Simulated critical care calls: a simple way to teach complex skills
Bibliographic record
Abstract
This abstract outlines the use of simulated critical care telephone calls into the education of trainees. We hope others may consider it for their centres. The Capital Health Region provides advanced healthcare for 2 million people, but spread over 9,800 km. We therefore rely heavily on transportation of critically ill patients to a single urban centre. In addition to geographic and climatic factors, bed pressures complicate how we triage, stabilize, transport and receive those patients. A major strategy is the 'Critical-Care-Line': a 24-hour telephone service with teleconference capabilities and contact numbers. However, experience suggests it takes practice to become proficient with its use. Given the importance of optimal communication, we arrange simulated calls. Senior trainees are paged during a normal workday by the Critical-Care-Line: just as they will be once in independent practice. The facilitator then assumes the role of a referring doctor in a small town. Peer-reviewed cases are used that include pertinent teaching points. Applicable staff at the teaching centre are briefed of this exercise and asked to act as they normally would. For example, emergency physicians, internists, senior nurses and administrators are notified that they may be brought into the call, depending on whether the trainee decides to involve other services (for example, if he/she decides a patient requires further work-up before deciding upon ICU or if he/she decides to bring the patient to emergency if no ICU bed is currently available). All calls are recorded to aid debriefing. This method allows us to ascertain how trainees ask focused histories, offer practical advice based upon the variable skill set of referring physicians, and deal with complex ethical decisions (for example, if a family wishes to override a patient's previous wish; or how aggressively to treat the terminal patient for whom no prior discussions have occurred). It allows us to test the trainees' knowledge, but more importantly we can determine how well that knowledge is applied in everyday practice. In Canada, the Royal College of Physician and Surgeons has decreed that trainees become not just medical experts, but also proficient communicators, collaborators, and managers [1]. These goals, while laudable, have been very difficult to capture without novel approaches such as the one outlined. This simple and cost-free addition to our training has been very well received. Initial success means it will now be expanded throughout acute care specialist training.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.012 |
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".