Impact of crisis resource management simulation-based training for interprofessional and interdisciplinary teams: A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Crisis resource management (CRM) abilities are important for different healthcare providers to effectively manage critical clinical events. This study aims to review the effectiveness of simulation-based CRM training for interprofessional and interdisciplinary teams compared to other instructional methods (e.g., didactics). Interprofessional teams are composed of several professions (e.g., nurse, physician, midwife) while interdisciplinary teams are composed of several disciplines from the same profession (e.g., cardiologist, anaesthesiologist, orthopaedist). Medline, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials, and ERIC were searched using terms related to CRM, crisis management, crew resource management, teamwork, and simulation. Trials comparing simulation-based CRM team training versus any other methods of education were included. The educational interventions involved interprofessional or interdisciplinary healthcare teams. The initial search identified 7456 publications; 12 studies were included. Simulation-based CRM team training was associated with significant improvements in CRM skill acquisition in all but two studies when compared to didactic case-based CRM training or simulation without CRM training. Of the 12 included studies, one showed significant improvements in team behaviours in the workplace, while two studies demonstrated sustained reductions in adverse patient outcomes after a single simulation-based CRM team intervention. In conclusion, CRM simulation-based training for interprofessional and interdisciplinary teams show promise in teaching CRM in the simulator when compared to didactic case-based CRM education or simulation without CRM teaching. More research, however, is required to demonstrate transfer of learning to workplaces and potential impact on patient outcomes.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 it