Understanding Clinicians’ Informational Needs for AI-Driven Clinical Decision Support Systems: Qualitative Interview Study

To improve AI-CDSS adoption in clinical practice, reporting standards must be designed for better clinician comprehension and usability. Enhancing transparency, particularly regarding training data and performance, can likely help clinicians assess AI-CDSS more effectively. Information should be delivered in an accessible, layered format, fitting clinical workflows. Co-creation with clinicians throughout AI-CDSS development was a cross-cutting theme, highlighting its importance in ensuring tools are not only technically sound but also practically usable. Future research should explore how to structurally report on performance and validation metrics for clinician understanding and assess the impact of information provision on AI-CDSS adoption.