Twelve months of implementation of health care performance‐based financing in <scp>B</scp>urkina <scp>F</scp>aso: A qualitative multiple case study
Bibliographic record
Abstract
To improve health services' quantity and quality, African countries are increasingly engaging in performance-based financing (PBF) interventions. Studies to understand their implementation in francophone West Africa are rare. This study analysed PBF implementation in Burkina Faso 12 months post-launch in late 2014. The design was a multiple and contrasted case study involving 18 cases (health centres). Empirical data were collected from observations, informal (n = 224) and formal (n = 459) interviews, and documents. Outside the circle of persons trained in PBF, few in the community had knowledge of it. In some health centres, the fact that staff were receiving bonuses was intentionally not announced to populations and community leaders. Most local actors thought PBF was just another project, but the majority appreciated it. There were significant delays in setting up agencies for performance monitoring, auditing, and contracting, as well as in the payment. The first audits led rapidly to coping strategies among health workers and occasionally to some staging beforehand. No community-based audits had yet been done. Distribution of bonuses varied from one centre to another. This study shows the importance of understanding the implementation of public health interventions in Africa and of uncovering coping strategies.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".