Agreement Among Pediatric Health Care Professionals With the Pediatric Canadian Triage and Acuity Scale Guidelines
Bibliographic record
Abstract
OBJECTIVES: To compare triage level assignment, using case scenarios, in a pediatric emergency department between registered nurses (RNs) and pediatric emergency physicians (PEPs) based on the Pediatric Canadian Triage and Acuity Scale (P-CTAS) guidelines. To compare triage level assignment of the RNs and PEPs to that done by a panel of experts using the same P-CTAS guidelines. METHODS: A cross-sectional questionnaire survey (55 case scenarios) was sent to all RNs and PEPs working in the emergency department after the P-CTAS was implemented. Participants were instructed to assign a triage level for each case. A priori, all cases were assigned a triage level by a panel of experts using the P-CTAS guidelines. Kappa statistics and the mean number (+/-1SD) of correct responses were calculated. RESULTS: A response rate of 85% was achieved (29 RNs, 15 PEPs). The kappa level of agreement (95% CI) among RNs was 0.51 (0.50-0.52) and was 0.39 (0.38-0.41) among PEPs (P < 0.001). The mean number of correct responses (+/-1SD) for RNs was 64% +/- 27% and for PEPs 60% +/- 22% (P = 0.31). Levels of agreement did not vary according to experience or type of shift work done or work status of RNs and PEPs. CONCLUSIONS: With the introduction of the P-CTAS, the level of agreement and accuracy of triage categorization remained moderate for both RNs and PEPs. The reliability of the P-CTAS needs to be further assessed and the requirements for revisions considered prior to its widespread use.
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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 | 0.019 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".