# Automated Substance Use Detection from Electronic Health Records in the Pediatric Setting

> **NIH NIH R03** · CINCINNATI CHILDRENS HOSP MED CTR · 2022 · $79,500

## Abstract

Project Summary
The majority of adults with substance use disorders (SUD) report beginning to use substances as adolescents;
thus, adolescence represents a critical time for screening of substance use initiation and implementing
interventions to prevent or reduce use. The healthcare system prioritizes substance use screening, including
during adolescence, with the goal of identifying when substance use is occurring and monitoring use to
determine necessary intervention. Unfortunately, the majority of this information is documented in unstructured
clinical notes, making it difficult for providers to monitor change in substance use for an adolescent over
encounters. Published studies also suggest bias around substance use screening such as laboratory tests
exists. Both limitations prevent electronic health record (EHR) data from being used to study the contexts and
consequences of substance use in populations of adolescents. Rather than changing clinician behavior, which
can be challenging, this study utilizes automated artificial intelligence algorithms to detect substance use
screening occurrences and results in the EHRs. Our work could allow current provider-led preferences and
practices in substance use documentation to continue while simultaneously increasing access to documented
information and mitigating screening bias to avoid perpetuating racism and inequity in healthcare. As a result,
the study has the potential to aid in long-term efforts to target prevention, intervention, and referral for
treatment in adolescence and ultimately reduce risk of SUD across the lifespan. Our work will be completed
through accomplishing the following aims: Aim 1: Examine the generalizability of an automated substance use
detection system in a sample of ~5,000 adolescent patients who receive well child and/or outpatient specialty
visits, maximizing contexts where substance use screening is most likely to occur; and Aim 2: Assess
differences in substance use screening and positive screening results by gender, insurance type, minoritized
race and ethnicity status, and clinical context, evaluating whether bias is detected in structured data,
unstructured data, or both data sources. In addition, participatory research principles will be used to solicit
feedback from clinicians and researchers about the application of findings to clinical care. By the end of the
funding period, we will have validated the performance of the automated system, assessed bias in identifying
substance use screening results, and gained insights from clinician feedback about application to clinical care.

## Key facts

- **NIH application ID:** 10447967
- **Project number:** 1R03DA054256-01A1
- **Recipient organization:** CINCINNATI CHILDRENS HOSP MED CTR
- **Principal Investigator:** Sarah Beal
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $79,500
- **Award type:** 1
- **Project period:** 2022-04-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10447967

## Citation

> US National Institutes of Health, RePORTER application 10447967, Automated Substance Use Detection from Electronic Health Records in the Pediatric Setting (1R03DA054256-01A1). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10447967. Licensed CC0.

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