{"doi":"10.1101/2020.08.04.20168161","title":"Developing and Validating a Computable Phenotype for the Identification of Transgender and Gender Nonconforming Individuals and Subgroups","abstract":"Abstract Transgender and gender nonconforming (TGNC) individuals face significant marginalization, stigma, and discrimination. Under-reporting of TGNC individuals is common since they are often unwilling to self-identify. Meanwhile, the rapid adoption of electronic health record (EHR) systems has made large-scale, longitudinal real-world clinical data available to research and provided a unique opportunity to identify TGNC individuals using their EHRs, contributing to a promising routine health surveillance approach. Built upon existing work, we developed and validated a computable phenotype (CP) algorithm for identifying TGNC individuals and their natal sex (i.e., male-to-female or female-to-male) using both structured EHR data and unstructured clinical notes. Our CP algorithm achieved a 0.955 F1-score on the training data and a perfect F1-score on the independent testing data. Consistent with the literature, we observed an increasing percentage of TGNC individuals and a disproportionate burden of adverse health outcomes, especially sexually transmitted infections and mental health distress, in this population.","journal":"medRxiv","year":2020,"id":119924,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":14,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9468,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":322718,"name":"Xing He","orcid":"0000-0003-0290-8058","position":1,"is_corresponding":false},{"id":285592,"name":"Tianchen Lyu","orcid":"0000-0002-0981-3847","position":2,"is_corresponding":false},{"id":322719,"name":"Hansi Zhang","orcid":"0000-0003-4585-0888","position":3,"is_corresponding":false},{"id":285007,"name":"Yonghui Wu","orcid":"0000-0002-6780-6135","position":4,"is_corresponding":false},{"id":263948,"name":"Xi Yang","orcid":"0000-0003-2981-3972","position":5,"is_corresponding":false},{"id":233707,"name":"Zhaoyi Chen","orcid":"0000-0002-4062-0867","position":6,"is_corresponding":false},{"id":556130,"name":"Merry Jennifer Markham","orcid":"0000-0003-3567-3494","position":7,"is_corresponding":false},{"id":473951,"name":"François Modave","orcid":"0000-0003-4366-0757","position":8,"is_corresponding":false},{"id":556131,"name":"Mengjun Xie","orcid":"0000-0001-5089-9614","position":9,"is_corresponding":false},{"id":23319,"name":"William R. Hogan","orcid":"0000-0002-9881-1017","position":10,"is_corresponding":false},{"id":285594,"name":"Christopher A. Harle","orcid":"0000-0002-4803-3632","position":11,"is_corresponding":false},{"id":284551,"name":"Elizabeth Shenkman","orcid":"0000-0003-4903-1804","position":12,"is_corresponding":false},{"id":23318,"name":"Jiang Bian","orcid":"0000-0002-2238-5429","position":13,"is_corresponding":false},{"id":263949,"name":"Yi Guo","orcid":"0000-0003-0587-4105","position":0,"is_corresponding":true}],"reference_count":15,"raw_metadata":null,"created_at":"2026-07-18T23:14:13.002105Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}