A Cost‐effectiveness Analysis of Propofol versus Midazolam for Procedural Sedation in the Emergency Department
Bibliographic record
Abstract
OBJECTIVES: To determine the incremental cost-effectiveness of using propofol versus midazolam for procedural sedation (PS) in adults in the emergency department (ED). METHODS: The authors conducted a cost-effectiveness analysis from the perspective of the health care provider. The primary outcome was the incremental cost (or savings) to achieve one additional successful sedation with propofol compared to midazolam. A decision model was developed in which the clinical effectiveness and cost of a PS strategy using either agent was estimated. The authors derived estimates of clinical effectiveness and risk of adverse events (AEs) from a systematic review. The cost of each clinical outcome was determined by incorporating the baseline cost of the ED visit, the cost of the drug, the cost of labor of physicians and nurses, the cost and probability of an AE, and the cost and probability of a PS failure. A standard meta-analytic technique was used to calculate the weighted mean difference in recovery times and obtain mean drug doses from patient-level data from a randomized controlled trial. Probabilistic sensitivity analyses were conducted to examine the uncertainty around the estimated incremental cost-effectiveness ratio using Monte Carlo simulation. RESULTS: Choosing a sedation strategy with propofol resulted in average savings of $17.33 (95% confidence interval [CI] = $24.13 to $10.44) per sedation performed. This resulted in an incremental cost-effectiveness ratio of -$597.03 (95% credibility interval -$6,434.03 to $6,113.57) indicating savings of $597.03 per additional successful sedation performed with propofol. This result was driven by shorter recovery times and was robust to all sensitivity analyses performed. CONCLUSIONS: These results indicate that using propofol for PS in the ED is a cost-saving strategy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".