Leveraging Big Data for Transgender and Gender Minority Health Equity Research

项目总结 性别少数群体的健康差距和保健障碍(即变性人、性别不一致、 非二元、双性人和其他少数族裔性别认同)已被确定并作为目标 许多组织和机构，包括美国国立卫生研究院，都在消灭这种病毒。一个不断增长的 大量研究表明，性别少数群体在各个领域普遍受到歧视和耻辱。 环境(例如，医疗保健、就业、住房、公共住宿和教育)--这对 影响他们的身体、心理、行为和社会健康。更令人担忧的是缺乏强劲的数据 为监测美国性别少数群体的健康需求所需的收集工作。 该项目的目标是发展世界上最大的性别少数(GM)患者队列，使用私人 包含超过330亿条索赔记录和超过1.5亿条保险的医疗保险索赔数据 住在美国。使用来自Fair Health(由提交的私人保险索赔存储库)的数据 超过60个国家和地区付款人和第三方管理人)，该项目将识别、描述和 比较健康结果、健康服务利用率和健康的社会决定因素 转基因和非转基因患者的队列。我们还将评估国家政策环境和 在公平的健康数据中转基因患者和非转基因患者之间的健康差异。最后，我们将确定一个纵向的 随着时间的推移，转基因和非转基因个人的队列将被跟踪。这个项目将带来新的发现 了解全球机制的健康结果、健康服务利用情况和健康的社会决定因素 在美国的人们。

PROJECT SUMMARY Health disparities and barriers to health care for gender minorities (i.e., transgender, gender non-conforming, non-binary, intersex individuals, and other minority gender identities) have been identified and targeted for elimination by numerous organizations and agencies, including the National Institutes of Health. A growing body of research indicates that gender minorities experience widespread discrimination and stigma in various contexts (e.g., health care, employment, housing, public accommodations, and education) — which negatively affects their physical, mental, behavioral, and social health. More concerning is the absence of robust data collection efforts needed to monitor the health needs of gender minority (GM) populations in the United States. The goal of this project is to develop the world’s largest cohort of gender minority (GM) patients using private health insurance claims data that contains more than 33 billion claim records and over 150 million covered lives in the United States. Using data from FAIR Health (a repository of private insurance claims submitted by over 60 national and regional payors and third-party administrators), this project will identify, describe, and compare health outcomes, health services utilization, and the social determinants of health between a matched cohort of GM and non-GM patients. We will also evaluate correlations between state policy environments and health disparities between GM and non-GM patients in FAIR Health data. Finally, we will identify a longitudinal cohort of GM and non-GM individuals to follow over time. This project will lead to new discoveries in understanding health outcomes, health services utilization, and the social determinants of health for GM people in the United States.