CitationRich, Ashleigh J.; Poteat, Tonia; Koehoorn, Mieke; Li, Jenny; Ye, Monica; Sereda, Paul; Salway, Travis; & Hogg, Robert (2021). Development of a Computable Phenotype to Identify a Transgender Sample for Health Research Purposes: A Feasibility Study in a Large Linked Provincial Healthcare Administrative Cohort in British Columbia, Canada. BMJ Open, 11(3), e040928. PMCID: PMC7996659
AbstractOBJECTIVES: Innovative methods are needed for identification of transgender people in administrative records for health research purposes. This study investigated the feasibility of using transgender-specific healthcare utilisation in a Canadian population-based health records database to develop a computable phenotype (CP) and identify the proportion of transgender people within the HIV-positive population as a public health priority.
DESIGN: The Comparative Outcomes and Service Utilization Trends (COAST) Study cohort comprises a data linkage between two provincial data sources: The British Columbia (BC) Centre for Excellence in HIV/AIDS Drug Treatment Program, which coordinates HIV treatment dispensation across BC and Population Data BC, a provincial data repository holding individual, longitudinal data for all BC residents (1996-2013).
SETTING: British Columbia, Canada.
PARTICIPANTS: COAST participants include 13 907 BC residents living with HIV (≥19 years of age) and a 10% random sample comparison group of the HIV-negative general population (514 952 individuals).
PRIMARY AND SECONDARY OUTCOME MEASURES: Healthcare records were used to identify transgender people via a CP algorithm (diagnosis codes+androgen blocker/hormone prescriptions), to examine related diagnoses and prescription concordance and to validate the CP using an independent provider-reported transgender status measure. Demographics and chronic illness burden were also characterised for the transgender sample.
RESULTS: The best-performing CP identified 137 HIV-negative and 51 HIV-positive transgender people (total 188). In validity analyses, the best-performing CP had low sensitivity (27.5%, 95% CI: 17.8% to 39.8%), high specificity (99.8%, 95% CI: 99.6% to 99.8%), low agreement using Kappa statistics (0.3, 95% CI: 0.2 to 0.5) and moderate positive predictive value (43.2%, 95% CI: 28.7% to 58.9%). There was high concordance between exogenous sex hormone use and transgender-specific diagnoses.
CONCLUSIONS: The development of a validated CP opens up new opportunities for identifying transgender people for inclusion in population-based health research using administrative health data, and offers the potential for much-needed and heretofore unavailable evidence on health status, including HIV status, and the healthcare use and needs of transgender people.
Reference TypeJournal Article
Journal TitleBMJ Open
Author(s)Rich, Ashleigh J.