Objective: To create a natural language pro­cessing (NLP) algorithm to identify transgen­der patients in electronic health records.Design: We developed an NLP algorithm to identify patients (keyword + billing codes). Patients were manually reviewed, and their health care services categorized by billing code.Setting: Vanderbilt University Medical CenterParticipants: 234 adult and pediatric trans­gender patientsMain Outcome Measures: Number of transgender patients correctly identified and categorization of health services utilized.Results: We identified 234 transgender pa­tients of whom 50% had a diagnosed men­tal health condition, 14% were living with HIV, and 7% had diabetes. Largely driven by hormone use, nearly half of patients attended the Endocrinology/Diabetes/Me­tabolism clinic. Many patients also attended the Psychiatry, HIV, and/or Obstetrics/Gyne­cology clinics. The false positive rate of our algorithm was 3%.Conclusions: Our novel algorithm correctly identified transgender patients and provided important insights into health care utiliza­tion among this marginalized population. Ethn Dis. 2019;29(Suppl 2): 441-450. doi:10.18865/ed.29.S2.441

We conducted in-depth, semi-structured interviews with LGBTQ+-identified individuals (n = 31) to explore the range of LGBTQ+ perspectives on genomic research using either sexual orientation or gender identity (SOGI) data. Most interviewees presumed that research would confirm genetic contributions to sexual orientation and gender identity. Primary hopes for such confirmation included validating LGBTQ+ identities, improved access to and quality of healthcare and other resources, and increased acceptance in familial, socio-cultural, and political environments. Areas of concern included threats of pathologizing and medicalizing LGBTQ+ identities and experiences, undermining reproductive rights, gatekeeping of health or social systems, and malicious testing or misuse of genetic results, particularly for LGBTQ+ youth. Overall, interviewees were divided on the acceptability of genomic research investigating genetic contributions to sexual orientation and gender identity. Participants emphasized researchers’ ethical obligations to LGBTQ+ individuals and endorsed engagement with LGBTQ+ communities throughout all aspects of genomic research using SOGI data.

Transgender and nonbinary (TNB) individuals experience significant marginalization, including in the workplace and higher education. Although the number of TNB scholars and educators is growing, little attention has been given to the supervision of TNB individuals in research contexts. This lack of attention is particularly pronounced for TNB people working on trans-related research projects. Using intersectionality and queer theory, the present study examines the lived experiences of TNB individuals working on cisgender-led research projects, with the goal of enhancing awareness among cisgender researchers on strategies to support the growth of emerging TNB scholars. The importance of these findings is relevant for cisgender educators, researchers, and practitioners who work with TNB individuals and/or lead trans-related projects.