PURPOSE Medicaid expansion was designed to increase access to health care. Evidence is mixed, but theory and empirical data suggest that lower cost of care through greater access to insurance increases health care utilization and possibly improves the health of poor and sick populations. However, this major health policy has yet to be thoroughly investigated for its effect on health disparities. The current study is motivated by one of today’s most stark inequalities: the disparity in breast cancer mortality rates between Black and White women. METHODS This analysis used a difference-in-difference fixed effects regression model to evaluate the impact of Medicaid expansion on the disparity between Black and White breast cancer mortality rates. State-level breast cancer mortality data were obtained from the Centers for Disease Control and Prevention. Each state’s Medicaid expansion status was provided by a Kaiser Family Foundation white paper. Two tests were conducted, one compared all expanding states with all nonexpanding states, and the second compared all expanding states with nonexpanding states that voted to expand—but did not by 2014. The difference-in-difference regression models considered the year 2014 a washout period and compared 2012 and 2013 (pretreatment) with 2015 and 2016 (posttreatment). RESULTS Medicaid expansion did not lower the disparity in breast cancer mortality. In contrast to expectations, the Black/White mortality ratio increased in states expanding Medicaid for all Medicaid-eligible age groups, with significant effects in younger age groups ( P = .01 to .15). CONCLUSION These results suggest that states cannot solely rely on access to insurance to alleviate disparities in cancer or other chronic conditions. More exploration of the impacts of low-quality health systems is warranted.

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BackgroundOver a decade of evidence supports the claim that increased access to insurance through Medicaid expansions improves early detection of cancer. Yet, evidence linking Medicaid expansions to early detection of head and neck cancers (HNC) of the oral cavity and pharynx, specifically, may be limited by the lack of attention to Human Papillomavirus (HPV) etiology, generosity of dental coverage, and valid inference analyzing state cancer registry data.AimsThis study reexamined the effect of Medicaid expansion on early detection of HPV+/− HNC in states offering extensive dental benefits.Materials and MethodsSpecialized data from the Surveillance, Epidemiology, and End Results (SEER) program was analyzed to account for, previously unmeasurable, differential detection patterns of HNCs associated with HPV. Then, to identify the effect of increasing Medicaid eligibility on staging patterns in states offering extensive benefits amidst potentially non‐common trends between states, a “Triple Differences” design identifies the differential effect of Medicaid Expansion (with dental coverage) on HPV‐negative HNCs relative to the change in HPV‐positive HNCs. For valid inference analyzing a small number of state clusters (12) in cancer registry data, each regression model applies a Wild Cluster Bootstrap.ResultsExpanding Medicaid eligibility was found to be associated with a decrease in the proportion of distant‐stage diagnoses of HPV(−) HNCs, but only among states which increased Medicaid dental generosity at the time of Medicaid expansion.ConclusionsThese results suggest that adding extensive Medicaid dental benefits was the primary mechanism impacting HNC detection. This study highlights the potential positive spillover effects of policies which increase access to public dental coverage for low‐income adults, while also showing the limitation of access to dental services for improving early detection of HPV+ HNCs.

We examine the Affordable Care Act Medicaid expansion effects on self-rated health status over 5 years. The study uses data from the Behavioral Risk Factor Surveillance System for 2011-2018 and a difference-in-differences design. There is improvement in health status on a 1 to 5 point scale from poor to excellent health among individuals below 100% of the federal poverty line by 0.031, 0.068, 0.031, 0.064, and 0.087 points in 2014, 2015, 2016, 2017, and 2018, respectively. Changes in 2015, 2017, and 2018 are statistically significant ( p < .05), and the 2014 change is marginally significant. The difference between 2014 and 2018 effects is statistically significant ( p < .05). In most years, we cannot distinguish changes in days not in good physical or mental health from no effect. Overall, there is only minimal evidence for effects intensifying over time, suggesting that health gains thus far have mostly occurred early on due to unmet needs among those previously uninsured.