Optimal & Equitable Care: Medicaid Data Research Infrastructure

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DESCRIPTION (provided by applicant): Purpose: This is a Data Capacity-Building Project, to build a robust comparative effectiveness research infrastructure, agenda, and collaborative partnerships focused on eliminating health disparities. Specifically we will build a database comprised of all Medicaid enrollees and claims in the states that share in common both adverse minority health outcomes and the historical roots of racial health disparities in the South. Setting & Participants: Our CMS data request has already been approved and we have actually purchased (but not yet received) a 100% sample of four years (2004-07) of Medicaid Analytic Extract (MAX-file) data (plus Medicare-linked claims for dual-eligibles) from fourteen southern states, representing 3.8 to 5.4 million persons each year (one-third of all U.S. Medicaid enrollees, nearly half [48%] of African American and 21 % of Latino Medicaid enrollees in the U.S). This region is the epicenter of the black-white health disparities epidemic, and has also experienced a recent and rapid influx of Latino immigrants. Our HBCU-based team has previously had extensive experience training health services researchers (especially minority investigators) to use Medicaid claims data for research, but we currently lack the personnel and infrastructure support needed to efficiently organize and analyze these data to support minority investigators. Specific Alms: Using Medicaid Claims Data: 1. To build a Medicaid claims data set (including socio-economic, contextual, and geospatial analytic variables, NDC cross-walk data and therapeutic class codes, as well as certain Medicare data for dualeligibles) to support projects focused on the intersection between disparities research and comparative effectiveness research in clinically and socially complex patient populations. 2. To create an efficient process for assisting non-Morehouse investigators to develop research protocols, analysis plans, CMS data re-use requests, and analytic files for collaborative research. 3. To train, develop, cultivate, and support emerging minority investigators (especially at HBCUs and other minority-serving institutions) as independently-funded health services researchers who are increasingly proficient in multivariate analysis of Medicaid and Medicare claims data. 4. Cultivate comparative effectiveness and disparities research collaborations with Georgia Tech experts in mathematics, complexity science, simulation modeling, and interactive computing. PUBLIC HEALTH RELEVANCE: Medicaid patients are characterized by clinical and social complexity - the very characteristics that often exclude them from clinical trials and yet drive health disparities. This Medicaid based data set will populate studies that help us understand how local-area, provider-level, and patient-level differences in treatment (natural experiments in comparative effectiveness) influence clinical and economic outcomes. Variation implies that disparities are not inevitable. The comparative impact of this natural variation can be measured in meaningful outcomes such as emergency department visits, hospital admissions, inpatient bed-days, deaths, and total Medicaid expenditures, as well as community-level disparity rate-ratios. Medicaid data allow us to follow a complex patient (e.g., co-morbid diabetes and schizophrenia or COPD and CHF) from treatment to outcomes through every billable service in the healthcare system {i.e., from doctor's visit to lab tests to prescriptions to emergency room visits or hospital admissions). Morehouse School of Medicine has a unique ability to develop a new cadre of minority investigators to conduct and interpret the results of health services research with a racially-sensitive, culturally-competent perspective.