Using Predictive Analytics to Guide Patient Care and Research in a National Health System

Excerpt

Although complex, high-need patients account for the majority of health care spending,¹ the use of predictive analytics for pro-active patient management of high-risk populations has been limited. The Veterans Health Administration (VHA) developed the Care Assessment Needs (CAN) score² to help primary care teams identify high-risk patients. The CAN score reflects clinical and demographic characteristics that predicted future hospitalization and mortality for 4,598,408 VHA primary care patients² with robust areas under the curve (AUCs) for predicting hospitalization (0.84), death (0.86), and hospitalization and/or deaths (0.82). The original CAN score algorithm had 90 input variables; the current version has 36 variables and has similar predictive accuracy. All VHA primary care providers and teams have access to a dashboard of CAN scores for their patient panels calculated weekly. The CAN score is expressed as a percentile of probabilities ranging from 0 percentile (lowest risk) to 99th percentile (highest risk). In this paper, we describe the population identified by the CAN score report and assess primary care team experience using the CAN score. …