An Evaluation of the Outcomes of Mutual Health Organizations in Benin
Bibliographic record
Abstract
BACKGROUND: Mutual health organizations (MHO) have been seen as a promising alternative to the fee-based funding model but scientific foundations to support their generalization are still limited. Very little is known about the extent of the impact of MHOs on health-seeking behaviours, quality and costs. METHODOLOGY/PRINCIPAL FINDINGS: We present the results of an evaluation of the effects attributable to membership in an MHO in a rural region of Benin. Two prospective studies of users (parturients and hospitalized patients) were conducted on the territory of an inter-mutual consisting of 10 MHOs and as many healthcare centres (one, Ouessé, serving as a referral hospital) and one hospital (Papané). Members and non-members were matched (142 pairs of parturients and 109 triads of hospitalized patients) and multilevel multiple regression was used. Results show that member parturients went to healthcare centres sooner (p = 0.049) and were discharged more quickly after delivery (p = 0.001) than non-members. Length of stay in some cases was longer for hospitalized member parturients (+41%). Being a member did not shorten hospital stay, total length of episode of care, or time between appearance of symptoms and recourse to care. Regarding expenses, member parturients paid one-third less than non-members for a delivery. For hospitalized patients, the average savings for members was around $35 US. Total expenses incurred by patients hospitalized at Papané Hospital were higher than at Ouessé but the two hospitals' relative advantages were comparable at -36% and -39%, respectively. CONCLUSION/SIGNIFICANCE: These results confirm mutual health organizations' capacity to protect households financially, even if benefits for the poor have not been clearly determined. The search for scientific evidence should continue, to understand their impacts with regard to services obtained by their members.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".