ReviewHealth research policy and systems2025
A bespoke rapid evidence review process engaging stakeholders for supporting evolving and time-sensitive policy and clinical decision-making: reflection and lessons learned from the Wales COVID-19 Evidence Centre 2021-2023.
Review in Health research policy and systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Informing evidence-based policy during the COVID-19 pandemic and recovery period: learning from a national evidence centre.Global health research and policy · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe COVID-19 pandemic presented policymakers with time-sensitive decision problems and a rapidly increasing volume of research, not all of which was robust, or relevant to local contexts. A bespoke evidence review process supporting stakeholder engagement was developed as part of the Wales COVID-19 Evidence Centre (WCEC), which could flexibly react to the needs of decision-makers, to address urgent requests within days or months as required.
aimsTo describe and appraise the WCEC review process and methods and identify key learning points.
methodsThree types of rapid review products were used, which could accommodate the breadth of decision problems and topics covered. Stakeholder (including public) engagement was integrated from the onset and supported throughout. The methods used were tailored depending on the needs of the decision-maker, type of research question, timeframe, and volume and type of evidence. We appraised the overall process and compared the methods used with the most recent and relevant best practice guidance.
resultsThe remote collaboration between research teams, establishing a clear pathway to impact upfront, and the strong stakeholder involvement embedded in the review process were considered particular strengths. Several key learning points were identified, which focused on: enhancing stakeholders' abilities to identify focused policy-relevant research questions; the collection and storage of review protocols at a central location; tightening quality assurance process regarding study selection, data extraction and quality assessment; adequate reporting of methodological shortcuts and understanding by stakeholders; piloting of an algorithm for assigning study design descriptors, and a single quality assessment tool covering multiple study designs; and incorporate, where appropriate an assessment of the confidence in the overall body of evidence using GRADE or similar framework.
conclusionsThe review process enabled a high volume of questions that were directly relevant to policy and clinical decision making to be addressed in a timely manner using a transparent and tailored approach.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.