Trauma-Related Clinical Practice Variation in Dutch Emergency Departments
Bibliographic record
Abstract
Structural insights in the use of protocols and the extent of practice variation in EDs are lacking. The objective is to determine the extent of practice variation in EDs in The Netherlands, based on specified common practices. We performed a comparative study on Dutch EDs that employed emergency physicians to determine practice variation. Data on practices were collected via a questionnaire. Fifty-two EDs across The Netherlands were included. Thrombosis prophylaxis was prescribed for below-knee plaster immobilization in 27% of EDs. Vitamin C was prescribed in 50% of EDs after a wrist fracture. Splitting of applied casts to the upper or lower limb was performed in one-third of the EDs. Analysis of the cervical spine after trauma was performed by the NEXUS criteria (69%), the Canadian C-spine Rule (17%) or otherwise. The imaging modality for cervical spine trauma in adults was a CT scan (98%). The cast used for scaphoid fractures was divided between the short arm cast (46%) and the navicular cast (54%). Locoregional anaesthesia for femoral fractures was applied in 54% of the EDs. EDs in The Netherlands showed considerable practice variation in treatments among the subjects studied. Further research is warranted to gain a full understanding of the variation in practice in EDs and the potential to improve quality and efficiency.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".