Diabetic Retinopathy Screening Among at Risk Populations: Protocol for Distributional Cost-Effectiveness Analysis
Bibliographic record
Abstract
BACKGROUND: Diabetic retinopathy (DR) remains the primary vision complication of diabetes and the leading cause of blindness among adults, with up to 30% prevalence among low-income populations. Tele-retina is a cost-effective screening alternative to vision loss prevention, yet there is an adverse association between screening and income. Intersectionality theory notes that barriers to achieving health equity result from the intersection of personal and social characteristics. Experiences at this intersection are influenced by interpersonal and structural systems of oppression. Studies have found that tele-retina is the preferred strategy over standard of care screening for at-risk populations. No study has assessed the economic equity impact of DR screening using a theoretical foundation. OBJECTIVE: This study aims to address shortcomings related to the utilization of intersectionality theory in the economic evaluation of DR screening. We propose conducting a distributional cost-effectiveness analysis (DCEA) of the tele-retina program. METHODS: The study will be undertaken using a deductive theoretical drive sequential multimethod approach, consisting of two studies: (1) a modified Delphi study and (2) DCEA. The Delphi panel (patient partners, field experts, and decision makers; N=35-50) will select the social constructs (eg, age, gender) for at-risk populations and potential trade-offs between health maximization and equity. The research will be guided by a social theory framework (intersectionality theory) to understand the impact of social constructs on economic outcomes. Social constructs that are selected by the Delphi panel will be integrated into the validated tele-retina cost-effectiveness analysis model, which will serve as a case study for DCEA. RESULTS: We have submitted the research ethics board application to the University Health Network Research Ethics Board and are expecting to begin recruitment for the Delphi study in Spring 2025. We anticipate beginning work on the model in the summer of 2025 and completing it by early 2026. CONCLUSIONS: The Delphi study will provide an understanding of which social factors are deemed necessary by the stakeholders for guiding the inequity in care access. Study results will offer information related to the net health benefit of the intervention and the health equity impact of the tele-retina program, hence providing a more comprehensive valuation of the tele-retina program, which is informative to policy makers and governments whose goal is to mitigate the drivers of health inequities. We anticipate that each of these drivers will raise important questions regarding the implications for decision-making that may have not yet been addressed by Canadian health technology assessment bodies, such as the Canada Drug Agency. This is the first Canadian study to (1) have social constructs for DCEA selected by the Delphi panel, (2) mainstream how health equity framework and social constructs are used in economic assessment, (3) improve DR screening programs by using health equity lens, and (4) scale and adopt "de-novo" integration of social constructs in economic models for program evaluation. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/60488.
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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 | 0.068 | 0.089 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.128 | 0.012 |
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".