Effectiveness of the Gratuité user fee exemption policy on utilization and outcomes of maternal, newborn and child health services in conflict-affected districts of Burkina Faso from 2013 to 2018: a pre-post analysis
Bibliographic record
Abstract
BACKGROUND: Evidence on effectiveness of user fee exemption policies targeting maternal, newborn, and child health (MNCH) services is limited for conflict-affected settings. In Burkina Faso, a country that has had its fair share of conflicts, user fee exemption policies have been piloted since 2008 and implemented along with a national government-led user fee reduction policy ('SONU': Soins Obstétricaux et Néonataux d'Urgence). In 2016, the government transitioned the entire country to a user fee exemption policy known as Gratuité. Our study objective was to assess the effect of the policy on the utilization and outcomes of MNCH services in conflict-affected districts of Burkina Faso. METHODS: We conducted a quasi-experimental study comparing four conflict-affected districts which had the user fee exemption pilot along with SONU before transitioning to Gratuité (comparator) with four other districts with similar characteristics, which had only SONU before transitioning (intervention). A difference-in-difference approach was initiated using data from 42 months before and 30 months after implementation. Specifically, we compared utilization rates for MNCH services, including antenatal care (ANC), facility delivery, postnatal care (PNC) and consultation for malaria. We reported the coefficient, including a 95% confidence interval (CI), p value, and the parallel trends test. RESULTS: Gratuité led to significant increases in rates of 6th day PNC visits for women (Coeff 0.15; 95% CI 0.01-0.29), new consultations in children < 1 year (Coeff 1.80; 95% CI 1.13-2.47, p < 0.001), new consultations in children 1-4 years (Coeff 0.81; 95% CI 0.50-1.13, p = 0.001), and uncomplicated malaria cases treated in children < 5 years (Coeff 0.59; 95% CI 0.44-0.73, p < 0.001). Other service utilization indicators investigated, including ANC1 and ANC5+ rates, did not show any statistically significant positive upward trend. Also, the rates of facility delivery, 6th hour and 6th week postnatal visits were found to have increased more in intervention areas compared to control areas, but these were not statistically significant. CONCLUSIONS: Our study shows that, even in conflict-affected areas, the Gratuité policy significantly influences MNCH service utilization. There is a strong case for continued funding of the user fee exemption policy to ensure that gains are not reversed, especially if the conflict ceases to abate.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".