Code Blue Emergencies: A Team Task Analysis and Educational Initiative
Bibliographic record
Abstract
INTRODUCTION: The objective of this study was to identify factors that have a positive or negative influence on resuscitation team performance during emergencies in the operating room (OR) and post-operative recovery unit (PAR) at a major Canadian teaching hospital. This information was then used to implement a team training program for code blue emergencies. METHODS: In 2009/10, all OR and PAR nurses and 19 anesthesiologists at Vancouver General Hospital (VGH) were invited to complete an anonymous, 10 minute written questionnaire regarding their code blue experience. Survey questions were devised by 10 recovery room and operation room nurses as well as 5 anesthesiologists representing 4 different hospitals in British Columbia. Three iterations of the survey were reviewed by a pilot group of nurses and anesthesiologists and their feedback was integrated into the final version of the survey. RESULTS: Both nursing staff (n = 49) and anesthesiologists (n = 19) supported code blue training and believed that team training would improve patient outcome. Nurses noted that it was often difficult to identify the leader of the resuscitation team. Both nursing staff and anesthesiologists strongly agreed that too many people attending the code blue with no assigned role hindered team performance. CONCLUSION: Identifiable leadership and clear communication of roles were identified as keys to resuscitation team functioning. Decreasing the number of people attending code blue emergencies with no specific role, increased access to mock code blue training, and debriefing after crises were all identified as areas requiring improvement. Initial team training exercises have been well received by staff.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 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".