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Transphobia, encoded: an examination of trans-specific terminology in SNOMED CT and ICD-10-CM

The work

AuthorsA Ram; Clair A. Kronk; Jacob R. Eleazer; Joseph Lucien Goulet; Cynthia Brandt; Karen Wang
Editors
Typearticle
Year2021
Citekeyram2021transphobia

Where it appeared

Published inJournal of the American Medical Informatics Association
PublisherOxford University Press
Volume29
Issue2
Pages404--410

Identifiers

DOI10.1093/jamia/ocab200
OpenAlexW3202883451

From OpenAlex, which stores abstracts as an index of words and their positions: what is shown is rebuilt from that, and reads fluently whether or not it is what the author wrote.

Abstract

Transgender people experience harassment, denial of services, and physical assault during healthcare visits. Electronic health record (EHR) structure and language can exacerbate the harm they experience by using transphobic terminology, emphasizing binary genders, and pathologizing transness. Here, we investigate the ways in which SNOMED CT and ICD-10-CM record gender-related terminology and explore their shortcomings as they contribute to this EHR-mediated violence. We discuss how this "standardized" gender-related medical terminology pathologizes transness, fails to accommodate nonbinary patients, and uses derogatory and outmoded language. We conclude that there is no easy fix to the transphobia beleaguering healthcare, provide options to reduce harm to patients, and ultimately call for a critical examination of medicine's role in transphobia. We aim to demonstrate the ways in which the [mis]use and [mis]understanding of gender-specific terminology in healthcare settings has harmed and continues to harm trans people by grounding our discussion in our personal experiences.

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Added2026-10-23 13:49 UTC
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Cite it as

@article{ram2021transphobia,
  title        = {Transphobia, encoded: an examination of trans-specific terminology in SNOMED CT and ICD-10-CM},
  author       = {A Ram and Clair A. Kronk and Jacob R. Eleazer and Joseph Lucien Goulet and Cynthia Brandt and Karen Wang},
  year         = {2021},
  journal      = {Journal of the American Medical Informatics Association},
  publisher    = {Oxford University Press},
  volume       = {29},
  number       = {2},
  pages        = {404--410},
  doi          = {10.1093/jamia/ocab200},
}

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