VA Informatics and Computing Infrastructure, VA Salt Lake City Healthcare System, Salt Lake City, UT, USA.
VA HSR&D Center for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
Genet Med. 2019 May;21(5):1139-1154. doi: 10.1038/s41436-018-0315-y. Epub 2018 Oct 23.
Precision medicine promises to improve patient outcomes, but much is unknown about its adoption within health-care systems. A comprehensive implementation plan is needed to realize its benefits.
We convened 80 stakeholders for agenda setting to inform precision medicine policy, delivery, and research. Conference proceedings were audio-recorded, transcribed, and thematically analyzed. We mapped themes representing opportunities, challenges, and implementation strategies to a logic model, and two implementation science frameworks provided context.
The logic model components included inputs: precision medicine infrastructure (clinical, research, and information technology), big data (from data sources to analytics), and resources (e.g., workforce and funding); activities: precision medicine research, practice, and education; outputs: precision medicine diagnosis; outcomes: personal utility, clinical utility, and health-care utilization; and impacts: precision medicine value, equity and access, and economic indicators. Precision medicine implementation challenges include evidence gaps demonstrating precision medicine utility, an unprepared workforce, the need to improve precision medicine access and reduce variation, and uncertain impacts on health-care utilization. Opportunities include integrated health-care systems, partnerships, and data analytics to support clinical decisions. Examples of implementation strategies to promote precision medicine are: changing record systems, data warehousing techniques, centralized technical assistance, and engaging consumers.
We developed a theory-based, context-specific logic model that can be used by health-care organizations to facilitate precision medicine implementation.
精准医学有望改善患者的治疗效果，但人们对其在医疗系统中的应用知之甚少。需要制定全面的实施计划，以实现其效益。
我们召集了 80 名利益攸关方，就精准医学的政策、实施和研究进行了议程设置。会议记录被录音、转录，并进行了主题分析。我们将代表机遇、挑战和实施策略的主题映射到一个逻辑模型中，并提供了两个实施科学框架的背景。
逻辑模型的组成部分包括投入：精准医学基础设施（临床、研究和信息技术）、大数据（从数据源到分析）和资源（如劳动力和资金）；活动：精准医学研究、实践和教育；产出：精准医学诊断；结果：个人效用、临床效用和医疗保健利用；以及影响：精准医学的价值、公平性和可及性以及经济指标。精准医学实施面临的挑战包括：证明精准医学实用性的证据差距、准备不足的劳动力、需要改善精准医学的可及性和减少差异、以及对医疗保健利用的不确定影响。机遇包括一体化的医疗保健系统、合作伙伴关系和数据分析，以支持临床决策。促进精准医学的实施策略示例包括：改变记录系统、数据仓库技术、集中技术援助和消费者参与。
我们开发了一个基于理论、特定于背景的逻辑模型，医疗保健组织可以使用该模型来促进精准医学的实施。
