Cost‐effectiveness of School Hearing Screening Programs: A Scoping Review
Bibliographic record
Abstract
OBJECTIVE: School hearing screening is a public health intervention that can improve care for children who experience hearing loss that is not detected on or develops after newborn screening. However, implementation of school hearing screening is sporadic and supported by mixed evidence to its economic benefit. This scoping review provides a summary of all published cost-effectiveness studies regarding school hearing screening programs globally. At the time of this review, there were no previously published reviews of a similar nature. DATA SOURCES: A structured search was applied to 4 databases: PubMed (Medline), Embase, CINAHL, and Cochrane Library. REVIEW METHODS: The database search was carried out by 2 independent researchers, and results were reported in accordance with the PRISMA-ScR checklist and the JBI methodology for scoping reviews. Studies that included a cost analysis of screening programs for school-aged children in the school environment were eligible for inclusion. Studies that involved evaluations of only neonatal or preschool programs were excluded. RESULTS: Four of the 5 studies that conducted a cost-effectiveness analysis reported that school hearing screening was cost-effective through the calculation of incremental cost-effectiveness ratios (ICERs) via either quality- or disability-adjusted life years. One study reported that a new school hearing screening program dominated the existing program; 2 studies reported ICERs ranging from 1079 to 4304 international dollars; and 1 study reported an ICER of £2445. One study reported that school-entry hearing screening was not cost-effective versus no screening. CONCLUSION: The majority of studies concluded that school hearing screening was cost-effective. However, significant differences in methodology and region-specific estimates of model inputs limit the generalizability of these findings.
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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 | 0.021 | 0.099 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.016 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".