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中文摘要
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描述(由申请人提供):本提案是对PHS 2007-2 NIDA主题“用于临床试验数据收集和管理的电子数据捕获系统开发自动化”的回应。我们建议开发电子数据捕获自动化开发(AD-EDC)系统,这是一套图形工具和自动化软件应用程序,将有助于简化,自动化,标准化,并降低创建和报告药物滥用临床试验中使用的研究仪器的成本。该项目的主要目标是开发以下技术:(1)显著降低开发用于临床试验的电子数据捕获(EDC)仪器所涉及的成本和错误;(2)显著减少报告和分享研究结果所涉及的成本和错误;(3)与广泛的信息系统和商用、现成的临床试验管理系统(CTMS)进行互操作,并利用临床数据交换标准联盟(CDISC)标准;(4)为非技术、临床用户提供一个易于使用的系统,包括可访问性支持,这将允许视觉、听觉、身体和认知障碍的用户有效地参与临床试验。第一阶段的研究工作将集中于定义AD-EDC系统的高级架构,细化AD-EDC软件组件的功能规范和用户界面设计,定义电子数据字典的开放格式,并进行成本效益分析,以证明通过软件自动化和计算机辅助设计工具,该项目的具体目标是可行的。第二阶段的工作将集中于实现研究设计工具、研究报告工具和系统互操作性组件的完整集合,这些将是实现项目目标所必需的。在第二阶段结束时,AD-EDC系统将在多种现实世界的临床环境中进行试点测试,并进行成本效益分析,以验证该系统是否达到了项目目标。
英文摘要
DESCRIPTION (provided by applicant): This proposal is in response to PHS 2007-2 NIDA Topic "Automation of the Development of Electronic Data Capture System for Clinical Trials Data Collection and Management". We propose to develop the Automated Development of Electronic Data Capture (AD-EDC) System, a set of graphical tools and automated software applications that will help simplify, automate, standardize, and reduce the cost of creating and reporting the research instruments used in substance abuse clinical trials. The main objectives of the project are to develop technologies that will: (1) significantly reduce the costs and errors involved in developing electronic data capture (EDC) instruments for clinical trials; (2) significantly reduce the costs and errors involved in reporting and sharing study results; (3) interoperate with a wide-range of information systems and commercial, off-the-shelf clinical trial management systems (CTMS) and utilize Clinical Data Interchange Standards Consortium (CDISC) standards; and (4) provide non-technical, clinical users an easy to use system that includes accessibility support, which will allow users with visual, hearing, physical, and cognitive impairments to effectively participate in clinical trials. The Phase I research effort will focus on defining a high-level architecture for the AD-EDC System, refining functional specifications and user interface designs for the AD-EDC software components, defining an open format for electronic data dictionaries, and performing a cost-benefit analysis to demonstrate that, through software automation and computer-assisted design tools, the project's specific aims are feasible. The Phase II effort will focus on implementing the complete set of study design tools, study reporting tools, and system interoperability components that will be necessary to achieve the project's aims. At the end of Phase II, the AD-EDC System will be pilot tested in a diverse set of real-world clinical settings and a cost-benefit analysis will be performed to validate that the system achieves the project aims. PUBLIC HEALTH RELEVANCE: The AD-EDC System consists of set of graphical tools and automated software modules that will help simplify, automate, standardize, and reduce the cost of creating and reporting clinical research instruments used in substance abuse clinical trials. The AD-EDC System is designed to interoperate with commercial, off-the-shelf clinical trials management systems either through a standard CDISC- compliant ODM interface or through custom external system adapters. Standard data representations based on CDISC standards are used by the tools and components of the AD-EDC System to support interoperability and persistence.
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Deep-CDS: Deep Learning Semantic Data Lake for Clinical Decision Support
  • 批准号:
    10546333
  • 项目类别:
  • 资助金额:
    $25.35万
  • 财政年份:
    2022
  • 负责人:
    Mansur R. Kabuka
  • 依托单位:
Deep-CDS: Deep Learning Semantic Data Lake for Clinical Decision Support
  • 批准号:
    10747223
  • 项目类别:
  • 资助金额:
    $71.43万
  • 财政年份:
    2022
  • 负责人:
    Mansur R. Kabuka
  • 依托单位:
Microbiome Meta-Analysis Platform
  • 批准号:
    10011865
  • 项目类别:
  • 资助金额:
    $29.38万
  • 财政年份:
    2017
  • 负责人:
    Mansur R. Kabuka
  • 依托单位:
Semantic Data Lake for Biomedical Research
  • 批准号:
    9536289
  • 项目类别:
  • 资助金额:
    $58.97万
  • 财政年份:
    2016
  • 负责人:
    Mansur R. Kabuka
  • 依托单位:
海外基金