Applying Computational Phenotypes To Assess Mental Health Disorders Among Transgender Patients in the United States

项目总结 变性人(TG)抑郁的患病率很高(%)，而且患抑郁症的可能性几乎是前者的九倍 与普通人群相比，企图自杀的人数更多。研究并没有始终如一地收集与TG相关的数据 他们也没有使用推荐的两步法，即在出生时和现在询问指定的性别 性别认同。由于样本量小，这一人群在流行病学研究中很大程度上被忽视了。使用 TG患者在真实数据来源中的不一致和不准确的确定，TG人被怀念 随着时间的推移，他们的健康趋势还没有得到充分的研究。研究人员无法确定和有意义的 解决这一人群的心理健康不平等问题，这可能会进一步加剧和延续精神病 条件。目前尚不清楚患有精神疾病的TG患者的医疗保健利用趋势是什么 随着时间的推移，精神障碍及其对精神药物的坚持和坚持。理解这一点 为了优化护理管理，利用大数据集进行人群心理健康研究势在必行 TG人群所经历的精神状况。 该方案的目标是：(1)应用和评估现有计算模型的性能 表型(CP)用于识别患有抑郁障碍(DD)、焦虑和注意力缺陷的TG患者 精神障碍(ADD)，(2)评估TG患者的精神药物依从性和流行率 被诊断为精神障碍的患者与患有这些诊断的顺性患者进行比较，以及(3) 检查接受甘油三酯治疗的精神障碍患者中非致命性自残的风险 心理治疗与未接受心理治疗的TG患者进行比较。对于所有AIMS，IBM MarketScan来自 将使用2008至2020年，这是一个大型的纵向医疗索赔数据库，包括 住院和门诊就诊和处方药使用。完成建议的目标后， 为美国的TG个人提供关于心理健康护理的真实证据。 本建议书中概述的培训计划将使申请者具备重要的知识和必要的 具备社会和药物流行病学以及变性人心理健康方面的技能。这项计划将使他做好准备 成功完成建议的目标，并成为独立、跨学科的角色 研究美国药物流行病学和变性人健康公平交叉的研究人员。 申请人得到了一个由社会、精神病学和其他学科组成的跨学科小组的大力支持 药物流行病学教员、健康差距研究人员和药物研究人员 必要的专业知识来支持他的博士研究，并为他职业生涯的下一阶段做好准备。

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.