The impact of health insurance on health services utilization and health outcomes in Vietnam
Bibliographic record
Abstract
In recent years, a number of low- and middle-income country governments have introduced health insurance schemes. Yet not a great deal is known about the impact of such policy shifts. Vietnam's recent health insurance experience including a health insurance scheme for the poor in 2003 and a compulsory scheme that provides health insurance to all children under six years of age combined with Vietnam's commitment to universal coverage calls for research that examines the impact of health insurance. Taking advantage of Vietnam's unique policy environment, data from the 2002, 2004 and 2006 waves of the Vietnam Household Living Standard Survey and single-difference and difference-in-differences approaches are used to assess whether access to health insurance--for the poor, for children and for students--impacts on health services utilization and health outcomes in Vietnam. For the poor and for students, results suggest health insurance increased the use of inpatient services but not of outpatient services or health outcomes. For young children, results suggest health insurance increased the use of outpatient services (including the use of preventive health services such as vaccination and check-up) but not of inpatient services.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".