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变革健康的未来:构建全球学习型健康系统。

Transforming the future of health: building learning health systems across the globe.

作者信息

Yankah Sandra, Saunders Robert, Tykocinski Mark, Salzberg Claudia, Gonzalez-Smith Jonathan, Bonesteel Rachel, Joyce Cameron, Kahn Charles, McClellan Mark, Zimlichman Eyal

机构信息

Duke-Margolis Institute for Health Policy, Washington, DC 20004, United States.

Department of Pathology and Genomic Medicine, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA 19107, United States.

出版信息

Health Aff Sch. 2025 May 21;3(6):qxaf103. doi: 10.1093/haschl/qxaf103. eCollection 2025 Jun.


DOI:10.1093/haschl/qxaf103
PMID:40463804
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12128919/
Abstract

Health care has faced disruptions over the past 5 years, including a global pandemic, supply chain interruptions, workforce shifts, and the introduction of new artificial intelligence (AI) tools. Health care organizations continue to leverage the learning health system (LHS) concept to adapt to these challenges through iterative feedback loops. The Future of Health (FOH), an international community of over 50 senior health leaders that focuses on shared challenges across international health systems, collaborated with the Duke-Margolis Institute for Health Policy in a consensus-building process with FOH members to identify opportunities for action in an LHS. Key areas for action identified include opportunities to leverage data and AI to support clinical decision-making, steps to create an organizational culture of learning, and strategies to engage patients and caregivers, illustrated through case examples.

摘要

在过去五年中,医疗保健行业面临诸多干扰,包括全球大流行、供应链中断、劳动力转移以及新人工智能(AI)工具的引入。医疗保健组织继续利用学习型健康系统(LHS)概念,通过迭代反馈循环来应对这些挑战。“健康未来”(FOH)是一个由50多位资深医疗领导者组成的国际团体,专注于国际医疗系统中的共同挑战,它与杜克-马戈利斯健康政策研究所合作,在与FOH成员的共识构建过程中,确定学习型健康系统中的行动机会。确定的关键行动领域包括利用数据和人工智能支持临床决策的机会、营造学习型组织文化的步骤以及让患者和护理人员参与的策略,并通过案例进行说明。

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本文引用的文献

[1]
The potential for artificial intelligence to transform healthcare: perspectives from international health leaders.

NPJ Digit Med. 2024-4-9

[2]
Synthetic data in cancer and cerebrovascular disease research: A novel approach to big data.

PLoS One. 2024

[3]
Harnessing the power of synthetic data in healthcare: innovation, application, and privacy.

NPJ Digit Med. 2023-10-9

[4]
A policy ethnography study of a Singapore regional health system on its governance adaptations and associated challenges as a project organisation to implement Healthier Singapore.

Public Health Pract (Oxf). 2023-9-18

[5]
Revolutionizing patient safety with artificial intelligence: the potential of natural language processing and large language models.

Int J Qual Health Care. 2023-7-7

[6]
Clarifying the concept of a learning health system for healthcare delivery organizations: Implications from a qualitative analysis of the scientific literature.

Learn Health Syst. 2021-7-22

[7]
The Science of Learning Health Systems: Scoping Review of Empirical Research.

JMIR Med Inform. 2022-2-23

[8]
Culture as infrastructure in learning health systems.

Learn Health Syst. 2021-5-5

[9]
Sustainable generation of patient-led resources in a learning health system.

Learn Health Syst. 2021-2-12

[10]
Learning health care systems: Highly needed but challenging.

Learn Health Syst. 2020-1-13

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