Policy options for strengthening evidence-informed health policy-making in Iran: overall SASHA project findings
Bibliographic record
Abstract
BACKGROUND: The institutionalization of evidence-informed health policy-making (EIHP) is complex and complicated. It is complex because it has many players and is complicated because its institutionalization will require many changes that will be challenging to make. Like many other issues, strengthening EIHP needs a road map, which should consider challenges and address them through effective, harmonized and contextualized strategies. This study aims to develop a road map for enhancing EIHP in Iran based on steps of planning. METHODS: This study consisted of three phases: (1) identifying barriers to EIHP, (2) recognizing interventions and (3) measuring the use of evidence in Iran's health policy-making. A set of activities was established for conducting these, including foresight, systematic review and policy dialogue, to identify the current and potential barriers for the first phase. For the second phase, an evidence synthesis was performed through a scoping review, by searching the websites of benchmark institutions which had good examples of EIHP practices in order to extract and identify interventions, and through eight policy dialogues and two broad opinion polls to contextualize the list of interventions. Simultaneously, two qualitative-quantitative studies were conducted to design and use a tool for assessing EIHP in the third phase. RESULTS: We identified 97 barriers to EIHP and categorized them into three groups, including 35 barriers on the "generation of evidence" (push side), 41 on the "use of evidence" (pull side) and 21 on the "interaction between these two" (exchange side). The list of 41 interventions identified through evidence synthesis and eight policy dialogues was reduced to 32 interventions after two expert opinion polling rounds. These interventions were classified into four main strategies for strengthening (1) the education and training system (6 interventions), (2) the incentives programmes (7 interventions), (3) the structure of policy support organizations (4 interventions) and (4) the enabling processes to support EIHP (15 interventions). CONCLUSION: The policy options developed in the study provide a comprehensive framework to chart a path for strengthening the country's EIHP considering both global practices and the context of Iran. It is recommended that operational plans be prepared for road map interventions, and the necessary resources provided for their implementation. The implementation of the road map will require attention to the principles of good governance, with a focus on transparency and accountability. Video abstract.
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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 | 0.051 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".