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: 10606011
• 负责人: CASEY OVERBY TAYLOR
• 金额: $ 28.85万
• 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/10606011
• 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.

项目摘要 由于越来越多的健康个体可以接受基因组测试结果，表明他们患贫困的风险 结果(例如疾病或药物不良反应)，医疗保健提供者需要确保结果 通过处理收到结果、工作流程挑战和责任问题，谨慎处理。 鉴于临床基因组测试可以在临床环境之外(例如，在研究研究中)启动，从 从临床医生的角度来看，他们可以被描述为主动获得的基因组结果(UGR)。临床决策 支持(CDS)通过为临床医生提供建议，具有简化UGR采用的巨大潜力 以及在特定时间提供与患者有关的信息，以加强临床护理。为UGR部署CDS 然而，在可扩展的医疗保健环境中，将取决于我们利用当地机构的能力 政策和监督结构，以批准CDS指导和UGR战略。的具体目标 本研究的目的是开发和评估循证决策支持的实施情况 随时间推移(编辑)模型，用于确定已部署的CDS for UGR的优先顺序并进行修订。编辑模型将使 地方监督委员会，如药房和治疗委员会，将在CDS审查中发挥作用 在现有机构社交系统中使用公认的组织和部署流程 流程。这项工作的直接好处将是一个可供Supervisor使用的编辑仪表板 确定新CDS的优先顺序并修订已部署的CDS的委员会，以及关闭学习循环的基础设施 通过将监督委员会成员批准的CDS修订版转移到部署的CDS中 UGR。编辑模型的实施将通过混合方法通知研究策略：策略1，我们将 与监督委员会成员一起组织焦点小组，以了解当前的角色、任务和目标 以及收集关于确定优先次序、审查和批准的最佳程序的意见 作为委员会会议活动的一部分，UGR的新的和修订的CDS。研究策略2，我们将进行一项 对患者进行的调查研究，以评估使用CDS的UGR返回的偏好，以及使用 监督委员会成员收集对编辑仪表板设计的反馈。策略3，我们将进行 在中部署编辑模型之前和之后地方监督委员会会议的时间动态观察 为了规划未来的、多机构的、具有统计能力的时间运动研究，以检测 使用编辑控制面板的监督委员会和不使用编辑仪表板的监督委员会。假设是花在时间上 使用编辑仪表板，确定新的和修订的CDS的优先顺序将会更短。总体而言，编辑模型 建立流程，降低实施强大的基因组医学计划的门槛，这些计划可以 其他人紧随其后。基因组创新者奖将使我能够在团队科学项目中研究如何 编辑模式可以加快CDS对UGR的机构审查和审批过程。更广泛的影响 这项工作的一部分是能够研究医疗保健提供者为UGR部署的CDS采用UGR的比率。