Electronic health record (EHR)-derived data has become an invaluable resource for biomedical research, but is seldom used for the study of the health impacts of social and environmental factors due in part to the unavailability of relevant variables. We describe how EHR-derived data can be enhanced via linking of external sources of social, economic and environmental data when patient-related geospatial information is available, and we illustrate an approach to better understand the geospatial patterns of asthma exacerbation rates in Philadelphia. Specifically, we relate the spatial distribution of asthma exacerbations observed in EHR-derived data to that of known and potential risk factors (i.e., economic deprivation, crime, vehicular traffic, tree cover). Areas of highest risk based on integrated social and environmental data were consistent with an area with increased asthma exacerbations, demonstrating that data external to the EHR can enhance our understanding of negative health-related outcomes.

Learning Objective 1: Social, economic and environmental data can be linked to EHR-derived data when patient-related geospatial information is available to understand health risk factors in real life populations.

Learning Objective 2: The geospatial distribution of asthma exacerbations in Philadelphia as estimated from EHR-derived data may be explained by spatial variations in economic deprivation, crime, and traffic density.


Sherrie Xie (Presenter)
University of Pennsylvania

Blanca Himes, University of Pennsylvania

Presentation Materials: