精准预防:利用数据在正确的时间,在正确的社区以正确的强度进行正确的干预。

Yearbook of medical informatics Pub Date : 2024-08-01 Epub Date: 2025-04-08 DOI:10.1055/s-0044-1800713
Evelyn Gallego, Eugenia McPeek Hinz, Bria Massey, Elizabeth Cuervo Tilson, Jessica D Tenenbaum
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引用次数: 0

摘要

目的:本调查报告总结了公共卫生领域“精准预防”的最新趋势,重点介绍了信息学的重大发展,以实现有针对性的预防和改善公共卫生。方法:鉴于迄今为止文献中“精确预防”一词的使用相对有限,结合同行评议文献之外该领域的重大发展,该主题不适合采用系统综述方法。相反,合著者使用了一种叙事回顾的方法,结合相关的搜索词和互补的专业知识来开发和完善要包括的子主题。然后使用先验知识和特定相关搜索词的组合来编写每个部分。结果:本文首先对“精准预防”一词进行了解释,包括其起源及其与其他概念(如精准医学)的关系。然后概述了与精确预防相关的数据类型,以及如何在不同情况下通过不同方式收集这些数据。作者随后描述了HL7重力项目,这是一个多利益相关者公共协作项目,旨在实现社会决定因素空间的数据标准化。最后,作者介绍了这些数据类型如何在从临床护理到人类服务的目标外展到数据驱动的卫生政策的各个领域中使用。结论: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,现在被认为至关重要,特别是考虑到2019冠状病毒病大流行对健康差距和社会后果的关注。优化针对不同社区和人群的干预措施将需要以新颖和创新的方式收集、使用和传播数据、信息和知识。国际信息学界的才能和技能对这项工作的成功至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Precision Prevention: Using Data to Target the Right Intervention at the Right Intensity in the Right Community at the Right Time.

Objectives: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

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来源期刊
Yearbook of medical informatics
Yearbook of medical informatics Medicine-Medicine (all)
CiteScore
4.10
自引率
0.00%
发文量
20
期刊介绍: Published by the International Medical Informatics Association, this annual publication includes the best papers in medical informatics from around the world.
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