{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T21:31:50Z","timestamp":1783805510284,"version":"3.55.0"},"reference-count":14,"publisher":"Georg Thieme Verlag KG","issue":"05","funder":[{"name":"New York-Presbyterian Hospital"},{"DOI":"10.13039\/100007273","name":"Weill Cornell Medical College","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100007273","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Clinical and Translational Sciences Center","award":["ULI TR000457"],"award-info":[{"award-number":["ULI TR000457"]}]},{"name":"Joint Clinical Trials Office"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2020,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>\n          Background\u2003Although 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.<\/jats:p><jats:p>\n          Objectives\u2003We seek to improve the availability and quality of structured race data available to researchers by integrating values from multiple local sources.<\/jats:p><jats:p>\n          Methods\u2003To address the deficiency in race data availability, we implemented a method to supplement OMB race values from four local sources\u2014inpatient 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.<\/jats:p><jats:p>\n          Results\u2003The 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.<\/jats:p><jats:p>\n          Conclusion\u2003Implementation of this method can successfully increase OMB race data availability, potentially enhancing accrual of patients from underserved populations to research studies.<\/jats:p>","DOI":"10.1055\/s-0040-1718756","type":"journal-article","created":{"date-parts":[[2020,11,26]],"date-time":"2020-11-26T01:13:48Z","timestamp":1606353228000},"page":"785-791","source":"Crossref","is-referenced-by-count":21,"title":["A Method to Improve Availability and Quality of Patient Race Data in an Electronic Health Record System"],"prefix":"10.1055","volume":"11","author":[{"given":"Marika M.","family":"Cusick","sequence":"additional","affiliation":[{"name":"Information Technologies and Services Department, Weill Cornell Medicine, New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evan T.","family":"Sholle","sequence":"additional","affiliation":[{"name":"Information Technologies and Services Department, Weill Cornell Medicine, New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcos A.","family":"Davila","sequence":"additional","affiliation":[{"name":"Information Technologies and Services Department, Weill Cornell Medicine, New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph","family":"Kabariti","sequence":"additional","affiliation":[{"name":"Information Technologies and Services Department, Weill Cornell Medicine, New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Curtis L.","family":"Cole","sequence":"additional","affiliation":[{"name":"Information Technologies and Services Department, Weill Cornell Medicine, New York, New York, United States"},{"name":"Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"Jr.","given":"Thomas R.","family":"Campion","sequence":"additional","affiliation":[{"name":"Information Technologies and Services Department, Weill Cornell Medicine, New York, New York, United States"},{"name":"Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, United States"},{"name":"Clinical and Translational Science Center, Weill Cornell Medicine, New York, New York, United States"},{"name":"Department of Pediatrics, Weill Cornell Medicine, New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"194","published-online":{"date-parts":[[2020,11,25]]},"reference":[{"key":"ref1","volume-title":"Who, when, and how: the current state of race, ethnicity, and primary language data collection in hospitals","author":"Commonwealth Fund"},{"issue":"131","key":"ref2","first-page":"36873","article-title":"Recommendations from the interagency committee for the review of the racial and ethnic standards to the office of management and budget concerning changes to the standards for the classification of federal data on race and ethnicity","volume":"62","author":"Office of Management and Budget","year":"1997","journal-title":"Fed Regist"},{"issue":"12","key":"ref3","doi-asserted-by":"crossref","first-page":"1170","DOI":"10.1056\/NEJMsb025007","article-title":"The importance of race and ethnic background in biomedical research and clinical practice","volume":"348","author":"E G Burchard","year":"2003","journal-title":"N Engl J Med"},{"issue":"09","key":"ref4","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1056\/NEJMms2004740","article-title":"Hidden in plain sight \u2014 reconsidering the use of race correction in clinical algorithms","volume":"383","author":"D A Vyas","year":"2020","journal-title":"N Engl J Med"},{"issue":"07","key":"ref5","doi-asserted-by":"crossref","first-page":"t2007","DOI":"10.1186\/gb-2002-3-7-comment2007","article-title":"Categorization of humans in biomedical research: genes, race and disease","volume":"3","author":"N Risch","year":"2002","journal-title":"Genome Biol"},{"issue":"S 07","key":"ref6","first-page":"1091","article-title":"Twenty years post-NIH Revitalization Act: enhancing minority participation in clinical trials (EMPaCT): laying the groundwork for improving minority clinical trial accrual: renewing the case for enhancing minority participation in cancer clinical trials","volume":"120","author":"M S Chen Jr","year":"2014","journal-title":"Cancer"},{"key":"ref7","first-page":"1581","article-title":"Secondary use of patients' electronic records (SUPER): an approach for meeting specific data needs of clinical and translational researchers","volume":"2017","author":"E T Sholle","year":"2018","journal-title":"AMIA Annu Symp Proc"},{"issue":"06","key":"ref8","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1056\/NEJMp1006114","article-title":"The \u201cmeaningful use\u201d regulation for electronic health records","volume":"363","author":"D Blumenthal","year":"2010","journal-title":"N Engl J Med"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1093\/jamia\/ocz113","article-title":"Challenges with quality of race and ethnicity data in observational databases","volume":"26","author":"F CG Polubriaginof","year":"2019","journal-title":"J Am Med Inform Assoc"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1093\/jamia\/ocz040","article-title":"Underserved populations with missing race ethnicity data differ significantly from those with structured race\/ethnicity documentation","volume":"26","author":"E T Sholle","year":"2019","journal-title":"J Am Med Inform Assoc"},{"issue":"04","key":"ref11","doi-asserted-by":"crossref","first-page":"624","DOI":"10.1373\/49.4.624","article-title":"LOINC, a universal standard for identifying laboratory observations: a 5-year update","volume":"49","author":"C J McDonald","year":"2003","journal-title":"Clin Chem"},{"issue":"01","key":"ref12","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1136\/amiajnl-2011-000681","article-title":"Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research","volume":"20","author":"N G Weiskopf","year":"2013","journal-title":"J Am Med Inform Assoc"},{"issue":"02","key":"ref14","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1055\/s-0040-1709506","article-title":"Leveraging electronic dental record data for clinical research in the national dental PBRN practices","volume":"11","author":"T P Thyvalikakath","year":"2020","journal-title":"Appl Clin Inform"},{"issue":"02","key":"ref15","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1136\/amiajnl-2014-003023","article-title":"Implications of an emerging EHR monoculture for hospitals and healthcare systems","volume":"22","author":"R Koppel","year":"2015","journal-title":"J Am Med Inform Assoc"}],"container-title":["Applied Clinical 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