An implementation evaluation of a policy aiming to improve financial access to maternal health care in Djibo district, Burkina Faso
Bibliographic record
Abstract
BACKGROUND: To bring down its high maternal mortality ratio, Burkina Faso adopted a national health policy in 2007 that designed to boost the assisted delivery rate and improving quality of emergency obstetrical and neonatal care. The cost of transportation from health centres to district hospitals is paid by the policy. The worst-off are exempted from all fees. METHODS: The objectives of this paper are to analyze perceptions of this policy by health workers, assess how this health policy was implemented at the district level, identify difficulties faced during implementation, and highlight interactional factors that have an influence on the implementation process. A multiple site case study was conducted at 6 health centres in the district of Djibo in Burkina Faso. The following sources of data were used: 1) district documents (n = 23); 2) key interviews with district health managers (n = 10), health workers (n = 16), traditional birth attendants (n = 7), and community management committees (n = 11); 3) non-participant observations in health centres; 4) focus groups in communities (n = 62); 5) a feedback session on the findings with 20 health staff members. RESULTS: All the activities were implemented as planned except for completely subsidizing the worst-off, and some activities such as surveys for patients and the quality assurance service team aiming to improve quality of care. District health managers and health workers perceived difficulties in implementing this policy because of the lack of clarity on some topics in the guidelines. Entering the data into an electronic database and the long delay in reimbursing transportation costs were the principal challenges perceived by implementers. Interactional factors such as relations between providers and patients and between health workers and communities were raised. These factors have an influence on the implementation process. Strained relations between the groups involved may reduce the effectiveness of the policy. CONCLUSIONS: Implementation analysis in the context of improving financial access to health care in African countries is still scarce, especially at the micro level. The strained relations of the providers with patients and the communities may have an influence on the implementation process and on the effects of this health policy. Therefore, power relations between actors of the health system and the community should be taken into consideration. More studies are needed to better understand the influence of power relations on the implementation process in low-income countries.
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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 | 0.020 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".