A Cost-effectiveness Analysis of Early vs Late Tracheostomy
Bibliographic record
Abstract
Importance: The timing of tracheostomy in critically ill patients requiring mechanical ventilation is controversial. An important consideration that is currently missing in the literature is an evaluation of the economic impact of an early tracheostomy strategy vs a late tracheostomy strategy. Objective: To evaluate the cost-effectiveness of the early tracheostomy strategy vs the late tracheostomy strategy. Evidence Acquisition: This economic analysis was performed using a decision tree model with a 90-day time horizon. The economic perspective was that of the US health care third-party payer. The primary outcome was the incremental cost per tracheostomy avoided. Probabilities were obtained from meta-analyses of randomized clinical trials. Costs were obtained from the published literature and the Healthcare Cost and Utilization Project database. A multivariate probabilistic sensitivity analysis was performed to account for uncertainty surrounding mean values used in the reference case. Results: The reference case demonstrated that the cost of the late tracheostomy strategy was $45 943.81 for 0.36 of effectiveness. The cost of the early tracheostomy strategy was $31 979.12 for 0.19 of effectiveness. The incremental cost-effectiveness ratio for the late tracheostomy strategy compared with the early tracheostomy strategy was $82 145.24 per tracheostomy avoided. With a willingness-to-pay threshold of $50 000, the early tracheostomy strategy is cost-effective with 56% certainty. Conclusions and Relevance: The adaptation of an early vs a late tracheostomy strategy depends on the priorities of the decision-maker. Up to a willingness-to-pay threshold of $80 000 per tracheostomy avoided, the early tracheostomy strategy has a higher probability of being the more cost-effective intervention.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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".