HHS · no agency ID · record R0640

Detecting Stimulant and Opioid Misuse and Illicit Use

Department of Health and Human Services · HHS/CDC

Overview

Development stage: PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2024-03 (month precision)Source: Mar-24
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Health and Medical
Operational functions: Clinical and medical Derived by keyword rules; see methodology

Problem the AI is intended to solve

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.

Expected benefits

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.

System outputs

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.

Technology

AI classification: Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
System name(s): Not reported
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: No
Demographic features: k) None of the above
Training and evaluation data: National Hospital Care Survey 2020 clinical notes
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported