Effect of Physician Remuneration Fees on Glaucoma Procedure Rates in Canada
Bibliographic record
Abstract
PURPOSE: Earlier studies have reported wide regional variability in glaucoma procedure rates, suggesting nonclinical factors influencing procedure rates. This study was designed to investigate the possible influence of fees on procedure rates. METHODS: Databases were accessed to obtain yearly provincial population, procedure and ophthalmologist numbers, and physician fees for trabeculoplasties, trabeculectomies, and glaucoma drainage device (GDD) implantations from 1992 to 2007. Regression models using generalized estimating equation methods were used to evaluate the influence of fees on procedure rates after adjusting for temporal trends and the number of ophthalmologists per 1000 persons with glaucoma. RESULTS: Trends in glaucoma procedure rates and fees varied widely among provinces: decrease of 98% to an increase of 380% for trabeculoplasties, decrease of 72% to an increase of 42% for trabeculectomies, and decrease of 32% to an increase of 1292% for GDD. In 2007, provincial remuneration varied from $125 to $553 for trabeculoplasties, $370 to $748 for trabeculectomies, and $426 to $956 for GDD. The regression models found for every 1000 persons with glaucoma, a $100 increase in fee was associated with 0.68 more trabeculoplasties (P=0.94), 1.2 fewer trabeculectomies (P=0.17), and 0.18 more GDD implantations (P=0.18); and for every additional ophthalmologist per 1000 persons with glaucoma, 53.8 more trabeculoplasties (P=0.24), 0.34 more trabeculectomies (P=0.86), and 0.79 more GDD implantations (P=0.0004). A regression model examining procedure substitution effect did not find any association between relative remuneration and procedure rate. CONCLUSION: Our analysis did not show an influence of physician remuneration fee on procedure rates in Canada during the study period.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".