The health equity explorer: an open-source resource for distributed health equity visualization and research across common data models
Date
2024-04-05
Authors
Adams, William G.
Version
OA Version
Citation
Adams WG, Gasman S, Beccia AL, Fuentes L. The Health Equity Explorer: An open-source resource for distributed health equity visualization and research across common data models. Journal of Clinical and Translational Science. 2024;8(1):e72. doi:10.1017/cts.2024.500
Abstract
Introduction:
There is an urgent need to address pervasive inequities in health and healthcare in the USA. Many areas of health inequity are well known, but there remain important unexplored areas, and for many populations in the USA, accessing data to visualize and monitor health equity is difficult.
Methods:
We describe the development and evaluation of an open-source, R-Shiny application, the “Health Equity Explorer (H2E),” designed to enable users to explore health equity data in a way that can be easily shared within and across common data models (CDMs).
Results:
We have developed a novel, scalable informatics tool to explore a wide variety of drivers of health, including patient-reported Social Determinants of Health (SDoH), using data in an OMOP CDM research data repository in a way that can be easily shared. We describe our development process, data schema, potential use cases, and pilot data for 705,686 people who attended our health system at least once since 2016. For this group, 996,382 unique observations for questions related to food and housing security were available for 324,630 patients (at least one answer for all 46% of patients) with 65,152 (20.1% of patients with at least one visit and answer) reporting food or housing insecurity at least once.
Conclusions:
H2E can be used to support dynamic and interactive explorations that include rich social and environmental data. The tool can support multiple CDMs and has the potential to support distributed health equity research and intervention on a national scale.
Description
License
© The Author(s), 2024. Published by Cambridge University Press on behalf of Association for Clinical and Translational Science. This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial licence (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use. This article has been published under a Read & Publish Transformative Open Access (OA) Agreement with CUP.