Gallego Evelyn, Hinz Eugenia McPeek, Massey Bria, Tilson Elizabeth Cuervo, Tenenbaum Jessica D
EMI Advisors.
Duke University Health System.
Yearb Med Inform. 2024 Aug;33(1):6-17. doi: 10.1055/s-0044-1800713. Epub 2025 Apr 8.
This survey paper summarizes the recent trend of "Precision Prevention" in public health, focusing on significant developments in informatics to enable targeted prevention and improved public health.
Given relatively limited use of the term "Precision Prevention" in the literature to date, com-bined with significant developments in this space outside of peer reviewed literature, the topic was ill-suited for a systematic review approach. Instead, the co-authors used a narrative review approach, combining related search terms and complementary expertise to develop and refine sub-topics to be included. Each section was then written using a combination of prior knowledge and specific relevant search terms.
The paper opens with an explanation of the term "precision prevention", including its origins and relationship to other concepts such as precision medicine. It then provides an overview of types of data relevant to precision prevention, as well as how those data are collected in different contexts and through different modalities. The authors then describe the HL7 Gravity Project, a multi-stakeholder public collaborative project aimed at data standardization in the social determinants space. Finally, the authors present how those data types are used across the spectrum from clinical care to target outreach for human services, to data-driven health policy.
Precision prevention, targeting the right intervention to the right population at the right time, is now recognized as of vital importance, particularly in light of the COVID-19 pandemic's spotlight on health disparities and societal consequences. Optimizing interventions targeted at different communities and populations will require novel and innovative collection, use, and dissemination of data, information, and knowledge. The talent and skills of the international informatics community are critical for success in this work.
本综述文章总结了公共卫生领域“精准预防”的最新趋势，重点关注信息学方面的重大进展，以实现有针对性的预防并改善公众健康。
鉴于目前文献中“精准预防”一词的使用相对有限，再结合同行评审文献之外该领域的重大进展，该主题不太适合采用系统综述方法。相反，共同作者采用了叙述性综述方法，结合相关搜索词和互补的专业知识来开发和完善要纳入的子主题。然后，每个部分都结合了先验知识和特定的相关搜索词进行撰写。
本文开篇解释了“精准预防”一词，包括其起源以及与精准医学等其他概念的关系。接着概述了与精准预防相关的数据类型，以及这些数据在不同背景下和通过不同方式是如何收集的。作者随后介绍了HL7引力项目，这是一个多利益相关方的公共合作项目，旨在实现社会决定因素领域的数据标准化。最后，作者展示了这些数据类型如何在从临床护理到人类服务的目标推广，再到数据驱动的卫生政策等各个层面得到应用。
精准预防，即在正确的时间针对正确的人群采取正确的干预措施，如今被认为至关重要，尤其是鉴于新冠疫情凸显了健康差异和社会后果。优化针对不同社区和人群的干预措施将需要新颖且创新的数据、信息和知识的收集、使用及传播。国际信息学社区的人才和技能对于这项工作的成功至关重要。
