Financial burden of care greatest among rural beneficiaries in Medicare advantage.

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Learn more: PMC Disclaimer | PMC Copyright Notice Health Serv Res . 2024 Oct 9;60(3):e14393. doi: 10.1111/1475-6773.14393 Financial burden of care greatest among rural beneficiaries in Medicare advantage Sungchul Park 1, ✉ , David J Meyers 2 , Yubin Park 3 , Amal N Trivedi 4 Author information Article notes Copyright and License information 1 Department of Health Policy and Management, College of Health Science, Korea University, BK21 FOUR R&E Center for Learning Health Systems, Korea University, Seoul, Republic of Korea 2 Department of Health Services, Policy, and Practice, School of Public Health, Brown University, Providence, Rhode Island, USA 3 Department of Computer Science, College of Arts and Sciences, Emory University, Atlanta, Georgia, USA 4 Department of Health Services, Policy, and Practice, School of Public Health, Brown University, Center of Innovation for Long‐term Services and Supports, Providence Veterans Affairs Medical Center, Providence, Rhode Island, USA * Correspondence , Sungchul Park, Department of Health Policy and Management, College of Health Science, Korea University, BK21 FOUR R&E Center for Learning Health Systems, Korea University, 145 Anam‐ro, Seongbuk‐gu, Seoul 02841, Republic of Korea. Email: sungchul_park@korea.ac.kr ✉ Corresponding author. Issue date 2025 Jun. © 2024 Health Research and Educational Trust. PMC Copyright notice PMCID: PMC12120509  PMID: 39384529 Abstract Objective To examine differences in access to care and financial burden between Traditional Medicare (TM) and Medicare Advantage (MA) beneficiaries in rural and urban areas and then explore whether there were potential differences in MA benefits between urban and rural areas. Study Setting and Design We conducted a cross‐sectional study within the Medicare setting in the United States. Data Sources and Analytical Sample Data from three distinct sources for 2017–2021: the Medicare Current Beneficiary Survey, the MA landscape data, and the Plan Benefit Package data. Our sample comprised 43,343 Medicare beneficiary‐years, including TM and MA beneficiaries in urban and rural areas. Principal Findings Our adjusted analysis showed that rural MA beneficiaries experienced higher rates of delayed care due to costs (10.0% [95% confidence interval (CI): 8.8–11.1]) compared with rural TM (9.5% [8.8–10.2]), urban MA (7.9% [7.4–8.4]), and urban TM (7.9% [7.5–8.2]) beneficiaries. Similarly, rural MA beneficiaries (11.4% [95% CI: 10.3–12.5]) reported more difficulty paying medical bills compared with rural TM (9.4% [8.7–10.1]), urban MA (8.1% [7.7–8.6]), and urban TM (7.8% [7.5–8.2]) beneficiaries. This disparity was associated with less generous financial structures in rural MA plans. Compared to urban MA plans, rural MA plans offered lower out‐of‐pocket maximums for in‐network care ($5918 vs. $5439), but required higher copayments ($1686 vs. $1724 for a 5‐day hospitalization, $37 vs. $41 for a specialist visit, and $35 vs. $38 for a mental health visit). However, differences in quality of care and provision of supplemental benefits were small. Conclusion Rural Medicare beneficiaries reported a greater financial burden of care than urban Medicare beneficiaries, but the most significant burden was observed among MA beneficiaries in rural areas. One possible mechanism could be the less generous financial structures offered by rural MA plans. These findings suggest the need for policies addressing the affordability of care for rural MA beneficiaries. Keywords: access to care, financial burden of care, Medicare, Medicare advantage, rural residence, traditional Medicare What is known on this topic Rural Medicare beneficiaries often face a challenging combination of lower incomes and greater chronic disease burdens compared with urban Medicare beneficiaries. Medicare Advantage (MA) plans, however, may address these unique needs by providing a wider range of benefits. Yet it remains unclear whether enrollment in MA plans translates into improvements in access to care and financial burden of care for rural beneficiaries. What this study adds Rural Medicare beneficiaries reported a higher financial burden of care than urban Medicare beneficiaries, but the most pronounced burden was observed among MA beneficiaries in rural areas. This disparity was likely attributed to less generous financial structures provided by rural MA plans. These findings underscore the need for policy interventions that specifically address the disproportionate financial burden experienced by rural MA beneficiaries. 1. INTRODUCTION Enrollment in Medicare Advantage (MA), a private insurance alternative to Traditional Medicare (TM), has grown rapidly over the past decade. 1 However, this growth is particularly pronounced in rural areas compared with urban areas with enrollment rates in rural areas more than doubling from 17% in 2014 to 40% in 2023, compared with 34% to 53% in urban areas during the same period. 2 Consequently, over 1.8 million rural beneficiaries were covered by MA plans in 2023. This trend may be partly attributable to an increased availability of MA plans in rural areas. The number of MA plans accessible to the average rural beneficiary tripled between 2014 and 2023, increasing from 9 to 27. 2 While rural Medicare beneficiaries often face a challenging combination of lower incomes and higher chronic disease burdens compared with urban Medicare beneficiaries, 3 MA plans may address these unique needs by offering a wider range of benefits. 4 For example, MA plans often provide extra benefits not included in TM such as supplemental nonmedical benefits that address enrollees' health‐related social needs. 5 The scope of these benefits has recently expanded to include primarily health‐related benefits such as home‐based palliative care and in‐home support services and Special Supplemental Benefits for the Chronically Ill such as food, transportation, and structural home modifications. 6 , 7 In 2022, approximately 43% of MA plans provided these supplemental benefits, though evidence on enrollees' use of these supplemental benefits remains largely unavailable. 8 Furthermore, unlike TM, MA plans have out‐of‐pocket spending limits, potentially providing financial protection against high health care expenses. In 2022, these limits were established at $4972 for in‐network services and $9245 for in/out‐of‐network services. 9 Despite the potential benefits of MA enrollment for rural Medicare beneficiaries, a critical question remains unanswered: does MA enrollment translate into improvements in access to care and financial burden of care for rural beneficiaries? Limited access to healthcare providers, particularly specialists, is a longstanding challenge in rural areas. 10 This limited access may contribute to higher mortality rates in rural areas compared with urban areas. 3 , 11 On one hand, increased availability of MA plans may enhance access to and use of care due to a broader range of covered services. Additionally, out‐of‐pocket spending limits may offer financial protection. On the other hand, concerns exist regarding potential negative impacts of MA plans on rural beneficiaries, particularly regarding network restrictions. MA plans tend to have narrower networks, with an average of less than half (46%) of all physicians in a county. 12 Rural areas face even more restrictive networks compared with urban areas (31.6% of all physicians in rural vs. 61.5% in urban). 13 , 14 These narrower networks in rural areas may limit access to specialists and result in higher out‐of‐pocket costs if needed care falls outside the plan's network. While some studies suggest that health care experiences and clinical care were similar among TM and MA beneficiaries in both rural and urban areas, 15 others indicate that rural beneficiaries disenrolled from MA plans at higher rates compared with urban beneficiaries. 16 This raises questions about the effectiveness of MA plans in meeting the specific needs of rural population. This knowledge gap necessitates further research to understand the implications of MA enrollment in rural areas. Our study aimed to address this gap by examining differences in access to care and financial burden of care among TM and MA beneficiaries in rural and urban counties. 2. METHODS 2.1. Data We employed a cross‐sectional study using data from three distinct sources for the years 2017 through 2021. Our primary data source was the Medicare Current Beneficiary Survey (MCBS), which is a nationally representative survey of Medicare beneficiaries. The MCBS provides individual‐level data on demographics, health status, and health care experiences collected through surveys and claims data for both MA and TM enrollees. Participants were interviewed three times annually either in person or by phone. We used the Public Use Files, which are de‐identified versions of the data made available to the public. Although some beneficiaries participated across multiple years, the Public Use Files do not include individual identifiers across time and thus support only cross‐sectional analysis, not longitudinal analysis. Therefore, we treated the data for each year as an independent annual cross‐sectional survey. In addition to individual‐level data, we used two sets of plan‐level data: the MA landscape data and the Plan Benefit Package data. The MA landscape data provide information about MA plan availability and general benefit structures, while the Plan Benefit Package data offer detailed information on the specific benefits and coverage provided by individual MA plans. 2.2. Study sample We first identified all community‐dwelling Medicare beneficiaries (including those younger than 65 and those 65 years or older) who were continuously enrolled in either MA or TM for a full year. We excluded those with missing data on residence and those with missing data on other variables. We then categorized the sample into four mutually exclusive groups based on coverage type (TM or MA) and residence (rural or urban). We defined MA enrollment as having MA coverage for a full year. We defined rural residence using county‐level 2013 Rural–Urban Continuum Codes developed by the Economic Research Services at the Department of Agriculture. 17 Beneficiaries residing in counties classified as metropolitan areas were categorized as urban and those residing in nonmetropolitan areas were considered as rural. 2.3. Outcome measures We assessed two outcome variables. First, we included three binary measures to evaluate access to care: whether respondents had a particular place for medical care, whether respondents had trouble getting needed health care, and whether respondents experienced delayed care due to costs. Second, we included three binary measures to evaluate the financial burden of care: whether respondents ever had a problem paying medical bills, paid medical bills over time, and were contacted by collection agency due to medical bills. 2.4. Covariates To adjust for differences in sample characteristics between TM and MA beneficiaries in urban and rural areas, we included the following individual‐level characteristics: age (<65, 65–75, or ≥75), sex (male or female), race/ethnicity (non‐Hispanic White, non‐Hispanic Black, Hispanic, or non‐Hispanic Other, which includes Asian, Native American/Alaskan Native, Pacific Islander, or Multiracial individuals), education (less than high school, high school, more than high school), family income (≤100% of federal poverty level [FPL], 100–200% of FPL, or ≥200% of FPL), marital status (married or not), health insurance (Medicaid‐Medicare dual coverage or Medigap coverage), comorbidities (acute myocardial infarction, congestive heart failure, cancer, dementia, depression, diabetes, or stroke), self‐reported good health status (good or not), functional limitations (no functional limitation, instrumental activities of daily living [IADL] only, 1–2 activities of daily living [ADLs], or 3+ ADLs), and body mass index (underweight/healthy [<25], overweight [25–30], or obese /high‐risk obese [≥30]). The categories of health insurance are not mutually exclusive. Medigap was defined as self‐purchased private health insurance. 18 2.5. Statistical analysis Using the MCBS data, we first compared sample characteristics of TM and MA beneficiaries in urban and rural areas. To estimate adjusted differences in outcomes between TM and MA beneficiaries across these areas, we used linear probability models that controlled for the individual‐level characteristics described above and year‐fixed effects as well as MA enrollment, rural residence, and the interaction term of MA enrollment and rural residence. All covariates were treated as categorical variables. From the regression results, we used predictive margins to calculate the mean adjusted values of the outcomes for TM and MA beneficiaries in both urban and rural areas while holding constant all other variables. This approach allowed us to compare the outcomes of interest between TM and MA beneficiaries in urban and rural areas. We also conducted several sensitivity analyses. As it is possible that reductions in the financial burden of care may be due to some beneficiaries not using health services, we investigated whether there were differences in the utilization of preventive services, specifically the receipt of blood pressure checks, cholesterol checks, flu shots, and pneumonia shots in the past year. We did not examine general health care utilization such as outpatient visits as these findings can be difficult to interpret. For example, lower utilization might indicate either poor access to care or low medical needs. In contrast, the use of preventive care offers a more straightforward measure. Furthermore, to determine whether disparities in access to care and financial burden between TM and MA beneficiaries in urban and rural areas could be attributed to differences in health insurance literacy, we examined whether beneficiaries knew enough about Medicare, found Medicare easy to understand, and visited the Medicare website for information based on prior research. 19 Moreover, we accounted for a range of covariates to control for potential confounding factors. However, some of these covariates might be influenced by MA enrollment, which could impact our findings. To mitigate this issue, we conducted a sensitivity analysis using year‐fixed effects only. Additionally, Medigap is private supplemental insurance available only to TM beneficiaries, while MA beneficiaries cannot purchase Medigap. Thus, comparing TM beneficiaries with Medigap to MA beneficiaries without Medigap would not be appropriate. Therefore, we limited our sample to beneficiaries without Medigap and conducted the analysis. Finally, to explore whether the financial burden of care is more pronounced among low‐income beneficiaries, we conducted a subgroup analysis focusing on those with incomes between 0% and 200% of the FPL. For all analyses, we used survey weights to adjust the sample characteristics to be nationally representative. We also accounted for the complex survey design in standard error estimation. To explore whether there were potential differences in MA benefits between urban and rural areas, we analyzed the MA landscape data and the Plan Benefit Package data for 2017–2021. Using the data, we identified unique MA plans based on contract and plan identifiers. The unit of analysis was at the county‐plan‐year level. We examined five domains: plan access and participation (the number of available MA plans and MA penetration rates), financial performance (additional premiums for MA enrollment, the percentage of MA plans with no additional premiums, and in‐network out‐of‐pocket limits), cost‐sharing (inpatient hospital stay for 5 days, primary care physician visit, specialist visit, and mental health visit), quality of care (2–2.5 stars, 3–3.5 stars, and 4–5 stars), and provision of each supplemental benefit (health education, in‐home safety assessment, personal emergency response system, medical nutrition therapy, post discharge in‐home medication reconciliation, readmission prevention, wigs for hair loss related to chemotherapy, weight management programs, alternative therapies, nutritional/dietary benefit, additional sessions of smoking and tobacco cessation counseling, fitness benefit, enhanced disease management, telemonitoring services, remote access technologies, bathroom safety devices, and counseling services). We also assessed primary care provider network breadth using methods previously applied to the Ideon provider network data. 20 Network breadth was calculated by dividing the number of providers included in the network for a given contract (numerator) by the total number of providers listed in the National Provider Identifier registry who practice in the counties covered by the contract's service area (denominator). In summary, for each contract's service area, we calculated the proportion of primary care physicians included in the network. We then aggregated these proportions, weighted by the number of beneficiaries enrolled, to the contract level. Networks were classified into categories based on coverage: 10% fewer, 10%–25%, 25%–40%, and 60% or greater coverage of all primary care providers in the area. 3. RESULTS 3.1. Sample characteristics Our sample comprised 43,343 Medicare beneficiary‐years (weighted: 184,901,590 beneficiary‐years), including 18,126 TM beneficiary‐years in urban areas, 15,206 MA beneficiary‐years in urban areas, 7044 TM beneficiary‐years in rural areas, and 2967 MA beneficiary‐years in rural areas (Table 1 ). MA enrollment rates increased in both urban and rural areas, but the magnitude of the increase was greater in rural areas (25.5% in 2017 to 39.4% in 2021) compared with urban areas (41.4% in 2017 to 51.9% in 2021) (not shown). TABLE 1. Characteristics of Traditional Medicare and Medicare Advantage beneficiaries by rurality, 2017–2021. Characteristics Weighted % Urban Rural TM ( N = 18,126) MA ( N = 15,206) TM ( N = 7044) MA ( N = 2967) Age <65 15.1 13.0 19.1 18.2 65–75 36.7 35.0 36.1 34.1 ≥75 48.2 52.0 44.7 47.7 Female 46.9 43.8 47.6 45.5 Race/ethnicity Non‐Hispanic White 77.9 66.4 85.0 79.3 Non‐Hispanic Black 8.4 12.2 5.8 11.8 Hispanic 7.8 16.2 3.5 2.5 Non‐Hispanic other 5.9 5.3 5.8 6.4 Education Less than high school 10.3 18.6 16.0 20.8 High school 28.7 32.4 41.1 43.5 More than high school 61.0 49.0 42.9 35.7 Family income ≤100% of FPL 13.5 18.3 18.2 19.2 100–200% of FPL 19.4 29.3 28.8 38.9 ≥200% of FPL 67.0 52.5 53.0 41.9 Married 50.7 47.6 51.1 50.8 Health insurance Medicaid‐Medicare dual coverage 15.4 22.6 20.0 23.3 Medigap coverage 42.1 0.0 41.4 0.0 Comorbidities Acute myocardial infarction 9.4 10.8 11.8 12.5 Congestive heart failure 6.1 6.6 8.2 8.8 Cancer 19.9 19.0 19.5 20.4 Dementia 3.6 4.4 3.0 3.9 Depression 26.1 26.5 25.6 27.9 Diabetes 32.6 37.1 33.1 39.3 Stroke 9.5 10.2 11.1 12.2 Good self‐reported health status 81.0 79.2 77.4 76.0 Functional limitations No functional limitation 57.7 57.1 55.1 54.3 IADLs only 15.4 14.6 16.0 15.4 1–2 ADLs 17.7 18.7 19.2 19.8 3+ ADLs 9.2 9.6 9.7 10.5 BMI Underweight/healthy (<25) 31.8 30.0 28.1 27.4 Overweight (25–30) 35.8 36.7 35.4 33.8 Obese/high‐risk obese (≥30) 32.4 33.3 36.5 38.8 Open in a new tab Note : MA enrollment was defined as having MA coverage for a full year. Rural residence was defined using county‐level 2013 Rural–Urban Continuum Codes developed by the Economic Research Services at the Department of Agriculture. Beneficiaries residing in counties classified as metropolitan areas were categorized as urban and those residing in nonmetropolitan areas were considered as rural. Private health insurance was defined as coverage obtained through an employer or union, purchased individually from a private insurance company (including Medigap), or provided through TRICARE. Survey weights were used to generate nationally representative estimates. Abbreviations: ADL, activities of daily living; BMI, body mass index; FPL, federal poverty level; IADL, instrumental activities of daily living; MA, Medicare Advantage; TM, traditional Medicare. Compared to TM beneficiaries, MA beneficiaries were more likely to be older than 75, identify as non‐Hispanic Black or Hispanic, have Medicaid coverage, and have prescription drug coverage (Table 1 ). MA beneficiaries were less likely to have educational attainment beyond high school, have a family income exceeding 200% of the FPL, and private coverage. However, there were minimal differences in comorbidities, self‐reported good health status, functional limitations, and body mass index. Notably, these patterns were similarly observed in TM and MA beneficiaries across urban and rural areas, but rural beneficiaries were more likely to be non‐Hispanic White and less likely to have educational attainment beyond high school, have a family income exceeding 200% of the FPL. 3.2. Access to care Overall access to care did not differ significantly between TM and MA beneficiaries in urban counties, but financial barriers to care was more prominent among rural beneficiaries, particularly for MA beneficiaries (Figure 1 ). Specifically, there were no significant differences in having a particular place for medical care and experiencing trouble getting needed health care. However, the adjusted proportion of beneficiaries experiencing delayed care due to cost was notably higher in rural areas, especially for MA beneficiaries: 10.0% (95% CI: 8.8–11.1) for MA beneficiaries in rural areas, 9.4% (95% CI: 8.7–10.1) for TM beneficiaries in rural areas, 8.0% (95% CI: 7.5–8.4) for MA beneficiaries in urban areas, and 7.8% (95% CI: 7.5–8.2) for TM beneficiaries in urban areas. The unadjusted and adjusted values for each outcome are presented in Appendix Tables A and B . The interaction terms between MA enrollment and rural residence were not statistically significant in all access to care measures (Appendix Table C ). Full regression results are presented in Appendix Table C . FIGURE 1. Open in a new tab Access to care between Traditional Medicare and Medicare Advantage beneficiaries by rurality, 2017–2021. TM; traditional Medicare, MA; Medicare Advantage. Bars indicate adjusted rates of reporting access to care, and whiskers indicate 95% confidence intervals. Reported results are based on analyses using linear probability models controlling for age, sex, race/ethnicity, education, family income, marital status, health insurance, comorbidities, self‐reported good health status, functional limitations in terms of instrumental activities of daily living and activities of daily living, body mass index, year‐fixed effects as well as MA enrollment, rural residence, and the interaction term of MA enrollment and rural residence. MA enrollment was defined as having MA coverage for a full year. Rural residence was defined using county‐level 2013 Rural–Urban Continuum Codes developed by the Economic Research Services at the Department of Agriculture. From the regression results, we used predictive margins to calculate the mean adjusted values of the outcomes for TM and MA beneficiaries in both urban and rural areas while holding constant all other variables. Survey weights were used to generate nationally representative estimates. 3.3. Financial burden of care While the financial burden of care was generally higher among rural beneficiaries than urban beneficiaries, the highest burden was observed among MA beneficiaries in rural areas (Figure 2 ). Specifically, the adjusted proportion of beneficiaries reporting problems paying medical bills was notably higher in rural areas, especially for MA beneficiaries: 11.4% (95% CI: 10.3–12.5) for MA beneficiaries in rural areas, 9.4% (95% CI: 8.7–10.1) for TM beneficiaries in rural areas, 8.1% (95% CI: 7.7–8.6) for MA beneficiaries in urban areas, and 7.8% (95% CI: 7.5–8.2) for TM beneficiaries in urban areas. Similar patterns were observed in reporting medical bills being paid off over time (6.9% [95% CI: 6.1–7.7] for MA beneficiaries in rural areas, 4.9% [95% CI: 4.4–5.4] for TM beneficiaries in rural areas, 4.0% [95% CI: 3.7–4.4] for MA beneficiaries in urban areas, and 3.7% [95% CI: 3.5–4.0] for TM beneficiaries in urban areas) and reporting contact by a collection agency due to medical bills (5.5% [95% CI: 4.7–6.3] for MA beneficiaries in rural areas, 4.1% [95% CI: 3.6–4.5] for TM beneficiaries in rural areas, 3.53 [95% CI: 3.0–3.6] for MA beneficiaries in urban areas, and 3.4% [95% CI: 3.2–3.7] for TM beneficiaries in urban areas). The interaction terms between MA enrollment and rural residence were statistically significant for all financial burden of care measures (Appendix Table D ). Full regression results are presented in Appendix Table D . FIGURE 2. Open in a new tab Financial burden of care between Traditional Medicare and Medicare Advantage beneficiaries by rurality, 2017–2021. TM; traditional Medicare, MA; Medicare Advantage. Bars indicate adjusted rates of reporting financial burden of care, and whiskers indicate 95% confidence intervals. Reported results are based on analyses using linear probability models controlling for age, sex, race/ethnicity, education, family income, marital status, health insurance, comorbidities, self‐reported good health status, functional limitations in terms of instrumental activities of daily living and activities of daily living, body mass index, year‐fixed effects as well as MA enrollment, rural residence, and the interaction term of MA enrollment and rural residence. MA enrollment was defined as having MA coverage for a full year. Rural residence was defined using county‐level 2013 Rural–Urban Continuum Codes developed by the Economic Research Services at the Department of Agriculture. From the regression results, we used predictive margins to calculate the mean adjusted values of the outcomes for TM and MA beneficiaries in both urban and rural areas while holding constant all other variables. Survey weights were used to generate nationally representative estimates. 3.4. Sensitivity analysis Our adjusted analysis found lower use of preventive services among rural beneficiaries than urban beneficiaries, but there were no significant differences between TM and MA beneficiaries (Appendix Figure A ). Furthermore, health insurance literacy levels appeared similar across all groups (Appendix Figure B ). On the other hand, sensitivity analyses using only year‐fixed effects yielded results similar to those from our original analysis, which included a range of covariates (Appendix Figure C,D ). Furthermore, sensitivity analyses limited to those without Medigap also produced similar results (Appendix Figure E,F ). Finally, beneficiaries with low incomes reported a significantly higher overall financial burden of care, and this result was more pronounced among rural MA beneficiaries (Appendix Figure G ). However, statistical significance was not observed. 3.5. Comparison of MA benefits Several differences were observed in the characteristics of MA plans in urban and rural areas, but the most notable differences were found in financial structures (Table 2 ). Rural and urban beneficiaries had access to an average of 10.2 and 17.7 MA plans, respectively. Compared to MA plans in urban areas, MA plans in rural areas required higher additional premiums ($46 vs. $62), were more likely to charge an additional premium (34.5% vs. 58.2%), but offered lower out‐of‐pocket maximums for in‐network care ($5918 vs. $5439). Compared to MA plans in urban areas, MA plans in rural areas also had higher copayments ($1686 vs. $1724 for a 5‐day hospitalization, $37 vs. $41 for a specialist visit, and $35 vs. $38 for a mental health visit). Furthermore, compared with urban areas, rural areas had a lower proportion of highly rated plans (53.6% and 3.3% for 4–4.5 and 5 stars vs. 44.6% and 1.5% for 4–4.5 and 5 stars). However, there was no conclusive evidence indicating that the provision of supplemental benefits was lower in rural areas than urban areas. Finally, the breadth of primary care provider networks was found to be similar between urban and rural areas. Specifically, 12.3% and 27.8% of MA plans in rural areas covered 10% fewer or 10%–25% of all primary care providers in the areas compared with 14.8% and 26.5% in urban areas. TABLE 2. Characteristics of Medicare Advantage plans by rurality, 2017–2021. Characteristics Urban Rural Average number of MA plans, N 17.7 10.2 Financial performance Additional premium for MA, $ 46 62 % of MA plans without additional premium, % 58.2 34.5 Out‐of‐pocket limit for in‐network, $ 5918 5439 Copay, $ Hospitalization for 5 days 1686 1724 Primary care per visit 9 11 Specialist per visit 37 41 Mental health per visit 35 38 Quality of care based on star rating, % 2–2.5 1.5 1.7 3–3.5 41.4 51.8 4–5 56.9 46.4 Provision of supplemental benefits, % Health education 54.9 47.8 In‐home safety assessment 22.7 18.2 Personal emergency response system 27.0 29.3 Medical nutrition therapy 94.7 95.7 Post discharge in‐home medication reconciliation 9.7 8.7 Readmission prevention 5.4 9.4 Wigs for hair loss related to chemotherapy 64.7 53.2 Weight management programs 8.8 9.7 Alternative therapies 6.8 6.5 Nutritional/dietary benefit 4.7 7.5 Additional sessions of smoking cessation counseling 12.6 12.0 Fitness benefit 7.1 9.0 Enhanced disease management 2.7 3.0 Telemonitoring services 1.5 2.3 Remote access technologies 4.1 4.5 Bathroom safety devices 3.4 3.2 Counseling services 6.1 1.9 % of providers in network ≤10 14.8 12.3 10–25 26.5 27.8 25–40 19.1 16.5 40–60 3.8 5.3 >60 35.7 37.8 Open in a new tab Note : Using the MA landscape data and the Plan Benefit Package data for 2017–2021, unique MA plans were identified based on contract and plan identifiers. The unit of analysis was at the county‐plan‐year level. Rural areas were defined using county‐level 2013 Rural–Urban Continuum Codes developed by the Economic Research Services at the Department of Agriculture. Medicare Advantage plans in counties classified as metropolitan areas were categorized as urban and those in nonmetropolitan areas were considered as rural. Abbreviation: MA, Medicare advantage. 4. DISCUSSION Our nationally representative study reveals a significant disparity in the financial burden of care experienced by rural Medicare beneficiaries. While rural Medicare beneficiaries generally faced greater financial challenges than urban Medicare beneficiaries, the most pronounced burden was observed among rural MA beneficiaries. These findings indicate that affordability of care may be a pressing concern for rural beneficiaries, particularly for MA beneficiaries. Our study builds upon existing research that identifies limited access to care as a major barrier in rural areas. 3 , 10 , 11 However, our findings highlight an additional layer of disparity between urban and rural Medicare beneficiaries that extends beyond access to care. Affordability emerges as a challenge for rural beneficiaries due to several multifaceted issues. 21 As rural beneficiaries often face a challenging combination of lower incomes and higher chronic disease burdens compared with urban beneficiaries, 3 these groups may already confront financial hardships. However, rural areas typically have fewer health care facilities, resulting in long travel distances for rural residents to reach specialists, hospitals, or even basic care providers. 22 , 23 Moreover, public transportation options are often scarce or nonexistent in rural areas, leading residents to rely on personal vehicles, which can incur significant expenses for gas and maintenance. These factors may exacerbate the financial hardships faced by rural beneficiaries. Our study pinpointed that rural MA beneficiaries experienced the most significant financial burden. This finding is particularly concerning as substantial growth in MA enrollment has been driven by a combination of rural beneficiaries and socially disadvantaged populations. 2 , 24 , 25 , 26 This trend is likely attributable in part to the perception of MA as a more affordable health insurance coverage option than TM. 27 Indeed, MA plans impose out‐of‐pocket cost limits and offer extra benefits compared with TM. 4 Also, a recent survey found that one in five MA enrollees cited a limit on out‐of‐pocket spending as the main reason for choosing an MA plan. 27 However, there is no evidence that MA enrollment was associated with any substantial decrease in the financial burden of care. 28 , 29 This suggests that despite the increased availability of and enrollment in MA plans, there are persistent disparities in financial barriers that disproportionately impact MA beneficiaries in rural areas. Our study identified specific mechanisms contributing to the higher financial burden of care among rural MA beneficiaries. We found evidence suggesting that rural MA plans offer less generous benefits compared with urban plans, resulting in higher deductibles, co‐pays, or coinsurance requirements. This finding aligns with prior research indicating that MA beneficiaries in rural areas were more likely to pay an additional premium (beyond Medicare Parts A and B) to obtain MA coverage compared with MA beneficiaries in urban areas. 30 These higher upfront costs act as a financial barrier for rural beneficiaries, potentially leading to delayed or avoided care. Moreover, it is plausible that rural MA plans have narrower provider networks. While our study did not detect disparities in the breadth of primary care provider networks, prior research suggests that rural areas suffer from even more restrictive networks compared with urban areas, particularly for specialists such as cardiologist, endocrinologist, and rheumatologist. 13 , 14 This could force rural beneficiaries to either incur higher costs by utilizing out‐of‐network providers or travel longer distances to access in‐network specialists, further exacerbating the financial strain. Our study underscores the need for policymakers to address the financial burden of care among Medicare beneficiaries in rural areas, particularly for MA beneficiaries. While limited access to care remains a significant barrier in rural areas, our findings emphasize affordability as a critical obstacle, calling for a multifaceted approach. 31 Specifically, rural MA beneficiaries often face higher premiums, but these additional costs do not necessarily translate into improved benefits for rural MA beneficiaries. Further, prior evidence suggests that the average Medicare payment rate to urban and rural MA plans within the same regions are similar and rural MA plan availability in rural areas is robust, with rural enrollees able to select from an average of 27 MA plans. 32 Therefore, the mechanisms why rural MA plans have less generous benefits than urban plans despite similar payment rates and robust insurer participation in the rural MA market deserve further investigation. 4.1. Limitations Our study has several limitations. First, we controlled for various potential confounders, but the possibility of unobserved characteristics remains a concern. Furthermore, the MCBS Public Use Files provide limited information, preventing us from including more detailed categories such as specific income levels or types of health insurance, which might have provided further insight into the findings. Second, we considered the MA program as a whole, but substantial variation exists across MA plans in terms of benefit generosity. However, due to limited data availability, we were unable to fully investigate these variations and their potential consequences. Third, understanding the specific mechanisms underlying the observed associations remains a key question. To address this, we analyzed plan‐level data. However, as the publicly available MCBS does not provide plan‐level information, we could not link the individual‐level data to the plan‐level data. Fourth, we limited our sample to Medicare beneficiaries with full‐year enrollment in either MA or TM, and thus our findings may not be applicable to those with partial‐year enrollment. Of note, beneficiaries without dual Medicaid coverage are typically locked into their choice of MA plan during the calendar year. Fifth, we relied on survey data, which may introduce self‐reporting error and bias into our findings. For example, we assessed the financial burden of care using subjective measures, but objective measures such as out‐of‐pocket spending could not be evaluated due to limited data availability. Sixth, we evaluated a limited domain of MA plan benefits due to limited data availability. For example, cost‐sharing was assessed for only four types of services. The PBP data provide service‐specific values, but generating a single aggregate estimate is challenging due to the complexity of the data. Thus, we reported copayments for specific services, which are more comparable based on prior studies. Therefore, further research is warranted to determine if these findings are applicable to other domains. Finally, we used MCBS data collected during the COVID‐19 pandemic in 2020, which may have influenced responses. However, prior research has indicated that these impacts were minimal. 33 5. CONCLUSION Rural Medicare beneficiaries reported a greater financial burden of care than urban Medicare beneficiaries, but the most significant burden was observed among MA beneficiaries in rural areas. One potential mechanism is the less generous financial structures of rural MA plans. Additionally, even with similar benefit packages and network sizes, the restrictive nature of networks and utilization management could further exacerbate financial burdens in rural areas as rural beneficiaries might face higher out‐of‐pocket costs due to more frequent out‐of‐network care or longer travel distances to access covered services. Understanding these mechanisms is crucial for developing effective policies and interventions to ensure affordable access to care regardless of location. These findings highlight the need for policy interventions that specifically address the disproportionate financial burden faced by rural MA beneficiaries. CONFLICT OF INTEREST STATEMENT The author declares no conflicts of interest. Supporting information Appendix Table A. Unadjusted outcomes between TM and MA enrollees by rurality, 2017–2021 MCBS. Appendix Table B. Adjusted outcomes between TM and MA enrollees by rurality, 2017–2021 MCBS. Appendix Table C. Regression results for access to care, 2017–2021 MCBS. Appendix Table D. Regression results for financial burden of care, 2017–2021 MCBS. Appendix Figure A. Use of preventive services between TM and MA enrollees by rurality, 2017–2021 MCBS. Appendix Figure B. Health insurance literacy between TM and MA enrollees by rurality, 2017–2021 MCBS. Appendix Figure C. Access to care between TM and MA enrollees by rurality (adjusting for year‐fixed effects only), 2017–2021. Appendix Figure D. Financial burden of care between TM and MA enrollees by rurality (adjusting for year‐fixed effects only), 2017–2021. Appendix Figure E. Access to care between TM and MA enrollees by rurality (after excluding those with Medigap), 2017–2021. Appendix Figure F. Financial burden of care between TM and MA enrollees by rurality (after excluding those with Medigap), 2017–2021. Appendix Figure G. Financial burden of care between TM and MA enrollees by rurality among low‐income Medicare beneficiaries, 2017–2021. HESR-60-0-s001.docx (695.6KB, docx) ACKNOWLEDGMENTS The authors have nothing to report. Park S, Meyers DJ, Park Y, Trivedi AN. Financial burden of care greatest among rural beneficiaries in Medicare advantage. Health Serv Res. 2025;60(3):e14393. doi: 10.1111/1475-6773.14393 REFERENCES 1. Ochieng N, Biniek JF, Freed M, Damico A, Neuman T. Medicare Advantage in 2023: Enrollment Update and Key Trends. 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Regression results for financial burden of care, 2017–2021 MCBS. Appendix Figure A. Use of preventive services between TM and MA enrollees by rurality, 2017–2021 MCBS. Appendix Figure B. Health insurance literacy between TM and MA enrollees by rurality, 2017–2021 MCBS. Appendix Figure C. Access to care between TM and MA enrollees by rurality (adjusting for year‐fixed effects only), 2017–2021. Appendix Figure D. Financial burden of care between TM and MA enrollees by rurality (adjusting for year‐fixed effects only), 2017–2021. Appendix Figure E. Access to care between TM and MA enrollees by rurality (after excluding those with Medigap), 2017–2021. Appendix Figure F. Financial burden of care between TM and MA enrollees by rurality (after excluding those with Medigap), 2017–2021. Appendix Figure G. Financial burden of care between TM and MA enrollees by rurality among low‐income Medicare beneficiaries, 2017–2021. 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