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: 10672256
• 负责人: CASEY OVERBY TAYLOR
• 金额: $ 48.14万
• 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/10672256
• 关键词: Acceleration; Address; Adopted; Adoption; Area; Award; Clinical; Committee Members; Data; Diagnosis; Disease; 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; Prevention; Process; Recommendation; Research; Research Methodology; Risk; Role; Science; Structure; Surveys; System; Test Result; Testing; Therapeutics Committee; Time; Time and Motion Studies; Vision; Work; adverse drug reaction; clinical care; clinical decision support; computerized tools; dashboard; design; empowerment; evidence base; genetic makeup; genomic data; health care settings; implementation science; improved; 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，表明他们患上贫困的风险 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 通过解决结果的接收、工作流程挑战和责任问题来谨慎处理。 鉴于临床基因组测试可以在临床环境之外（例如，在研究中）启动， 从临床医生的角度来看，它们可以被描述为主动提供的基因组结果（UGR）。临床决策 支持 (CDS) 通过向临床医生提供建议，具有促进 UGR 采用的巨大潜力 以及在特定时间呈现的患者相关信息，以加强临床护理。为 UGR 部署 CDS 然而，在医疗保健环境中以可扩展的方式将取决于我们利用当地机构的能力 批准 CDS 指导和 UGR 战略的政策和监督结构。具体目标 该研究计划旨在开发和评估基于证据的决策支持实施 随着时间的推移 (EDIT) 模型，用于对 UGR 部署的 CDS 进行优先级排序和修改。 EDIT 模型将赋能 地方监督委员会（例如药剂学和治疗委员会）在 CDS 审查中发挥作用 和现有机构社会系统内使用公认的组织的部署过程 流程。这项工作的直接好处将是一个可供监督使用的编辑仪表板 委员会优先考虑新的和修改已部署的 CDS 以及基础设施以形成学习闭环 卫生系统，将监督委员会成员批准的 CDS 修订版转移到已部署的 CDS 中，以用于 UGR。编辑模型的实施将通过混合方法研究策略进行通知：策略 1，我们将 与监督委员会成员进行焦点小组讨论，以了解当前的角色、任务和目标 委员会的意见，并收集有关确定优先顺序、审查和批准的最佳流程的意见 新的和修订的 UGR CDS 作为委员会会议活动的一部分。研究策略2，我们将进行 对患者进行调查研究，以评估使用 CDS 恢复 UGR 的偏好以及使用 CDS 进行可用性研究 监督委员会成员收集有关编辑仪表板设计的反馈。策略3，我们将进行 在部署 EDIT 模型之前和之后对地方监督委员会会议的时间动态观察 为了计划未来的多机构时间运动研究，具有统计能力来检测之间的差异 使用和不使用 EDIT 仪表板的监督委员会。假设是花费的时间 使用 EDIT 仪表板，可以更短地确定新的和修订的 CDS 的优先级。总体而言，EDIT 模型 建立降低实施稳健基因组医学计划障碍的流程，这些计划可以 其次是其他人。基因组创新者奖将使我能够在团队科学项目中研究如何 EDIT模型可以加速UGR CDS的机构审查和批准过程。更广泛的影响 这项工作的重点是能够研究医疗保健提供者对 UGR 部署 CDS 的 UGR 采用率。

项目成果

Willingness to Share Wearable Device Data for Research Among Mechanical Turk Workers: Web-Based Survey Study.

• DOI: 10.2196/19789
• 发表时间: 2021-10-21
• 期刊: Journal of medical Internet research
• 影响因子: 7.4
• 作者: Taylor CO;Flaks-Manov N;Ramesh S;Choe EK
• 通讯作者: Choe EK

Risk for Poor Post-Operative Quality of Life Among Wearable Use Subgroups in an All of Us Research Cohort

我们所有人研究队列中可穿戴设备亚组术后生活质量差的风险

• DOI: 10.1142/9789811270611_0004
• 发表时间: 2022
• 期刊: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
• 作者: Nidhi Soley;Shanshan Song;N. Flaks;Casey Overby Taylor
• 通讯作者: Casey Overby Taylor

Facilitating Genetics Aware Clinical Decision Support: Putting the eMERGE Infrastructure into Practice.

• DOI: 10.1055/s-0041-1729981
• 发表时间: 2021-07
• 期刊: ACI open
• 作者: Taylor, Casey Overby;Rasmussen, Luke V;Rasmussen-Torvik, Laura J;Prows, Cynthia A;Dorr, David A;Samal, Lipika;Aronson, Samuel
• 通讯作者: Aronson, Samuel

Will the Doctor "See" You Now? The Development and Implementation of a Targeted Telemedicine System for Primary Care.

• DOI: 10.1055/s-0043-1776038
• 发表时间: 2023-07
• 期刊: ACI open