Artificial intelligence in emergency department triage: perspective of human professionals

Abstract

Background: The triage process in emergency departments (EDs) is complex, and AI-based solutions have begun to target it. At this pivotal stage, the challenge lies less in designing smarter algorithms than in fostering trust and alignment among medical and technical stakeholders. We explored professional attitudes towards AI in ED triage, focusing on alignments and misalignments across backgrounds. Methods: ) was conducted based on GAAIS-positive, GAAIS-negative, and AIAS-4 scores. Results: ± SD scores: (a) for data availability/quality, 2.95 ± 1.98 (K0), 4.27 ± 1.1 (K1), and 4.20 ± 0.94 (K2); (b) for the integration of AI-based applications into existing workflows, 2.95 ± 1.05, 4.20 ± 0.94, and 3.47 ± 1.02 in K0, K1, and K2, respectively. Among the UTAUT2 constructs, hedonic motivation differed most significantly, with mean ± SD values of 3.41 ± 1.0 (K0), 6.86 ± 0.97 (K1), and 5.07 ± 1.08 (K2). Conclusions: Stakeholders' perspectives on AI in ED triage are heterogeneous and not solely determined by professional background or role. Hedonic motivation emerged as a key driver of enthusiasm. Educational strategies should follow two directions: (a) structured AI programs for enthusiastic developers from diverse fields, and (b) AI literacy for all healthcare professionals to support competent use as consumers.

Ähnliche Arbeiten