Impact of eyewear insurance coverage on utilization of eyecare providers in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVE: To obtain prescription eyewear in Ontario, eye exams must be performed by optometrists or ophthalmologists (eye care providers [ECPs]). In 2004, government-insured routine eye exams were delisted for Ontarians aged 20-64 leaving eye exam coverage only for those aged ≤19 and 65+. We assessed whether having eyewear insurance impacts Ontarians' utilization of ECPs. DESIGN: Cross-sectional survey. PARTICIPANTS: Ontarians aged 12+ without diabetes responding to the Canadian Community Health Survey in 2003, 2005, and 2013/2014. METHODS: We compared the utilization of ECPs by eyewear insurance status and eligibility for government-funded eye exams. Individuals with eyewear insurance funded by employers, government or privately were considered to have insurance. RESULTS: ECP utilization was significantly higher in Ontarians with eyewear insurance versus those without, in all survey years and all age groups, including those eligible for government-funded eye exams (e.g., 66.4% vs 59.1% [p < 0.05] for the 65+). This higher level of utilization was particularly evident among Ontarians aged 20-64 in 2013/2014, when this group no longer had government-funded eye exams (34.9% vs 19.9% among 20-39-year-olds, 43.4% vs 32.9% among 40-64-year-olds, p < 0.05 for both). Adjusting for confounding effects, the likelihood of visiting an ECP was greater among Ontarians with eyewear insurance than those without (adjusted prevalence ratio 1.26 for Ontarians aged 12+ and 1.41 for those aged 20-64; p < 0.05 for both). CONCLUSIONS: Lack of eyewear insurance negatively impacts the utilization of ECPs, even among Ontarians eligible for government-funded eye exams, where the cost barrier for eye exams has been removed by the Ontario government.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".