• Elham Hatef, Kelly M Searle, Zachary Predmore, Elyse C Lasser, Hadi Kharrazi, Karin Nelson, Philip Sylling, Idamay Curtis, Stephan D Fihn, and Jonathan P Weiner.
• Center for Population Health IT, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland. Electronic address: ehatef1@jhu.edu.
• Am J Prev Med. 2019 Jun 1; 56 (6): 811-818.

IntroductionThis study aims to assess the effect of individual and geographic-level social determinants of health on risk of hospitalization in the Veterans Health Administration primary care clinics known as the Patient Aligned Care Team.MethodsFor a population of Veterans enrolled in the primary care clinics, the study team extracted patient-level characteristics and healthcare utilization records from 2015 Veterans Health Administration electronic health record data. They also collected census data on social determinants of health factors for all U.S. census tracts. They used generalized estimating equation modeling and a spatial-based GIS analysis to assess the role of key social determinants of health on hospitalization. Data analysis was completed in 2018.ResultsA total of 6.63% of the Veterans Health Administration population was hospitalized during 2015. Most of the hospitalized patients were male (93.40%) and white (68.80%); the mean age was 64.5 years. In the generalized estimating equation model, white Veterans had a 15% decreased odds of hospitalization compared with non-white Veterans. After controlling for patient-level characteristics, Veterans residing in census tracts with the higher neighborhood SES index experienced decreased odds of hospitalization. A spatial-based analysis presented variations in the hospitalization rate across the Veterans Health Administration primary care clinics and identified the clinic sites with an elevated risk of hospitalization (hotspots) compared with other clinics across the country.ConclusionsBy linking patient and population-level data at a geographic level, social determinants of health assessments can help with designing population health interventions and identifying features leading to potentially unnecessary hospitalization in selected geographic areas that appear to be outliers.Copyright © 2019 American Journal of Preventive Medicine. All rights reserved.

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