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从基础研究到政策制定:医疗保健中循证决策模型的批判性分析。

From bench to policy: a critical analysis of models for evidence-informed policymaking in healthcare.

机构信息

School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.

Virtual School of Medical Education and Management, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

出版信息

Front Public Health. 2024 Mar 26;12:1264315. doi: 10.3389/fpubh.2024.1264315. eCollection 2024.

Abstract

BACKGROUND

The use of research evidence in policy making is a complex and challenging process that has a long history in various fields, especially in healthcare. Different terms and concepts have been used to describe the relationship between research and policy, but they often lack clarity and consensus. To address this gap, several strategies and models have been proposed to facilitate evidence informed policy making and to identify the key factors and mechanisms involved. This study aims to critically review the existing models of evidence informed policy making (EIPM) in healthcare and to assess their strengths and limitations.

METHOD

A systematic search and review conducted to identify and critically assess EIPM models in healthcare. We searched PubMed, Web of Science and Scopus databases as major electronic databases and applied predefined inclusion criteria to select the models. We also checked the citations of the included models to find other scholars' perspectives. Each model was described and critiqued each model in detail and discussed their features and limitations.

RESULT

Nine models of EIPM in healthcare were identified. While models had some strengths in comprehension, flexibility and theoretical foundations, analysis also identified limitations including: presupposing rational policymaking; lacking alternatives for time-sensitive situations; not capturing policy complexity; neglecting unintended effects; limited context considerations; inadequate complexity concepts; limited collaboration guidance; and unspecified evidence adaptations.

CONCLUSION

The reviewed models provide useful frameworks for EIPM but need further improvement to address their limitations. Concepts from sociology of knowledge, change theory and complexity science can enrich the models. Future EIPM models should better account for the complexity of research-policy relationships and provide tailored strategies based on the policy context.

摘要

背景

研究证据在政策制定中的应用是一个复杂而具有挑战性的过程,在各个领域,尤其是在医疗保健领域,都有着悠久的历史。不同的术语和概念被用来描述研究与政策之间的关系,但它们往往缺乏清晰度和共识。为了解决这一差距,已经提出了几种策略和模型,以促进循证政策制定,并确定所涉及的关键因素和机制。本研究旨在批判性地回顾医疗保健领域现有的循证政策制定(EIPM)模型,并评估它们的优势和局限性。

方法

进行了系统的搜索和综述,以确定和批判性评估医疗保健中的 EIPM 模型。我们搜索了 PubMed、Web of Science 和 Scopus 数据库作为主要的电子数据库,并应用了预先确定的纳入标准来选择模型。我们还检查了纳入模型的引文,以寻找其他学者的观点。每个模型都进行了描述和详细的批评,并讨论了它们的特点和局限性。

结果

确定了 9 种医疗保健中的 EIPM 模型。虽然这些模型在理解、灵活性和理论基础方面具有一些优势,但分析也发现了一些局限性,包括:假设理性的决策制定;缺乏针对时间敏感情况的替代方案;无法捕捉政策的复杂性;忽视了意外的影响;对背景因素的考虑有限;复杂概念不足;合作指导有限;以及证据适应性不明确。

结论

所审查的模型为 EIPM 提供了有用的框架,但需要进一步改进以解决其局限性。知识社会学、变革理论和复杂性科学的概念可以丰富这些模型。未来的 EIPM 模型应更好地考虑研究-政策关系的复杂性,并根据政策背景提供量身定制的策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/11002157/37c089a7bf6c/fpubh-12-1264315-g001.jpg

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