Promoting the use of evidence in health policymaking in the ECOWAS region: the development and contextualization of an evidence-based policymaking guidance
Bibliographic record
Abstract
BACKGROUND: The Economic Commission of the West African States (ECOWAS), through her specialised health Institution, the West African Health Organization (WAHO) is supporting Members States to improve health outcomes in West Africa. There is a global recognition that evidence-based health policies are vital towards achieving continued improvement in health outcomes. The need to have a tool that will provide systematic guide on the use of evidence in policymaking necessitated the production of the evidence-based policy-making (EBPM) Guidance. METHODS: Google search was performed to identify existing guidance on EBPM. Lessons were drawn from the review of identified guidance documents. Consultation, interaction and interviews were held with policymakers from the 15 West African countries during WAHO organized regional meetings in Senegal, Nigeria, and Burkina Faso. The purpose was to elicit their views on the strategies to promote the use of evidence in policymaking to be included in the EBPM Guidance. A regional Guidance Validation Meeting for West African policymakers was thereafter convened by WAHO to review findings from review of existing guidance documents and validate the EBPM Guidance. RESULTS: Out of the 250 publications screened, six publications fulfilled the study inclusion criteria and were reviewed. Among the important issues highlighted include: what evidence informed decision-making is; different types of research methods, designs and approaches, and how to judge the quality of research. The identified main target end users of the EBPM Guidance are policy/decision makers in the West African sub-region, at local, sub-national, national and regional levels. Among the key recommendations included in the EBPM Guidance include: properly defining/refining policy problem; reviewing contextual issues; initiating policy priority setting; considering political acceptability of policy; commissioning research; use of rapid response services, use of policy advisory/technical/steering committees; and use of policy briefs and policy dialogue. CONCLUSION: The EBPM Guidance is one of the emerging tools that can enhance the understanding of evidence to policy process. The strategies to facilitate the use of evidence in policymaking outlined in the Guidance, can be adapted to local context, and incorporated validated approaches that can be used to promote evidence-to-policy-to-practice process in West Africa.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.470 | 0.537 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.026 | 0.018 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.041 | 0.034 |
| Open science | 0.008 | 0.028 |
| Research integrity | 0.021 | 0.024 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".