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DOI: 10.1055/s-0040-1718756
A Method to Improve Availability and Quality of Patient Race Data in an Electronic Health Record System
Funding This study received support from New York-Presbyterian Hospital and Weill Cornell Medical College, including the Clinical and Translational Sciences Center (ULI TR000457) and Joint Clinical Trials Office.


Abstract
Background Although federal regulations mandate documentation of structured race data according to Office of Management and Budget (OMB) categories in electronic health record (EHR) systems, many institutions have reported gaps in EHR race data that hinder secondary use for population-level research focused on underserved populations. When evaluating race data available for research purposes, we found our institution's enterprise EHR contained structured race data for only 51% (1.6 million) of patients.
Objectives We seek to improve the availability and quality of structured race data available to researchers by integrating values from multiple local sources.
Methods To address the deficiency in race data availability, we implemented a method to supplement OMB race values from four local sources—inpatient EHR, inpatient billing, natural language processing, and coded clinical observations. We evaluated this method by measuring race data availability and data quality with respect to completeness, concordance, and plausibility.
Results The supplementation method improved race data availability in the enterprise EHR up to 10% for some minority groups and 4% overall. We identified structured OMB race values for more than 142,000 patients, nearly a third of whom were from racial minority groups. Our data quality evaluation indicated that the supplemented race values improved completeness in the enterprise EHR, originated from sources in agreement with the enterprise EHR, and were unbiased to the enterprise EHR.
Conclusion Implementation of this method can successfully increase OMB race data availability, potentially enhancing accrual of patients from underserved populations to research studies.
Keywords
electronic health records and systems - data quality - data completeness - clinical research informatics - data collection - recruitmentProtection of Human and Animal Subjects
The study was performed in compliance with the “Federal Policy for the Protection of Human Subjects” by the U.S. Department of Health and Human Services and was reviewed by the WCM Institutional Review Board.
Publication History
Received: 29 May 2020
Accepted: 16 September 2020
Article published online:
25 November 2020
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