A cost-effectiveness analysis of self-debriefing versus instructor debriefing for simulated crises in perioperative medicine in Canada
Bibliographic record
Abstract
PURPOSE: High-fidelity simulation training is effective for learning crisis resource management (CRM) skills, but cost is a major barrier to implementing high-fidelity simulation training into the curriculum. The aim of this study was to examine the cost-effectiveness of self-debriefing and traditional instructor debriefing in CRM training programs and to calculate the minimum willingness-to-pay (WTP) value when one debriefing type becomes more cost-effective than the other. METHODS: This study used previous data from a randomized controlled trial involving 50 anesthesiology residents in Canada. Each participant managed a pretest crisis scenario. Participants who were randomized to self-debrief used the video of their pretest scenario with no instructor present during their debriefing. Participants from the control group were debriefed by a trained instructor using the video of their pretest scenario. Participants individually managed a post-test simulated crisis scenario. We compared the cost and effectiveness of self-debriefing versus instructor debriefing using net benefit regression. The cost-effectiveness estimate was reported as the incremental net benefit and the uncertainty was presented using a cost-effectiveness acceptability curve. RESULTS: Self-debriefing costs less than instructor debriefing. As the WTP increased, the probability that self-debriefing would be cost-effective decreased. With a WTP ≤Can$200, the self-debriefing program was cost-effective. However, when effectiveness was priced higher than cost-savings and with a WTP >Can$300, instructor debriefing was the preferred alternative. CONCLUSION: With a lower WTP (≤Can$200), self-debriefing was cost-effective in CRM simulation training when compared to instructor debriefing. This study provides evidence regarding cost-effectiveness that will inform decision-makers and clinical educators in their decision-making process, and may help to optimize resource allocation in education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".