Has Vietnam Health care funds for the poor policy favored the elderly poor?
Bibliographic record
Abstract
BACKGROUND: The elderly population is increasing in Vietnam. Access to health services for the elderly is often limited, especially for those in rural areas. User fees at public health care facilities and out-of-pocket payments for health care services are major barriers to access. With the aim of helping the poor access public health care services and reduce health care expenditures (HCE), the Health Care Funds for the Poor policy (HCFP) was implemented in 2002. The aim of this study is to investigate the impacts of this policy on elderly households. METHODS: Elderly households were defined as households which have at least one person aged 60 years or older. The impacts of HCFP on elderly household HCE as a percentage of total expenditure and health care utilization were assessed by a double-difference propensity score matching method using panel data of 3,957 elderly households in 2001, 2003, 2005 and 2007, of which 509 were classifies as "treated" (i.e. covered by the policy). Variables included in a logistic regression for estimating the propensity scores to match the treated with the control households, were household and household-head characteristics. RESULTS: In the first time period (2001-2003) there were no significant differences between treated and controls. This can be explained by the delay in implementing the policy by the local governments. In the second (2001-2005) and third period (2001-2007) the utilizations of Communal Health Stations (CHS) and go-to-pharmacies were significant. The treated were using CHS and pharmacies more between 2001 and 2007 while control households decreased their use. CONCLUSION: The main findings suggest HCFP met some goals but not all in the group of households having at least one elderly member. Utilization of CHS and pharmacies increased while the change in HCE as a proportion of total expenditures was not significant. To some extent, private health care and self-treatment are replaced by more utilization of CHS, indicating the poor elderly are better off. However, further efforts are needed to help them access higher levels of public health care (e.g. district health centers and provincial/central hospitals) and to reduce their HCE.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".