The evaluation of an experiment in healthcare user fees exemption for vulnerable groups in Burkina Faso
Bibliographic record
Abstract
Introduction: The African Union and United Nations agencies requested that children under five years and pregnant women be exempt from healthcare payment at the point of service. Indeed, this payment method is a financial barrier to healthcare access that the most vulnerable populations cannot overcome. Since Burkina Faso had not yet implemented such a policy, an experiment was undertaken starting in 2008 in two districts of the Sahel region in order to produce evidence. Methods: A research programme was organised in order to evaluate the effectiveness, equity, processes, costs and social effects of this experiment. Twelve studies were undertaken that used a concurrent mixed method design with data collected from individuals, households, health centres and villages. Results: The experiment was integrated into the health system and was fully appreciated by all. The third-party payer system was effective. Pregnant women and children under the age of five years had faster and broader access to the health system. The poorest among them substantially benefited from the intervention. The quality of care was sustained and costs were controlled. Conclusion: Since equity is a priority for the government and its financial partners, the research results suggest that exemption should be extended to the national level and that measures should be organised to break down the geographic barrier.
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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 | 0.033 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".