Inter-rater reliability of a computerized presenting-complaint–linked triage system in an urban emergency department
Bibliographic record
Abstract
BACKGROUND: Triage reliability studies typically use hypothetical scenarios and weighted kappa scores where agreement within one level is considered satisfactory. But if triage category is used to help define ED case-mix groups for comparative or benchmarking processes, agreement on exact triage level and major system involved is important. Our hypothesis was that a computerized menu that links presenting complaints to preferred triage levels (PC-linked triage) would provide high triage reliability. OBJECTIVES: Our objective was to assess inter-rater reliability of PC-linked triage using the Canadian Emergency Department Triage and Acuity Scale (CTAS) in a real-time clinical setting, considering agreement on exact triage level and primary body system involved. METHODS: On duty triage nurses entered patient presenting complaint and PC-linked triage level as per standard procedure. In a convenience sample of patients, a second nurse, blinded to triage assignment, observed the triage interaction and independently entered presenting complaint and triage level on a dummy terminal. RESULTS: During the study, 15 nurse pairs triaged 266 patients. Study patients matched actual emergency department case mix closely. Triage nurses agreed exactly in 74% of cases and within one level in 94% of cases. The unweighted kappa value was 0.66 (95% confidence interval [CI], 0.60-0.73) and the quadratic weighted kappa value was 0.75 (95% CI, 0.68-0.81). Kappa for agreement on major system involved was 0.80 (95% CI, 0.69-0.91). CONCLUSION: PC-linked triage has high inter-rater reliability in a real-time clinical setting. PC-linked triage may be useful as one factor in defining case-mix groups for benchmarking and comparative purposes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".