Prehospital transfusion training in Canada: a national survey of critical care transport organizations
Bibliographic record
Abstract
BACKGROUND: Hemorrhagic shock is a leading cause of preventable death, and prehospital transfusion has been associated with improved outcomes in select trauma and medical patients. In Canada, several Critical Care Transport Organizations (CCTOs) have implemented prehospital transfusion programs to reduce geographic disparities in access to definitive care. However, limited evidence exists on how providers are trained to deliver this intervention. While simulation-based education and instructional design features improve skill retention in other contexts, their application in prehospital transfusion training has not been systematically evaluated. This study aimed to assess current training practices among Canadian CCTOs and evaluate their effectiveness. METHODS: We conducted a cross-sectional survey across all Canadian CCTOs. Data were analyzed descriptively using the Kirkpatrick Model framework, which evaluates training effectiveness across four levels: learner satisfaction, knowledge acquisition, behaviour change, and patient outcomes. Reporting followed the Consensus-based checklist for reporting of survey studies (CROSS) guidelines. RESULTS: All seven Canadian CCTOs with active prehospital transfusion programs participated (100% response rate), with respondents including one transport physician, three registered nurses, and three critical care paramedics per organization. Programs represented fixed-wing, rotor-wing, and land-based transport systems operating in urban, suburban, rural, and remote settings. Training approaches varied across CCTOs. Checklists were universally used to assess competency, with four organizations incorporating additional tools such as global rating scales and scenario-based evaluations. Recertification practices were inconsistent: one CCTO required annual recertification, three used bi-annual reviews, and three had no formal recertification process. Using the Kirkpatrick Model, all seven CCTOs demonstrated Level 1 (Reaction) through provision of training; five used structured feedback mechanisms, while two relied on informal feedback. At Level 2 (Learning), six organizations used didactics, practical workshops, and field training, while one relied solely on mentorship. Level 3 (Behaviour) evaluations were conducted by four CCTOs, primarily through structured assessments; three relied on documentation audits or informal peer review. No CCTOs reported Level 4 (Results) assessments through tracking of patient outcomes related to transfusion. CONCLUSIONS: Considerable variability exists in prehospital transfusion training across Canadian CCTOs. Establishing training standards may support improved provider preparedness and contribute to enhanced patient care, although further evaluation is needed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".