NIH-funded research R01 grant

AI-augmented care to guide hospital treatment for opioid and alcohol use disorders

Official title: Artificial Intelligence Augmentation to Guide Clinicians in Hospital-Based Treatment of Substance Use Disorders

Funded at University of Wisconsin-Madison · NIH-11455604 · Data updated 2026-11-12

A hospital-based AI tool helps clinicians decide and guide treatment for patients with opioid or alcohol use disorders in ED and inpatient settings.

More Substance Use research and trials

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionUniversity of Wisconsin-Madison
NIH-funded
Lab location1 site (Madison, United States)
Project startSeptember 30, 2020
Project endJune 30, 2030
Funding year2026
Award (this year)$710,159
NIH project number2R01DA051464-06A1
Project IDNIH-11455604 on NIH RePORTER

Who could benefit from this research

Could help

Adults with opioid use disorder or alcohol use disorder presenting to or admitted through the hospital who receive care in ED or inpatient units and whose clinicians use the AI-augmented decision support.

Less likely to help

Patients without these conditions or those not receiving hospital-based care may not benefit from this AI tool.

What this research studies

This project aims to use an artificial intelligence system integrated with electronic health records to support addiction treatment decisions in hospital settings. Building on prior work, the team seeks to improve when and how medications for opioid use disorder and alcohol use disorder are started, optimized, and communicated to patients. The approach focuses on real-time clinical decision support to reduce readmissions and improve cost-effectiveness while addressing barriers like stigma and inconsistent protocols. The study targets patients presenting to the emergency department or admitted for substance-related issues, with clinicians able to rely on AI-guided recommendations to inform care plans. The goal is to enhance the quality and consistency of evidence-based treatment for OUD and AUD at the point of care.

Why it matters

Potential benefit: If successful, this AI tool could lead to more patients receiving guideline-based treatments for OUD and AUD during hospital stays and after discharge.

How similar studies have gone: Earlier work showed that an EHR-integrated AI screener could identify at-risk patients and reduce readmissions, suggesting potential for improved outcomes with enhanced CDS.

Where this research is happening

  • University of Wisconsin-Madison
    Madison, United States
    Active

Researchers

  • Principal investigator: Afshar, Majid — University of Wisconsin-Madison
  • Study coordinator: Afshar, Majid

Related research

Other NIH-funded projects on the same topics.

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.