Method and apparatus for prediction of complications after surgery

Abstract

Methods and systems disclosed herein utilize an automated analytics framework to implement a perioperative complication risk algorithm that uses existing clinical data in electronic health records to forecast patient-level probabilistic risk scores for eight major postoperative complications. An example method includes accessing health record data for a patient, normalizing the accessed health record data to generate a health record data set for the patient, transforming one or more features from the health record data set, selecting one or more transformed features from the health record data set, calculating risk probabilities for one or more complication risk categories based on the health record data set and the selected one or more features, calculating mortality risk probabilities for one or more mortality risk categories based on the calculated risk probabilities, and generating a personalized risk panel based on the calculated risk probabilities and the calculated mortality risk probabilities.