A Computable Phenotype Model for Classification of Men Who Have Sex With Men Within a Large Linked Database of Laboratory, Surveillance, and Administrative Healthcare Records.

Most public health datasets do not include sexual orientation measures, thereby limiting the availability of data to monitor health disparities, and evaluate tailored interventions. We therefore developed, validated, and applied a novel computable phenotype model to classify men who have sex with men (MSM) using multiple health datasets from British Columbia, Canada, 1990-2015. Three case surveillance databases, a public health laboratory database, and five administrative health databases were linked and deidentified (BC Hepatitis Testers Cohort), resulting in a retrospective cohort of 727,091 adult men. Known MSM status from the three disease case surveillance databases was used to develop a multivariable model for classifying MSM in the full cohort. Models were selected using "elastic-net" (GLMNet package) in R, and a final model optimized area under the receiver operating characteristics curve. We compared characteristics of known MSM, classified MSM, and classified heterosexual men. History of gonorrhea and syphilis diagnoses, HIV tests in the past year, history of visit to an identified gay and bisexual men's clinic, and residence in MSM-dense neighborhoods were all positively associated with being MSM. The selected model had sensitivity of 72%, specificity of 94%. Excluding those with known MSM status, a total of 85,521 men (12% of cohort) were classified as MSM. Computable phenotyping is a promising approach for classification of sexual minorities and investigation of health outcomes in the absence of routinely available self-report data.