themes and ideas. Next, we conducted a thematic analysis of the interviews, developing the coding scheme on the basis of repeated readings of the materials, using inductive and deductive development of themes. Because we were more interested in a thematic and policy analysis than development of grounded theory, we were able to perform the coding manually. We created a typology of themes related to readmissions that interviewees believed were important, and each hospital’s notes were coded into a matrix. The matrix listed groups of comments or subthemes and indicated the frequency with which they were mentioned and the intensity of the opinions as best as could be determined from the interview notes and audiotapes. Intensity was coded as “low” or “high” as follows:

• Low: Respondents expressed simple agreement with a theme but did not express strong feelings on the subject.

• High: Respondents expressed strong agreement with the stated theme, as evidenced by language such as “very important” or being dismissive of the importance.

Relevant quotations from respondents explaining or elaborating on a theme or subtheme were noted and keyed to a separate file of quotations.

The data were sifted and interpreted to produce the preliminary findings. The preliminary findings were distributed to study staff for input, and discussions were held to assemble a coherent understanding of the data. This process was repeated until all study team members were in agreement on the themes and subthemes included in the manuscript.

Finally, we summarized key characteristics of each participating hospital and the broader group of acute care hospitals in the United States by using Medicare and American Hospital Association data, as well as publicly available data on each hospital’s 2013 and 2014 HRRP penalty amounts.

Results

Sample Characteristics

Of the eight hospitals in the study sample, two were small, two were medium-sized, and four were large (Table 1, right). The majority were private, nonprofit hospitals, and half were located in urban areas; all eight were safety-net hospitals on the basis of the DSH index in the top quartile nationally. The median proportion of black patients at the hospitals in our sample was 67.5%, compared with 2.2% at other hospitals in the United States, and the median proportion of patients with Medicaid eligibility was 34.6%, compared with 16.7% at other hospitals. The median risk-adjusted readmission rate at hospitals in our sample from 2008 to 2010 was 20.2% for acute myocardial infarction, 27.1% for congestive heart failure, and 21.5% for pneumonia; all of which were higher than the median of other hospitals (Table 1). The study hospitals faced a median penalty from the HRRP of 0.42% in FY 2013 and of 0.40% in FY 2014, compared with 0.14% and 0.10% for the remainder of the hospitals in the program.

Table 1.

Sample Characteristics

Characteristic	Case Study Sites N = 8	US Acute Care Hospitals N = 4,788
Hospital Size
Small (< 100 beds)	25.0%	50.0%
Medium (100–399 beds)	25.0%	40.6%
Large (≥ 400 beds)	50.0%	9.3%
Profit Status
For-profit	12.5%	18.3%
Private nonprofit	62.5%	59.0%
Public	25.0%	22.7%
Region
Northeast	25.0%	12.4%
Midwest	37.5%	29.4%
South	37.5%	38.2%
West	0%	19.9%
Rurality
Urban	50.0%	46.0%
Suburban	25.0%	22.2%
Rural	25.0%	31.9%
Teaching Status
Teaching	50.0%	5.8%
Nonteaching	50.0%	94.2%
Safety-Net Status
Safety-net	100%	25.0%
Non-safety-net	0%	75.0%
Disproportionate Share Index (Mean)	0.531	0.278
Median Proportion Black	67.5%	2.2%
Median Proportion Medicaid	34.6%	16.7%
Median Proportion Medicare	40.1%	48.6%
Median AMI Readmission Rate 2008–2010	20.2%	18.2%
Median CHF Readmission Rate 2008–2010	27.1%	24.2%
Median PN Readmission Rate 2008–2010	21.5%	17.9%
Median HRRP Penalty, FY 2013*	0.42%	0.14%
Median HRRP Penalty, FY 2014†	0.40%	0.10%

AMI, acute myocardial infarction; CHF, congestive heart failure; PN, pneumonia; HRRP, Hospital Readmission Reduction Program; FY, fiscal year.

^*The FY 2013 penalty was calculated on the basis of readmission rates between 7/1/2008 and 6/30/2011. The penalty was applied to all Medicare payments for patient stays between 10/1/2012 and 9/30/2013.

^†The FY 2014 penalty was calculated on the basis of readmission rates between 7/1/2009 and 6/30/2012. The penalty was to be applied to all Medicare payments for patient stays between 10/1/2013 and 9/30/2014.

In total, we conducted 39 hour-long interviews, with between 1 and 11 individuals recruited from each site (Table 2, page 438). Hospital leadership (C-suite) comprised 14 (36%) of the interviews, and readmissions staff (case management, care coordination, and so forth) comprised 9 (23%). The remainder of the interviews were with department chiefs, division chairs, staff physicians, nurses, and nurse managers.

Table 2.

Interviewees

Title	Site 1	Site 2	Site 3	Site 4	Site 5	Site 6	Site 7	Site 8	Total
Chief Executive Officer	1		1						2
Chief Medical Officer	1			1	1		1	1	5
Chief Financial Officer				1					1
Chief Nursing Officer	1			1				1	3
Chief Quality Officer/VP Quality Management/Director of Quality	1	1			1	2			5
Director of Care Coordination/Transition Management/Case Management	1	2		3	1		1	2	10
Director of Service Line (Hospital Medicine, General Medicine, General Medicine Clinic, Internal Medicine, Emergency Medicine)		1		4			1		6
Nurse Manager								1	1
Other	1	2		1				2	6
Total	6	6	1	11	3	2	3	7	39

VP, vice president.

One study hospital was unengaged in trying to reduce readmissions because hospital leadership believed that it was not in the hospital’s best financial interest to do so. The remaining seven hospitals were all engaged, to some degree, in efforts to reduce readmissions.

Lessons

Four main lessons emerged from our work (Table 3, right), each of which we now elucidate.

Table 3.

Main Lessons Learned

Hospitals have only a general awareness of their performance on readmissions metrics but nevertheless place a high priority on reducing readmissions Federal readmissions policy has had a clear impact on hospital efforts to reduce readmission rates: Positive: forcing hospital leadership to address an important issue Negative: failing to adequately address the specific needs of these hospitals Most study hospitals followed a similar progression in strategies to reduce readmissions: Improving discharge → Creating customized approaches to improving transitional care → Building community supports Hospitals face a consistent set of challenges in reducing readmissions: Limited resources Need to address a large array of idiosyncratic patient needs Insufficient control over community care Misaligned incentives

Lesson 1. Hospitals have only a general awareness of their performance on readmissions metrics but nevertheless place a high priority on reducing readmissions.

Most respondents were aware of their hospital’s performance on readmissions compared with other hospitals in general terms (that is, “better” or “worse” than other local hospitals), but few respondents could cite actual readmission rates. Respondents pointed out that the publicly reported rates for Medicare patients reflected only a portion of their patients and that the numbers reflected “old” data rather than current performance. In addition, although the majority of respondents stated that they had a mechanism for tracking patients readmitted to their own hospital, none could reliably track patients readmitted to other facilities, and thus even these readmission rates were recognized to be imprecise. However, despite only general knowledge about readmission rates, interviewees at seven of the eight case study hospitals, as noted earlier, saw readmissions as high priority. The majority of the organizations were tracking their internally measured readmission rate over time, although few were specifically measuring the impact of each individual intervention on readmission rates; instead, most organizations were implementing a variety of interventions in multiple settings and monitoring general trends in readmission rates as a metric of the interventions’ collective impact.

Lesson 2. Federal readmissions policy has had a clear impact on hospital efforts to reduce readmission rates.

Respondents reported that the threat of penalties, not just from Medicare but also the assumption that other payers would follow suit, was having a major impact on the hospital’s efforts to re duce readmissions, as reflected in the following response:

… we’re not fooling ourselves, [the penalty] will get bigger and bigger and then other payers are going to pick up on it.

Despite broad agreement that the HRRP was leading to a significant response, we heard both positive and negative comments about the policy from the respondents in our sample.

Positive Opinions About the HRRP.

Many frontline staff respondents reported that the HRRP had forced hospital leadership to pay attention to an issue that had previously been acknowledged only at the case manager and nursing level. They felt that to reduce readmissions was “doing the right thing” for patients and patient care:

I think it’s awesome because it puts pressure where it needs to be put. We see it every day, we understand, we know the importance of it. … In order to get a response from administration, you have to penalize. … the fact that CMS is looking at this is a good thing because it will stimulate more conversations, more resources that are designated where we want them designated.

Negative Opinions About the HRRP.

Respondents at these high-minority hospitals were concerned about the lack of adjustment for differences in socioeconomic factors, as well as differences in patients’ adherence to medical recommendations and engagement in their own medical care, all of which were felt to adversely affect readmission rates. Interestingly, the focus of their attention was almost entirely on social factors, not race per se:

All hospitals are not the same. It’s unrealistic that our neighborhood should have to play by the same rules.

Respondents also expressed concern about the penalties in the HRRP taking resources away from hospitals that need them most:

The underserved population is at particular risk … and there are only a few hospitals providing care to these patients … and so you get penalized for trying to do the right thing.

The burden of the readmissions program falls disproportionately on safety-net hospitals, mainly because the program only puts in place a penalty but provides no support. Therefore, safety-net clinics that have fewer resources to begin with and serve the most complex patients incur the highest penalty.

Lesson 3. Most study hospitals followed a similar progression in strategies to reduce readmissions.

We identified three strategic approaches that were commonly employed by the seven hospitals in our sample that were actively working to reduce readmissions, which we now describe.

Start with the Discharge Day.

Respondents overwhelmingly reported that the first steps they took to reduce readmissions were focused on the discharge day, which included efforts to standardize discharge forms, employ a discharge planner to help ensure that discharge needs were met, and improve the electronic discharge process. One of the seven study hospitals that were engaged in trying to reduce readmissions had just begun to implement these reforms; the remaining six had these strategies in place for at least six months to a year:

CMS came out with this readmissions penalty, so we put a group together to figure out what was our readmission rate, where was it coming from, and what we could do about it … our grades weren’t great … so we started to develop some systems and access for discharge. Then we tried to identify who was at highest risk for readmission. Eventually that transitioned into making clinic appointments available and other initiatives.

Patients were sent home with big gaps … so to try to make the discharge process more efficient we created a discharge form.

We’re looking at issues related to communication. … How we do our discharge instructions, how we’re coordinating and referring to post-acute agencies.

Hospitals Should Customize Their Approach.

Many respondents reported that fixing the discharge day did not adequately address their patients’ problems because the majority of the issues were related to care outside the walls of the hospital. Surprisingly, none of the hospitals in our sample were using commercially available readmissions reduction guides or toolkits, for several reasons. First, they thought that these protocols were too resource-intensive to implement in the context of the hospitals’ other pressing needs:

We have to spend money on all these initiatives (Value-Based Purchasing, meaningful use, etc.), so we can’t buy the tools that help with clinical care. … It is all hitting so quickly, and it all costs money. Money we just don’t have.

Second, respondents felt that the commercially available programs were poorly targeted to their specific patient population. For example, at least one site was frustrated with a published readmissions reduction program that relied on home visits because their experience strongly suggested resistance by their patients to allow strangers into their homes; some also worried about the safety of home visits. Third, some respondents felt that existing programs provided useful guidance for case management and care coordination but didn’t go far enough beyond the hospital walls to make an impact on readmissions.

All seven hospitals reported, however, that they routinely relied on the evidence-based principles from published programs to design their own internal interventions. For example, many respondents reported a number of innovative fixes spearheaded by care coordinators that were aimed at supporting specific patients’ needs, such as arranging transportation to dialysis sessions, paying for prescriptions, and contacting patients to remind them of follow-up appointments:

… different issues specifically related to the patient. A lot of that comes down to health literacy, their awareness of their diagnoses, socioeconomic barriers that they may have to be able to adhere to the treatment plan once they leave the hospital.

We know the patients who keep coming back. … we have a risk assessment for our patient population based on what we see—things like living situation and diagnosis.

Improving Resources in the Community Must Be a Priority.

Improving and expanding the available resources in the community was seen as an essential component in reducing readmissions. Efforts in this regard included purchasing primary care practices and moving them to areas (that is, inner-city locations) that would improve access for their patients and selective contracting with primary care practices willing to provide more flexible hours. Hospitals also reported creating networks between hospitals and community organizations, such as dialysis centers, adult day care programs, and churches and other religious organizations, to share information on particularly high-risk patients:

It’s not about the hospital doing a good job on discharge; it’s about the support system outside of the hospital.

Lesson 4. Hospitals face a consistent set of challenges in reducing readmissions.

Four challenges in reducing readmissions were consistently identified by our respondents, as we now describe.

Finances and Personnel Resources Are Limited.

Respondents cited financial constraints as a major issue as they worked to reduce readmissions, particularly in terms of hiring social workers, nurses, other outpatient staff, or even project managers to special initiatives:

Obviously we care about patients and don’t want them to have to come back in, but we don’t have the resources to really address it.

Focusing on Patients’ Unique Needs Is Required.

As noted earlier, respondents were less focused on race and more attuned to other patient factors felt to directly affect readmissions. Respondents reported that patients’ mental health and substance abuse issues, as well as homelessness, nonadherence to medications and lifestyle changes, and lack of transportation, were major factors in readmissions but very difficult to address:

It doesn’t matter how well you coordinate some patients’ care—some people just have unlivable lives, and they are in the hospital because they have nowhere else to go.

I can control a lot of things, but that’s one thing I can’t control—other people. As much as I’d like to make sure that people go home and take their medicine, I can’t ensure that.

Furthermore, individual patients may have unique needs, and it can be frustrating to determine the right combination of services and interventions that work for which patients:

Something like quality or safety are cut and dry, and it is clear how to address it. With readmissions, it’s fluid—each patient is different.

Even with a case manager who sets up an appointment for dialysis, sends transportation for follow-up, etc., some patients just do not participate. And you cannot deny them admission. But that readmission is treated exactly the same as one that we did not follow up with or put any resources into—and management gets dinged on both.

Many respondents recognized that their minority patients were more likely to be readmitted than other patients but, with few exceptions, felt that this was not about race but rather about poverty and the social and clinical ills that accompany it:

We have a large black population that has more hypertension, cardiac disease, and chronic disease due to a lack of primary care. But I don’t know if this is necessarily a race factor. It could just be that this race is more likely to be socioeconomically challenged.

In our patient population, culture or ethnicity is not the biggest predictor [of high readmission rates]. It’s the comorbidities—mental health, substance abuse. These conditions track with poverty but not minority status.

Factors Outside the Hospital Are Difficult to Change.

Factors outside the hospital, particularly access to primary care, were thought to be particularly difficult challenges to address, and ones that were salient to minority populations in particular:

The PCP [primary care provider] is crucial to readmissions. Most of our patients don’t have a PCP. … Not many PCPs want to practice here, and those who do are full, so we end up being the primary care.

Outpatient access is the single most important thing to reducing readmissions.

Incentives Are Misaligned.

Respondents felt that financial incentives were misaligned in a fee-for-service environment that depends on the volume of admissions. One hospital felt that it was not in its best interest to reduce readmissions in the long run because the loss in revenue would outweigh any penalties incurred; other hospitals recognized the misalignment but decided to proceed with readmissions reduction programs nonetheless:

It’s a quagmire: If you affect the population correctly, you will reduce both readmissions and overall admissions, which is good for the patient but financially bad for the hospital.

Discussion

In a sample of eight hospitals serving a high proportion of minority patients, we found that a majority of hospital leaders and mid-level managers were knowledgeable about the problem of readmissions and were dedicated to reducing their frequency. These hospitals encountered a consistent set of challenges, including lack of financial resources, lack of personnel resources, unique patient needs, and uncoordinated community resources. Hospital leaders generally felt that readmissions were more a matter of socioeconomics than of race. The seven of the eight study hospitals that were engaged in trying to reduce readmissions initiated a host of efforts, incorporating a similar set of approaches that focus first on discharge planning, then individualizing post discharge care, and, finally, fortifying community relationships.

There are three major implications from our findings. First, currently available readmission reduction guides and toolkits, such as the Society of Hospital Medicine’s Project BOOST (Better Outcomes by Optimizing Safe Transitions)^11,20 or Boston University Medical Center’s Project RED (Re-Engineered Discharge),²¹ even though they are ostensibly free or low-cost, were not perceived to be adequately meeting the needs of hospitals that serve a high proportion of minority patients. Through our study, we discovered a number of reasons why this may be the case. First, even “free” programs require personnel who may be in short supply at safety-net hospitals; second, the programs are not perceived to be relevant to these hospitals’ patient population; and third, some components of the programs, such as the in-home visits suggested in Coleman’s Care Transitions Program,²² were met with resistance from some of their high-risk patients. This suggests two potential solutions: providing additional financial resources or trained personnel to help these hospitals participate in proven programs and designing new programs that are specifically feasible within and applicable to resource-limited settings serving low-income patients.

Second, we know the HRRP will disproportionately penalize minority-serving hospitals as a result of their high readmission rates.⁵ Our findings suggest that these hospitals are struggling even at their current level of resources to implement programs to reduce readmissions and that this policy could exacerbate existing racial disparities in health and health outcomes, as already underresourced hospitals face further reductions in their financial resources. On one hand, our case studies highlight the potential issues with public policies that institute punitive financial penalties without widespread training and support for quality improvement. On the other hand, previous work has shown that hospitals serving poor patients may respond to positive financial incentives by significantly improving their performance,¹⁵ although there is no prior research on the impact of negative financial incentives on hospitals serving the poor. There are a number of ways in which the HRRP could be altered to minimize the negative impact on the safety net while still incenting a focus on reducing readmissions. For example, the Medicare Payment Advisory Commission (MedPAC) has recommended that hospital readmission penalties be stratified by socioeconomic status.²³ Other potential solutions include rewarding hospitals for improvement rather than for their absolute readmission rates, or moving to population-based measures that assign responsibility beyond a single hospital. It will be critically important to track the impact of this policy going forward, particularly as the size of the penalty increases in coming years.³

Third, addressing readmissions will require a community-facing strategy that extends beyond the hospital walls—an approach that may be difficult in our fragmented system of care. Currently, hospitals are incented to reduce readmissions, but the solutions by necessity must come from outpatient providers and community organizations; this may be relatively straightforward within integrated delivery networks and others with a broad community reach at baseline, but for a standalone hospital, the challenges in providing incentives for these solutions in unaffiliated outpatient providers are immense. To fully address readmissions as a systemwide endeavor, we may need new ways of paying for and structuring services. For example, in a recent paper, Shortell suggests moving toward “a risk-adjusted community population–wide health budget to local consortia of health care, public health, and community and social service organizations.”^{24(p. 1122)} Although this would represent a significant departure from our current model, it would likely enable collaborations that could prove fruitful in reducing readmissions, particularly in the context of the safety net, including minority-serving hospitals.

There are limitations to our study. We conducted case studies at only eight sites, and although we chose them to be representative of different hospital types, we were not able to perform quantitative analyses of our findings because of the small sample. Our findings may not generalize to a broader group of minority-serving hospitals. We are also unable to comment on whether the challenges we identified are unique to minority-serving hospitals or are present in other safety-net hospitals or even other non-safety-net hospitals. We focused our study on hospitals serving black patients, so these results may not generalize to hospitals whose patient population is composed of other racial and ethnic minorities. The perception that reducing readmissions was a high priority may have occurred in part because only those persons who felt that readmissions were high priority would agree to participate. The number of interviews and diversity of roles sampled differed by site, largely as a function of hospital size and complexity; at two small hospitals we had a limited number of key informants. We interviewed only hospital staff and did not solicit input from community physicians or from patients or family members, all of whom are likely to have distinct and important perspectives on readmissions that were beyond the scope of our study. Because of the observational nature of our study, we could not assess whether any of the themes or relationships we found were causal. Finally, our study was cross-sectional, and we did not evaluate improvement in readmission rates over time. As the HRRP continues, understanding more about the strategies employed by minority-serving or safety-net hospitals that ultimately manage to improve their readmission rates may be a particularly important area of study.

Our study adds to the literature on the challenges faced by hospital leadership and frontline staff as they work to reduce readmissions, although, to our knowledge, this is the first such study to focus specifically on minority-serving hospitals. The National Association of Public Hospitals and Health Systems (now America’s Essential Hospitals) studied readmissions by surveying its members and conducting case studies in 2010,¹³ and found that the areas most commonly identified as important contributors to readmissions included drug and alcohol abuse, patients not following up with appointments, homelessness, and patients not filling prescriptions, which are issues also raised in our study. The Commonwealth Fund used case studies from four very high-performing hospitals to suggest six specific strategies: invest in overall quality, use health information technology, improve care management and discharge planning, educate patients and families, provide postdischarge communication, and work with community providers.¹² Our study adds to this literature by exploring hospital leaders’ opinions on readmissions policy, by pointing out where the major barriers arise in trying to implement these strategies, and by bringing up additional issues that may be particularly salient to minority-serving providers.

Conclusions

Hospitals that serve a high proportion of minority patients face a specific set of challenges when working to reduce readmissions. Many strategies and programs that have been touted as highly successful in other settings are less relevant for minority-serving hospitals, which often do not have the resources or personnel to implement them. Our findings uncover the importance in this set of hospitals of innovative efforts that focus on addressing issues specific to each patient population and community, and the importance of reaching outside the walls of the hospital to implement programs that improve outpatient access and management.