This chapter describes important goals related to using data-driven approaches and addresses the high utilizer problem. It discusses challenges related to using data-driven methods to identify and predict high utilizers in health care. The Agency for Healthcare Research and Quality reported that in 2012, the top 10% of the health care-utilizing population accounted for 66% of overall health care expenditures in the United States. Health care is one of the largest components of the global economy. According to the World Bank, in 2014, health care expenditures accounted for 9.95% of the world’s total gross domestic product. Health care utilization routinely generates vast amounts of data from sources, ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Specifically, if researchers can forecast expenditures at the patient-level with acceptable accuracy, they can improve targeted care by anticipating health care needs of high-cost, high-need patients. The chapter also presents an overview of the key concepts discussed in this book.