Overdose Risk Prediction Algorithms: The Need For A Comprehensive Legal Framework

Risk prediction has permeated many aspects of modern life, including health care. Algorithms developed using advanced statistical methods have been used to identify hospitalized adults at risk of clinical deterioration, reduce hospital readmission rates, and improve resource allocation and health care use. These methods have also been used to develop predictive models for overdose risk among specific patient populations. Most of these overdose-specific applications, however, have been limited to health care settings using health care utilization or insurance claims data. State and local governments are increasingly integrating health- and non-health-sector data for public health purposes, creating an opportunity to use these data to improve overdose risk prediction models.