Cost and quality of life of overlooked eye care needs of children
Bibliographic record
Abstract
BACKGROUND: The objective of this research was to conduct a systematic review and cost analysis to summarize, from the Ministry of Health perspective, the costs families might incur because of their child's prescription for refractive errors and amblyopia correction. METHODS: Databases including MEDLINE, Embase, BIOSIS, CINAHL, HEED, ISI Web of Science, and the Cochrane Library as well as the gray literature were searched. Systematic review was conducted using EPPI-Reviewer 4. Percentage difference in cost of glasses and patches per patient per various diagnoses were computed. The cost of glasses and patches was projected over a 5-year time horizon. Cost-utility analysis was performed. RESULTS: In total, 302 records were retrieved from multiple databases and an additional 48 records were identified through gray literature search. From these, a total of 14 studies (10,388 subjects) were eligible for quantitative analysis. The cost of glasses increased significantly for congenital cataract patients to US$1,820, esotropia patients to US$840, myopes to US$411, amblyopes (mixed) to US$916, anisometropes to US$521, and patients with strabismus to US$728 over a 5-year period making them unaffordable for low-income families. Incremental cost of glasses of congenital cataract patients with delayed treatment was computed to be US$1,690 per health utility gained. Incremental cost of glasses for high refractive error was US$93 per health utility gained in non-compliant children. For amblyopia patients, incremental cost of glasses per quality-adjusted life years gained was US$3,638. CONCLUSION: Cost of corrective lenses is associated with significant financial burden and thus other means of mitigating costs should be considered. Eyesight problems in children are perceived as low-priority health needs. Thus, educational interventions on substantial visual deficits of not wearing glasses should be offered to families and governmental health agencies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".