Evidence map›Paper›PMID 33129335›Full record

SynthesisHealth research policy and systems2020

Lessons learned from descriptions and evaluations of knowledge translation platforms supporting evidence-informed policy-making in low- and middle-income countries: a systematic review.

Arun C R Partridge, Cristián Mansilla, Harkanwal Randhawa, John N Lavis, Fadi El-Jardali, Nelson K Sewankambo

Abstract readSystematic Review
In one paragraph

Synthesis in Health research policy and systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. An ethical analysis of policy dialogues.Health research policy and systems · 2023
    Article
  18. Article
  19. Article
  20. 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

6 authors.

Arun C R PartridgeDepartment of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Canada. arun.partridge@ucalgary.ca.ORCID http://orcid.org/0000-0002-4191-0970
Cristián MansillaMcMaster Health Forum and Health Policy PhD Program, McMaster University, Hamilton, Canada.
Harkanwal RandhawaMichael G. DeGroote School of Medicine, McMaster University, Hamilton, Canada.
John N LavisMcMaster Health Forum and Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada.
Fadi El-JardaliKnowledge to Policy Center and Department of Health Management and Policy, American University of Beirut, Beirut, Lebanon.
Nelson K SewankamboClinical Epidemiology and Biostatistics Unit, Department of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda. sewankam@infocom.co.ug.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKnowledge translation (KT) platforms are organisations, initiatives and networks that focus on supporting evidence-informed policy-making at least in part about the health-system arrangements that determine whether the right programmes, services and products get to those who need them. Many descriptions and evaluations of KT platforms in low- and middle-income countries have been produced but, to date, they have not been systematically reviewed.

methodsWe identified potentially relevant studies through a search of five electronic databases and a variety of approaches to identify grey literature. We used four criteria to select eligible empirical studies. We extracted data about seven characteristics of included studies and about key findings. We used explicit criteria to assess study quality. In synthesising the findings, we gave greater attention to themes that emerged from multiple studies, higher-quality studies and different contexts.

resultsCountry was the most common jurisdictional focus of KT platforms, EVIPNet the most common name and high turnover among staff a common infrastructural feature. Evidence briefs and deliberative dialogues were the activities/outputs that were the most extensively studied and viewed as helpful, while rapid evidence services were the next most studied but only in a single jurisdiction. None of the summative evaluations used a pre-post design or a control group and, with the exception of the evaluations of the influence of briefs and dialogues on intentions to act, none of the evaluations achieved a high quality score.

conclusionsA large and growing volume of research evidence suggests that KT platforms offer promise in supporting evidence-informed policy-making in low- and middle-income countries. KT platforms should consider as next steps expanding their current, relatively limited portfolio of activities and outputs, building bridges to complementary groups, and planning for evaluations that examine 'what works' for 'what types of issues' in 'what types of contexts'.

Indexed as

Developing CountriesTranslational Research, BiomedicalGovernment ProgramsHealth PolicyHumansPolicy MakingEvidence-informed policyHealth systemsKnowledge translationSystematic evaluation

Identifiers

PMID33129335
PMCPMC7603785

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.