Health Care Supply for Cataract in Austrian Public and Private Hospitals
Bibliographic record
Abstract
PURPOSE: This study aims to explain spatial variability or cataract and cataract surgery in Austria. The effect of the availability of health care services on spatial variation is investigated. METHODS: A retrospective study, using routine hospital data from all Austrian public and private hospitals. Calculation of age- and gender-standardized hospitalization ratios (SHR) for all 121 Austrian districts. Poisson regression for age-specific relative risks was performed. RESULTS: The authors found high regional variability between districts and significant differences in the hospitalization rates of cataract disease and extraction between men and women. There was a significant correlation between standardized hospitalization ratios for districts and the availability of hospitals with departments of ophthalmology. There was a significant difference in length of stay for patients with cataract surgery between public and private hospitals. CONCLUSIONS: Use of routine hospital data in geographic analysis allows large regional studies on health care supply for cataract surgery. Differences in the supply by hospitals between districts depend on the availability of hospitals with departments of ophthalmology. The overall demand for cataract surgery in Austria finds its proper supply in many Austrian regions, but needs further development.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".