Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a larg...

This brief uses California’s CURES (Controlled Substance Utilization Review and Evaluation System) 2.0 data to analyze county-level opioid prescribing rates in California from 2012 to 2017 from multiple perspectives. The book summarizes California’s county-level opioid prescribing trends, examines potential correlates of opioid prescribing rates, and assesses the association of opioid prescribing on both criminal justice and public health outcomes. Finally, the authors discuss their princi...