Low-Value Inter-hospital Transfers in Canadian Trauma Care: Protocol for an Environmental Scan
Bibliographic record
Abstract
Injuries place a substantial burden on Canadian society, resulting in a significant loss of life-years and immense healthcare costs. Within trauma systems, low-value transfers—defined as unnecessary, inappropriate, or inefficient inter-facility patient movements—are a pervasive source of low-value care. They impose a considerable economic and ecological burden and compromise care quality by exposing individuals to avoidable risks such as prolonged transport times, delayed access to definitive care, and an increased potential for adverse events. Furthermore, they can inflict significant psychological distress and personal costs on caregivers. Recognizing these multifaceted detrimental impacts, reducing low-value transfers has been identified as a trauma system improvement priority across Canada. This protocol describes a comprehensive national environmental scan designed to systematically assess current trauma transfers structures within all Canadian provincial trauma systems. The anticipated results will provide a foundational understanding and detailed mapping of existing trauma transfer structures across Canada.
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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 | 0.036 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.087 | 0.015 |
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".