An institutional approach to support the conduct and use of health policy and systems research: The Nodal Institute in the Eastern Mediterranean Region
Bibliographic record
Abstract
BACKGROUND: The use of health policy and systems research (HPSR) to support decision making in health systems is limited in the Eastern Mediterranean Region (EMR). This is partly due to the lack of effective initiatives to strengthen regional HPSR capacities and promote its use in decision making. This paper offers a structured reflection on the establishment and core functioning of a HPSR Nodal Institute for the EMR with specific focus on the approach used to support the conduct and use of HPSR. It seeks to gain better understanding of the activities conducted by the Nodal Institute, the methods by which the Nodal Institute implemented these activities, and the outcomes of these activities. METHODS: A multi-faceted approach was implemented by the Nodal Institute in collaboration with regional academic/research institutions, Sub-Nodes. The overall approach was a phased one that included the selection of Sub-Nodes, mapping of academic/research institutions in the EMR, stakeholders' meetings, and HPSR capacity building workshops, and culminated with a regional meeting. RESULTS: The mapping of academic/research institutions in the EMR resulted in the identification of 50 institutions, of which only 32 were engaged in HPSR. These institutions have the highest HPSR involvement in information/evidence (84%) and the lowest in human resources for health (34%). Their main HPSR focus areas included quality of healthcare services, patient safety, management of non-communicable diseases, and human resources for health. Regional HPSR challenges among these institutions were identified. The validation and ranking questionnaires resulted in the identification of country-specific HPSR priorities according to stakeholders in three countries. From these results, cross-cutting HPSR priorities among the countries related to primary healthcare, non-communicable diseases, human resources for health, as well as cross-cutting HPSR priorities among stakeholders and according to stakeholders of the countries, were extracted. CONCLUSION: The Nodal Institute in the EMR is a promising initiative to support the conduct and use of HPSR in health policies. The approach and findings reported in this paper allow for the development of opportunities towards the building of capacity for HPSR in the region and other countries and provide a roadmap for academic/research institutions interested in HPSR in the region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.176 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".