Clinical decision-making: Cognitive biases and heuristics in triage decisions in the emergency department
Thilini Nisansala Egoda Kapuralalage, Ho Fai Chan, Uwe Dulleck, James A. Hughes, Benno Torgler, Stephen Whyte
Abstract
BACKGROUND: In emergency medicine, triage decisions are critical for ensuring patient safety and optimizing resource usage. Such decisions involve a complex interplay of rational and analytical thinking, combined with an intuitive and humanistic approach. However, the influence of cognitive biases on triage decisions remains poorly understood. METHODS: Between February 20 and June 27, 2023, we conducted an online scenario-based survey with 78 triage-competent Registered Nurses in the emergency department at Princess Alexandra Hospital in Australia. Co-designed with nurse educators and nursing academics, the survey included domains covering demographic information, tailored diagnostic tests to capture the presence of cognitive biases and risk-taking behavior, and six vignettes requiring triage using the Australasian Triage Scale. Logistic mixed-effects and multivariate Poisson regression models were performed to identify the influence of cognitive biases and risk-taking behavior on triage decision accuracy. RESULTS: We identified negative framing bias (82.5 %), anchoring bias (82 %), and availability bias (62.8 %) as the most prevalent cognitive biases among triage nurses. After adjusting for age, sex, education, and triage work experience, no statistically significant associations were observed between cognitive biases or risk-taking behavior and triage accuracy. This indicates that cognitive biases may have a limited influence on well-trained nurses. However, age, sex, and triage work experience were found to be significant predictors of inaccurate triaged decisions. CONCLUSION: Our study provides preliminary evidence that cognitive biases and risk-taking behavior are not associated with triage accuracy among well-experienced and trained emergency triage nurses. Further research is required to fully understand the impact of cognitive biases on emergency triage decisions.