Cost-effectiveness of Metered-Dose Inhalers for Asthma Exacerbations in the Pediatric Emergency Department
Bibliographic record
Abstract
OBJECTIVE: To compare the incremental cost and effects (averted admission) of using a metered-dose inhaler (MDI) against wet nebulization to deliver bronchodilators for the treatment of mild to moderately severe asthma in pediatric emergency departments (EDs). METHODS: We measured the incremental cost-effectiveness from the perspective of the hospital, by creating a model using outcome characteristics from a Cochrane systematic review comparing the efficacy of using MDIs versus nebulizers for the delivery of albuterol to children presenting to the ED with asthma. Cost data were obtained from hospitals and regional authorities. We determined the incremental cost-effectiveness ratio and performed probabilistic sensitivity analyses using Monte Carlo simulations. RESULTS: Using MDIs in the ED instead of wet nebulization may result in net savings of Can$154.95 per patient. Our model revealed that using MDIs in the ED is a dominant strategy, one that is more effective and less costly than wet nebulization. Probabilistic sensitivity analyses revealed that 98% of the 10 000 iterations resulted in a negative incremental cost-effectiveness ratio. Sensitivity analyses around the costs revealed that MDI would remain a dominant strategy (90% of 10 000 iterations) even if the net cost of delivering bronchodilators by MDI was Can$70 more expensive than that of nebulized bronchodilators. CONCLUSIONS: Use of MDIs with spacers in place of wet nebulizers to deliver albuterol to treat children with mild-to-moderate asthma exacerbations in the ED could yield significant cost savings for hospitals and, by extension, to both the health care system and families of children with asthma.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".