Changes in Economic Status of Households Associated with Catastrophic Health Expenditures for Cancer in South Korea
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Bibliographic record
Abstract
BACKGROUND: Cancer imposes significant economic challenges for individuals, families, and society. Households of cancer patients often experience income loss due to change in job status and/or excessive medical expenses. Thus, we examined whether changes in economic status for such households is affected by catastrophic health expenditures. MATERIALS AND METHODS: We used the Korea Health Panel Survey (KHPS) Panel 1st-4th (2008- 2011 subjects) data and extracted records from 211 out of 5,332 households in the database for this study. To identify factors associated with catastrophic health expenditures and, in particular, to examine the relationship between change in economic status and catastrophic health expenditures, we conducted a generalized linear model analysis. RESULTS: Among 211 households with cancer patients, 84 (39.8%) experienced catastrophic health expenditures, while 127 (40.2%) did not show evidence of catastrophic medical costs. If a change in economic status results from a change in job status for head of household (job loss), these households are more likely to incur catastrophic health expenditure than households who have not experienced a change in job status (odds ratios (ORs)=2.17, 2.63, respectively). A comparison between households with a newly-diagnosed patient versus households with patients having lived with cancer for one or two years, showed the longer patients had cancer, the more likely their households incurred catastrophic medical costs (OR=1.78, 1.36, respectively). CONCLUSIONS: Change in economic status of households in which the cancer patient was the head of household was associated with a greater likelihood that the household would incur catastrophic health costs. It is imperative that the Korean government connect health and labor policies in order to develop economic programs to assist households with cancer patients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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