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A novel method for estimating transgender status using electronic medical records
Douglas Roblin1, Joshua Barzilay2, Dennis Tolsma2
1School of Public Health, Georgia State University, Atlanta; Center for Clinical and Outcomes Research, Kaiser Permanente Georgia, Atlanta.
Annals of Epidemiology
|February 25, 2016
Summary
A new algorithm efficiently identifies transgender individuals in electronic health records, distinguishing between male-to-female (MTF) and female-to-male (FTM) identities. This method aids in transgender health research by improving data accuracy and accessibility.
Area of Science:
- Health Informatics
- Medical Record Analysis
- Transgender Health
Background:
- Accurate identification of transgender individuals in electronic medical records (EMRs) is crucial for health research and care.
- Existing methods may not effectively capture the nuances of gender identity within diverse healthcare systems.
Purpose of the Study:
- To develop and evaluate a novel algorithm for identifying transgender individuals within an integrated health system's EMRs.
- To determine the male-to-female (MTF) and female-to-male (FTM) identities of identified transgender individuals.
Main Methods:
- A computer program scanned EMRs for diagnostic codes and keywords related to transgender identity.
- Eligibility was confirmed through text string reviews, with in-depth reviews for ambiguous cases.
- A secondary program and review process assessed MTF or FTM identity.
Main Results:
- The algorithm identified 271 potential transgender individuals from over 813,000 members.
- 185 individuals (68%) were confirmed as transgender, with 54% MTF and 45% FTM.
- The prevalence of transgender individuals increased significantly from 2006 to 2014.
Conclusions:
- The developed algorithm offers a low-cost and efficient method for identifying transgender individuals in EMRs.
- This approach is applicable to other similar healthcare systems for improving transgender health research.
- The study highlights the increasing prevalence of transgender individuals within the healthcare system.
