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Kronk CA, Everhart AR, Ashley F, et al. Transgender data collection in the electronic health record: Current concepts and issues. J Am Med Inform Assoc. 2022;29(2):271-284doi: 10.1093/jamia/ocab136.
Kronk, C. A., Everhart, A. R., Ashley, F., Thompson, H. M., Schall, T. E., Goetz, T. G., Hiatt, L., Derrick, Z., Queen, R., Ram, A., Guthman, E. M., Danforth, O. M., Lett, E., Potter, E., Sun, S. E. D., Marshall, Z., & Karnoski, R. (2022). Transgender data collection in the electronic health record: Current concepts and issues. Journal of the American Medical Informatics Association : JAMIA, 29(2), 271-284. https://doi.org/10.1093/jamia/ocab136
Kronk, Clair A, et al. "Transgender data collection in the electronic health record: Current concepts and issues." Journal of the American Medical Informatics Association : JAMIA vol. 29,2 (2022): 271-284. doi: https://doi.org/10.1093/jamia/ocab136
Kronk CA, Everhart AR, Ashley F, Thompson HM, Schall TE, Goetz TG, Hiatt L, Derrick Z, Queen R, Ram A, Guthman EM, Danforth OM, Lett E, Potter E, Sun SED, Marshall Z, Karnoski R. Transgender data collection in the electronic health record: Current concepts and issues. J Am Med Inform Assoc. 2022 Jan 12;29(2):271-284. doi: 10.1093/jamia/ocab136. PMID: 34486655; PMCID: PMC8757312.
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J Am Med Inform Assoc. 2022 Jan 12;29(2):271-284. doi: 10.1093/jamia/ocab136.

Transgender data collection in the electronic health record: Current concepts and issues.

Journal of the American Medical Informatics Association : JAMIA

Clair A Kronk, Avery R Everhart, Florence Ashley, Hale M Thompson, Theodore E Schall, Teddy G Goetz, Laurel Hiatt, Zackary Derrick, Roz Queen, A Ram, E Mae Guthman, Olivia M Danforth, Elle Lett, Emery Potter, Simón E D Sun, Zack Marshall, Ryan Karnoski

Affiliations

  1. Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut, USA.
  2. Population, Health, and Place Program, Spatial Sciences Institute, University of Southern California, Los Angeles, California, USA.
  3. Center for Applied Transgender Studies, Chicago, Illinois, USA.
  4. Faculty of Law and Joint Centre for Bioethics, University of Toronto, Toronto, Ontario, Canada.
  5. Department of Psychiatry and Behavioral Science, Rush University Medical Center, Chicago, Illinois, USA.
  6. Berman Institute of Bioethics, Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
  7. Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  8. University of Utah School of Medicine, Salt Lake City, Utah, USA.
  9. School of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada.
  10. Health Information Science, School of Human and Social Development, University of Victoria, Victoria, British Columbia, Canada.
  11. Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA.
  12. Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA.
  13. Department of Family Medicine, Samaritan Health Services Geary St. Clinic, Albany, Oregon, USA.
  14. Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  15. Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Ontario, Canada.
  16. Center for Neural Science, New York University, New York, New York, USA.
  17. Department of Neuroscience and Physiology, Neuroscience Institute, NYU Grossman Medical Center, New York, New York, USA.
  18. School of Social Work, McGill University, Montreal, Quebec, Canada.
  19. School of Social Welfare, University of California, Berkeley, Berkeley, California, USA.

PMID: 34486655 PMCID: PMC8757312 DOI: 10.1093/jamia/ocab136

Abstract

There are over 1 million transgender people living in the United States, and 33% report negative experiences with a healthcare provider, many of which are connected to data representation in electronic health records (EHRs). We present recommendations and common pitfalls involving sex- and gender-related data collection in EHRs. Our recommendations leverage the needs of patients, medical providers, and researchers to optimize both individual patient experiences and the efficacy and reproducibility of EHR population-based studies. We also briefly discuss adequate additions to the EHR considering name and pronoun usage. We add the disclaimer that these questions are more complex than commonly assumed. We conclude that collaborations between local transgender and gender-diverse persons and medical providers as well as open inclusion of transgender and gender-diverse individuals on terminology and standards boards is crucial to shifting the paradigm in transgender and gender-diverse health.

© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: [email protected].

Keywords: bioethics; electronic health records; gender and sexual minorities; transgender persons

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