Clinical Decision Support for Unsolicited Genomic Results

主动提供的基因组结果的临床决策支持

• 批准号: 10318291
• 负责人: CASEY OVERBY TAYLOR
• 金额: $ 7.39万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10318291
• 关键词: Address; Adopted; Adoption; Area; Award; Clinical; Committee Members; Custom; Data; Diagnosis; Disease; Ensure; Feedback; Focus Groups; Future; Genomic medicine; Genomics; Goals; Health; Health Personnel; Health system; Healthcare; Individual; Infrastructure; Institution; Institutional Policy; Learning; Modeling; Motion; National Human Genome Research Institute; Outcome; Patients; Persons; Pharmacy and Therapeutics Committee; Prevention; Process; Recommendation; Research; Research Methodology; Risk; Role; Science; Structure; Surveys; System; Test Result; Testing; Time; Time and Motion Studies; Vision; Work; adverse drug reaction; base; clinical care; clinical decision support; computerized tools; dashboard; design; evidence base; genetic makeup; genomic data; health care settings; implementation science; improved; innovation; interest; meetings; preference; programs; provider adoption; research study; social; usability

PROJECT SUMMARY As healthy individuals increasingly can receive genomic testing results that indicate their risk for poor outcomes (e.g. diseases or adverse drug reactions), healthcare providers will need to ensure that the results are handled prudently, by addressing the receipt of the results, the workflow challenges, and liability issues. Given that clinical genomic tests can be initiated outside of the clinical setting (e.g., in a research study), from the clinician’s perspective, they can be characterized as unsolicited genomic results (UGR). Clinical decision support (CDS) has great potential to ease the adoption of UGR by providing clinicians with recommendations and patient-related information presented at particular times to enhance clinical care. Deploying CDS for UGR in a healthcare setting in a scalable way, however, will depend on our capacity to leverage local institutional policy and oversight structures to approve of CDS guidance and strategies for UGR. The specific objective of this research program is to develop and evaluate the Evidence-based Decision support Implementation over Time (EDIT) model for prioritizing and revising deployed CDS for UGR. The EDIT model will empower local oversight committees such as Pharmacy & Therapeutics committees to have a role in the CDS review and deployment processes within existing institutional social systems using accepted organizational processes. The direct benefits of this work will be an EDIT dashboard that can be used by oversight committees to prioritize new and to revise deployed CDS, and infrastructure to close the loop of the learning health system by transferring CDS revisions approved by oversight committee members into deployed CDS for UGR. EDIT model implementation will be informed by mixed methods research strategies: Strategy 1, we will conduct focus groups with oversight committee members in order to understand current roles, tasks and goals of the committee, as well as to capture opinions about the best processes to prioritize, review and approve of new and revised CDS for UGR as part of committee meeting activities. Research Strategy 2, we will conduct a survey study with patients to assess preferences for the return of UGR with CDS and usability studies with oversight committee members to gather feedback on the EDIT dashboard design. Strategy 3, we will conduct time-motion observations of local oversight committee meetings prior to and after deploying the EDIT model in order to plan a future, multi-institution, time- motion study with statistical power to detect differences between oversight committees that use the EDIT dashboard and those that do not. The hypothesis is that time spent prioritizing new and revised CDS will be shorter with use of the EDIT dashboard. Overall, the EDIT model establishes processes that lower barriers to implementing robust genomic medicine programs that can be followed by others. The Genomic Innovator Award will enable me to study, in team-science projects, how the EDIT model can accelerate the institutional review and approval process of CDS for UGR. The broader impact of this work is being able to study rate of UGR adoption by healthcare providers for deployed CDS for UGR.

项目概要 随着健康个体越来越多地获得基因组检测结果，表明他们出现不良结果的风险 （例如疾病或药物不良反应），医疗保健提供者需要确保结果得到处理 谨慎地，通过解决结果的接收、工作流程挑战和责任问题。 基因组测试可以在临床环境之外（例如，在研究中）从临床医生的角度启动 从角度来看，它们可以被描述为主动提供的基因组结果（UGR）。 通过向人群提供建议和患者相关信息，有巨大的潜力来简化 UGR 的采用 在特定时间提供的信息，以加强在医疗保健环境中部署 UGR 的 CDS。 然而，以可扩展的方式将取决于我们利用当地机构政策和监督的能力 批准 CDS 指导和 UGR 策略的结构 该研究计划的具体目标。 是开发和评估循证决策支持随时间实施 (EDIT) 模型 用于对 UGR 部署的 CDS 进行优先级排序和修订 EDIT 模型将赋予地方监督委员会权力。 例如药学和治疗委员会在 CDS 审查和部署流程中发挥作用 使用公认的组织流程的现有制度社会系统 这样做的直接好处。 工作将是一个编辑仪表板，监督委员会可以使用它来确定新内容的优先顺序并进行修改 部署 CDS 和基础设施，通过传输 CDS 修订来关闭学习健康系统的循环 由监督委员会成员批准进入已部署的 CDS 以进行 EDIT 模型实施。 混合方法研究策略：策略 1，我们将在监督下开展焦点小组活动 委员会成员，以了解委员会当前的角色、任务和目标，并了解 关于优先考虑、审查和批准 UGR 新的和修订的 CDS 的最佳流程的意见，作为 委员会会议活动研究策略2，我们将与患者进行调查研究以评估。 与监督委员会成员一起收集 CDS 和可用性研究中 UGR 回归的偏好 关于 EDIT 仪表板设计的反馈策略 3，我们将对本地监督进行时间动态观察。 在部署 EDIT 模型之前和之后召开委员会会议，以便规划未来的、多机构的、时间- 具有统计能力的运动研究，可以检测使用编辑的监督委员会之间的差异 假设是，花在优先考虑新的和修订的 CDS 上的时间将会减少。 总体来说，EDIT 模型建立的流程可以降低障碍。 实施可供其他人效仿的强大基因组医学计划。 将使我能够在团队科学项目中研究 EDIT 模型如何加速机构审查 这项工作的更广泛影响是能够研究 UGR 的比率。 医疗保健提供商采用为 UGR 部署 CDS。