Rates of Disenrollment From Medicare Advantage Plans Are Higher for Racial/Ethnic Minority Beneficiaries

Abstract

Background: Each year, about 10% of Medicare Advantage (MA) enrollees voluntarily switch to another MA contract, while another 2% voluntarily switch from MA to fee-for-service Medicare. Voluntary disenrollment from MA plans is related to beneficiaries’ negative experiences with their plan, disrupts the continuity of care, and conflicts with goals to reduce Medicare costs. Little is known about racial/ethnic disparities in voluntary disenrollment from MA plans. Objective: The objective of this study was to investigate differences in rates of voluntary disenrollment from MA plans by race/ethnicity. Subjects: A total of 116,770,319 beneficiaries enrolled in 736 MA plans in 2015. Methods: Differences in rates of disenrollment across racial/ethnic groups [Asian or Pacific Islander (API), Black, Hispanic, and White] were summarized using 4 types of logistic regression models: adjusted and unadjusted models estimating overall differences and adjusted and unadjusted models estimating within-plan differences. Unadjusted overall models included only racial/ethnic group probabilities as predictors. Adjusted overall models added age, sex, dual eligibility, disability, and state of residence as control variables. Between-plan differences were estimated by subtracting within-plan differences from overall differences. Results: Adjusted rates of disenrollment were significantly (P<0.001) higher for Hispanic (+1.2 percentage points), Black (+1.2 percentage points), and API beneficiaries (+2.4 percentage points) than for Whites. Within states, all 3 racial/ethnic minority groups tended to be concentrated in higher disenrollment plans. Within plans, API beneficiaries voluntarily disenrolled considerably more often than otherwise similar White beneficiaries. Conclusion: These findings suggest the need to address cost, information, and other factors that may create barriers to racial/ethnic minority beneficiaries’ enrollment in plans with lower overall disenrollment rates.

Trends in Cumulative Disenrollment in the Medicare Advantage Program, 2011-2020

“…The levels of disenrollment that we measured are larger than in previous studies that only focused on 1-year disenrollment . On one hand, these levels of disenrollment may be indicative of a healthy MA marketplace, with beneficiaries freely choosing contracts and making different elections if better choices become available.…”

“…A key feature of MA is that beneficiaries may choose from a wide variety of plans in their markets and may change their enrollment on an annual basis. Prior work has found that annual disenrollment rates from MA plans are higher for beneficiaries with greater health needs . However, little is known about disenrollment over a longer term.…”

“…Prior work has found that annual disenrollment rates from MA plans are higher for beneficiaries with greater health needs. 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 However, little is known about disenrollment over a longer term. While disenrollment reflects beneficiaries’ preferences, churn of beneficiaries into and out of contracts reduces plans’ incentives to invest in longer-term interventions to improve population health since beneficiaries may no longer be enrolled in the plan or may even be enrolled with a competing MA insurer.…”

Estimates of diagnosed dementia prevalence and incidence among diverse beneficiaries in traditional Medicare and Medicare Advantage

“…Second, controls for observable differences between the beneficiaries in MA and TM does not account for differences in the patient populations that may be unobserved and related to dementia diagnosis. Third, beneficiaries in MA plans may switch to TM, with higher rates of switching for racial and ethnic minority groups 17 . We quantified dementia prevalence and incidence by race and ethnicity for beneficiaries in MA 2017 and did not restrict them to MA in 2018.…”

Evaluating equitable care in the ICU: Creating a causal inference framework to assess the impact of life-sustaining interventions across racial and ethnic groups

“…Conducting randomized controlled trials (RCTs) to understand how life-sustaining interventions might lead to different outcomes across racial and ethnic groups is both unethical and impracticable. These types of research questions are best answered using observational data, but there are limitations to databases such as claims registries, which often lack important clinical details 10,11 . With the development of high-resolution datasets such as MIMIC-IV, we can apply a causal inference framework to leverage this real-world data in understanding how different patients have been affected by different interventions 12 .…”