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Scalable decision support and shared decision making for lung cancer screening

Scalable decision support and shared decision making for lung cancer screening
肺癌筛查的可扩展决策支持和共享决策
批准号:
9793912
负责人:
Kensaku Kawamoto
金额:
$39.63万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-07-01 至 2022-04-30

项目摘要

项目成果

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中文摘要
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英文摘要
PROJECT SUMMARY Lung cancer is the second most commonly diagnosed cancer in the United States, and it is the leading cause of cancer-related deaths among both men and women. A screening test known as low-dose computed tomography (LDCT) can detect lung cancer early and reduce lung cancer deaths among individuals with a history of heavy smoking, but this test requires patients and their physicians to consider potential benefits and harms that differ according to each patient’s individual risk profile, and less than 5% of eligible patients receive the screening every year. This project will address this urgent need by analyzing patients’ electronic health records, prompting eligible patients and their physicians to consider lung cancer screening, and providing individually-tailored information on the potential benefits and harms of lung cancer screening, so that patients and their physicians can make informed, patient-centered decisions regarding this potentially life-saving test. This project will build off of a stand-alone tool for LDCT shared decision making that has been progressively enhanced by the project team through real-world clinical use, and it will be fully integrated with the electronic health record (EHR) so that it can pull in relevant patient risk data and be seamlessly integrated with routine clinical workflows. This tool, which we call Decision Precision+, will present individually-tailored information on the potential benefits and harms of screening, enabling patients and their physicians to make informed and patient-centered decisions on whether to screen for lung cancer through LDCT testing. Additional tools will also be developed for prompting use of Decision Precision+ for eligible patients and for collecting required smoking history when it is missing. Following its design and development, Decision Precision+ will be implemented and evaluated at the primary care clinics of University of Utah Health. Decision Precision+ will also be made available to other healthcare organizations as a free tool that can be downloaded and used with their own EHR systems. The project team will support the use of Decision Precision+ by other healthcare organizations, so that as many patients as possible can benefit from appropriate LDCT testing and associated reductions in deaths due to lung cancer.
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会议论文
Engaging patients to enable interoperable lung cancer decision support at scale
  • 批准号:
    10621197
  • 项目类别:
  • 资助金额:
    $99.38万
  • 财政年份:
    2022
  • 负责人:
    Kensaku Kawamoto
  • 依托单位:
Engaging patients to enable interoperable lung cancer decision support at scale
  • 批准号:
    10410792
  • 项目类别:
  • 资助金额:
    $99.45万
  • 财政年份:
    2022
  • 负责人:
    Kensaku Kawamoto
  • 依托单位:
Enabling Personalized Medicine through Clincal Decision Support
  • 批准号:
    7449085
  • 项目类别:
  • 资助金额:
    $18.08万
  • 财政年份:
    2008
  • 负责人:
    Kensaku Kawamoto
  • 依托单位:
Enabling Personalized Medicine through Clincal Decision Support
  • 批准号:
    7681707
  • 项目类别:
  • 资助金额:
    $18.68万
  • 财政年份:
    2008
  • 负责人:
    Kensaku Kawamoto
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
补偿性还是非补偿性规则:探析风险决策的行为与神经机制
  • 批准号:
    31170976
  • 项目类别:
    面上项目
  • 资助金额:
    64.0万元
  • 批准年份:
    2011
  • 负责人:
    李纾
  • 依托单位:
基于神经营销学方法的品牌延伸认知与决策研究
  • 批准号:
    70772048
  • 项目类别:
    面上项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2007
  • 负责人:
    马庆国
  • 依托单位: