518 - Leveraging the OMOP Common Data Model to Support Distributed Health Equity Research
Friday, April 28, 2023
5:15 PM – 7:15 PM ET
Poster Number: 518 Publication Number: 518.116
William G. Adams, Boston Medical Center/Boston University School of Medicine, Wayland, MA, United States; Sarah Gasman, Boston Medical Center/Boston University School of Medicine, Cambridge, MA, United States; Ariel Beccia, Boston Children's Hospital, Cambridge, MA, United States; Howard J. Cabral, Boston University School of Public Health, Boston, MA, United States
Boston Medical Center/Boston University School of Medicine Wayland, Massachusetts, United States
Background: To better support health equity research on a national scale, there is a pressing need to: 1) expand foundational data systems to include information on social and environmental factors that represent multilevel drivers of child health; and 2) develop informatics tools to support visualization and statistical analyses in ways that are easy to use and share across research organizations. Objective:
Objective: Develop a health equity research platform within a large urban safety-het health system to: 1) expand an existing de-identified Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) repository, the "Data for Equity (D4E) Platform", to include extensive census-level "place-based" social and environmental drivers of health (e.g. Child Opportunity Index (COI), Social Vulnerability Index (SVI), American Community Survey (ACS)); 2) develop a library of reusable analytic code to assess associations between a broad range of health outcomes and drivers of health (Table 1); and 3) provide an easy to use data visualization tool, the "Health Equity Explorer", to allow users to explore health equity themselves via graphs, maps, and statistical analyses. Design/Methods: We used an interactive design process with input from multiple stakeholders including leaders of the Boston Medical Center “Health Equity Accelerator” and a community advisory board. We also leveraged materials from the Observational Health Data Sciences and Informatics (OHDSI) Community, open source statistical and application development tools, and standard measure specifications and value sets for target outcome measures. Results: We have developed an open-source, OMOP CDM-based, platform with clinical and place-based social and environmental data, re-usable code, and a visualization tool to support health and health equity exploration (visually and statistically). We have implemented a diverse and growing set of medical and behavioral health outcomes for children and adults in a way that allows dynamic exploration of the contributions of individual social need, and place-based social and environmental drivers of health. Summary data from analyses can be easily shared to support real-world distributed health equity research on a national scale.
Conclusion(s): D4E and the Health Equity Explorer can be used to support dynamic and interactive explorations into the factors that support (or hinder) health equity. With expanded use and partnerships, these tools have the potential to support distributed health equity research and action on a national scale.
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