From bench to policy: a critical analysis of models for evidence-informed policymaking in healthcare
- PMID: 38596514
- PMCID: PMC11002157
- DOI: 10.3389/fpubh.2024.1264315
From bench to policy: a critical analysis of models for evidence-informed policymaking in healthcare
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.
Keywords: critical review; evidence-informed policymaking; health policy; knowledge translation; model; research utilization.
Copyright © 2024 Jabali, Yazdani, Pourasghari and Maleki.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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