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. 2022 Jun;112(6):923-930.
doi: 10.2105/AJPH.2022.306783. Epub 2022 Apr 21.

Linking Electronic Health Records to the American Community Survey: Feasibility and Process

Victoria Udalova  1 , Timothy S Carey  1 , Paul Roman Chelminski  1 , Lucinda Dalzell  1 , Patricia Knoepp  1 , Joanna Motro  1 , Barbara Entwisle  1
Affiliations

Linking Electronic Health Records to the American Community Survey: Feasibility and Process

Victoria Udalova et al. Am J Public Health. 2022 Jun.

Abstract

Objectives. To assess linkages of patient data from a health care system in the southeastern United States to microdata from the American Community Survey (ACS) with the goal of better understanding health disparities and social determinants of health in the population. Methods. Once a data use agreement was in place, a stratified random sample of approximately 200 000 was drawn of patients aged 25 to 74 years with at least 2 visits between January 1, 2016, and December 31, 2019. Information from the sampled electronic health records (EHRs) was transferred securely to the Census Bureau, put through the Census Person Identification Validation System to assign Protected Identification Keys (PIKs) as unique identifiers wherever possible. EHRs with PIKs assigned were then linked to 2001-2017 ACS records with a PIK. Results. PIKs were assigned to 94% of the sampled patients. Of patients with PIKs, 15.5% matched to persons sampled in the ACS. Conclusions. Linking data from EHRs to ACS records is feasible and, with adjustments for differential coverage, will advance understanding of social determinants and enhance the ability of integrated delivery systems to reflect and affect the health of the populations served. (Am J Public Health. 2022;112(6):923-930. https://doi.org/10.2105/AJPH.2022.306783).

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FIGURE 1—
FIGURE 1—
Matching Electronic Health Records (EHRs) to American Community Survey (ACS) Sample: United States
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