Predicting diabetes and ENT emergency department admissions using hospital records

Background: Healthcare costs, especially those associated with emergency department (ED) visits, are increasing at an unsustainable rate. Often, ED visits for certain conditions can be prevented through patients utilizing their primary care physician. We consider two of these conditions: diabetes for adults (n=342,286 patient quarters), and ear, nose, and throat (ENT) conditions for children (n=2,660,733 patient quarters). Being able to identify patients at risk of an avoidable admission to the ED could lead to dramatically reduced costs for both patients and healthcare systems. We develop models to predict avoidable admissions (defined as visits to the ED for either of these ambulatory care sensitive conditions) and reduce healthcare costs.