Eye-care utilization among a Canadian diabetic refugee population: retrospective cohort study of an interdisciplinary care model
Bibliographic record
Abstract
Introduction Vision health is an important and underutilized health service among newly arrived refugees in Canada, yet the body of literature on eye-care delivery in this population is limited. The study objective was to identify patterns of eye-care utilization among refugee patients with type 2 diabetes mellitus (T2DM) in Newfoundland and Labrador (NL) under an interdisciplinary clinic model comprised of family physicians, eye-care providers, and settlement services. Methods This was a retrospective cohort study at the Memorial University Family Medicine clinic. All patients with a new T2DM diagnosis between 2015–2020 were included. Data were described using basic statistics and unpaired t-tests. This study received full ethics approval. Results Seventy-three (18 refugee, 55 non-refugee) patients were included. Refugees had a higher rate of referral to an eye-care provider ( p = 0.0475) and were more likely to attend their eye-care provider appointment than non-refugees ( p = 0.016). The time from diagnosis to referral was longer for refugees than non-refugees ( p = 0.0498). A trend towards longer time from referral to appointment attendance for refugees than non-refugees was noted ( p = 0.9069). Discussion Refugee patients had higher rates of referral to eye-care providers and utilization of eye-care services. However, refugees also experienced a longer time to access vision screening services suggesting possible gaps in accessible care delivery. This suggests that the interdisciplinary model of care may be effective in referring refugee patients for vision screening and there may be a role for increased collaboration across family physicians, eye-care providers, and settlement services to improve accessibility of vision screening services.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".