The factors affecting the institutionalisation of two policy units in Burkina Faso’s health system: a case study
Bibliographic record
Abstract
BACKGROUND: This paper is one of three linked studies that attempts to understand the process of institutionalisation of policy units within Burkina Faso's health system. It examines the relationships between the existence of an institutional framework, data production capacity and other resource availability in the institutionalisation of policy units in health systems. It therefore contributes to our understanding of the dynamics linking the key drivers and indicators of institutionalisation. Additionally, it examines how factors within the managerial setting, including workplace environment, and budgetary and human resource availability, may influence the institutionalisation process. METHODS: The study used an explanatory qualitative case study approach, examining two policy units in Burkina Faso's Ministry of Health, the first of which had been institutionalised successfully and the other less so. Data were collected from key policymakers, including 13 connected with the first policy unit and 10 with the second, plus two funders. We also conducted a documentary analysis of the National Program for Health Development, two mid-term strategic plans, 230 action plans, eight Ministry of Health state budgets, eight Ministry of Health annual statistics reports, 16 policy unit budgets and published literature. RESULTS: The framework within which the government gave the policy unit its mandate and policy focus had the strongest effect on the institutionalisation process. Institutionalisation depended on political will, in both the host government and any donors, and the priority given to the policy unit's focus. It was also affected by the leadership of the policy unit managers. These factors were influenced by human resource capacity, and our findings suggest that, for successful institutionalisation in Burkina Faso's health system, policy units need to be given sufficient human resources to achieve their objectives. CONCLUSION: Policy units' institutionalisation in Burkina Faso's health system depend on the leadership of the unit managers to implement relevant activities, mobilise funding, and recruit and maintain enough human resources, as well as the mandate given by the government.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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; a candidate call from one teacher head, 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".