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

Objectives 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.