Evaluating the Effect of Medicaid Expansion on Black/White Breast Cancer Mortality Disparities: A Difference-in-Difference Analysis

Abstract

PURPOSE This analysis used a difference-in-difference (DID) fixed effects regression model to evaluate the impact of Medicaid Expansion on the disparity between black and white breast cancer mortality rates. 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. The goal of Medicaid Expansion was to improve equity. However, this major health policy has yet to be thoroughly investigated for its effect on health disparities. Many widely accepted methods exist to evaluate variations in health policy, but few studies have used such quasi-experimental designs to explore 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. To test the impact Medicaid Expansion had on the black/white breast cancer mortality ratio, a DID analysis calculated the policy’s average treatment effect (ATE). METHODS 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 other compared all expanding states with nonexpanding states that voted to expand (but did not by 2014). Fixed-effects and random-effects regression models were constructed for each specific age group. A Hausman test was calculated to determine which model was most appropriate. The DID regression models considered the year 2014 a wash-out period and compared 2012 and 2013 (pretreatment) to 2015 and 2016 (post-treatment). A graph was presented to test the necessary parallel trend assumption for expanding and nonexpanding states. DID estimators (average treatment effect) and respective P values were reported for each age group. Non–Medicaid-eligible age groups were included as a pseudo-control. RESULTS Medicaid Expansion did not lower the disparity in breast cancer mortality. Converse 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 Investigators should use proven quasi-experimental methods to analyze the effect of policy variation on health disparities. Policy makers must consider institutional factors that may limit minority groups from benefiting from macrochanges in health policy. These results suggest that states cannot solely rely on access to insurance to alleviate disparities in cancer or other chronic conditions. More exploration into the impacts of low-quality health systems remain warranted.