Racial/Ethnic Disparities in Cost-Related Barriers to Care Among Near-Poor Beneficiaries in Medicare Advantage vs Traditional Medicare

ABSTRACT

Objective: To compare racial and ethnic disparities in cost-related medical care and dental care barriers and use of vision care among near-poor Medicare beneficiaries in Medicare Advantage (MA) vs traditional Medicare (TM) overall and stratified by supplemental insurance enrollment.

Study Design: Cross-sectional analysis of 2015-2019 data from the nationally representative Medicare Current Beneficiary Survey.

Methods: Propensity score–weighted difference-in-disparities analyses comparing Black-White and Hispanic-White disparities in MA vs TM among near-poor Medicare beneficiaries with incomes between 101% and 250% of the federal poverty level. We assessed differences in cost-related medical care barriers and cost-related dental care barriers as well as receipt of annual eye exams in MA vs TM.

Results: For cost-related barriers to medical care, Hispanic-White disparities were narrower by 8.8 (95% CI, –14.0 to –3.6) percentage points in MA relative to TM but differences in Black-White disparities were not statistically significant. MA was not associated with narrower differences in Hispanic-White or Black-White disparities in dental care access. Higher proportions of Black and Hispanic beneficiaries in MA received an annual eye exam vs White beneficiaries in both MA and TM. MA was associated with narrower racial disparities primarily compared with TM without supplemental insurance.

Conclusions: Among near-poor Black and Hispanic Medicare beneficiaries, MA was associated with greater use of vision care and narrowing of some disparities in cost-related access barriers vs TM. However, MA did not uniformly narrow racial/ethnic disparities in access and use. These findings highlight the importance of maintaining and enhancing features of Medicare coverage that may promote equitable access to care, including additional benefits and lower cost sharing.

Am J Manag Care. 2024;30(10):e297-e304. https://doi.org/10.37765/ajmc.2024.89622

Takeaway Points

This study examined whether Medicare Advantage (MA)—the private alternative to traditional Medicare (TM)—was associated with narrower racial/ethnic disparities in access to and use of medical, dental, and vision care among near-poor Medicare beneficiaries.

• MA was associated with narrower Hispanic-White disparities but not narrower Black-White disparities in cost-related barriers to medical care vs TM without supplemental insurance.
• MA promoted greater vision care use among Black and Hispanic beneficiaries but was not associated with narrower disparities in dental care access.
• This study adds to the literature by focusing on near-poor beneficiaries who face financial constraints accessing care and often lack supplemental insurance in TM.

Black and Hispanic Medicare beneficiaries have a higher disease burden than non-Hispanic White beneficiaries and are simultaneously more likely to report difficulty obtaining health care due to cost concerns.^1-4 These disparities in health status and access have prompted renewed focus on efforts to advance health care equity by CMS.⁵

Enrollment in different types of primary and supplemental Medicare coverage may directly affect health care access and use.^6,7 Medicare beneficiaries elect to receive primary insurance through private Medicare Advantage (MA) plans or the federally administered traditional Medicare (TM) program. In TM, enrollees have access to a largely unrestricted network of clinicians and hospitals but can face high cost sharing (eg, 20% coinsurance for outpatient services) without an annual out-of-pocket limit. TM also does not cover services such as dental and vision care. Conversely, MA plans have lower cost sharing and a cap on annual out-of-pocket costs and often cover supplemental benefits, such as dental and vision services, with no additional premium.^8,9 Unlike TM, MA plans may have narrow clinician and hospital networks and employ utilization management tools such as prior authorization that could limit access to care.^10,11 In addition, beneficiaries may obtain supplemental insurance through Medicaid or private sources (eg, Medigap or employer-based plans) to fill gaps in Medicare coverage and pay for cost sharing. However, enrollment in supplemental insurance varies widely by income, race, and ethnicity.^12,13

Coverage differences may be particularly important for Black and Hispanic beneficiaries with low to moderate incomes. Approximately 30% of beneficiaries overall and 40% of Black or Hispanic beneficiaries are near poor, with incomes between 101% and 250% of the federal poverty level (FPL).¹⁴ Near-poor individuals have incomes above the limit for Medicaid supplemental insurance that pays for Medicare cost sharing (100% of the FPL) and often have difficulty affording care. Recent research shows that exceeding the income limit for Medicaid was associated with larger racial and ethnic health care disparities among near-poor Medicare beneficiaries, in part because Black and Hispanic beneficiaries were less likely than White beneficiaries to have sufficient savings or supplemental insurance to pay for care.⁷ For this near-poor population, MA’s lower cost sharing and coverage of additional benefits may mitigate access barriers disproportionately experienced by Black and Hispanic beneficiaries.

MA enrollment increased substantially over the past decade, particularly among Black and Hispanic individuals, who often select MA in part because of its lower cost sharing and additional benefits.^15,16 Several studies examined whether MA compared with TM is associated with reduced racial and ethnic disparities in care access and use.^4,6,17-19 However, these studies included individuals at all income levels rather than focusing on near-poor individuals, and many did not examine dental and vision care. Such services are crucial not only for oral health and eyesight but also for maintaining cognition and overall health.^20-24

Understanding whether MA promotes equitable access to care is important amid increased scrutiny of its per-enrollee costs to the federal government, which exceed those in TM.²⁵ Therefore, we examined whether enrollment in MA was associated with narrower racial and ethnic disparities in cost-related medical care barriers and cost-related dental care barriers as well as receipt of eye exams among near-poor Medicare beneficiaries. We further examined the extent to which racial and ethnic disparities were narrower among MA enrollees than TM enrollees who did and did not have private supplemental insurance.

METHODS

Data

We analyzed the Medicare Current Beneficiary Survey (MCBS), pooling data from the 2015-2019 surveys. The MCBS is a nationally representative survey of the Medicare population that collects information on respondent-reported sociodemographic characteristics, health status, and access to care.¹⁴ The MCBS uses a rotating panel design, following each respondent for up to 4 years. We analyzed restricted-use files that included linked administrative Medicare and Medicaid enrollment records. This study was approved by the University of Pittsburgh Institutional Review Board.

Population

We included community-dwelling MCBS respondents with incomes from 101% to 250% of the FPL. We included annual survey data for individuals whose income was within this range for at least 1 survey year (eAppendix Table 1 [eAppendix available at ajmc.com]).

We excluded beneficiaries with incomes equal to or below 100% of the FPL because these individuals may qualify for full Medicaid or partial Medicaid via the Qualified Medicare Beneficiary (QMB) program, both of which cover out-of-pocket costs in Medicare. Some beneficiaries with incomes greater than 100% of the FPL may receive Medicaid due to state differences in Medicaid eligibility rules or alternative eligibility pathways (eg, spend-down pathways for individuals with high medical expenses).²⁶ Therefore, we excluded beneficiaries who were enrolled in full Medicaid or in partial Medicaid via QMB in any survey year. Analyses also excluded beneficiaries living in US territories (eg, Puerto Rico) because of differences in health care systems in these jurisdictions vs mainland US.

Race and Ethnicity

We used respondent-reported race and ethnicity to define racial and ethnic groups. Our sample included respondents who identified their ethnicity as Hispanic or their race as Black/African American or White. We categorized respondents into 3 groups: Hispanic, non-Hispanic White, and non-Hispanic Black. Samples of other groups were too small to independently examine differences between MA and TM.

Medicare Coverage

For our primary analyses, we categorized beneficiaries in each year as enrolled in MA or TM based on monthly administrative enrollment variables in the MCBS. Because Medicare beneficiaries who do not have Medicaid may only switch plans during certain times of the year (ie, during the annual open enrollment period), we used January enrollment data to categorize coverage for the full year.

Outcome Variables

We examined 3 respondent-reported outcomes. First, we assessed whether respondents reported cost-related barriers to medical care in the past year (further defined in eAppendix Table 2). Second, we assessed whether respondents reported being unable to access needed dental care due to cost in the past year. The dental care question was introduced in 2016 and analyzed for 2016 to 2019. Third, we assessed whether respondents reported receiving an eye exam in the past year because most MA plans cover vision services that would otherwise require enrollees to pay out of pocket.^25,27 Individuals who did not respond to one of these questions or indicated that they did not know were excluded from analyses of that outcome (eAppendix Figure and eAppendix Table 3).

Covariates

We used the MCBS to assess respondent-reported age, sex, education, marital status, difficulties with activities of daily living and instrumental activities of daily living, and presence of chronic conditions. We used administrative data linked to the MCBS to identify respondents’ original reason for Medicare entitlement (age, disability, or end-stage renal disease). Finally, we linked the Area Health Resources File to MCBS respondents at the county level to identify residents of rural counties and assess the county-level supplies of physicians, dentists, and optometrists per 1000 residents.

Propensity Score Weighting

We used propensity score weighting to balance the samples of MA and TM enrollees on measured demographic and health characteristics. Specifically, we estimated a separate propensity score model for each racial and ethnic group that predicted MA enrollment as a function of the covariates previously described. These covariates were measured comparably for MA and TM enrollees because they are reported by MCBS respondents rather than measured from administrative data. We constructed the average treatment effect on treated weights to weight TM enrollees to resemble MA enrollees within each racial and ethnic group. We incorporated survey weights by multiplying propensity score weights by MCBS survey weights to produce estimates that were representative of the Medicare population.

Statistical Analysis

We conducted a difference-in-disparities analysis to compare Black-White and Hispanic-White disparities between MA and TM. We fit a respondent-year–level linear regression model that predicted each outcome as a function of Medicare coverage type, race and ethnicity, and the interactions between these terms, controlling for respondent- and area-level covariates and year fixed effects. This model tested for Black-White and Hispanic-White disparities within TM and within MA and for the difference in disparities between MA and TM. Difference-in-disparities estimates represent the degree to which MA is associated with greater or lesser disparities relative to TM. All estimates were weighted using a composite of propensity score and survey weights to produce nationally representative estimates. To account for repeated observations for the same respondent, SEs were clustered at the respondent level.

Because disparities may vary by both primary and supplemental coverage, we also compared differences in disparities between MA and TM with private supplemental insurance and without private supplemental insurance. Private supplemental coverage was self-reported by respondents and included employer-sponsored, retiree, and self-purchased (ie, Medigap) plans. We analyzed MA as a single category because MA enrollees are not allowed to purchase Medigap plans and relatively few have employer-sponsored or retiree supplemental coverage.¹³ We reestimated (within race/ethnicity) propensity score models to separately weight TM enrollees who did and did not have supplemental coverage to resemble MA enrollees.

Supplementary Analyses

We conducted 2 supplementary analyses. First, to control for regional differences in care patterns, we additionally adjusted for hospital referral regions (HRRs) identified based on respondents’ zip codes. Second, because eye exams are necessary screening exams for people with diabetes and CMS measures the receipt of eye exams among people with diabetes as a component of MA plan Star Ratings,²⁸ we analyzed use of vision care among near-poor Medicare beneficiaries with diabetes.

RESULTS

Our sample included 26,103 respondent-year observations, which represented 20,832,659 weighted person-years in the community-dwelling Medicare population. This sample included 21,535 non-Hispanic White respondent-years (17,063,806 weighted person-years); 2611 non-Hispanic Black respondent-years (2,306,499 weighted person-years); and 1957 Hispanic respondent-years (1,462,354 weighted person-years) (Table 1). In the survey-weighted population, 35.7% of non-Hispanic White beneficiaries, 45.3% of non-Hispanic Black beneficiaries, and 56.2% of Hispanic beneficiaries were enrolled in MA plans (eAppendix Table 4).

Within all racial and ethnic groups, MA enrollees were generally older, had less education, and were less likely to reside in a rural county than TM enrollees (Table 1). Among Black and Hispanic beneficiaries, a smaller proportion of those in MA vs TM qualified for Medicare due to disability. Propensity score weighting reduced differences between MA and TM enrollees in each racial and ethnic group (eAppendix Table 5).

Adjusted Differences in Disparities Between MA and TM

Cost-related barriers to medical care. In TM, 19.1% of Hispanic enrollees and 12.5% of White enrollees reported cost-related barriers to medical care (Figure 1), representing a Hispanic-White disparity of 6.6 (95% CI, 2.3-10.9; P < .01) percentage points (pp) (Table 2). Conversely, in MA, 12.2% of Hispanic enrollees and 14.4% of White enrollees reported cost barriers—a difference of 2.2 (95% CI, –5.3 to 0.8; P = .15) pp, which was not statistically significant. Thus, enrollment in MA relative to TM was associated with an 8.8 (95% CI, –14.0 to –3.6; P < .01) pp narrower Hispanic-White disparity in cost-related medical care barriers.

Higher proportions of Black beneficiaries reported cost-related medical care barriers (15.5% in TM and 15.9% in MA) than did White beneficiaries (12.5% in TM and 14.4% in MA) (Figure 1). However, these Black-White disparities were not statistically significant within MA or TM (Table 2). Black-White disparities in reporting cost barriers also did not differ significantly between MA and TM.

Cost-related barriers to dental care. Within TM, 16.6% of Hispanic enrollees, 14.4% of Black enrollees, and 10.7% of White enrollees reported cost-related barriers to dental care (Figure 1), representing a 5.9 (95% CI, 0.5-11.2; P = .03) pp Hispanic-White disparity (Table 2) and a 3.7 (95% CI, –0.9 to 8.2; P = .12) pp Black-White disparity. Within MA, 11.7% of Hispanic enrollees, 13.8% of Black enrollees, and 10.2% of White enrollees reported cost-related barriers to dental care, representing a 1.5 (95% CI, –2.0 to 5.1; P = .38) pp Hispanic-White disparity and a 3.6 (95% CI, 0.3-7.0; P =.03) pp Black-White disparity. Neither Black-White nor Hispanic-White disparities in cost-related dental care barriers differed significantly between MA and TM.

Receipt of eye exams. In TM, 53.5% of Hispanic enrollees, 55.3% of Black enrollees, and 55.7% of White enrollees reported receiving an eye exam in the past year (Figure 1). Within MA, 58.9% of Hispanic enrollees, 60.9% of Black enrollees, and 54.5% of White enrollees reported receiving an annual eye exam. Thus, Black and Hispanic enrollees in MA were more likely to have had an eye exam than White enrollees in MA (Table 2). The difference-in-disparities estimates indicate greater use of vision care among Black vs White (6.8 pp; 95% CI, 0.8-12.7; P = .03) and Hispanic vs White (6.6 pp; 95% CI, –0.2 to 13.3; P = .06) enrollees in MA compared with TM.

Differences by Supplemental Coverage

Near-poor beneficiaries in TM without supplemental coverage were most likely to report cost-related barriers to medical care and least likely to report receipt of an eye exam compared with those in MA or TM with supplemental coverage (Figure 2; eAppendix Table 6). Hispanic-White disparities in reporting cost-related medical care barriers were narrower by 9.7 (95% CI, –17.5 to –1.9; P = .02) pp in MA vs TM without supplemental insurance (eAppendix Table 7) and by 4.9 (95% CI, –10.2 to 0.3; P = .07) pp in MA vs TM with supplemental insurance. MA was associated with a higher rate of annual eye exams among Black and Hispanic vs White enrollees compared with TM without supplemental coverage but not TM with supplemental coverage. Conversely, MA was associated with narrower Hispanic-White disparities in cost-related dental care barriers vs TM with supplemental coverage (–8.7 pp; 95% CI, –16.5 to –1.0; P = .03) but not TM without supplemental coverage. Black-White disparities for cost-related medical care barriers and cost-related dental care barriers were not significantly different in comparisons of MA vs TM with or without supplemental coverage.

Supplementary Analyses

Findings were similar in models that additionally adjusted for HRR fixed effects (eAppendix Table 8). Among beneficiaries with diabetes, Black and Hispanic MA enrollees were significantly more likely to receive an eye exam than White MA enrollees (eAppendix Table 9).

DISCUSSION

This nationally representative study found that among near-poor Medicare beneficiaries, enrollment in MA vs TM was associated with narrower disparities in cost-related care barriers (for medical care and dental care) among Hispanic beneficiaries compared with White beneficiaries but not among Black beneficiaries compared with White beneficiaries. Black and Hispanic enrollees in MA were also more likely to receive annual eye exams than White enrollees in MA and TM. However, Black beneficiaries were more likely to report cost-related medical and dental care barriers than White beneficiaries in both MA and TM. These findings suggest that enrollment in MA reduces racial and ethnic disparities in health care access among Medicare beneficiaries with limited incomes across some, but not all, cost-related access measures.

Our results extend prior research that compared racial and ethnic health care disparities between MA and TM. For example, an analysis by Gangopadhyaya et al, which included Medicare beneficiaries at all income levels, found that for the probability of experiencing cost-related barriers to care, MA was associated with narrower Hispanic-White disparities but not narrower Black-White disparities.¹⁸ Other studies found that MA lessened racial and ethnic disparities in primary care access and use of preventive services (eg, breast cancer screening)¹⁹ but reported mixed findings for disparities in hospitalization-related outcomes (eg, readmissions).^17,29-31 Findings from several studies attributed narrower disparities in MA, in part, to worse access in MA vs TM among White beneficiaries rather than better access among Black or Hispanic beneficiaries.^4,18 However, we found that White beneficiaries reported similar rates of cost-related access barriers in MA and TM and that Hispanic beneficiaries in MA were less likely to report cost-related barriers.

This study’s findings underscore the importance of both primary and supplemental insurance in moderating health care disparities within Medicare. We found that MA was associated with narrower Hispanic-White disparities in the probability of having cost-related medical care barriers, especially compared with TM without supplemental insurance. This is consistent with evidence that gaps in supplemental insurance exacerbate cost-related access barriers, particularly among Medicare beneficiaries of color.^6,7 Lower cost sharing in MA, especially vs TM without supplemental insurance, could mitigate cost-related access barriers disproportionately experienced by Black and Hispanic beneficiaries.

Findings from this study also highlight the importance of benefit design differences between TM and MA, including coverage of vision and dental services offered by many MA plans. Because these services are not covered by TM, enrollees in TM must either obtain supplemental insurance or fully pay for these services out of pocket, which may be financially prohibitive for individuals with lower incomes. Our findings suggest that MA improves Black and Hispanic beneficiaries’ access to services that many MA plans cover as supplemental benefits—notably, vision care. However, the extent to which MA narrowed access barriers for people of color was not uniform across the outcomes examined. For example, Black Medicare beneficiaries were more likely to report cost-related dental care barriers compared with White beneficiaries in both MA and TM.

Although our results show some benefits of the MA program for Black and Hispanic individuals with lower incomes, they also highlight a need for ongoing efforts to reduce inequities in health care access and use. Ongoing Medicare initiatives³² to measure and evaluate equitable care could help policy makers and plans address both financial and nonfinancial (eg, transportation) access barriers that disproportionately affect populations of color.³³ In addition, policy makers have opportunities to promote equitable care through reforms to MA payment policy. Payments to MA plans have drawn scrutiny in recent years, partly because of policies that raise MA payments above spending levels in traditional Medicare in some markets.³⁴ Although some MA plans contend that higher payments enable them to finance supplemental benefits and offer lower cost sharing, empirical evidence suggests that policies to curb MA spending would likely have a small impact on coverage generosity.^35,36 Addressing policies known to contribute to artificially high payments to some MA plans, coupled with incentives for investment in services and cost-sharing protections that enhance equitable access to care, could help balance fiscal and equity goals in MA payment policy.

Finally, MA may not be the only vehicle for lowering cost sharing and covering additional health benefits in Medicare. For example, policy makers recently proposed adding coverage of vision and dental care to TM.^37,38 Although these efforts have stalled, there remains an opportunity to understand how other programwide Medicare reforms, not limited to MA, affect equitable access to care. For example, the Inflation Reduction Act of 2022 will introduce a new cap on drug out-of-pocket prescription spending in Medicare Part D beginning in 2025.³⁹ Evaluating whether this cap lessens racial and ethnic disparities in cost-related barriers to medication use could provide evidence to guide how policy makers approach future Medicare programwide reforms to advance health care equity.

Limitations

Our study had several limitations. First, unobserved factors could confound relationships between coverage type and study outcomes. For example, beneficiaries’ decisions to select MA vs TM coverage may be related to preferences for lower cost sharing for vision and dental services. To the extent that these factors are unmeasured, they limit our ability to attribute study findings to differences in plan design.⁴⁰ We attempted to mitigate selection effects between MA and TM by controlling for a broad set of observed demographic and socioeconomic characteristics using propensity score weighting and covariate adjustment. Second, county-level variation in MA plan design and availability may also confound our outcomes. Our results were consistent when adjusting for HRR fixed effects, but fixed effects for smaller geographic areas were not feasible to estimate given the MCBS sampling frame. Third, small sample sizes for Black and Hispanic beneficiaries limited our ability to precisely estimate disparities, particularly in analyses examining differences by supplemental coverage. Relatedly, we were unable to examine outcomes in racial and ethnic groups with smaller representation in our sample.

Further work is needed to examine disparities in access to other services that MA plans may offer as supplemental benefits, such as meals, transportation, and newer Special Supplemental Benefits for the Chronically Ill.²⁹ Similarly, MA plan attributes (eg, provider networks) may influence the extent to which MA narrows or widens disparities in access and use of care relative to TM. Future research could focus on characterizing heterogeneity across MA plans to help identify plan attributes that may be most important for advancing health care equity.

CONCLUSIONS

In this nationally representative study of near-poor Medicare beneficiaries, we found that enrollment in MA compared with TM was associated with narrower Hispanic-White disparities in reporting cost-related barriers to medical care and that Black and Hispanic beneficiaries in MA were more likely to receive an eye exam than White beneficiaries in either MA or TM. However, Black beneficiaries in MA or TM were more likely than White beneficiaries to report cost-related barriers to medical care and to dental care. Our mixed findings suggest the need for greater monitoring of and emphasis on equitable access to care in future Medicare reforms. 

Author Affiliations: University of Pittsburgh School of Public Health (AGH), Pittsburgh, PA; Department of Internal Medicine, Division of General Medicine, University of Michigan (RT, JZA, JTK), Ann Arbor, MI; Institute for Healthcare Policy and Innovation, University of Michigan (RT, JZA, ES), Ann Arbor, MI; Department of Medicine, Division of General Internal Medicine, University of Pittsburgh School of Medicine (GES), Pittsburgh, PA; Department of Health Management and Policy, University of Michigan School of Public Health (JZA, JTK), Ann Arbor, MI; VA Center for Clinical Management Research, VA Ann Arbor Healthcare System (JTK), Ann Arbor, MI; University of Pennsylvania Perelman School of Medicine (ETR), Philadelphia, PA.

Source of Funding: This research was supported by the National Institute on Aging (NIA) of the National Institutes of Health (grant R01AG076437).

Author Disclosures: Dr Hames reports an internship with Humana Healthcare Research. Dr Tipirneni reports funding received in the past year from the NIA, National Institute of Allergy and Infectious Diseases, Blue Cross Blue Shield of Michigan, National Institute on Minority Health and Health Disparities, Michigan Department of Health and Human Services, The Commonwealth Fund, and Agency for Healthcare Research and Quality. Dr Ayanian represented the University of Michigan on the board of Physicians Health Plan without additional compensation. Dr Roberts reports funding from the NIA of the National Institutes of Health. 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 (AGH, RT, GES, JZA, ETR); acquisition of data (ETR); analysis and interpretation of data (AGH, RT, GES, JZA, JTK, ES, ETR); drafting of the manuscript (AGH, RT, ETR); critical revision of the manuscript for important intellectual content (AGH, RT, GES, JZA, JTK, ES, ETR); statistical analysis (AGH, ETR); obtaining funding (RT, ETR); administrative, technical, or logistic support (ES); and supervision (RT, JTK, ETR).

Address Correspondence to: Alexandra G. Hames, PhD, University of Pittsburgh School of Public Health, 130 De Soto St, Pittsburgh, PA 15261. Email: alexandra.hames@pitt.edu.

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