An Evaluation of Healthcare Use and Child Morbidity 4 Years After User Fee Removal in Rural Burkina Faso
Bibliographic record
Abstract
Objectives Increasing financial access to healthcare is proposed to being essential for improving child health outcomes, but the available evidence on the relationship between increased access and health remains scarce. Four years after its launch, we evaluated the contextual effect of user fee removal intervention on the probability of an illness occurring and the likelihood of using health services among children under 5. We also explored the potential effect on the inequality in healthcare access. Methods We used a comparative cross-sectional design based upon household survey data collected years after the intervention onset in one intervention and one comparison district. Propensity scores weighting was used to achieve balance on covariates between the two districts, which was followed by logistic multilevel modelling to estimate average marginal effects (AME). Results We estimated that there was not a significant difference in the reduced probability of an illness occurring in the intervention district compared to the non-intervention district [AME 4.4; 95% CI 1.0–9.8)]. However, the probability of using health services was 17.2% (95% CI 15.0–26.6) higher among children living in the intervention district relative to the comparison district, which rose to 20.7% (95% CI 9.9–31.5) for severe illness episodes. We detected no significant differences in the probability of health services use according to socio-economic status [χ2 (5) = 12.90, p = 0.61]. Conclusions for Practice In our study, we found that user fee removal led to a significant increase in the use of health services in the longer term, but it is not adequate by itself to reduce the risk of illness occurrence and socioeconomic inequities in the use of health services.
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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 | 0.001 | 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 | 0.001 |
| 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".