Work

Detecting Opioid-Related Aberrant Behavior using Natural Language Processing.

Year: 2017

Type: article

Abstract: . 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.

Source: PubMed Central

Authors: Jesse M Lingeman, Priscilla Wang, William Becker, Hong Yu

Institutions: University of Massachusetts Amherst, Yale University, VA Connecticut Healthcare System, University of Massachusetts Chan Medical School

Language: English

Topic: Opioid Use Disorder Treatment

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W2786391630

FWCI: 1.537

Cites: 7

Cited by: 21

Related to: 10