Predicting Patients at Risk of Becoming Hospital Super-Utilizers
Programs designed to intervene with hospital super-utilizers to reduce costs and improve outcomes commonly rely on predictive models to identify patients at highest risk of excess future hospital utilization, target scarce interventional resources and provide supplemental clinical and social decision support.
Super-utilizers typically have a variety of clinical, social and behavioral complexities that add extreme difficulty in the design of interventions designed to reduce their ED utilization. Successful interventions have focused on pain management, mental illness and substance abuse among patients by investing in integrated care delivery models that provide medical, social and mental health supports.
Hospital Super-Utilizers and Transitions of Care
The disproportionate concentration of health care consumption and expenditures among a small portion of the population is a well-documented facet of the health system in the U.S. The top 1 percent of the population consistently consumes more than one-fifth of health care resources, the top 5 percent account for half of all spending and half of the population accounts for 97 percent of health care utilization and expenditures.
Because of new paradigms in accountable care and population health management, one particular segment of high-cost patients — hospital “super-utilizers”— has been the focus of emerging models of patient-centered care delivery that concentrate on both medical and socioeconomic conditions. The foundational elements of these models include robust data analysis and patient-centered transitions of care from the hospital to patients’ communities.