Performance of an Algorithm Grading Surgery-Related Adverse Events According to the Clavien-Dindo Classification.

Objective: To assess performance of an algorithm for automated grading of surgery-related adverse events (AEs) according to Clavien-Dindo (C-D) classification.

Summary Background Data: Surgery-related AEs are common, lead to increased morbidity for patients, and raise healthcare costs. Resource-intensive manual chart review is still standard and to our knowledge algorithms using electronic health record (EHR) data to grade AEs according to C-D classification have not been explored.