Applying machine learning and natural language processing to patient safety event reports: Identifying patterns of cardiovascular diagnostic errors.

Patient safety report analysis can provide important avenues for error identification and improvement opportunities. This study explores using natural language processing (NLP) and machine learning (ML) to identify cardiovascular diagnostic errors from patient safety event reports. Findings demonstrate feasibility, bridging data science methods with patient safety needs. This approach can enhance surveillance of diagnostic errors, supporting quality improvement efforts in cardiovascular care.