Enhancing Secondary-use of Electronic Health Records for Geospatial-temporal Population Health Research

Abstract

For almost three decades, the United States Department of Human and Health Services, Center for Disease Control, and the World Health Organization have recognized the role of social and environmental determinants of health in understanding the health of populations. Community and population health is a function of each individual’s health and wellness, determined in large by their socioeconomic status, environmental factors, and access to healthcare services. In disastrous times, spatiotemporally-relevant information escalate in importance as health systems strive to address emergent concerns, pre-existing needs, population migration, while experiencing disruption in available resources and infrastructure. With their adoption by hospitals and health systems, Electronic Health Records (EHRs) contain a richness and diversity of information about patients. EHRs could inform where and how to prepare for population-scale patient needs in future disaster scenarios with a timely, equitable, and data-driven approach; however, the ability to apply spatiotemporal reasoning with EHRs have remained an underrepresented capacity. Informatics innovations would need to account for the operational, technical, and ethical constraints felt by those who study the health of populations. In this dissertation, I focus on three areas for building capacities to use of geospatial-temporal information to address population health needs. The aims are to: 1) assess information needs and priority use-cases for population health research in hydrologic disaster preparedness, 2) design spatiotemporal use-case workflows to survey trends and anomalies for regional areas using gridded hydrometeorological data products, a surrogate for structured multivariate datasets, and 3) develop an approach for spatiotemporal inferential statistics of EHR patient diagnosis information. This work incorporates flexible design and secondary-use of data for population health research and geographic inferences in preparation for future disasters.