Delisted Routine Eye Exams and the Increased Use of Family Physicians and Ophthalmologists for Glaucoma Diagnosis
Bibliographic record
Abstract
Purpose: To investigate if delisting routine eye exams in 2004 for Ontarians aged 20-64 was associated with increased use of family physicians (FPs) and ophthalmologists for new glaucoma diagnoses.Methods: The utilization of FPs and ophthalmologists for new glaucoma diagnoses from 1997-2019 was analyzed using administrative data and interrupted time series analysis. Results: In policy-affected groups, FP utilization for glaucoma diagnoses significantly increased post- versus pre-delisting: 14.6% (95% confidence interval [CI] 11.0%~18.3%) for the 20-39 group and 9.9% (95% CI 8.2%~11.5%) for the 40-64 group. Ophthalmologist utilization for glaucoma diagnoses increased substantially: 41.5% (95% CI 37.8%~45.3%) for those 20-39 and 40.3% (95% CI 35.7%~45.0%) for those 40-64. In the policy-unaffected 65+ group, minimal increases were observed: 1.9% (95% CI 0.6%~3.2%) for FPs and 4.4% (95% CI 0.4%~8.4%) for ophthalmologists. Conclusions: Delisting routine eye exams for individuals aged 20-64 was associated with increased use of FPs and ophthalmologists for glaucoma diagnoses.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".