Misrepresentation of Female and Gender-Diverse Patients in the ICD and SNOMED CT Systems: A Critical Review

Authors

• Evan A. Glover, University of LynchburgFollow

Specialty

Women's Health

Abstract

Abstract

The International Classification of Diseases (ICD) and the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) are foundational infrastructures for clinical documentation, research, and reimbursement. Despite extensive updates, both systems retain structural and linguistic biases that misrepresent female and gender-diverse patients. Female sexual health (FSH) diagnoses are frequently ill-defined, inconsistently categorized, or entirely absent, while outdated and pathologizing terminology persists in reference to gender-diverse populations. Rooted in cisnormative and binary design frameworks, these inequities create diagnostic gaps that compromise documentation accuracy, research validity, patient-provider trust, and equitable reimbursement.

Emerging evidence demonstrates disproportionate misclassification of gender-diverse patients due to binary identity fields, alongside persistent underrepresentation of female sexual health conditions. Although these inequities have been examined separately, no published review has analyzed their shared structural origins across ICD and SNOMED CT.

This review synthesizes current literature to identify common architectural drivers of inequity and their clinical, financial, and research implications.  It proposes interdisciplinary strategies for reform, including inclusive terminology updates, policy advocacy, educational initiatives, community engagement, and pilot testing of revised codes. Addressing these systemic gaps is essential to improving documentation fidelity, research integrity, and advancing equitable, patient-centered care across diverse populations.

Recommended Citation

Glover EA. Misrepresentation of Female and Gender-Diverse Patients in the ICD and SNOMED CT Systems: A Critical Review. University of Lynchburg DMSc Doctoral Project Assignment Repository. 2026; 8(1).