Bundled Payment Impacts Uptake of Prescribed Home Health Care

ABSTRACT

Objective: To determine whether the CMS Comprehensive Care for Joint Replacement (CJR) Model, which incentivizes coordinated and efficient care, increased home health care (HHC) uptake among patients referred to HHC after major joint replacement surgery.

Study Design: Cohort study using a difference-in-differences design comparing hospitals in 75 metropolitan statistical areas randomized into CJR by CMS with non-CJR hospitals in 119 areas as controls.

Methods: The primary outcome was the case mix–adjusted, hospital-level HHC uptake rate, which is the rate of patients referred to HHC at hospital discharge receiving an HHC visit within 14 days. Secondary outcomes included HHC uptake rate by race/ethnicity and the quality of HHC agencies used among referrals, which was measured by agency-level improvement in ambulation, unplanned hospitalizations, emergency department visits, time to the first home health visit, and distinct number of agencies.

Results: After the launch of CJR, HHC uptake decreased nationally but there was a 3.73–percentage point (4.5%) lower decrease in CJR hospitals; this was driven by White patients (3.54–percentage point differential; P = .026). A marginally statistically significant (P = .054) 5.05–percentage point differential increase for Black patients was observed due to a slight increase in the treatment group and a large decrease in the control group. There was no statistically significant change for Hispanic or Asian American/Pacific Islander populations. No statistically significant increases were observed in the quality of HHC used.

Conclusions: CJR mitigated a trend of decreased HHC uptake, but more work is needed to improve uptake for larger portions of the patient population. Our results suggest that addressing care coordination incentives via CJR may mitigate some racial disparities.

Takeaway Points

Only 79.17% of patients referred to home health care after joint replacement use it. During the Comprehensive Care for Joint Replacement (CJR) Model, uptake of home health care decreased compared with prior years, but for patients at CJR hospitals, the decrease was mitigated, resulting in a differential increase of 3.73 percentage points (4.5%) in home health care uptake.

• The difference in uptake was driven by White and Black patients (differentials of 3.54 and 5.05 percentage points, respectively).
• There is room for improvement to increase uptake of prescribed care, particularly for Hispanic and Asian American/Pacific Islander patients.
• Regional variation in home health care may explain differences in uptake.

Nonadherence to medical regimens leads to poor health outcomes, preventable progression of disease, and billions in avoidable health care expenses.^1-5 Home health care (HHC), which helps patients rehabilitate following injury or illness,⁶ is increasingly prescribed to help older adults safely recover in the community.⁷ However, 1 in 5 older adults in the US who are referred to HHC for postacute recovery after joint replacement surgery do not receive it.⁸ Uptake rates are even worse in the general Medicare population, with nearly half not receiving prescribed HHC.⁹ Moreover, rates of HHC uptake (ie, HHC use among patients referred to HHC) vary by race and ethnicity, with 15% to 20% lower rates among Black and Hispanic individuals compared with White individuals.⁹ Reasons for low HHC uptake rates are poorly understood but may include patient factors, such as concerns about privacy and trust, and provider factors, such as a lack of coordination with postdischarge providers to ensure that all necessary postdischarge treatments are received.^5,10,11

To improve care coordination and decrease total spending, CMS implemented the Comprehensive Care for Joint Replacement (CJR) Model in April 2016. Hospitals that achieved low Medicare spending while maintaining quality from admission through 90 days after discharge received financial rewards, which incentivized hospitals to more holistically consider the needs of patients receiving major joint replacement surgery.¹² Studies to date have shown that CJR increased HHC utilization in lieu of institutional postacute care, particularly among Black and Hispanic patients.^13-16 Utilization rates, however, do not inform uptake rates because postdischarge referral patterns may have changed under CJR. Thus, it is unclear whether postacute HHC uptake rates improved under CJR.

HHC uptake might improve if CJR led to care improvement, such as more patient engagement and better care coordination.¹⁰ For instance, some CJR hospitals focused on improving patient understanding of postdischarge services and set up monitoring to maintain communication with patients after discharge.¹⁷ In another example, some providers developed narrow HHC networks,¹⁸ which may increase the likelihood of patients receiving HHC as ordered. On the other hand, if CJR hospitals solely focused on cutting institutional postacute care without improving postdischarge care quality, then there might be little effect on HHC uptake rates. If true, this could be particularly detrimental to racial/ethnic minority populations for whom uptake of HHC is especially low.^8,9

Our objective was therefore to determine whether CJR increased HHC uptake after major joint replacement surgery. To account for possible changes in the HHC referral composition, our primary outcome measure was hospital-level, case mix–adjusted uptake rates. We used national data from 2014 to 2018 and a difference-in-differences design to compare uptake rates among patients referred to HHC before and after the adoption of CJR. Second, we assessed whether uptake varied by whether CJR patients were White, Black, Hispanic, or Asian American/Pacific Islander (AAPI). Third, we assessed whether CJR led to the use of higher-quality HHC. Given the continued difficulty in improving patient adherence to recommended medical care and the large shares of patients who do not receive HHC despite referral, our findings provide timely information on the role of bundled payment incentives in addressing patient needs.

METHODS

Experimental Design

CMS used a stratified design to randomly select 75 treatment metropolitan statistical areas (MSAs) and 121 control MSAs from a total of 196 MSAs. All eligible hospitals within MSAs selected for CJR were mandated to participate in the program’s first 2 years, which lasted from April 2016 through December 2017. Involvement in CJR became voluntary after 2018 (eAppendix 1 [eAppendices available at ajmc.com]).

Study Data and Population

Our population included hip or knee joint replacement discharges (diagnosis related group [DRG] 469 or DRG 470) with referrals to HHC from hospitals within 1 of 196 MSAs eligible for the CJR program. From this population, we constructed a sample of 194 MSAs (75 treatment and 119 control MSAs), 1366 hospitals, and 354,861 episodes. To arrive at this sample, we excluded hospitals in the Bundled Payments for Care Improvement initiative because they were exempt from CJR. We included patients with both Medicare Parts A and B coverage in the month of hospitalization through 90 days after discharge who were 65 years or older and qualified for Medicare for reasons besides end-stage renal disease. We included discharges prior to CJR (July 2014 to June 2015) and following CJR (April 2016 to December 2018).

We used several data sources. We used 100% Medicare Provider Analysis and Review data to capture each patient’s primary diagnosis and discharge disposition. We used the Outcome and Assessment Information Set (OASIS) to identify HHC use. We identified beneficiary demographic and insurance enrollment information from the Master Beneficiary Summary File Base Segment. We obtained hospital characteristics from the Provider of Services files, bundled payment operational files, American Hospital Association 2014 file, and HHC agency quality information from CareCompare.com. Finally, we obtained zip code poverty rates from the American Community Survey.

Primary Outcome: HHC Uptake

We sought to determine whether CJR affected HHC uptake rates among referrals to HHC at hospital discharge. Following prior literature,^8,9,19 we defined HHC uptake as receipt of a home health visit (as recorded in OASIS data) in the 14 days after referral, and we identified referrals using the discharge destination code in the hospital discharge record. However, because CJR may have changed the composition of referrals, such as increasing referrals to HHC (and home without HHC) and decreasing referrals to institutional postacute care (eAppendix Table 1), examining unadjusted uptake rates would not allow us to disentangle changes in composition from changes in hospital care that may have affected uptake rates. Thus, we used hospital-level, case mix–adjusted uptake rates as our main outcome measure.

Our case mix–adjusted uptake rate is the ratio of observed to expected uptake counts, scaled by the mean uptake rate in the control group following methods employed by the CMS²⁰ and Agency for Healthcare Research and Quality.²¹ Observed uptake counts were the sum of the total number of discharges that received HHC within 14 days of discharge from each hospital. Expected uptake counts were the sum of expected probabilities of receipt of HHC for each hospital (eAppendix 2). The overall C statistic of the prediction model was 0.67, comparable to published and widely used models predicting hospital readmission risk.²²

Secondary Outcomes

We used 5 hospital-level measures to characterize the average quality of HHC used by those who received care as prescribed. The first 3 were agency-level variables obtained from CareCompare.com that were then aggregated to the hospital level: percentages of patients with (1) improved ambulation between the end and start of HHC, (2) unplanned hospitalizations within 60 days of the start of HHC, and (3) emergency department visits without hospitalization within 60 days of the start of HHC. Next, we examined (4) the days between hospital discharge and the date that the patient received their first HHC visit. Finally, we examined (5) the distinct number of HHC agencies used by discharges of each hospital. An increase in (1) and a decrease in averages of (2), (3), and (4) suggest that the quality of the HHC used improved.²³ A decrease in (5) may be indicative of hospitals establishing preferred HHC networks, leading to patients in fewer agencies. All outcomes are further described in eAppendix 3.

Subgroups

We were also interested in whether CJR may have affected racial/ethnic populations differently. We used the Research Triangle Institute race codes, contained in Medicare enrollment data, to identify patients who were non-Hispanic White (hereafter, “White”), non-Hispanic Black (hereafter, “Black”), Hispanic, and AAPI.

Statistical Analysis

We used a hospital-level linear probability model with a difference-in-differences design to estimate the effects of CJR on uptake rates, comparing hospitals in treatment and control MSAs before the announcement of CJR (July 2014-June 2015) and after CJR’s implementation (April 2016-December 2018) (eAppendix 4). We included 2018 data (when CJR became voluntary) and thus conducted an intent-to-treat analysis similar to prior literature.^15,16

Sensitivity Analysis

We also conducted several robustness checks, including assessing for violations of parallel pretrends in outcomes for a difference-in-differences approach (eAppendix Figures 1-5); restricting our sample to hospitals with at least 10 discharges to HHC in both the pre- and posttreatment periods (eAppendix Table 2); restricting our sample to the first 2 years of CJR when the program was mandatory (eAppendix Table 3); examining the effects of CJR on intervening events (ie, institutionalization, death [there were no decedents]) that may prevent uptake of HHC (eAppendix Table 4); and examining effects on unadjusted uptake rates (eAppendix Table 5). Robustness checks indicated similar results, although estimates for AAPI patients should be interpreted with caution (eAppendix Figure 5) given the potential violation of the parallel pretrends assumption.

RESULTS

We first show unadjusted, descriptive statistics of the analytic sample at the hospital level, comparing treatment and control groups before and after CJR. Prior to CJR, treatment and control groups were similar, indicative of successful randomization, although there were some slight differences that make it appropriate to control for group-level differences via approaches such as difference-in-differences (Table 1 and eAppendix Table 6). CJR hospitals performed slightly fewer joint replacement episodes per month before vs after CJR (13.6 vs 15.3, respectively). During baseline, treatment and control hospitals had similar referral rates to HHC agencies (31.6% vs 31.9%). HHC referrals were similar clinically and demographically. However, CJR hospitals had a slightly lower rate of unadjusted uptake (83.9% vs 85.5%).

Descriptive statistics also suggest that hospitals increasingly referred patients to HHC and that the composition of referrals changed over time (Table 1). Referrals to HHC at control group hospitals increased from 31.9% to 35.6%, which was slightly lower than but similar to the increase among CJR hospitals (31.6% to 38.2%). HHC referrals under CJR were more likely for racial/ethnic minority groups and patients who were dually eligible for Medicare and Medicaid. Moreover, patients without use of hospital or institutional postacute care (ie, skilled nursing facility, inpatient rehabilitation, long-term care hospital) in the last half-year before receiving joint replacement surgery became a smaller share of those with referrals to HHC after CJR (Table 1). Patterns for patients referred to HHC were similar to patterns for the overall joint replacement patients (eAppendix Table 7).

Figure 1 compares trends in HHC uptake rates, separately for treatment and control groups, in quarterly increments. Both treatment and control groups had similar uptake rates in the year before CJR participants were announced. The treatment and control groups diverged during the period between the date of announcement and implementation. In the 3 program years following CJR implementation, estimated rates were initially nearly identical between treatment and control during the first program year, followed by a gap between treatment and control hospitals.

Figure 2 shows unadjusted HHC uptake at the MSA level before CJR (panel A) and the within-MSA change after CJR (panel B). Unadjusted uptake rates ranged from 51.06% in Rochester, New York, to 98.7% in Beaumont–Port Arthur, Texas, in the period before CJR. The largest improvement in HHC uptake was 18.9 percentage points and the largest decline was 22.9 percentage points.

Table 2 shows means and mean differences before and after CJR within treatment and control groups as well as the regression-derived difference-in-differences estimates. Prior to CJR, a comparison of case mix–adjusted means indicated that the overall HHC uptake rate among treatment hospitals (83.59%) was lower than in control hospitals (85.34%) (Table 2). After CJR, mean case mix–adjusted uptake rates decreased for both treatment (81.26%) and control (79.17%) groups. Regression estimates indicate that CJR was associated with a 3.73–percentage point differential increase (95% CI, 0.97-6.49; P = .008) in HHC uptake rates among patients referred to HHC (Table 2).

The regression results also indicate that the effects of CJR on uptake rates differentially improved by 3.54 percentage points for White individuals (95% CI, 0.42-6.65; P = .026). There was a marginally statistically significant improvement of 5.05 percentage points for Black individuals (95% CI, −0.09 to 10.18; P = .054) due to worsened uptake for the control group rather than improved uptake for the treatment group. In contrast, point estimates were small, negative, and not statistically significant for Hispanic (−0.82; 95% CI, –6.18 to 4.54; P = .763) and AAPI (−0.48; 95% CI, −10.18 to 9.22; P = .922) populations.

For patients who received HHC upon referral, there was modest suggestive evidence that hospitals discharged patients to higher-quality agencies under CJR (Table 3). The differential effect estimate for days to first HHC visit was −0.04 days (95% CI, −0.12 to 0.04; P = .337), and estimates for agency scores for walking improvements (0.32 with control average of 65.21%; 95% CI, −0.38 to 1.03; P = .365), emergency department visits (−0.12 with control average of 12.52%; 95% CI, −0.35 to 0.11; P = .300), and hospitalizations (−0.11 with control average of 16.16%; 95% CI, −0.38 to 0.15; P = .397) were all in directions consistent with greater use of higher-quality HHC agencies, but none were statistically significant. There was also no indication that the number of agencies used had changed. These patterns were qualitatively similar for White and Black populations but not for Hispanic or AAPI populations, for whom the patterns were mixed.

DISCUSSION

From April 2016 through December 2018, 79.17% of patients discharged after joint replacement surgery who were referred to HHC received it. During CJR, uptake of HHC decreased but the decrease was mitigated for patients at CJR hospitals, resulting in a differential of 3.73 percentage points in HHC uptake, or a 4.5% improvement in postacute HHC adherence. Uptake rates decreased less for White (3.54–percentage point differential) and Black (5.05–percentage point differential) patients, which were also the populations with the lowest uptake rates prior to CJR. We observed modest and statistically insignificant effects of CJR on the types of HHC agencies used. Bundled payment incentives likely improved quality by increasing patients’ uptake of prescribed postacute HHC, but more work is needed to ensure HHC access for large portions of the population, especially Hispanic and AAPI individuals.

Prior studies’ findings have convincingly shown that CJR increased use of HHC,^13-16 but they have not clarified whether CJR improved patient adherence to these new referral practices. Our study builds upon this knowledge by documenting that, at least in terms of patient adherence to HHC referrals, hospitals may have improved quality. Moreover, although noisily estimated, improvements in uptake rates were particularly large for Black individuals discharged from CJR hospitals, effectively making uptake rates the highest among Black individuals compared with all other racial/ethnic groups. However, this relative improvement appears to be driven by a decline in the uptake rates for Black patients in the control hospitals over the time period. These data suggest that CJR may have had beneficial effects for both quality improvement and health equity. Nonetheless, even with higher uptake of HHC under CJR, our results show that 15% to 20% of referrals do not result in receipt of HHC, which is in line with prior estimates,^8,24 highlighting substantial room for improvement.

Determining why HHC uptake is low is difficult due to both demand- and supply-side reasons for nonadherence. On the supply side, HHC worker numbers fell by nearly 12% from 2013 to 2019.²⁵ Thus, HHC agencies may have faced capacity constraints in meeting the volume of referrals from joint replacement discharges. On the demand side, our findings are consistent with explanations put forth in the literature, such as patients avoiding suboptimal HHC experiences, fearing loss of privacy and autonomy, and wanting to expedite their return to the community.¹⁰

Study findings suggest that actively involving patients and their caregivers in addressing concerns and explaining the value of postacute HHC might mitigate unrealistic patient expectations of recovery, potentially increasing their willingness to accept HHC assistance.¹⁰ Particularly if care is to be delivered at home, establishing trust between the health care team and patients requires explicit investment in understanding patient concerns.²⁶ For patients concerned about negative experiences with HHC, for instance, providers may need to be more engaged in helping them identify higher-quality HHC.¹¹

Studies have also found that patient adherence is related to how physicians communicate with patients, with better outcomes when patients are actively involved and there are open discussions of barriers to adherence.^2,27 Our null results for Hispanic and AAPI individuals, for whom language barriers are more prevalent, suggest a need for more effective communication among providers, patients, and caregivers. Nearly 40% of hospitals do not offer language services,²⁸ and approximately one-third of HHC aides report speaking a different language than their patients.²⁹ As a structural barrier to health care,³⁰ language-induced barriers may erode trust³¹ and lower patients’ willingness to let care providers complete medically necessary tasks.³² Our study results point to a need for future research to better understand the reasons for low HHC uptake.

Limitations

Our study has limitations. First, although we adjusted for the case mix of patients referred to HHC using established risk adjustment methods, prediction models are imperfect and limited by observables. Thus, our estimated effects of CJR on uptake may also reflect changes in patient composition rather than CJR interventions. Second, we used the discharge destination code in inpatient claims data to identify referrals to HHC, consistent with prior literature.^8,9,19 Although hospital discharge planners populate this field based on their assessment of patient needs for postdischarge care, care arrangements may change after discharge and not all hospitals update the destination code.²⁴ Therefore, the discharge destination code is a proxy for referrals and may contain errors. If CJR hospitals are differentially more likely to update discharge destination codes, then our estimate of the CJR’s effect on uptake may be biased upward. However, uptake rates for all groups, except for Black individuals, trended down, which is inconsistent with CJR hospitals more systematically and retroactively correcting documentation. Finally, we cannot extend our results beyond the hospitals in MSAs included in the original study design, which served a greater proportion of urban patients.

CONCLUSIONS

These limitations notwithstanding, this is the first study to examine the impact of bundled payment incentives on HHC uptake rates. Although we observed improved HHC uptake in CJR hospitals compared with controls, the potential impact varied by race and ethnicity and was modest, especially when considering the share of patients who do not receive HHC as prescribed. With HHC and the home environment becoming increasingly important as a site of care for aging adults, it remains a puzzle why sizeable proportions of patients miss out on these services. Future work is urgently needed to uncover how structural factors can be modified to alleviate patients’ concerns and decrease barriers to recommended care. 

Author Affiliations: Maxwell School of Citizenship and Public Affairs, Syracuse University (JL), Syracuse, NY; Labovitz School of Business and Economics, University of Minnesota Duluth (LL), Duluth, MN.

Source of Funding: This research was supported in part with a Health Services Research Grant (AOTFHSR21Li) to Dr Li funded by the American Occupational Therapy Foundation. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Prior Presentation:This work was presented at the American Society for Health Economists Annual Conference in 2023 and Association for Public Policy Analysis and Management Annual Meeting in 2023.

Author Disclosures: The 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 (JL, LL); acquisition of data (JL); analysis and interpretation of data (JL, LL); drafting of the manuscript (JL, LL); critical revision of the manuscript for important intellectual content (JL, LL); statistical analysis (JL); obtaining funding (JL); administrative, technical, or logistic support (JL); and supervision (JL).

Address Correspondence to: Jun Li, PhD, Maxwell School of Citizenship and Public Affairs, Syracuse University, 314 Lyman Hall, Room 320E, Syracuse, NY 13244. Email: jli208@syr.edu.

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