This retrospective cohort study of rural hospitals found that Medicare Advantage penetration increased substantially from 2008 to 2019 and was associated with greater hospital sustainability.
Objectives: A growing number of Medicare beneficiaries in rural areas are enrolled in Medicare Advantage plans, which negotiate hospital reimbursement. This study examined the association between Medicare Advantage penetration levels in rural areas and hospital financial distress and closure.
Study Design: This retrospective cohort study followed rural general acute care hospitals open in 2008 through 2019 or until closure using Healthcare Cost and Utilization Project State Inpatient Databases for 14 states.
Methods: The primary independent variables were the percentage of Medicare Advantage stays out of total Medicare stays at the hospital and the percentage of Medicare Advantage beneficiaries out of total beneficiaries in the hospital’s county. Financial distress was defined using the Altman Z score, where values less than or equal to 1.1 indicate financial distress and values greater than 2.8 indicate stability. The Z score was examined as a continuous outcome in hospital and county fixed-effects models. Risk of closure was examined using Cox proportional hazard models adjusted for hospital and market factors.
Results: Rural hospital Medicare Advantage penetration grew from 6.5% in 2008 to 20.6% in 2019. A 1–percentage point increase in hospital penetration was associated with an increase in financial stability of 0.04 units on the Altman Z score (95% CI, 0.00-0.08; P = .03) and a 4% reduction in risk of closure (HR, 0.96; 95% CI, 0.92-1.00; P = .04). Results were consistent when measuring Medicare Advantage penetration at the county level.
Conclusions: Our findings counter the notion that Medicare Advantage plans financially hurt rural hospitals because they pay less generously than traditional Medicare.
Am J Manag Care. 2023;29(11):594-600. https://doi.org/10.37765/ajmc.2023.89455
This study of rural hospitals in 14 US states adds to the scant literature on Medicare Advantage in rural areas.
Rural hospitals are an important source of care for millions of Americans. They provide inpatient services and emergency care to treat patients with time-sensitive conditions. Compared with urban hospitals, rural hospitals have a lower and less consistent volume of patients; they also have limited access to staffing and often are in financial distress, placing them at risk of closure.1 More than 100 rural hospitals have closed in the past decade.2
Many rural hospitals depend on Medicare as their main source of reimbursement because they serve populations older than the national averages.1 Most Medicare beneficiaries are enrolled in traditional Medicare (TM).3 However, Medicare beneficiaries are increasingly enrolled in private plans through Medicare Advantage (MA) that can offer expanded benefits and reduced risk of out-of-pocket expenses. Nationwide, MA penetration increased from 15% in 2001 to 42% in 2021.3 Unlike TM, which reimburses hospitals based on an amount set by CMS, MA plans have an opportunity to negotiate with hospitals to include them in the plan’s network. Negotiation includes establishing reimbursement rates, which may or may not replicate TM reimbursement structures, and potentially additional reporting requirements. Findings from studies examining whether MA plans pay more than, less than, or the same as TM for inpatient services have been mixed.4-7
Before the enactment of the Balanced Budget Act of 1997, only health maintenance organization (HMO) plans could offer private Medicare coverage. The private HMO Medicare plans were generally available only to beneficiaries in urban areas, where plans could form sizable networks. Under the Balanced Budget Act, health plans could offer preferred provider organization plans, which are easier to establish in areas with fewer providers, such as rural areas. MA enrollment in rural areas, particularly in preferred provider organization plans, has more than doubled in the past 10 years.8 If MA plans negotiate reimbursements with hospitals that are lower than TM rates, increasing MA penetration may be devastating to rural hospitals that are already operating with slim margins. Conversely, if MA plans are more generous with reimbursement in rural areas or steer enrollees to local sources of care, movement toward MA may support rural hospital stability.
In this study, we examined the growth of MA and its relationship to rural hospital financial distress and closures. We quantified MA penetration from 2008 to 2019 using 2 measures as follows: (1) MA penetration among Medicare beneficiaries residing in the county of the hospital and (2) the percentage of Medicare stays at the hospital with MA. Next we measured differences in rural hospitals with high and low MA penetration. Then we estimated the association of MA penetration with hospital financial distress and risk of closure.
Data Source and Study Population
This retrospective cohort study included acute care hospitals in rural areas open in 2008 and followed them through 2019 using Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases9 for 14 states (see eAppendix A [eAppendices available at ajmc.com]). These states represented 45% of the overall US population and 32% of the rural population in 2020. They were selected because (1) they had payer codes distinguishing MA plan from TM payment in all study years,10 (2) the percentage of Medicare stays with MA in HCUP is reasonably consistent with CMS enrollment data,11-13 and (3) they contained at least 1 rural hospital. Rural hospitals were defined based on zip codes eligible to receive funding from the Federal Office of Rural Health Policy,14 a broad definition that includes some metropolitan hospitals designated by other measures (eg, Rural-Urban Continuum Codes15).
Other data sources included CMS MA enrollment data, hospital closures identified from the University of North Carolina Cecil G. Sheps Center for Health Services Research, mergers and acquisitions identified from Irving Levin Associates,16 hospital characteristics from the American Hospital Association (AHA) Annual Survey, financial distress calculated from the CMS Cost Reports,17 hospital market characteristics from the American Community Survey,18 and state Medicaid expansion status from KFF.19
Primary Dependent Variables
We examined 2 outcomes: financial distress and closure. We used the Altman Z score, which has been used recently to monitor financial performance.20 The Altman Z score has been used over the past 4 decades in multiple industries, including the health care sector.21 The score has been updated as it applies to entities of different ownership (ie, private for profit and nonprofit).22 We applied the version used by McCay et al21 (ie, Z double prime) because it was developed for industries including nonprofit entities. We calculated the composite score by adding 4 components—liquidity, profitability, efficiency, and productivity. In regression models, we treated the Altman Z score as a continuous variable. Lower values reflect more financial distress and higher values reflect more stability. We provide descriptive information on a categorical variable of financially distressed (≤ 1.1), concerned (> 1.1 to ≤ 2.8), and stable (> 2.8) in eAppendix B.21
Primary Independent Variables
The primary independent variables were (1) MA penetration of Medicare beneficiaries in the county of the hospital (ie, county penetration) and (2) the percentage of Medicare stays at the hospital with MA as the primary expected payer (ie, hospital penetration). The county penetration measure is used to provide insight on MA penetration as a market characteristic, whereas the hospital penetration measure provides insight on hospital exposure to MA as a payer. Both variables were included in the models as continuous variables that varied over time.
We identified hospital affiliation status using mergers and acquisition data from Irving Levin Associates, augmented with self-reported affiliation from the AHA. We also included a number of hospital organizational, utilization, and market characteristics (eAppendix C).
In descriptive analyses, we examined county and hospital MA penetration from 2008 through 2019. Second, we examined characteristics of hospitals with high (≥ 20%) and low (< 20%) MA penetration. This cut point is consistent with existing literature.23,24
We used fixed-effects models to examine the association of MA penetration with hospital financial distress. The data set included a record for each hospital in each year it was open. The models examining county MA penetration included fixed effects for the hospital’s county. The models examining hospital MA penetration included hospital fixed effects. The county/hospital fixed effects limit the effect of MA penetration to variation within counties/hospitals across study years and control for confounders that do not vary over time. The effect of interest can be interpreted as the change in the Altman Z score associated with a 1–percentage point increase in MA penetration. SEs are robust, accounting for the clustering of observations within counties/hospitals over time.
Finally, we estimated survival models to quantify the association between MA penetration and hospital closure. We examined time to closure for hospitals open in 2008. Hospitals stopped contributing time in the year they closed. Thus, MA penetration corresponds to 1 year before each event. MA penetration was treated as a time-dependent covariate, where values could change over time. Proportional HRs are presented.
The survival models controlled for hospital organizational, utilization, and market characteristics measured at baseline in 2008. The hospital fixed effects controlled for all these factors at baseline in the financial distress models. We did not include additional time-varying covariates in the models because many of the variables may be on the causal pathway (eg, MA penetration may affect total discharge volume, which may affect financial distress) or may be a cause of financial distress (eg, financial distress may increase elimination of service lines).
The models are further stratified by financial distress and public vs private ownership, both measured in 2008. We estimated separate models for county MA penetration and hospital MA penetration.
Role of the Funding Organization
The funding organization (the Agency for Healthcare Research and Quality) had a role in data collection, data analysis and interpretation, and the right to approve or disapprove publication of the finished manuscript.
The final study sample included 556 rural hospitals, accounting for 25% of all rural community general acute care hospitals in 2008. Of these study hospitals, Medicare Advantage penetration of beneficiaries increased by 14 percentage points from 2008 through 2019 among rural hospitals’ counties (14.3% to 28.4%) and among Medicare inpatient stays (6.5% to 20.6%) (Figure). Mean hospital MA penetration was lower but followed nearly a parallel trend to the county measure. Because hospital-level penetration started at a lower baseline (ie, 6.5% at baseline), the percentage increase in penetration was much higher at the hospital level than at the county level (217% vs 99%). In 2008, 70.7% of hospitals had a low county penetration rate of less than 20%, and 90.3% had a low hospital penetration rate. By 2019, these rates had decreased to 31.5% and 51.7%, respectively (Table 1). However, one-fifth of all rural hospitals included in this study still served no MA inpatients in 2019. One-third of these hospitals were in counties with high MA penetration.
With respect to county MA penetration, hospitals with high vs low penetration were more likely to be affiliated with another hospital or health system (31.7% vs 19.8% in 2019) but less likely to be public hospitals (24.4% vs 50.0%) or critical access hospitals (CAHs) (41.4% vs 68.5%) (Table 1). These hospitals also had larger bed sizes and higher annual discharge volumes and were more likely to be in metropolitan areas. For hospitals with high vs low county penetration rates, Medicare stays constituted a smaller percentage of all discharges (58.1% vs 62.9% in 2019), but Medicaid stays accounted for a greater share of all stays (17.2% vs 13.7% in 2019). They also had a lower market share of inpatient stays (22.0% vs 29.7% in 2019). However, hospitals with high vs low county penetration had a greater percentage of surgical stays (9.5% vs 5.3% in 2019). Of hospitals with high and low county penetration in 2019, 9.6% and 40.7%, respectively, had no MA inpatient stays during the year, which equals a total of 100 hospitals, or approximately one-fifth of the 515 rural hospitals still operating in 2019. Many differences noted above were similar when we compared high and low hospital MA penetration, as opposed to county penetration (Table 1). Additional characteristics are provided in eAppendix B.
With respect to financial distress, where higher values on the Altman Z score correspond to more stability, a 1–percentage point increase in hospital MA penetration was associated with an increase of 0.04 in the Altman Z score (P = .03) (Table 2). Thus, the mean increase in MA penetration (for counties and hospitals) of approximately 14 percentage points from 2008 through 2019 would be associated with an increase in the Altman Z score of 0.56. The cut points denoting financial stability and distress are 2.8 and 1.1, respectively, a 1.7-unit difference. Note that the mean increase in the Altman Z score across all hospitals from 2008 through 2019 was 0.3.
A similar association (β = 0.08) was observed for county MA penetration but was not significant at the conventional level (P = .07). However, these associations persisted only among hospitals that were already distressed in 2008 (county penetration: β = 0.12; P = .02; hospital penetration: β = 0.05; P = .02) and among those that were privately owned (county penetration: β = 0.13; P = .02; hospital penetration: β = 0.07; P = .01).
The association between the Altman Z score and county MA penetration appeared to be larger than the association with hospital MA penetration (β = 0.08 vs 0.04), but the difference was not significant. Further, the coefficients were estimated from 2 models that may not be directly comparable.
With respect to risk of closure, a 1–percentage point increase in county MA penetration was associated with a 5% reduction in risk of closure (HR, 0.95; P = .01) (Table 3). Similarly, a 1–percentage point increase in hospital MA penetration was associated with a 4% reduction in risk of closure (HR, 0.96; P = .04). The relationship between county MA penetration and lower risk of closure generally persisted among hospitals that were financially distressed (HR, 0.95; P = .07), financially stable (HR, 0.86; P = .01), and privately owned (HR, 0.95; P = .04).
This study of rural hospitals in 14 states found that MA penetration is associated with increased financial stability and reduced likelihood of rural hospital closure, suggesting that the growth of MA in rural areas has not contributed to rural hospital closures. We measured MA penetration at both the hospital and the county levels. Hospital-level penetration offers insight into the relationship between the share of MA patients and hospital operation. County-level penetration reflects the market condition, which can have significant influence on hospital finance. Our county fixed-effects models showed a positive association of county MA penetration with reduced risk of hospital closure, which suggests that improvement in hospital financial performance was not just an issue of the hospital’s own operation but also related to those market conditions favorable to MA penetration.
Our findings counter the notion that MA plans hurt rural hospitals by not paying them as generously as TM. Although this study does not identify the mechanism underlying these findings, it could be that MA prices relative to TM fee-for-service rates are more generous in rural areas or that MA plans steer patients to local sources of care. Previous research is inconclusive on whether MA plans negotiate rates that are less than TM. Based on interviews with hospital and health plan executives in 2014, Berenson et al5 concluded that MA plans pay hospitals TM prices. In contrast, using data from Medicare and commercial insurers in 2009 and 2012, Baker et al4 found MA plans paid 5.6% less for hospital services than TM did after adjusting for differences in hospital networks, geographic areas, and case mix. Relevant to rural hospitals, a survey of 60 CAH administrators regarding MA reimbursement found that 29% of CAHs were reimbursed under the same terms as TM: 101% of reasonable and allowable costs.7 Some CAHs were reimbursed based on cost only and others were reimbursed on a per diem basis. This study was conducted using data from 2007, and since then, MA plans may have opted to increase reimbursement to CAHs and rural hospitals beyond TM rates because these hospitals must survive to provide MA enrollees with access to care.
Investigators have found concerning trends related to MA in rural areas that should be considered along with our results. For example, a recent study found that beneficiaries in rural areas enrolled in MA are more likely than their urban counterparts to switch back to TM.25 Future research should monitor how MA affects patient experiences and health outcomes in rural areas.
We also found that some rural hospitals located in high MA penetrating counties served no MA patients. It could be that these hospitals opt not to participate in an MA network because of undesirable terms. Alternatively, MA plans may have excluded these hospitals from their network and/or steered enrollees to other hospitals. A recent study found MA enrollees were more likely to go to average-quality hospitals than TM enrollees, suggesting that MA plans may intentionally exclude or steer enrollees to certain hospitals.26
This study fills several gaps in the literature. We found that MA penetration grew substantially from 2008 to 2019 (from 14.3% to 28.4%) in rural hospital counties. The percentage of Medicare inpatient stays that were MA at rural hospitals was lower but grew in parallel and at an even higher rate (from 6.5% to 20.6%). Our finding of lower MA penetration at the hospital vs the county level is not surprising, because MA enrollees tend to be healthier than TM beneficiaries and less likely to be hospitalized.27 The difference could also be driven by steering of MA enrollees to other hospitals or sources of care. Nonetheless, the gap between the hospital- and the county-level penetration rates declined over time. There may be less selection bias and less restriction on hospital use with these plans today than 10 years ago.
Finally, we found that hospitals in areas with higher county or hospital MA penetration differed from hospitals in areas with lower MA penetration. Specifically, hospitals in lower MA penetration areas were more likely to be public and independent and have fewer beds. This is consistent with previous research that found hospitals used by TM patients were more likely to be public and independent.13 We controlled for these differences in modeling and conducted stratified analyses excluding public hospitals, but unmeasured factors related to expansion of MA and hospital survival, including changes to the share of Medicare inpatients,28 might have confounded results. The consistency of our findings across county- and hospital-level growth in MA penetration lends robustness to our results. Finally, our study did not examine how MA penetration affects rural hospital volume. Increases in MA penetration might hasten rural hospital bypass in areas where no hospitals are in network.
Our findings of positive associations between MA penetration and rural hospital financial stability and sustainability differ from those of the limited previous work examining MA and hospital financial outcomes. Ramamonjiarivelo et al29 found MA penetration was negatively associated with total margin among public hospitals using a national sample of hospitals from 1997 to 2013. An analysis conducted by Large et al30 using 1992-1997 data found that Medicare HMO penetration was associated with a decline in profitability of hospitals in Florida. However, these earlier studies were focused on a specific type of hospital or health plan (public hospitals29 and HMO penetration in Florida30), were not limited to rural hospitals, and used older data. MA reimbursement for inpatient services may be more generous than Medicare reimbursement at rural but not urban hospitals. Thus, the effects of MA penetration on hospital performance were possibly lost in previous analyses, which looked at rural and nonrural hospitals, especially if nonrural hospitals have lower Medicare payer mixes and different associations between MA penetration and hospital finances.
This observational study was not designed to establish causation. Although we employed a survival model adjusting for baseline factors to examine hospital closures and a fixed-effects model to examine financial distress, there may be unmeasured time-varying factors associated with both MA penetration and hospital outcomes that confound results. For example, if total hospitalization volume increased in tandem with MA shares, such volume increases could contribute to hospital financial outcomes. Further, our analysis is limited to 14 states for which we could consistently distinguish between TM and MA admissions in HCUP data and is not necessarily generalizable to all states. Finally, although we assessed the overall financial condition of the hospitals, we were unable to compare actual payments between MA plans and TM.
The results of this study have important policy implications related to the sustainability of rural hospitals. Specifically, our study’s findings suggest that the growth of MA in rural areas over the past decade has not been associated with increasing rural hospital closures or financial distress. On the contrary, MA penetration may have improved the sustainability of rural hospitals. An important concern is the effect of MA on CAHs because they are paid cost-based rates by TM. Based on our analysis, most rural CAHs are located in low MA penetration markets. Thus, if MA penetration grows in these areas, these relationships should be monitored to uncover effects on these vulnerable hospitals.
The authors gratefully acknowledge staff formerly with IBM Watson Health, including Minya Sheng, MS; Jillian McCarty, MPH; and Olivia Reding, MPH, PMP, for assistance with data management, programming, and statistical support; and Mary Beth Schaefer, MS, for providing editorial review of the manuscript.
The authors also wish to acknowledge the HCUP Partner organizations that contributed to the data used in this study: California Office of Statewide Health Planning and Development, Connecticut Hospital Association, Florida Agency for Health Care Administration, Georgia Hospital Association, Kansas Hospital Association, Maryland Health Services Cost Review Commission, Massachusetts Center for Health Information and Analysis, Michigan Health & Hospital Association, Nevada Department of Health and Human Services, New Jersey Department of Health, New York State Department of Health, Tennessee Hospital Association, West Virginia Department of Health and Human Resources, West Virginia Health Care Authority, and Wisconsin Department of Health Services.
Author Affiliations: IBM Watson Health (RMH, KRF); now with Lewin Group (RMH), Boston, MA; Everytown for Gun Safety (KRF), New York, NY; Agency for Healthcare Research and Quality (LL, HJJ), Rockville, MD.
Source of Funding: HHS, Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project contract number HHSA-290-2018-00001-C.
Author Disclosures: Dr Henke and Dr Fingar were employed by IBM, which received funding from AHRQ for this research. 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 (RMH, KRF, LL, HJJ); acquisition of data (LL, HJJ); analysis and interpretation of data (RMH, KRF, LL, HJJ); drafting of the manuscript (RMH, KRF, LL, HJJ); critical revision of the manuscript for important intellectual content (RMH, KRF, LL, HJJ); statistical analysis (RMH, KRF, LL, HJJ); obtaining funding (RMH, LL, HJJ); administrative, technical, or logistic support (KRF); and supervision (RMH, HJJ).
Address Correspondence to: H. Joanna Jiang, PhD, Agency for Healthcare Research and Quality, 5600 Fishers Ln, Rockville, MD 20857. Email: email@example.com.
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