Economic evaluation of interventions for the treatment of asthma in children: A systematic review
Bibliographic record
Abstract
OBJECTIVES: This systematic review aimed to identify and critique full economic evaluations (EEs) of childhood asthma treatments with the intention to guide researchers and commissioners of pediatric asthma services toward potentially cost-effective strategies. METHODS: "MEDLINE," "Embase," "EconLit," "NHS EED," and "CEA" databases were searched to identify relevant EEs published between 2005 and May 2017. Quality of included studies was assessed with a published checklist. RESULTS: Eighteen studies were identified and comprised one cost-benefit analysis, 11 cost-effectiveness analyses, one cost-minimization analysis, and six cost-utility analyses. Treatments included pharmaceutical (n = 11) and non-pharmaceutical (n = 7) interventions. Fourteen studies identified cost-effective strategies. The quality of the studies varied and there were uncertainties due to the methods and relevance of data used. CONCLUSION: Good-quality economic evaluation studies of pediatric asthma treatments are lacking. EE of new technologies adapted to local settings is recommended and can result in cost savings.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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".