Abstract

Diabetes screening in urban Emergency Departments (EDs) can identify previously undiagnosed diabetes cases and link newly diagnosed patients to outpatient care. NYU Langone has recently implemented a system-wide initiative to screen ED patients for diabetes. However, only 23% of ED patients with newly diagnosed diabetes have been to a follow-up outpatient visit at NYU Langone. Thus, we wish to develop a machine learning-based predictive model, predicting the likelihood that an ED patient will follow up with outpatient care after a new diagnosis of diabetes. These models will inform targeted interventions to help bridge these critical gaps within the healthcare system. Skills in Python and Machine Learning are needed for this project.