Name
#174 A Review of AI and Smart Technology for Opioid Relapse Prevention: Opportunities for Cost Savings and Efficiency
Content Presented On Behalf Of:
USPHS
Services/Agencies represented
US Public Health Service/Health Human Services/Indian Health Service (USPHS/HHS/IHS)
Session Type
Poster
Date
Tuesday, March 3, 2026
Start Time
5:00 PM
End Time
7:00 PM
Location
Prince Georges Expo Hall E
Focus Areas/Topics
Technology
Learning Outcomes
Following this session, the attendee will be able to (1) Understand how smart technologies and AI can assist with reducing Opiod relapse (2) Describe benefits of real-time monitoring and AI in reducing Opiod relapse and associated cost savings (3) Summarize different AI applications/approaches in combating opiod relapse
Session Currently Live
Description

Background: The Department of Health and Human Services (HHS) is a lead proponent in the war against drugs. Multiple HHS agencies such as the Substance Abuse and Mental Health Services (SAMHSA), Health Resources and Services Administration (HRSA), and the National Institutes of Health (NIH) have spent billions of dollars on programs to help address the opioid crisis through various efforts focusing on research, education and treatment. However, the return on investment, specifically the effectiveness of these government led initiatives are often debatable as the rates of drug addiction and overdose deaths in the United States have increased steadily from 1999-2022. One potential cause is the high need for the patient to navigate the complexities of seeking out support and treatment, adhering to schedules while managing various stressors (i.e. social, economic, health) and actively recovering or seeking employment. While significant effort has been made to increase accessibility and navigation of services, however focused efforts are needed to encourage and support patients, especially in moments of active crisis, or near crisis. Intervention: With the increased availability of Artificial Intelligence (AI) tools and Smart Technology, real-time mood and behavior monitoring are possible, including positive encouragement and support while monitoring patients between clinical visits and behavioral health interventions. This work reviews existing smart devices and their applications in addressing opioid addition and relapse in opioid use disorder (OUD) and the outcomes. The emphasis of this work is on reviewing practical solutions that are being piloted or implemented in real OUD patients and their outcomes. The objective of this work is to inform on opportunities for focusing resources into practical applications that have meaningful outcomes, given the financial and resources constraints experienced by federal agencies, and the poor overall return on investment with prior funded passive programs. Results: When implemented properly, AI and Smart Technology have significant potential to complement larger existing initiatives in combating OUD, with scalability at the national level in an efficient and scalable manner. A key benefit of this approach is the use of technology for active monitoring and real-time intervention, a unique approach that helps to increase the efficacy of existing interventions and can be applied toward other mental health treatment domains.