Recognizing the need to support shorter lengths of stay, Dr. John Fahrenbach, a data scientist at the University of Chicago Medicine (UCM), developed a machine learning model that used clinical characteristics to identify patients most suitable for discharge after 48 hours. Using this tool, the hospital could ensure the timely release of specific patients by allocating and prioritizing care management resources, including discharge planning, home health services, and clinician or patient administrative assistance. During the development process, Dr. Fahrenbach's team determined that including zip codes as a feature increased the model's predictive accuracy. After introducing zip codes into the model, however, a team member who reviewed the output raised concerns. "We know Chicago's patient population and knew something was off when stratifying the model by race," said Dr. Fahrenbach.