Hospital Radiology Implements AI Decision Support

Researchers at Queensland University of Technology conducted a prospective qualitative study in a large Brisbane public tertiary hospital, interviewing 43 radiology staff across baseline, peri-, and postimplementation phases of an AI clinical decision support tool. They found organizational barriers dominated early phases, while technological issues (accuracy, interoperability, information overload) emerged during and after rollout; enablers increased but trust remained constrained by inconsistent performance and medicolegal uncertainty, indicating need for communication, training, and iterative vendor-user feedback.