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Title: Enhancing Electronic Health Record Data with Geospatial Information.

Authors: Xie, Sherrie; Greenblatt, Rebecca; Levy, Michael Z; Himes, Blanca E

Published In AMIA Jt Summits Transl Sci Proc, (2017)

Abstract: Electronic Health Record (EHR)-derived data is a valuable resource for research, and efforts are underway to overcome some of its limitations by using data from external sources to gain a fuller picture of patient characteristics, symptoms, and exposures. Our goal was to assess the utility of augmenting EHR data with geocoded patient addresses to identify geospatial variation of disease that is not explained by EHR-derived demographic factors. Using 2011-2014 encounter data from 27,604 University of Pennsylvania Hospital System asthma patients, we identified factors associated with asthma exacerbations: risk was higher in female, black, middle aged to elderly, and obese patients, as well as those with positive smoking history and with Medicare or Medicaid vs. private insurance. Significant geospatial variability of asthma exacerbations was found using generalized additive models, even after adjusting for demographic factors. Our work shows that geospatial data can be used to cost-effectively enhance EHR data.

PubMed ID: 28815121 Exiting the NIEHS site

MeSH Terms: No MeSH terms associated with this publication

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