Bundled Payments Lead to Quality Improvements in Hospitals’ Skilled Nursing Facility Referral Networks

ABSTRACT

Objectives: To assess whether hospitals participating in Medicare’s Bundled Payments for Care Improvement (BPCI) program for joint replacement changed their referral patterns to favor higher-quality skilled nursing facilities (SNFs).

Study Design: Retrospective observational study using 2009-2015 inpatient and outpatient claims from a 20% sample of Medicare beneficiaries undergoing joint replacement in US hospitals (N = 146,074) linked with data from Medicare’s BPCI program and Nursing Home Compare.

Methods: We ran fixed effect regression models regressing BPCI participation on hospital-SNF referral patterns (number of SNF discharges, number of SNF partners, and SNF referral concentration) and SNF quality (facility inspection survey rating, patient outcome rating, staffing rating, and registered nurse staffing rating).

Results: We found that BPCI participation was associated with a decrease in the number of SNF referrals and no significant change in the number of SNF partners or concentration of SNF partners. BPCI participation was associated with discharge to SNFs with a higher patient outcome rating by 0.04 stars (95% CI, 0.04-0.26). BPCI participation was not associated with improvements in discharge to SNFs with a higher facility survey rating (95% CI, –0.03 to 0.11), staffing rating (95% CI, –0.07 to 0.04), or registered nurse staffing rating (95% CI, –0.09 to 0.02).

Conclusions: BPCI participation was associated with lower volume of SNF referrals and small increases in the quality of SNFs to which patients were discharged, without narrowing hospital-SNF referral networks.

Am J Manag Care. 2024;30(6):e184-e190. https://doi.org/10.37765/ajmc.2024.89566

Takeaway Points

Medicare’s Bundled Payments for Care Improvement (BPCI) program for joint replacement has been associated with improvements in care quality. A common belief is that hospitals are achieving gains by narrowing postacute care networks of skilled nursing facilities (SNFs).

• We find that SNF referral networks did not change substantially under the BPCI program.
• Instead, the overall quality of SNFs in referral networks for BPCI-participating hospitals improved.
• Episode-based bundled payments may be an effective policy lever to improve the quality of postacute care.

Postacute care, which includes skilled nursing facilities (SNFs), inpatient rehabilitation programs, and long-term care hospitals, is one of the largest drivers of Medicare costs in the US.¹ Nearly 20% of Medicare beneficiaries are discharged to SNFs after a hospitalization,² and nearly a quarter of SNF-discharged patients are readmitted to the hospital within 30 days.³ In an attempt to reduce costs and improve quality for hospitalized beneficiaries, Medicare created the voluntary Bundled Payments for Care Improvement (BPCI) program in 2013. Under Model 2 of the BPCI program, the cost for all services rendered to Medicare fee-for-service beneficiaries during and up to 90 days after an acute care hospital stay was compared with a hospital-specific target price, and participating hospitals were issued a payment or penalty based on their performance compared with the target.² By holding hospitals accountable for the cost of all services provided after an acute-care stay, policy makers hoped that participating hospitals would improve care efficiency both during and after hospitalization. BPCI Model 2 laid the groundwork for the current BPCI Advanced (BCPI-A) program, which began in 2018 and enrolled more than 800 hospitals across more than 30 medical and surgical conditions.⁴

Findings of prior studies have shown that the biggest impact of BPCI was a reduction in postacute care spending, but the mechanism by which hospitals did so remains unclear. The most obvious one is to simply reduce postacute care use by sending patients home rather than to SNFs. Another possibility is that hospitals influenced the quality of postacute care to reduce readmissions and other adverse events that could increase spending. For example, hospitals could have invested in care coordination activities such as electronic information exchange and visiting care teams.⁵ Relatedly, hospitals could have aimed to concentrate their acute-care discharges among fewer SNFs, either to improve the efficiency of their investments in quality improvement or to steer patients toward higher-quality SNFs.⁶ Although Medicare fee-for-service beneficiaries have a choice of where they receive postacute care services, even under BPCI, hospitals are legally allowed to provide quality information to assist patient decision-making.¹ Some hospitals provide a list of “preferred SNFs” at discharge, some hospitals have formal committees dedicated to procuring and managing data from specific SNFs, and some SNFs agree to adhere to performance standards in exchange for being marketed as a preferred SNF.^5,7

Currently, it is unknown to what extent the BPCI program influenced hospital-SNF referral patterns and whether these changes are associated with SNF quality. Filling this knowledge gap is important to understanding the impact of payment reform on care delivery and contributes to our knowledge on how payment reform balances patient choice with care quality.^8-10 To understand whether hospitals in the BPCI program changed SNF referral patterns, we used 2009-2015 claims data on Medicare patients undergoing joint replacement, a procedure that is highly sensitive to postacute care quality. First, we assessed whether BPCI participation was associated with changes in discharge patterns in terms of volume, number of SNF partners, and concentration of SNF discharges. Then, we assessed whether patients were discharged to higher-quality SNFs after a hospital joined BPCI.

METHODS

Data Source and Study Population

For our study, we analyzed inpatient and outpatient Medicare claims from a random 20% beneficiary sample from 2009 to 2015. We began by identifying patients in our sample who were discharged directly to a SNF following an admission for joint replacement (diagnosis-related group 469 or 470) at an acute care, non–critical access hospital. To be eligible for inclusion, we required beneficiaries to be enrolled in parts A and B of fee-for-service Medicare 12 months prior to their index admission and 90 days post discharge (or until death) and to be residents of the continental US. Following prior work, we excluded beneficiaries with a SNF claim within the 3 months prior to the index admission because a beneficiary’s previous stay may influence a hospital’s future choice of SNF. We also excluded rehospitalizations that occurred within 30 days of the index admission.

BPCI Participation

The Center for Medicare and Medicaid Innovation1 developed the voluntary BPCI program in 2013 to incentivize hospitals to provide high-quality, low-cost care for up to 48 conditions. Although BPCI was made up of 4 model options, the vast majority of hospitals participated in Model 2 (Model 1 was a preliminary model that sunsetted early, Model 3 focused on SNFs, and Model 4 had minimal enrollees). For this article, we chose to focus on joint replacement because it is the most common condition chosen under the BPCI program and has been shown to be the most successful in reducing costs.¹¹ Our main independent variable was the percentage of the calendar year during which a hospital participated in Model 2 of the BPCI program for joint replacement, measured on a quarterly basis.

Main Outcomes

We counted the number of patients shared between every hospital-SNF pair per year over our study period. Then, we created a bipartite hospital-SNF network. Networks are a collection of points (called nodes) connected in pairs by lines (called edges). In bipartite networks, nodes can take on 2 different classes (ie, hospitals and SNFs). From these network data, we calculated 3 outcomes at the hospital-year level: the number of direct discharges to SNFs, the number of SNF partners, and the concentration of SNF referrals as measured by the Herfindahl-Hirschman Index, where 0 indicates that all SNF discharges are equally spread out among all SNF partners in the network and 1 indicates that all SNF discharges are concentrated among fewer SNF partners in the network. We chose these measures because they are directly comparable to other network measures in prior literature6 and because they can be easily interpreted.

Four measures of SNF quality were extracted from Nursing Home Compare (2009-2015): survey rating, outcomes rating, staffing rating, and registered nurse staffing rating. These measures are based on the 5-star rating developed by Nursing Home Compare, which ranks hospitals on a scale of 1 to 5 based on a variety of quality metrics.¹² The survey rating is based on the number, scope, and severity of deficiencies identified by facility inspections over 36 months and adjusted for the number of inspections. The outcomes rating is based on 10 risk-adjusted outcomes endorsed by the National Quality Forum (eg, percentage of short-term stay residents with pressure ulcers). Prior to release, CMS risk-adjusts all outcomes measures for beneficiary-level characteristics including baseline factors associated with differences in performance. The staffing and nurse staffing measures are based on the ratio of nursing hours per resident. Prior to release, CMS risk-adjusts all staffing measures for beneficiaries’ clinical severity. For this study, we calculated a quarterly average for each measure per calendar year. (For details, see eAppendix A [eAppendices available at ajmc.com].)

Hospital Control Characteristics

Hospital control characteristics included whether the hospital offered skilled nursing care via hospital, health system, or joint venture; teaching status (major teaching status was defined as membership in the Council of Teaching Hospitals and Health Systems, and minor teaching status was defined as accreditation by the Accreditation Council for Graduate Medical Education); system membership; and ownership (nonprofit, for profit, or government) from the American Hospital Association Annual Survey (2009-2015); accountable care organization (ACO) participation within Medicare, Medicaid, or a commercial ACO from the Leavitt Partners ACO database; and data on number of beds, market share, Medicaid Disproportionate Share Hospital (DSH) payments, case mix, and urbanicity from the Medicare Impact File (2009-2015). Hospital-county characteristics included the number of SNFs and the number of SNF beds from the Area Health Resources Files (2010-2015). Because these characteristics are unlikely to change much from year to year, data from previous years and then future years were used to fill in missing control characteristics.

Statistical Analysis

We ran 3 linear regression models on our hospital-level data set. The first model regressed the number of SNF discharges on BPCI participation, the second model regressed the number of SNF referral partners on BPCI participation, and the third model regressed hospital-level SNF referral concentration on BPCI participation, controlling for the number of SNF discharges. In the second and third models, we included a control for the number of total discharges to SNF partners to account for the impact of patient volume on these 2 network measures. All models included hospital control characteristics, year fixed effects, and hospital fixed effects.

To understand what kinds of SNFs receive a larger share of patients from hospitals, we estimated Poisson regression models on our discharge-level data set. We regressed the quality of a receiving SNF on the BPCI participation status of the discharging hospital at the time of patient discharge while controlling for hospital fixed effects, hospital characteristics, and year fixed effects. We ran 4 models, 1 for each measure of SNF quality. Each model was weighted by the inverse of the number of discharges per hospital to account for duplicate observations per hospital.

We conducted 3 sensitivity analyses. First, to test the sensitivity of our results to our treatment of missing data, we repeated our analyses on the subset of observations with full data (dropping the variables for percentage of SNF residents with Medicare/Medicaid and whether the SNF is a chain because these data were unavailable for 2013-2015). Second, because linear regression assumes an unbounded range for the dependent variable, yet our measure of referral concentration is bounded between 0 and 1, we used a fractional response regression with hospital-clustered SEs and hospital referral region (HRR) fixed effects. Because we were unable to include hospital fixed effects in the fractional response regression model, we present the results from the fixed effects linear regression as our main analysis. Finally, because some hospitals may have less control over SNF referral networks for patients discharged to SNFs outside their areas (eg, large referral centers may receive more out-of-town patients who choose to be discharged to SNFs closer to home), we dropped 6724 hospital-SNF pairs that were not in the same HRR, recalculated our measure of SNF referral concentration and number of SNF partner measures, and repeated our analyses.

RESULTS

The original claims data used for this study contained data on 159,775 discharges for 146,074 unique beneficiaries from 2765 hospitals (82% of all short stay hospitals in the US) to 12,773 SNFs (83% of all SNFs in the US) from 2009 to 2015. Of the 2765 hospitals, 2727 (99%) hospitals were successfully matched to American Hospital Association data on hospital characteristics, and 2354 (85%) hospitals had data on all hospital control variables; these hospitals made up our analytic sample for the hospital-level analysis, representing 14,295 hospital-year observations (eAppendix B). Of these hospitals, 235 ever participated in Model 2 of the BPCI program for joint replacement: 5 started participating in 2013, 55 started participating in 2014, and 175 started participating in 2015.

For the SNF quality analysis, 11,767 (92%) SNFs of the 12,773 in the original claims data were successfully matched to the Nursing Home Compare database, and 10,903 (85%) of these SNFs belonged to hospital-SNF pairs where the hospital had no missing data. An additional 520 SNFs were dropped because they were missing data on SNF quality; consequently, 8 additional hospitals were dropped because all their partnering SNFs were missing data. The final analytic data set for the SNF quality analysis contained observations on 139,452 discharges for 127,898 unique beneficiaries discharged from 2346 hospitals to 10,383 (88%) SNFs (eAppendix B).

Hospitals that joined the BPCI program differed significantly from hospitals that never joined the BPCI program. Hospitals that joined the BPCI program were significantly more likely to also be in an ACO, offer SNF services through their health care system or a joint venture, and be urban, teaching, and nonprofit. On average, they had more beds, a lower DSH percentage, and a sicker case mix, and came from counties with more SNF facilities and beds (Table 1). In our 20% sample, hospitals that joined the BPCI program discharged 17 Medicare fee-for-service patients with joint replacement per year to SNFs prior to joining the program and 16 such patients to SNFs after joining the program, whereas hospitals that never joined the BPCI program discharged 10 patients to SNFs per year. The mean SNF referral concentration for hospitals that joined the BPCI program was 0.36 prior to joining the program and 0.34 after joining the program, and it was 0.47 for hospitals that never joined the BPCI program. Hospitals that joined the BPCI program had 7 SNF partners prior to joining the program and 8 partners after joining the program, whereas hospitals that never joined the BPCI program had 5 partners.

After controlling for hospital characteristics and ACO participation, we found that the number of SNF discharges per hospital per year changed by –1.69 patients after hospitals joined the BPCI program, or 10% of the pre-BPCI mean; this effect was significant (95% CI, –2.53 to –0.85) (Table 2). SNF referral concentration changed by –0.01 after hospitals joined the BPCI program, or 3% of the pre-BPCI mean; this effect was not significant (95% CI, –0.04 to 0.03) (Table 2). The number of SNF partners changed by –0.12 SNFs after hospitals joined the BPCI program, or 2% of the pre-BPCI mean; this effect was not significant (95% CI, –0.39 to 0.15) (Table 2).

Patients were discharged to higher-quality SNFs after a hospital joined the BPCI program. BPCI participation was associated with a change of 0.04 stars for the survey rating (95% CI, –0.03 to 0.11), 0.20 stars for the outcomes rating (95% CI, 0.14-0.26), –0.10 stars for the staffing rating (95% CI, –0.07 to 0.04), and 0.04 stars for the registered nurse staffing rating (95% CI, –0.09 to 0.02) (Table 3¹³).

Sensitivity analysis using the subset of observations with full data suggests that our analyses were not significantly impacted by the way we handled missing data (eAppendix C) or our use of a linear model (eAppendix D). When we dropped hospital-SNF pairs not in the same HRR, results were consistent with our main analysis, except that the effect size of BPCI on survey rating was larger and significant (marginal effect, 0.08; 95% CI, 0.01-0.16) (eAppendix E).

DISCUSSION

In this national study on BPCI-participating hospitals, we found little evidence that SNF referral patterns changed after hospitals joined the BPCI program. After BPCI participation, the number of patients discharged to SNFs per hospital went down, and we found no change in the number of SNF partners or the concentration of SNF referrals. However, we did find that the quality of receiving SNFs was higher after hospitals joined the BPCI program. Taken together, this suggests that SNFs in BPCI-participating hospital referral networks are improving their quality of care. This explanation is supported by prior evidence suggesting that patients discharged from BPCI-participating hospitals have better postacute care outcomes than those discharged from nonparticipating hospitals.¹⁴ These findings are also consistent with the most recent formal evaluation of the BPCI program by CMS, which finds that among patients discharged to SNFs, BPCI participation was associated with a decrease in the overall length of stay, a common measure of postacute care quality.¹⁵ It may also be that hospitals are substituting lower-quality SNF partners for higher-quality partners, resulting in no perceivable net change in the number or concentration of SNF partners.

We also found that the BPCI program was associated with a significant decrease in the number of patients discharged to SNFs. This finding is consistent with those of recent studies suggesting that BPCI-participating hospitals are reducing SNF utilization to reduce costs.^11,14,16 However, our finding that SNF referral concentration did not change seems to point against qualitative evidence for the use of preferred networks to control costs.⁷ Similarly, we did not find evidence that the BPCI program is associated with a pruning of SNF partners. These findings suggest either that narrowing SNF networks is not a widely used strategy for BPCI-participating hospitals or that attempts to narrow SNF networks did not substantially change referral patterns. If the latter is true, it may speak to some of the challenges inherent in encouraging patients to receive SNF care from preferred providers, such as patient or provider preferences influenced by word of mouth or geography, limited SNF options in a given market, or Medicare restrictions on how hospitals can influence fee-for-service beneficiary choice of SNF.¹⁷ It is worth noting that this policy is different for Medicare Advantage beneficiaries, for whom payers can set network restrictions that limit patient choice of SNF.

Our finding that BPCI participation was significantly associated with SNFs’ outcome ratings and not the survey or staffing ratings could have several possible explanations. First, SNFs in BPCI-participating hospital networks may be improving quality without increasing performance on deficiency surveys or staffing. This is supported by prior work that finds that deficiency survey scores and staffing measures do not necessarily predict outcomes.^18-20 For example, as hypothesized, hospital investment in care coordination activities may be leading to better SNF outcomes. Alternatively, SNF-discharged patients may be discharged in better condition than before the hospital joined the BPCI program. This may certainly be the case if BPCI-participating hospitals are improving the quality of care during the index hospitalization through better adherence to evidence-based protocols as prior evidence suggests.²¹ Finally, it is possible that BPCI-participating hospitals are selecting patients with lower risk, decreasing the possibility of SNF-discharged patients experiencing an adverse event and improving the outcome rating of receiving SNFs.²²

Implications

This study has important implications for postacute care quality improvement efforts. First, policy interventions that target hospitals may be an effective way to improve the quality of postacute care. Hospitals have long been influential actors in the US health care system and their influence is likely to increase as Medicare pushes for more integrated approaches to care delivery.²³ Second, we found that hospital-SNF referral patterns did not change despite strong qualitative evidence of hospitals’ intention to utilize preferred SNFs.⁷ The lack of change in hospital-SNF referral patterns could be in part due to beneficiaries’ ability to choose their providers freely under fee-for-service Medicare.¹ This finding speaks to the challenges of influencing patients’ referral patterns¹⁷ and suggests that additional research is necessary to understand how to help patients and caregivers choose high-quality postacute care facilities. In addition, more research is necessary to understand how the BPCI program and its successor, BPCI-A, may have helped reduce the impact of pandemic-related staffing shortages on the quality of SNFs and whether the BPCI program is exacerbating or improving disparities in SNF quality and access among underserved populations such as residents living in rural areas, racial/ethnic minorities, and dual-eligible patients. For example, if hospitals in BPCI are shifting referrals from rural to urban SNFs, this may have an unintended consequence of reducing resources available to rural SNFs, exacerbating SNF shortages in rural areas.

Limitations

Findings from our study should be interpreted with limitations in mind. First, the generalizability of our results is limited to Medicare patients undergoing joint replacement and may not generalize to commercially insured patients or other diagnosis groups. However, given that Medicare is leading the movement behind bundled payments and that the BPCI program for joint replacement has been one of the most common (close to 60% of BPCI-participating hospitals participated in the joint replacement program), findings from this study still have important implications. Second, we were able to examine how referral patterns changed for only hospital-SNF discharges and not other postacute settings such as home health or rehabilitation programs. It is likely that participating hospitals shifted postacute care to these settings to improve cost efficiency. Finally, missing data may also limit generalizability. Hospitals and SNFs in the sample were different from those dropped due to missing data (eAppendices C and F). However, given the relatively small number of hospitals and SNFs dropped due to missing data (n = 411 and 2362; or 15% and 18%, respectively), we do not believe that this limitation severely limits generalizability.

CONCLUSIONS

In this study on the impact of the BPCI program on hospital-SNF referrals, we found that the BPCI program led to an overall decrease in SNF utilization, with no change in the concentration or number of SNF partners, and an increase in the quality of SNFs. Taken together, this study’s findings suggest that the BPCI program is associated with small improvements in the quality of SNF partners.

Author Affiliations: School of Medicine, Washington University in St Louis (SCL, KEJM), St Louis, MO; Carlson School of Management, University of Minnesota (RJF), Minneapolis, MN; School of Public Health, Brown University (AMR), Providence, RI; NorthShore University HealthSystem (JMH), Evanston, IL.

Source of Funding: This study was supported by the Agency for Healthcare Research and Quality grants 1R01HS024525 01A1 (JMH), 1R01HS024728 01 (JMH), and 1R36HS025875-01A1 (SCL).

Author Disclosures: Dr Joynt Maddox reports payment for participation on the Centene Health Policy Advisory Council, attendance of meetings of the American Heart Association and the Journal of the American Medical Association, and receipt of grants from the National Heart, Lung, and Blood Institute (R01HL164561), National Institute of Nursing Research (U01NR020555), National Institute on Aging (R01AG060935, R01AG063759, and R21AG065526), National Center for Advancing Translational Sciences (UL1TR002345), and Humana. Dr Hollingsworth reports receipt of a grant from the National Institute on Aging (R01AG068074). The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (SCL, RJF, JMH); acquisition of data (SCL, JMH); analysis and interpretation of data (SCL, RJF, AMR, KEJM, JMH); drafting of the manuscript (SCL, RJF, KEJM, JMH); critical revision of the manuscript for important intellectual content (SCL, RJF, AMR, KEJM, JMH); statistical analysis (SCL); obtaining funding (SCL, JMH); administrative, technical, or logistic support (AMR); and supervision (JMH).

Address Correspondence to: Sunny C. Lin, PhD, MS, School of Medicine, Washington University in St Louis, 4523 Clayton Ave, Campus Box 800, St Louis, MO 63110. Email: linsc@wustl.edu.

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