Factors affecting attitude and intention to adopt artificial intelligence for sustainable triage: An exploratory study of emergency department staff

Abstract

Emergency departments (EDs) are facing increasing overcrowding, which can be mitigated by implementing AI-based self-check-in systems that save registration time and alleviate nursing workload. To that end, triage staff must adapt to the changes and adopt an augmented approach. This exploratory study investigates the key factors influencing triage nurses' attitudes and intentions towards adopting this new paradigm. Utilizing SmartPLS, a structural equation modeling technique based on partial least squares, we examined several factors that impact staff's attitude and intention. Our results indicate that task-technology fit has a significant positive impact on staff's attitude, followed by facilitating conditions and perceived explainability. Notably, perceived substitution crisis negatively influences behavioral intention and moderates the relationship between attitude and behavioral intention. This study makes a valuable contribution to existing literature by providing insights into the factors influencing ED staff's attitudes and intentions towards augmented triage intelligence. The findings have significant implications for healthcare policymakers and practitioners seeking to improve triage practices and ensure sustainability in EDs.