The translation-to-policy learning cycle to improve public health

IF 2.6 Q2 HEALTH POLICY & SERVICES
Amy M. Kilbourne, Melissa Z. Braganza, Dawn M. Bravata, Jack Tsai, Richard E. Nelson, Alex Meredith, Kenute Myrie, Rachel Ramoni
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引用次数: 0

Abstract

Objective

Learning Health Systems (LHSs) have not directly informed evidence-based policymaking. The Translation-to-Policy (T2P) Learning Cycle aligns scientists, end-users, and policymakers to support a repeatable roadmap of innovation and quality improvement to optimize effective policies toward a common public health goal. We describe T2P learning cycle components and provide examples of their application.

Methods

The T2P Learning Cycle is based on the U.S. Department of Veterans Affairs (VA) Office of Research and Development and Quality Enhancement Research Initiative (QUERI), which supports research and quality improvement addressing national public health priorities to inform policy and ensure programs are evidence-based and work for end-users. Incorporating LHS infrastructure, the T2P Learning Cycle is responsive to the Foundations for Evidence-based Policymaking Act, which requires U.S. government agencies to justify budgets using evidence.

Results

The learning community (patients, providers, clinical/policy leaders, and investigators) drives the T2P Learning Cycle, working toward one or more specific, shared priority goals, and supports a repeatable cycle of evidence-building and evaluation. Core T2P Learning Cycle functions observed in the examples from housing/economic security, precision oncology, and aging include governance and standard operating procedures to promote effective priority-setting; complementary research and quality improvement initiatives, which inform ongoing data curation at the learning system level; and sustainment of continuous improvement and evidence-based policymaking.

Conclusions

The T2P Learning Cycle integrates research translation with evidence-based policymaking, ensuring that scientific innovations address public health priorities and serve end-users through a repeatable process of research and quality improvement that ensures policies are scientifically based, effective, and sustainable.

Abstract Image

从转化到政策的学习周期,以改善公共卫生。
目标:学习型卫生系统(LHS)并没有直接为循证决策提供信息。转化为政策(Translation-to-Policy,T2P)学习周期(Learning Cycle)将科学家、最终用户和政策制定者结合起来,支持可重复的创新和质量改进路线图,以优化有效政策,实现共同的公共卫生目标。我们介绍了 T2P 学习周期的组成部分,并提供了应用实例:T2P 学习周期以美国退伍军人事务部(VA)研发和质量改进研究计划办公室(QUERI)为基础,该计划支持针对国家公共卫生优先事项的研究和质量改进,为政策提供信息,确保计划以证据为基础并对最终用户有效。T2P 学习周期纳入了 LHS 基础设施,是对《循证决策基础法案》的回应,该法案要求美国政府机构利用证据证明预算的合理性:结果:学习社区(患者、医疗服务提供者、临床/政策领导者和研究人员)推动 T2P 学习循环,努力实现一个或多个特定的、共同的优先目标,并支持可重复的证据建设和评估循环。从住房/经济安全、精准肿瘤学和老龄化实例中观察到的 T2P 学习周期核心功能包括:管理和标准操作程序,以促进有效的优先事项设定;补充研究和质量改进措施,为学习系统层面的持续数据整理提供信息;以及持续改进和循证决策:T2P 学习周期将研究成果转化与循证决策相结合,通过可重复的研究和质量改进过程,确保科学创新能够解决公共卫生优先事项并服务于最终用户,从而确保政策具有科学依据、有效性和可持续性。
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来源期刊
Learning Health Systems
Learning Health Systems HEALTH POLICY & SERVICES-
CiteScore
5.60
自引率
22.60%
发文量
55
审稿时长
20 weeks
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