ArticleAnnals of epidemiology2016
A novel method for estimating transgender status using electronic medical records.
Article in Annals of epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
48 citing papers in PubMed.
- Development of a Keyword-Based Search Strategy to Identify Gender Diverse Youth in Electronic Medical Records.Transgender health · 2026Article
- A scoping review of models to identify transgender patients in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- When algorithms infer gender: revisiting computational phenotyping with electronic health records data.Biology of sex differences · 2025Review
- Availability of sexual orientation and gender identity (SOGI) information in a cohort of transgender and gender diverse people: An analysis of electronic health records.Annals of epidemiology · 2025Article
- Leveraging the Electronic Health Record to Characterize Health Care Utilization and Stressors Before a Suicide Attempt Among Transgender and Gender Diverse Patients.Transgender health · 2025Article
- A multidisciplinary look into transgender and gender diverse people with epilepsy: An at-risk and underreported population.Epilepsia · 2025Article
- Hematologists' comfort and experiences with providing care to transgender youth.Blood vessels, thrombosis & hemostasis · 2025Article
- Validating a Case Definition for Transgender Adults Using Administrative Data.JAMA network open · 2025Article
- Challenging Norms: The Impact of Transgender and Gender-Diverse Realities on Work and School Participation.The American journal of occupational therapy : official publication of the American Occupational Therapy Association · 2024Article
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- The Carolina hysterectomy cohort (CHC): a novel case series of reproductive-aged hysterectomy patients across 10 hospitals in the US south.BMC women's health · 2023Article
- The Health of Transmasculine Patients Compared With Cisgender Patients Treated With Hysterectomy in the U.S. South, 2014-2017.Annals of LGBTQ public and population health · 2023Article
- A deep learning approach for transgender and gender diverse patient identification in electronic health records.Journal of biomedical informatics · 2023Article
- An Exploratory Study to Describe Transgender People with HIV Who Accessed Medicaid and Their Viral Suppression Over Time in New York City, 2013-2017.Transgender health · 2023Article
- Article
- Disparities in Prostate Cancer Screening for Transgender Women: An Analysis of the MarketScan Database.Urology · 2023Article
- Transgender identity in young people and adults recorded in UK primary care electronic patient records: retrospective, dynamic, cohort study.BMJ medicine · 2023Article
- Transgender Individuals and Digital Health.Current HIV/AIDS reports · 2022Review
- Improving Data on the HIV Epidemic in New York City by Identifying Transgender Persons in Medicaid in 2013-2017.Transgender health · 2022Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
purposeWe describe a novel algorithm for identifying transgender people and determining their male-to-female (MTF) or female-to-male (FTM) identity in electronic medical records of an integrated health system.
methodsA computer program scanned Kaiser Permanente Georgia electronic medical records from January 2006 through December 2014 for relevant diagnostic codes, and presence of specific keywords (e.g., "transgender" or "transsexual") in clinical notes. Eligibility was verified by review of de-identified text strings containing targeted keywords, and if needed, by an additional in-depth review of records. Once transgender status was confirmed, FTM or MTF identity was assessed using a second program and another round of text string reviews.
resultsOf 813,737 members, 271 were identified as possibly transgender: 137 through keywords only, 25 through diagnostic codes only, and 109 through both codes and keywords. Of these individuals, 185 (68%, 95% confidence interval [CI]: 62%-74%) were confirmed as definitely transgender. The proportions (95% CIs) of definite transgender status among persons identified via keywords, diagnostic codes, and both were 45% (37%-54%), 56% (35%-75%), and 100% (96%-100%). Of the 185 definitely transgender people, 99 (54%, 95% CI: 46%-61%) were MTF, 84 (45%, 95% CI: 38%-53%) were FTM. For two persons, gender identity remained unknown. Prevalence of transgender people (per 100,000 members) was 4.4 (95% CI: 2.6-7.4) in 2006 and 38.7 (95% CI: 32.4-46.2) in 2014.
conclusionsThe proposed method of identifying candidates for transgender health studies is low cost and relatively efficient. It can be applied in other similar health care systems.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.