OBJECTIVE: To determine how much of the current biomedical literature would be flagged or require modification in relation to the presence of terms from leaked lists prepared by the Centers for Disease Control (CDC), the National Science Foundation (NSF), and the National Security Administration (NSA) in early 2025. MATERIALS AND METHODS: We searched PubMed (from 1996 to 2024) for all records that match at least one of the given terms, combined the terms and analyzed yearly and total frequency. RESULTS: At least 36.3% of all biomedical literature analyzed, representing more than 10 million records, would be flagged for review or modification with the given term lists. It is conservatively estimated that such term lists could impact more than 2.7 million biomedical publications over the next four years. DISCUSSION: Censorship of scientific findings and the use of term lists to judge the content of scientific materials could significantly impede scientific progress. CONCLUSION: Future research should investigate the long-term implications of, and interim strategies used to navigate, the imposition of censorship on the production and dissemination of scientific knowledge.

OBJECTIVES: In 2023, AMIA's Inclusive Language and Context Style Guidelines (the "Guidelines") were approved by the Board of Directors and made a publicly available resource. This work began in 2021 through AMIA's DEI Task Force and subsequent DEI Committee; many members provided input, feedback, and time to create the Guidelines. In this paper, the authors provide a transparent account of the origin, development, contents, and dissemination of the Guidelines and share plans for their future development and use. MATERIALS AND METHODS: Our approach to drafting, refining, and distributing the Guidelines included consulting existing language guides, AMIA member reviews, external expert reviews, webinars, and workshops. Through an iterative approach to drafting and refining the Guidelines, the authors consulted relevant language guidelines and many experts throughout and beyond the AMIA community. RESULTS: The Inclusive Language Context Guidelines were formally approved by the AMIA Board of Directors on February 15, 2023. The Guidelines included four principles to be considered in scientific communications: Plurality, Precision, Transparency, and Destigmatization. DISCUSSION: A moment of vulnerability where an AMIA member raised concerns about the use of harmful language during a presentation resulted in the creation of a principled approach to support inclusive language within biomedical and health informatics communications. We envision that the Guidelines will support health equity by challenging dominant public narratives around health, fostering stronger interdisciplinary collaboration and critical thinking about the impact of language, and creating a more welcoming environment for the broader AMIA community. This work could not have been completed without the support of many AMIA members and other researchers in biomedical and health informatics. The Guidelines are a living document that will continue to be updated with input and feedback from the AMIA community into the future.

OBJECTIVES: To propose an approach for semantic and functional data harmonization related to sex and gender constructs in electronic health records (EHRs) and other clinical systems for implementors, as outlined in the National Academies of Sciences, Engineering, and Medicine (NASEM) report Measuring Sex, Gender Identity, and Sexual Orientation and the Health Level 7 (HL7) Gender Harmony Project (GHP) product brief "Gender Harmony-Modeling Sex and Gender Representation, Release 1." MATERIALS AND METHODS: Authors from both publications contributed to a plan for data harmonization based upon fundamental principles in informatics, including privacy, openness, access, legitimate infringement, least intrusive alternatives, and accountability. RESULTS: We propose construct entities and value sets that best align with both publications to allow the implementation of EHR data elements on gender identity, recorded sex or gender, and sex for clinical use in the United States. We include usability- and interoperability-focused reasoning for each of these decisions, as well as suggestions for cross-tabulation for populations. DISCUSSION AND CONCLUSION: Both publications agree on core approaches to conceptualization and measurement of sex- and gender-related constructs. However, some clarifications could improve our ability to assess gender modality, alignment (or lack thereof) between gender identity and assigned gender at birth, and address both individual-level and population-level health inequities. By bridging the GHP and NASEM recommendations, we provide a path forward for implementation of sex- and gender-related EHR elements. Suggestions for implementation of gender identity, recorded sex or gender, and sex for clinical use are provided, along with semantic and functional justifications.

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.

OBJECTIVE: Accurate representation of clinical sex and gender identity in interoperable clinical systems is a major challenge for organizations intent on improving outcomes for sex- and gender-marginalized people. Improved data collection has been hindered by the historical approach that presumed a single, often binary, datum was sufficient. We describe the Health Level Seven International (HL7) Gender Harmony logical model that proposes an improved approach. MATERIALS AND METHODS: The proposed solution was developed via an American National Standards Institute (ANSI)-certified collaborative balloted process. As an HL7 Informative Document, it is an HL7 International-balloted consensus on the subject of representing sex and representing gender in clinical systems based on work of the gender harmony project led by the HL7 Vocabulary Work Group. RESULTS: The Gender Harmony Model is a logical model that provides a standardized approach that is both backwards-compatible and an improvement to the meaningful capture of gender identity, recorded sex or recorded gender, a sex for clinical use, the name to use, and pronouns that are affirmative and inclusive of gender-marginalized people. CONCLUSION: Most clinical systems and current standards in health care do not meaningfully address, nor do they consistently represent, sex and gender diversity, which has impeded interoperability and led to suboptimal health care. The Gender Harmony Project was formed to create more inclusive health information exchange standards to enable a safer, higher-quality, and embracing healthcare experience. The Gender Harmony Model provides the informative guidance for standards developers to implement a more thorough technical design that improves the narrow binary design used in many legacy clinical systems.

Journal of the American Medical Informatics Association, ocab196, https://doi.org/10.1093/jamia/ocab196 In the originally published version of this manuscript, there were several errors, which are listed in this corrigendum as follows: The acronym “SCFU” in the sections “Sex and gender in clinical systems”, “Health Level 7 Version 2”, “Digital Imaging and Communications in Medicine” and “Gender harmony logical model elements” should read “SFCU”. The acronym “2SLGBTQIA+” which appears in the “Background” section has been added to “Table 1: Glossary of additional key terms” with the following definition “acronym meaning two-spirit, lesbian, gay, bisexual, transgender, queer, intersexual, asexual, while “+” indicates that some individuals may express gender and sexuality in others ways”. These have been corrected online.

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.

OBJECTIVE: The study sought to create an integrated vocabulary system that addresses the lack of standardized health terminology in gender and sexual orientation. MATERIALS AND METHODS: We evaluated computational efficiency, coverage, query-based term tagging, randomly selected term tagging, and mappings to existing terminology systems (including ICD (International Classification of Diseases), DSM (Diagnostic and Statistical Manual of Mental Disorders ), SNOMED (Systematized Nomenclature of Medicine), MeSH (Medical Subject Headings), and National Cancer Institute Thesaurus). RESULTS: We published version 2 of the Gender, Sex, and Sexual Orientation (GSSO) ontology with over 10 000 entries with definitions, a readable hierarchy system, and over 14 000 database mappings. Over 70% of terms had no mapping in any other available ontology. DISCUSSION: We created the GSSO and made it publicly available on the National Center for Biomedical Ontology BioPortal and on GitHub. It includes clarifications on over 200 slang terms, 190 pronouns with linked example usages, and over 200 nonbinary and culturally specific gender identities. CONCLUSIONS: Gender and sexual orientation continue to represent crucial areas of medical practice and research with evolving terminology. The GSSO helps address this gap by providing a centralized data resource.