Using Physician Behavioral Big Data for High Precision Fraud Prediction and Detection, United States, 2000-2019

This project used big data from non-clinical physician behavior. These include traffic violations, substance abuse, property ownership, stressors (e.g., bankruptcy and divorce), social media data, and other life events data. These variables, all based on public records, were used to construct a predictive model of Medicare fraud using machine learning techniques.