Detecting Opioid-Related Aberrant Behavior using Natural Language Processing.

Journal: AMIA ... Annual Symposium proceedings. AMIA Symposium
Published Date:

Abstract

The United States is in the midst of a prescription opioid epidemic, with the number of yearly opioid-related overdose deaths increasing almost fourfold since 2000. To more effectively prevent unintentional opioid overdoses, the medical profession requires robust surveillance tools that can effectively identify at-risk patients. Drug-related aberrant behaviors observed in the clinical context may be important indicators of patients at risk for or actively abusing opioids. In this paper, we describe a natural language processing (NLP) method for automatic surveillance of aberrant behavior in medical notes relying only on the text of the notes. This allows for a robust and generalizable system that can be used for high volume analysis of electronic medical records for potential predictors of opioid abuse.

Authors

  • Jesse M Lingeman
    University of Massachusetts: Amherst, Amherst, MA.
  • Priscilla Wang
    Yale Medical School, New Haven, CT.
  • William Becker
    Yale Medical School, New Haven, CT.
  • Hong Yu
    University of Massachusetts Medical School, Worcester, MA.