Triage in Emergency Departments is a complex, high-stakes process that relies heavily on rapid decision-making under conditions of uncertainty, time pressure, and information gaps. This paper explores how digital technologies, particularly data-driven Clinical Decision Support Systems (CDSS), can augment triage decision-making to improve patient safety, operational efficiency, and clinical outcomes. Using Cognitive Task Analysis (CTA), the study examines the cognitive demands faced by triage nurses, the strategies they employ, potential sources of error, and design recommendations for future CDSS. Findings are organised into a cognitive demands table, identifying key areas where digital support can enhance clinical practice, such as automated priority suggestions, predictive resource allocation, real-time translation tools, and pattern recognition systems. The paper envisions a future where intelligent, adaptive CDSS integrated with real-time patient data, wearable technologies, and predictive analytics transform triage from a reactive to a proactive system. This paper also highlights critical considerations, including the risk of deskilling, biases, and trust in data-driven recommendations. Ultimately, the future of triage resides in systems developed from the ground up with direct input from triage nurses, thereby ensuring that technological innovations genuinely align with clinical realities. These systems should aspire to augment, rather than supplant, human expertise, thereby fostering a patient-centred, anticipatory, and resilient emergency care environment.
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Steve Agius (Wed,) studied this question.
Steve Agius
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