Impact of mutual health organizations: Evidence from West Africa. Health Policy and Planning
Bibliographic record
Abstract
Mutual health organizations (MHOs) are voluntary membership organizations providing health insurance services to their members. MHOs aim to increase access to health care by reducing out-of-pocket payments faced by households. We used multiple regression analysis of household survey data from Ghana, Mali and Senegal to investigate the determinants of enrolment in MHOs, and the impact of MHO membership on use of health care services and on out-of-pocket health care expenditures for outpatient care and hospitalization. We found strong evidence that households headed by women are more likely to enrol in MHOs than households headed by men. Education of the household head is positively asso-ciated with MHO enrolment. The evidence on the association between household economic status and MHO enrolment indicates that individuals from the richest quintiles are more likely to be enrolled than anyone else. We did not find evidence that individuals from the poorest quintiles tend to be excluded from MHOs. MHO members are more likely to seek formal health care in Ghana and Mali, although this result was not confirmed in Senegal. While our evidence on whether MHO membership is associated with higher probability of hospitaliza-tion is inconclusive, we find that MHO membership offers protection against the potentially catastrophic expenditures related to hospitalization. However, MHO membership does not appear to have a significant effect on out-of-pocket expenditures for curative outpatient care.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".