The effect of centrality bias on triage nurses in the emergency department
Bibliographic record
Abstract
Objective To investigate whether centrality bias is one of the contributing factors for patient mistriage in the emergency department. Methods A randomized, controlled, single-blinded trial was conducted in an emergency department triage station between April 1 and November 3, 2021. Experienced triage nurses were divided into control and treatment groups. The control group triaged patients using the Canadian Triage and Acuity Scale 1–5 triage scale, and the treatment group used a four-level triage scale (created by removing level 3 from the original Canadian Triage and Acuity Scale). Neither group was exposed to the other’s ranking and the control group determined the patient’s actual triage ranking. The accuracy of each group’s ranking was determined by triage experts. Triage nurses’ levels of confidence was investigated, as was the correlation between triage ranking accuracy and confidence level. Results After excluding 58 patients with missing data, 146 assessments were analyzed. Statistical analysis was performed to compare three different aspects of triage rankings between the nurses’ groups and the control group. In the first and second analyses, accuracy levels of 49% and 68% ( p = 0.003), 43% and 68% ( p < 0.0001) were found for the control and experimental groups, respectively. The third aspect showed no significant differences. Within the control and experimental groups, the difference in accuracy rate at levels 2 and 5 was the most significant, with 13% and 75% ( p = 0.40), 29% and 67% ( p = 0.009), respectively. Conclusions: Central tendency has the potential to affect the accuracy of ranking among triage nurses in the emergency department. Further research is needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".