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Can Coverage Expansions Address Racial and Gender Disparities in Health Outcomes Among Americans with Chronic Disease?

Jerome Dugan investigates the connection between health coverage type and access to affordable quality healthcare

As policymakers work to reduce the level of uninsured and improve access to healthcare services, as required by the Patient Protection and Affordable Care Act (PPACA), it is critical to understand how changes in health insurance coverage will impact inequalities in healthcare. This project will focus on three research questions that will improve our understanding of how health insurance coverage decisions may be used to resolve racial and gender disparities in health outcomes among patients with chronic disease. The first research question will investigate whether the financial risk that patients face from inadequate health insurance coverage (i.e., underinsurance) will generate inequalities in physician and resource utilization. The main analysis focuses on comparing utilization rates by the patient's cost sharing status, gender, and race. The second research question examines how a patient's expected source of payment for healthcare impacts the quality and quantity of care received. By restricting the study population to acute coronary heart disease patients, I can examine the use of specific treatment options (e.g., percutaneous coronary intervention, coronary artery bypass grafting, cardiac rehabilitation), readmission, and mortality. Last, the impact of financial pressures generated by changes in the distribution of patients covered by managed care plans (i.e., managed care penetration) on provider efficiency and efficacy will be examined.

Descriptive statistics and multivariate analysis will be used to investigate each research question. Additionally, quantile regression will allow me to assess if supplemental coverage influences medical costs differently for chronic disease patients with high resource utilization than those with average utilization. Last, fixed effects instrumental variables models are estimated with four exclusion restrictions to address the endogeneity of health insurance status and health outcomes.