May 26 - May 26
Tue - Tue

Work-In-Progress (WIP) Series: Tina Hernandez-Boussard

Predicting Acute to Chronic Conversion in Opioid Naïve Medicaid Patients

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Please note this presentation has been changed to a remote session only.  Zoom Link

The opioid crisis claims an average of 130 American lives each day1. Despite increased awareness to the potential risks associated with opioid use, recent studies indicate that the number of opioid prescriptions remained unchanged for some populations from 2007 to 20162. National agencies have published opioid prescribing guidelines to face this crisis4,5. Other stakeholders have focused on systematic interventions to curb the opioid epidemic6. However, little is known about how nuanced features of opioid prescriptions may affect patient outcomes, especially in vulnerable populations. The goal of this study was to develop predictive models to identify patients at highest risk for opioid misuse. Opioid naïve patients were identified in Medicaid claims data to characterize and predict patients who converted from acute to chronic opioid use.  This preliminary work using Medicaid claims data provides opportunities for health policy makers to address opioid prescribing patterns and improve patient outcomes with targeted outreach.


Tina Hernandez-Boussard
Associate Professor 
Department of Medicine
Biomedical Informatics
Biomedical Data Science
Stanford University