Improving healthcare professionals usage of artificial intelligence-powered risk recommenders through enhancement of trust and acceptance: a rapid realist review protocol

28 May 20264 min read0 viewsJournal Feed

GIST (Key Takeaways)

Introduction Healthcare professionals working in busy hospital environments are expected to make multiple back-to-back critical decisions related to patient assessment and treatment. Fatigue from a combination of complex decision-making over multiple patients can lead to less efficient care and an increased risk of error and harm.
Artificial intelligence (AI) risk recommendation systems, hereafter referred to as AI risk recommenders, have the potential to reduce the impact of decision fatigue by prompting healthcare professionals with appropriate recommendations for patient care and management. A key barrier to the effective usage of such systems is the establishment of trust and subsequent acceptance among healthcare professionals.
However, little is currently known about how trust and acceptance can be engendered. The aim of this review is to develop a theory explaining what influences healthcare professionals' usage of AI risk recommenders and how trust and acceptance, facilitate their usage of such systems.

Clinical Editorial

Summary

BMJ Open published a clinical update in Research Highlights on 28 May 2026.

The item focuses on Improving healthcare professionals usage of artificial intelligence-powered risk recommenders through enhancement of trust and acceptance: a rapid realist review protocol.

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