Culturally Competent Gender, Sex, and Sexual Orientation Information Practices and Electronic Health Records: Rapid Review
Bibliographic record
Abstract
BACKGROUND: Outdated gender, sex, and sexual orientation (GSSO) information practices in health care contribute to health inequities for sexual and gender minorities (SGMs). Governments, statistics agencies, and health care organizations are developing and implementing modernized practices that support health equity for SGMs. Extending our work, we conducted a rapid review of grey literature to explore information practices that support quality health care for SGMs. OBJECTIVE: The aim of this rapid review of grey literature was to elucidate modern GSSO information practices from leading agencies for adaptation, adoption, and application by health care providers and organizations seeking to modernize outdated GSSO information practices that contribute to health inequities among SGMs. METHODS: We searched MEDLINE and Google from 2015 to 2020 with terms related to gender, sex, sexual orientation, and electronic health/medical records for English-language grey literature resources including government and nongovernment organization publications, whitepapers, data standards, toolkits, health care organization and health quality practice and policy guides, conference proceedings, unpublished academic work, and statistical papers. Peer-reviewed journal articles were excluded, as were resources irrelevant to information practices. We also screened the reference sections of included articles for additional resources, and canvassed a working group of international topic experts for additional relevant resources. Duplicates were eliminated. ATLAS.ti was used to support analysis. Themes and codes were developed through an iterative process of writing and discussion with the research team. RESULTS: Twenty-six grey literature resources met the inclusion criteria. The overarching themes that emerged from the literature were the interrelated behaviors, attitudes, and policies that constitute SGM cultural competence as follows: shared language with unambiguous definitions of GSSO concepts; welcoming and inclusive care environments and affirming practices to reduce barriers to access; health care policy that supports competent health care; and adoption of modernized GSSO information practices and electronic health record design requirements that address invisibility in health data. CONCLUSIONS: Health equity for SGMs requires systemic change. Binary representation of sex and gender in electronic health records (EHRs) obfuscates natural and cultural diversity and, in the context of health care, places SGM patients at risk of clinical harm because it leads to clinical assumptions. Agencies and agents in health care need to be equipped with the knowledge and tools needed to cultivate modern attitudes, policies, and practices that enable health equity for SGMs. Adopting small but important changes in the language and terminology used in technical and social health care systems is essential for institutionalizing SGM competency. Modern GSSO information practices depend on and reinforce SGM competency in health care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.097 | 0.293 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.041 | 0.037 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".