Development of Bipolar and Generalized Anxiety Disorder Standard Data Elements

项目总结/摘要 这里提出的工作将导致双相和广泛性焦虑的合成数据元素 疾病，用于人类药物开发和评价。双相情感障碍和广泛性焦虑 疾病是FDA数据标准化的两个优先领域。这项工作的第一个目的是分析数据收集 自2000年以来批准的新药的病例报告表（CRF）， 双相情感障碍或广泛性焦虑障碍，以生成将支持 试验申办者数据收集的一致性。数据元素将由临床专家审查， 与现有标准保持一致。这项工作的第二个目标将作为一个项目提出， HL 7临床互操作性理事会，目的是在信息层面投票作为HL 7标准。 最终，数据元素将通过公共元数据注册表以电子方式提供。该团队将 通过映射到现有术语标准和CDISC SDTM来注释数据元素，进一步 增加对该资源的受管制行业的有用性。本书的第三个也是最后一个目的是探索 与精神卫生监管决策相关的丰富术语，例如，药物术语，结构化的 文档标准，例如，结构化的产品标签，策划的问卷调查，以及探索性的本体论 精神障碍诊断和统计手册双相情感障碍部分的代表， 识别具有标准数据元素的链接。吸链接将增加可以问的问题的类型 来自监管提交的数据。 !

Project Summary/Abstract The work proposed here will result in synthesized data elements for Bipolar and Generalized Anxiety Disorders, for use in human drug development and evaluation. Bipolar Disorder and Generalized Anxiety Disorder are two FDA priority areas for data standardization. The first aim of this work analyzes data collection forms (Case Report Forms (CRFs)) from new drugs approved since 2000 with an approved indication in Bipolar Disorder or Generalized Anxiety Disorder, to generate a master data element set that will support consistency in data collection by trial sponsors. The data elements will be vetted with clinical experts and harmonized with existing standards. The second aim of this work will be brought forward as a project in the HL7 Clinical Interoperability Council with the intent of balloting as an HL7 standard at the informative level. Ultimately, the data elements will be publically available through a public metadata registry. The team will annotate the data elements with mapping to existing terminology standards and to the CDISC SDTM, further increasing usefulness to the regulated industry of this resource. The third and final aim of this work explores rich terminologies relevant to regulatory decision-making in mental health, e.g., drug terminologies, structured document standards, e.g., structured product label, curated questionnaires, and an exploratory ontological representation of the Bipolar Disorder section of the Diagnostic and Statistical Manual of Mental Disorders, to identify links with standard data elements. Suck links will increase the types of questions that can be asked of data from regulatory submissions. !