How a Clinical Decision Support System Changed the Diagnosis Process: Insights from an Experimental Mixed-Method Study in a Full-Scale Anesthesiology Simulation

Recent advancements in artificial intelligence have sparked discussions on how clinical decision-making can be supported. New clinical decision support systems (CDSSs) have been developed and evaluated through workshops and interviews. However, limited research exists on how CDSSs affect decision-making as it unfolds, particularly in settings such as acute care, where decisions are made collaboratively under time pressure and uncertainty. Using a mixed-method study, we explored the impact of a CDSS on decision-making in anesthetic teams during simulated operating room crises. Fourteen anesthetic teams participated in high-fidelity simulations, half using a CDSS prototype for comparative analysis. Qualitative findings from conversation analysis and quantitative results on decision-making efficiency and workload revealed that the CDSS changed team structure, communication, and diagnostic processes. It homogenized decision-making, empowered nursing staff, and introduced friction between analytical and intuitive thinking. We discuss whether these changes are beneficial or detrimental and offer insights to guide future CDSS design.