This systematic review explored how artificial intelligence (AI) based on machine learning algorithms and natural language processing is used to address and report patient safety outcomes. The review suggests that AI-enabled decision support systems can improve error detection, patient stratification, and drug management, but that additional evidence is needed to understand how well AI can predict safety outcomes.  

This study evaluated cross-sectional survey data from pharmacists and patients to characterize organizational factors associated with variation in safety climate, patient satisfaction and self-reported medication adherence in community pharmacies in the United Kingdom. Safety climate was associated with pharmacy ownership, organizational culture, working hours, and employment of accuracy checkers. Skill mix and continuity of care also influenced safety culture and quality.