1. Detecting Opioid-Related Aberrant Behavior using Natural Language Processing.
- Author
-
Lingeman JM, Wang P, Becker W, and Yu H
- Subjects
- Analgesics, Opioid, Datasets as Topic, False Positive Reactions, Humans, Population Surveillance methods, Electronic Health Records, Natural Language Processing, Opioid-Related Disorders diagnosis, Support Vector Machine
- 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
1 . 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.- Published
- 2018