A tale of two cities: Understanding geographic differences by region and rurality in HIV care outcomes in the U.S.

University Of Alabama At Birmingham, Birmingham AL

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Abstract

The U.S. initiative of Ending the HIV Epidemic (EHE) has fallen short of its goals, and geographic differences in HIV care outcomes have only widened in the last decade. For example, here are significant differences in HIV care outcomes, such as viral suppression and hospitalization rates, among people living with HIV (PLWH) between the Western and Southern regions of the U.S., as well as among urban centers and rural areas. These geographic differences are also observed in other chronic diseases, yet, PLWH appear to be at higher risk of poorer health outcomes than persons not living with HIV (PNLWH), especially in rural areas. These geographic differences are likely largely driven by underlying factors in our health systems, such as access to healthcare, providers, and specialized care centers in rural areas—an understanding of these pathways that elucidate these differences is urgently needed to develop the next generation of HIV interventions operating at the health systems levels, and ever more now in the context of compounding chronic diseases affecting PLWH. The National Clinical Cohort Collaborative (N3C) leverages real-world, national data and presents an unprecedented opportunity to inform the NIH priority aims to understand the factors that affect both HIV and other chronic conditions. N3C is the largest electronic health record (EHR) repository in U.S. history (>20M patients), contains both unparalleled individual-level granular clinical and historical data, and represents the largest U.S. cohort of PLWH with their HIV and other chronic conditions outcomes data (>120K), allowing us to evaluate the bi-directional impact of existing HIV infection and other chronic diseases outcomes. Furthermore, individual-level data in the N3C are uniquely positioned to merge publicly available datasets that measure area-level health systems factors. Our central hypothesis is that the observed geographic differences in HIV and other chronic diseases occur in a larger context of individuals embedded in health systems with very significant differences across the U.S., between urban areas as well as between urban and nearby rural areas. Understanding these forces, allows us to determine the next generation of HIV interventions. Our three aims respond to the NIH call using data science, rigorous and reproducible machine and statistical learning, and multi-level mediation and epidemic modeling. The goal of Aim 1 (HIV outcomes) is to identify multilevel, geographic and health systems differences in HIV outcomes (e.g., viral suppression and hospitalization) over the recent years. The goal of Aim 2 (chronic diseases outcomes) is to understand the independent and aggregated impact of geographic differences and clinical characteristics on health outcomes (2a) and quantify the differential impact of HIV on other chronic diseases outcomes at the U.S. population level by geography (2b). The goal of Aim 3 (HIV epidemic modeling) is to quantify the impact of other chronic diseases on HIV care and prevention outcomes by geography at the population-level for the national EHE initiative’s priority jurisdictions.