Temporal and Geographic Patterns of Documentation of Sexual Orientation and Gender Identity Keywords in Clinical Notes.

OBJECTIVE: Disclosure of sexual orientation and gender identity correlates with better outcomes, yet data may not be available in structured fields in electronic health record data. To gain greater insight into the care of sexual and gender-diverse patients in the Veterans Health Administration (VHA), we examined the documentation patterns of sexual orientation and gender identity through extraction and analyses of data contained in unstructured electronic health record clinical notes. METHODS: Salient terms were identified through authoritative vocabularies, the research team's expertise, and frequencies, and the use of consistency in VHA clinical notes. Term frequencies were extracted from VHA clinical notes recorded from 2000 to 2018. Temporal analyses assessed usage changes in normalized frequencies as compared with nonclinical use, relative growth rates, and geographic variations. RESULTS: Over time most terms increased in use, similar to Google ngram data, especially after the repeal of the "Don't Ask Don't Tell" military policy in 2010. For most terms, the usage adoption consistency also increased by the study's end. Aggregated use of all terms increased throughout the United States. CONCLUSION: Term usage trends may provide a view of evolving care in a temporal continuum of changing policy. These findings may be useful for policies and interventions geared toward sexual and gender-diverse individuals. Despite the lack of structured data, the documentation of sexual orientation and gender identity terms is increasing in clinical notes.

Toward Community-Based Natural Language Processing (CBNLP): Cocreating With Communities.

Rapid development and adoption of natural language processing (NLP) techniques has led to a multitude of exciting and innovative societal and health care applications. These advancements have also generated concerns around perpetuation of historical injustices and that these tools lack cultural considerations. While traditional health care NLP techniques typically include clinical subject matter experts to extract health information or aid in interpretation, few NLP tools involve community stakeholders with lived experiences. In this perspective paper, we draw upon the field of community-based participatory research, which gathers input from community members for development of public health interventions, to identify and examine ways to equitably involve communities in developing health care NLP tools. To realize the potential of community-based NLP (CBNLP), research and development teams must thoughtfully consider mechanisms and resources needed to effectively collaborate with community members for maximal societal and ethical impact of NLP-based tools.

Digital Health Equity: Addressing Power, Usability, and Trust to Strengthen Health Systems.

BACKGROUND: Without specific attention to health equity considerations in design, implementation, and evaluation, the rapid expansion of digital health approaches threatens to exacerbate rather than ameliorate existing health disparities. METHODS: We explored known factors that increase digital health inequity to contextualize the need for equity-centered informatics. This work used a narrative review method to summarize issues about inequities in digital health and to discuss future directions for researchers and clinicians. We searched literature using a combination of relevant keywords (e.g., "digital health", "health equity", etc.) using PubMed and Google Scholar. RESULTS: We have highlighted strategies for addressing medical marginalization in informatics according to vectors of power such as race and ethnicity, gender identity and modality, sexuality, disability, housing status, citizenship status, and criminalization status. CONCLUSIONS: We have emphasized collaboration with user and patient groups to define priorities, ensure accessibility and localization, and consider risks in development and utilization of digital health tools. Additionally, we encourage consideration of potential pitfalls in adopting these diversity, equity, and inclusion (DEI)-related strategies.

Will clinical standards not be part of the choir? Harmonization between the HL7 gender harmony project model and the NASEM measuring sex, gender identity, and sexual orientation report in the United States.

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.

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

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.

Gender harmony: improved standards to support affirmative care of gender-marginalized people through inclusive gender and sex representation.

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.

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

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.

An ontology-based review of transgender literature: Revealing a history of medicalization and pathologization.

OBJECTIVES: To evaluate the linguistic changes of transgender-related resources prior to 1999 to create a comprehensive dataset of resources using an ontology-derived search system, laying a framework for ontology-based reviews to be used in informatics. METHODS: We analyzed 77 bibliographies and 11 databases for transgender resources published prior to 31 December 1999. We used 858 variants of the term "transgender" to identify resources. Individual sources were tagged by subject matter and major conceptual terminology usage. We evaluated the accuracy of a Gender, Sex, and Sexual Orientation (GSSO) ontology-based mechanism on tagging relevant literature searches. RESULTS: We identified 3,058 sources in 19 languages. Primary subjects covered included surgery, psychology, psychiatry, endocrinology, and sexology. The GSSO-based tagging mechanism correctly tagged 97.7% of MEDLINE resources as transgender-related. DISCUSSION: The GSSO-based tagging mechanism was more effective than keyword-specific elucidations of terminologically complex literature and was just as effective at manual identification of subjects discussed within resources. Diverse language relating to transgender persons can be identified using the GSSO, which can also be used for structured literature review based on subject matter thus improving research in the area.

Implementation of Gender Identity and Assigned Sex at Birth Data Collection in Electronic Health Records: Where Are We Now?

In 2015, the United States Department of Health and Human Services instantiated rules mandating the inclusion of sexual orientation and gender identity (SO/GI) data fields for systems certified under Stage 3 of the Meaningful Use of Electronic Health Records (EHR) program. To date, no published assessments have benchmarked implementation penetration and data quality. To establish a benchmark for a U.S. health system collection of gender identity and sex assigned at birth, we analyzed one urban academic health center's EHR data; specifically, the records of patients with unplanned hospital admissions during 2020 (N = 49,314). Approximately one-quarter of patient records included gender identity data, and one percent of them indicated a transgender or nonbinary (TGNB) status. Data quality checks suggested limited provider literacy around gender identity as well as limited provider and patient comfort levels with gender identity disclosures. Improvements are needed in both provider and patient literacy and comfort around gender identity in clinical settings. To include TGNB populations in informatics-based research, additional novel approaches, such as natural language processing, may be needed for more comprehensive and representative TGNB cohort discovery. Community and stakeholder engagement around gender identity data collection and health research will likely improve these implementation efforts.

Development of the Gender, Sex, and Sexual Orientation ontology: Evaluation and workflow.

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.

Creating a Queer Ontology: The Gender, Sex, and Sexual Orientation (GSSO) Ontology.

Cultural attitudes, linguistic variation, and historical pathology have led to a plethora of terms concerning gender, sex, and sexual orientation that have caused confusion and uneasiness among both lay people and relevant professionals. For members of the LGBTQIA+ community, these negative reactions are compounded by identities which have historically and contemporarily been mistreated by medical professionals. In an effort to provide a reliable resource for patients and clinicians, we have created the Gender, Sex, and Sexual Orientation (GSSO) ontology, which currently includes over 4,000 entities from multiple disciplines. The GSSO is a manually curated resource utilizing related glossaries from biology, medicine, psychology, sociology, and gender studies. With links to over 20 other ontology resources such as SNOMED-CT and MedDRA, the GSSO aims for accessibility and interoperability with existing systems. It is also open-source and features an easy-to-use web interface (https://github.com/Superraptor/GSSO). Future work involves multiple language support efforts and empirical evaluation.