QALY weights for neurosensory impairments in pediatric economic evaluations: case studies and a critique
Bibliographic record
Abstract
The use of utility weights for the calculation of quality-adjusted life years is particularly problematic for pediatric health states. This article reviews variability in utility weights for intellectual disability and permanent hearing loss in economic evaluations of newborn screening and childhood immunizations. Utility weights for severe intellectual disability ranged from 0.06 to 0.74. Most studies either did not vary these utility weights in sensitivity analyses or assumed low variability; consequently, the robustness of cost-effectiveness estimates was not fully assessed. Two recently published catalogs of utility weights for pediatric health states also show wide divergences in estimates. More work is needed to establish measures of health utilities for childhood health states in order to allow for comparable assessments of pediatric interventions.
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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 | 0.052 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.003 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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; both teacher heads agree on what is shown here.
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".