PROJECT SUMMARY Transgender (TG) individuals have high prevalence of depression (64%) and are nearly nine times as likely to attempt suicide compared to the general population. Studies have not consistently collected data related to TG identity nor have they used the recommended two-step method of asking for assigned sex at birth and current gender identity. This population is largely overlooked in epidemiologic studies due to small sample size. With inconsistent and inaccurate ascertainment of TG patients in real-world data sources, TG people are missed and their health trends over time are understudied. Researchers are unable to identify and meaningfully address mental health inequities for this population, which can further exacerbate and perpetuate psychiatric conditions. It remains unclear what the health care utilization trends are for TG patients with psychiatric disorders and their adherence and persistence to psychiatric medications over time. Understanding this population’s mental health using large datasets is imperative in order to optimize the care management of psychiatric conditions experienced by TG people. The objectives of this proposal are to: (1) apply and evaluate the performance of existing computational phenotypes (CPs) to identify TG patients with depressive disorders (DD), anxiety, and attention deficit disorders (ADD), (2) assess adherence and prevalence of psychiatric medications among TG patients diagnosed with psychiatric disorders compared to cisgender patients with these diagnoses, and (3) examine the risk of non-fatal self-harm among TG patients with psychiatric disorders receiving psychotherapy compared to TG patients not receiving psychotherapy. For all aims, IBM MarketScan from years 2008 to 2020 will be used, which is a large, longitudinal medical claims database that includes inpatient and outpatient visits and prescription medication use. The completion of the proposed aims will provide real-world evidence on mental health care for TG individuals in the United States. The training plan outlined in this proposal will equip the applicant with critical knowledge and necessary skills in social and pharmacoepidemiology and transgender mental health. This plan will prepare him to successfully complete the proposed aims and to progress into a role as an independent, interdisciplinary researcher studying the intersection of pharmacoepidemiology and transgender health equity in the US. The applicant is extremely well supported by an interdisciplinary group of social, psychiatric, and pharmacoepidemiology faculty, health disparities researchers, and pharmaceutical researchers with the requisite expertise to support his doctoral research and prepare him for the next phase of his career.

PROJECT NARRATIVE The utilization trends of mental health services among transgender (TG) people are poorly understood due to the limited sample sizes, yet there are increased efforts to identify TG people within large electronic health care data using computational phenotypes (CPs). Through this proposed research and training plan, the applicant will investigate the performance of existing CPs to assess the health care utilization trends of TG patients with depressive disorders (DD), anxiety, and attention deficit disorders (ADD) and their risk of self-harm. Ultimately, the results of this work can inform future mental health care policy and public health officials to inform interventions and improve mental health equity among this understudied population.