Examination of Healthcare Quality Indicators with a Two-Stage Panel Data Analysis: The Case of Cancer Care
Bibliographic record
Abstract
Purpose: The aim of this study was to examine the quality of care for cancer patients using survival rates for breast, cervical, colorectal, lung, and stomach cancers. Methods: The study population comprised OECD countries. Survival rates from breast, cervical, colorectal, lung, and stomach cancers, alcohol use, smoking, physical inactivity, and obesity rates, age, and income were selected as research data. A two-stage panel data analysis was performed. In the first stage, efficiency scores were found to be an indicator of the quality of cancer care through data envelopment analysis. In the second stage, the factors affecting efficiency were determined by panel tobit regression analysis. Results: In the first stage, Australia, Canada, Finland, Iceland, Israel, Israel, Korea, the Slovak Republic and Turkey were found to be efficient in all years. In the second stage, it was found that alcohol consumption, smoking, and inactivity statistically decreased cancer activity (p
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".