Tele-retina screening of diabetic retinopathy among at-risk populations: an economic analysis
Bibliographic record
Abstract
OBJECTIVES: To assess the cost-effectiveness of the pilot Toronto tele-retina screening program in comparison with existing standard of care (SOC) diabetic retinopathy (DR) screening for patients with diabetes mellitus and in a simulated Pan-Ontarian cohort. METHODS: Decision trees were constructed to compare tele-retina to SOC in the pilot and Pan-Ontarian cohort. Cost-effectiveness was assessed as cost per case detected (true-positive) and cost per case correctly diagnosed (true-positive and true-negative results). RESULTS: Pilot program screening costs were $95.77 and $137.56 for tele-retina and SOC, respectively. In the base-case analysis, cost per case correctly detected was $379.06 with tele-retina and $985.56 with SOC, and the cost per case correctly diagnosed was $109.29 and $315.22, respectively. In the sensitivity analysis, cost per case correctly detected was $467.29 with tele-retina and $894.93 with SOC, and the cost per case correctly diagnosed was $136.88 and $250.35, respectively. Pan-Ontarian screening costs were $57.58 and $137.56 for tele-retina and SOC, respectively. The cost per case correctly detected was $281.10 with tele-retina and $982.00 with SOC, and the cost per case correctly diagnosed was $82.21 and $314.14, respectively. For both pilot and Pan-Ontarian sensitivity analyses, tele-retina remained the dominant strategy (ICER <0). CONCLUSIONS: Findings from this study suggest that tele-retina is a more cost-effective means of screening for diabetic retinopathy than the SOC in urban and rural underscreened communities. Subsequent economic studies should focus on evaluations that consider the impact of tele-retina on the prevention of severe vision loss in underscreened urban and rural communities.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".