The impact of universal health coverage and COVID-19 pandemic on out-of-pocket expenses in Thailand: an analysis of household survey from 1994 to 2021
Bibliographic record
Abstract
After Thailand achieved Universal Health Coverage (UHC) in 2002, the extent of financial risk protection has not been assessed in the long term, especially after the COVID-19 pandemic. Therefore, this study aims to revisit the impact of UHC on out-of-pocket expenses (OOPE) for health and to descriptively explore the impact of COVID-19 on OOPE. This study was a secondary data analysis and used data from the Socio-Economic Survey from 1994 to 2021 in Thailand. The effect of UHC on the percentage of OOPE in total health expenditures (THE) from 1994 to 2019 was investigated with an interrupted time-series analysis. Descriptive analyses of OOPE in absolute value during the COVID-19 were conducted. The percentage of OOPE in THE significantly decreased both before (β −2.02%; 95% CI: −2.70% to − 1.33%) and during (β 1.41%; 95% CI: 0.70% to 2.11%) the UHC period. During the pandemic, total household OOPE for medical equipment was found to have rapidly increased from 643 million THB in 2019 to 9.4 billion THB in 2020. The trend of providing financial risk protection (measured by OOPE/THE) in Thailand continues until 2019. Providing medical equipment in sufficient and equally accessible manners should be prioritized during the future pandemic.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 teacher head, 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".