Temporal Trends in Patient Choice of Outpatient Care Provider Among Vietnam's Insured Rural Residents, 2006–2020
Bibliographic record
Abstract
Much of the existing empirical literature on patient choice of medical care provider in low- and middle-income countries is cross sectional in nature. Comparatively little is known about the dynamic shifts in patient choice of provider, particular under transitions to universal health coverage. Using eight biennial waves of Vietnam's Household Living Standard Survey covering the period 2006-2020 and a multilevel multinomial logit model, this study examined temporal trends in patient choice of provider among the insured rural residents. Patient choice of provider shifted steadily from commune health centres (CHCs) towards public hospitals and private health facilities over the study period. Patients were 3.9 and 8.3 times, respectively, as likely to use higher-level government hospitals and private hospitals over CHCs in 2018-2020 than in 2006-2008, and 2.8-3 times as likely to use district hospitals or private clinics. The shifts were more pronounced for economically better-off patients than the less better-off patients. Relative to 2006-2008, patients in the top three expenditure quintiles were 5.4 times as likely to use higher-level government hospitals over CHCs for a medical treatment in 2018-2020 than patients in the bottom two expenditure quintiles, and by as much as 11.5 times as likely to use private hospitals. These findings call for systemic policy measures that would relocate the entry point to the health system from hospital outpatient departments to grassroots primary care services and to improve public and private hospital accountability as a way of ensuring equitable access to high-quality essential health care for all.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".