The impact of community-based health insurance on the utilization of medically trained healthcare providers among informal workers in Bangladesh
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Bibliographic record
Abstract
We aimed to estimate the impact of a Community-Based Health Insurance (CBHI) scheme on utilization of healthcare from medically trained providers (MTP) by informal workers. A quasi-experimental study was conducted where insured households were included in the intervention group and uninsured households in comparison group. In total 1,292 (646 insured and 646 uninsured) households were surveyed from Chandpur district comprising urban and rural areas after 1 year period of CBHI introduction. Matching of the characteristics of insured and uninsured groups was performed using a propensity score matching approach to minimize the observed baseline differences among the groups. Multilevel logistic regression model, with adjustment for individual and household characteristics was used for estimating association between healthcare utilization from the MTP and insurance enrolment. The utilization of healthcare from MTP was significantly higher in the insured group (50.7%) compared to the uninsured group (39.4%). The regression analysis demonstrated that the CBHI beneficiaries were 2.111 (95% CI: 1.458-3.079) times more likely to utilize healthcare from MTP.CBHI scheme increases the utilization of MTP among informal workers. Ensuring such healthcare for these workers and their dependents is a challenge in many low and middle income countries. The implementation and scale-up of CBHI schemes have the potential to address this challenge of universal health coverage.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it