Evidence map›Paper›PMID 38596514›Full record

ReviewFrontiers in public health2024

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

Seyyed Hadi Jabali, Shahram Yazdani, Hamid Pourasghari, Mohammadreza Maleki

Abstract readReview
In one paragraph

Review in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Seyyed Hadi JabaliSchool of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
Shahram YazdaniVirtual School of Medical Education and Management, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Hamid PourasghariSchool of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
Mohammadreza MalekiSchool of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Evidence-Based MedicineHealth PolicyDelivery of Health CarePolicy Makingcritical reviewevidence-informed policymakinghealth policyknowledge translationmodelresearch utilization

Identifiers

PMID38596514
PMCPMC11002157

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.