Harnessing Electronic Health Records to Identify Participants and to Study Health Outcomes in Transition-Age Youth and Adults with Autism Spectrum Disorder

自闭症谱系障碍(ASD)患者的保健需求是复杂和多方面的， 获得优质医疗服务是一项重大挑战。同时发生的身体和精神健康状况高度 流行于过渡期青少年(Tay)和患有自闭症的成年人。治疗这些情况代表着一个重要的 为改善这一人群的生活质量而修建的大道。基于提供商的培训计划，如项目 扩展社区卫生保健成果(Echo项目)已被证明可以增加提供者 知识自我效能感，尽管它们对卫生保健结果和卫生保健利用的影响 成人ASD的研究还不够深入。 这个K18应用程序的总体目标是提供与以下相关的医疗服务研究培训 Tay/成人自闭症患者，专门专注于利用电子健康记录(EHR)中的数据进行研究 未来干预研究中的健康结果。这些技能是设计和实施 Echo项目的严格未来试验是Tay/成人ASD。在K18中，我将在以下位置使用确定的数据集 范德比尔特大学医学中心(VUMC)和北加州凯撒永久医院(KPNC)。我的 研究的具体目标是(1)确定应用新算法识别和 在VUMC确定的EHR中描述患有ASD的Tay/成年人的病例，并(2)分析有多常见 老年人身心健康状况及卫生服务利用措施随年龄增长的变化 KPNC EHR中现有的患有ASD的Tay/成人纵向队列。 我的培训目标是(1)学习如何使用实用工具，如自然语言处理和 Pheccodes，以识别患有ASD和共生疾病的Tay/成年人，以及(2)学习如何分析 纵向健康数据。我将通过KPNC和KPNC的Lisa Croen博士提供的指导获得此培训 当我进行我的研究项目时，VUMC的Jeffrey Neul博士和Lea Davis博士。中的正式课程作业 生物信息学和流行病学，以及负责任的研究行为，将增强我的实践 经验。VUMC和KPNC提供的环境非常适合进行这种培训，因为 这两个机构都在进行尖端的电子病历相关研究。考虑到拟议的使用情况，该项目具有创新性 识别和表征成人自闭症的新工具，以及拟议的分析 与健康状况和卫生保健利用有关的纵向电子健康记录数据。

The health care needs of individuals with autism spectrum disorder (ASD) are complex and multifaceted, with access to quality care a major challenge. Co-occurring physical and mental health conditions are highly prevalent in transition-age youth (TAY) and adults with ASD. Treating these conditions represents an important avenue for improving quality of life in this population. Provider-based training programs, such as Project Extension for Community Health Care Outcomes (Project ECHO), has been shown to increase provider knowledge self-efficacy, although their impact on health care outcomes and health care utilization in TAY/adults with ASD is understudied. The overarching goal of this K18 application is to provide training in health services research related to TAY/adults with ASD, specifically focused on harnessing data from electronic health records (EHR) to study health outcomes in future interventional studies. These skills are preparatory to designing and carrying out a rigorous future trial of Project ECHO is TAY/adults with ASD. In the K18, I will use deidentified datasets at Vanderbilt University Medical Center (VUMC) and Kaiser-Permanente Northern California (KPNC). My research specific aims are (1) Determine the utility of applying novel algorithms for identifying and characterizing cases of TAY/adults with ASD within the VUMC deidentified EHR and (2) Analyze how common physical and mental health conditions and measures of health care utilization change with increasing age in in an existing longitudinal cohort of TAY/adults with ASD within the KPNC EHR. My training goals are (1) Learn how to use pragmatic tools, such as natural language processing and phecodes, to identify TAY/adults with ASD and co-occurring conditions and (2) Learn how to analyze longitudinal health data. I will obtain this training through mentorship provided by Dr. Lisa Croen of KPNC and Drs. Jeffrey Neul and Lea Davis of VUMC as I conduct my research project. Formal coursework in Bioinformatics and Epidemiology, along with Responsible Conduct of Research, will enhance my practical experience. The environment provided by VUMC and KPNC is ideal for this training, given the expertise of both institutions in cutting-edge EHR-related research. The project is innovative given the proposed use of novel tools for identification and characterization of TAY/adults with ASD, and the proposed analysis of longitudinal EHR data related to health conditions and health care utilization.