Detecting Stimulant and Opioid Misuse and Illicit Use
Description
To detect and analyze non-therapeutic (illicit or misuse) stimulant and opioid use from free-text clinical notes in EHRs, which is not possible using standard medical codes.
Detailed example
Two machine learning models (one for internal use, one for public release) that, together with rule-based text analysis, determine whether a patient has used a drug therapeutically or non-therapeutically, providing new insights for health statistics.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
The AI models enable the extraction of novel insights from EHRs regarding non-therapeutic drug use, improving the statistical analysis of health data for the National Hospital Care Survey (NHCS). This supports more accurate public health statistics and may influence analysis of other datasets with EHR clinical notes.
Controls / human review
ATO: No; PIA: Not published
Data needed
National Hospital Care Survey 2020 clinical notes