Amanda N Burnside, Jennifer A Hoffmann, Douglas Lorenz, Jessica Walter, Johnny Berona, Aron Janssen
{"title":"Development of a Keyword-Based Search Strategy to Identify Gender Diverse Youth in Electronic Medical Records.","authors":"Amanda N Burnside, Jennifer A Hoffmann, Douglas Lorenz, Jessica Walter, Johnny Berona, Aron Janssen","doi":"10.1089/trgh.2023.0182","DOIUrl":null,"url":null,"abstract":"<p><p>A retrospective cross-sectional study of nearly 3 years of emergency department (ED) encounters was performed with the goal of developing an electronic medical record (EMR) search strategy to identify transgender and gender diverse (TGD) youth. A search of nine keywords to identify TGD youth was conducted in the EMR, and text from clinician notes was extracted and reviewed. Among 15,413 ED encounters, 1126 keywords were identified, and 91.2% were classified as TGD. The final dataset classified 605 ED encounters (428 unique youth) as TGD. The study offers a feasible technique to identify and prioritize TGD youth in health research using EMR data.</p>","PeriodicalId":94256,"journal":{"name":"Transgender health","volume":"11 3","pages":"220-223"},"PeriodicalIF":1.8000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13187367/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transgender health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1089/trgh.2023.0182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/6/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"PSYCHOLOGY, CLINICAL","Score":null,"Total":0}
引用次数: 0
Abstract
A retrospective cross-sectional study of nearly 3 years of emergency department (ED) encounters was performed with the goal of developing an electronic medical record (EMR) search strategy to identify transgender and gender diverse (TGD) youth. A search of nine keywords to identify TGD youth was conducted in the EMR, and text from clinician notes was extracted and reviewed. Among 15,413 ED encounters, 1126 keywords were identified, and 91.2% were classified as TGD. The final dataset classified 605 ED encounters (428 unique youth) as TGD. The study offers a feasible technique to identify and prioritize TGD youth in health research using EMR data.
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