Effectiveness of a Training Course on Accuracy of Triaging of Pediatric Patients
Bibliographic record
Abstract
BACKGROUND: In the context of a new but busy Pediatric Emergency Department, the risk of missing patients who need more emergent care can be reduced by timely and accurate triaging. In the emergency department of King Fahad Armed Forces Hospital, the Canadian Triage and Acuity Scale had already been implemented, including the pediatric version (PaedCTAS). However, a common observation remained that critical patients did not always receive priority with subsequent delays in management. To improve this accuracy, a training course was administered to health care professionals responsible for triaging of pediatric patients. AIM: To determine the effectiveness of a training course on accuracy of triaging of Pediatric Patients. METHODS: A triage training course was conducted over two months, with patient encounter sheets reviewed before the course for 6 months and after the course for 12 months. Accuracy was calculated by comparing it to level as determined by two pediatric emergency physicians. Also, admission rates were used as a surrogate marker to also determine accuracy. RESULTS: A total of 31 053 patient sheets were reviewed. There was a considerable improvement in the correct determination of all triage levels, with accuracy ranging from 56.5% to 78.3% before the course, and reaching from 79.1% to 90.8% after the course with a statistically significant difference. Triaging errors still present were mainly in the form of down-triage. CONCLUSION: Our training course in triage has a significant impact on the accuracy of triaging of ill pediatric patients. Further improvement can be obtained by repeated courses and direct feedback with debriefing sessions on challenges to triage level determination.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".