Fees-for-services, cost recovery, and equity in a district of Burkina Faso operating the Bamako Initiative.
Bibliographic record
Abstract
OBJECTIVE: To gauge the effects of operating the Bamako Initiative in Kongoussi district, Burkina Faso. METHODS: Qualitative and quasi-experimental quantitative methodologies were used. FINDINGS: Following the introduction of fees-for-services in July 1997, the number of consultations for curative care fell over a period of three years by an average of 15.4% at "case" health centres but increased by 30.5% at "control" health centres. Moreover, although the operational results for essential drugs depots were not known, expenditure increased on average 2.7 times more than income and did not keep pace with the decline in the utilization of services. Persons in charge of the management committees had difficulties in releasing funds to ensure access to care for the poor. CONCLUSION: The introduction of fees-for-services had an adverse effect on service utilization. The study district is in a position to bear the financial cost of taking care of the poor and the community is able to identify such people. Incentives must be introduced by the state and be swiftly applied so that the communities agree to a more equitable system and thereby allow access to care for those excluded from services because they are unable to pay.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".