Relapse rates after detox and rehabilitation remain a significant challenge in the treatment of substance use disorder (SUD). Studies show that between 40% and 60% of people with substance use disorder relapse after undergoing detox and rehabilitation. As these statistics persist, providers are increasingly turning to AI in addiction treatment as a tool to improve recovery outcomes and reduce the likelihood of relapse.
The Growing Role of AI in Addiction Treatment
Artificial intelligence has already made its mark in behavioral health treatment, and now, it’s becoming an essential component in the field of substance use disorder care. The integration of AI in addiction treatment is aimed at enhancing the relationship between patients and care teams, bridging the gap that exists between treatment and relapse prevention.
“We’ve had an issue of lack of insight into what’s going on between treatment and relapse for so long. We’ve thrown a lot of human capital and human hours at it, and haven’t moved the needle as much as we should,” said Brett Talbot, chief clinical officer and co-founder of Videra Health. “If we want to continue to address this problem, we have to leverage technology and automation to scale that interaction.”
Videra Health, based in Orem, Utah, operates an AI-powered video assessment platform designed to triage patients during intake or between treatment visits. This technology has been pivotal in creating a more personalized recovery experience for those struggling with SUD.
Discovery365: A Game-Changer in SUD Treatment
In collaboration with Discovery Behavioral Health, Videra has launched Discovery365, a new AI-driven platform focused on preventing relapse in the critical first year after treatment, when more than 85% of patients relapse. This platform, already in use by more than 2,500 patients across 140 Discovery locations, aims to address relapse before it occurs.
Patients discharged from a Discovery care center receive a text, email, or push notification two days after discharge, prompting them to answer a few questions and record a video response to an open-ended question. This approach allows patients to provide a more personal and open account of their current mental and emotional state.
The AI in addiction treatment then analyzes the videos, studying patterns in speech, language, and movement. This data helps providers identify subtle signs of relapse risk that might otherwise go unnoticed. According to Matthew Ruble, chief medical officer at Discovery Behavioral Health, the AI can recognize behavior patterns that correlate with past relapses, allowing healthcare providers to take proactive steps in addressing potential risks.
How AI Can Improve Communication and Support
AI technology doesn’t replace human care; instead, it enhances the connection between patients and their support teams. Human providers can use the insights gathered by AI to reach out to patients asynchronously, providing necessary support and resources before relapse occurs. This reduces the need for constant in-person check-ins, which can be challenging for both patients and providers.
Shrenik Jain, CEO of Marigold, a peer-support app for people in recovery, also emphasizes how AI in addiction treatment supports connection and community. Through the use of natural language processing (NLP), Marigold’s platform monitors user conversations to identify signs of issues such as depression or housing insecurity—potential relapse triggers. When AI detects concerning phrases or topics, staff are alerted and can intervene to prevent a crisis.
“The core concept is that peer support is how people get better and how people have always gotten better,” Jain explains. “Everybody gets better by building supportive relationships, being able to talk about their problems, and building healthy habits.”
AI Reduces Workload and Enhances Efficiency
One of the key benefits of using AI in addiction treatment is its ability to reduce the workload of human providers. Behavioral health professionals are often stretched thin due to high patient loads and limited resources. By automating certain tasks, AI technology allows providers to focus more on direct patient care and therapeutic interventions.
The use of AI in platforms like Marigold and Discovery365 exemplifies how technology can serve as a force multiplier. Instead of requiring large teams of staff to manually monitor and engage with patients, AI steps in to handle repetitive tasks, increasing the efficiency of care without compromising the quality of service.
The Challenges and Risks of AI in Addiction Treatment
Despite its potential, the use of AI in addiction treatment does not come without its challenges. Privacy, security, and bias remain critical concerns. Patients must trust that their personal data is handled securely and that AI algorithms don’t make biased decisions based on inaccurate or incomplete data.
However, both Marigold and Discovery365 have taken steps to ensure that their platforms are HIPAA-compliant and secure. AI developers, such as Talbot at Videra, have also emphasized the importance of eliminating biases from their systems. “We don’t release anything on the platform for analytics that has not been tested for bias,” Talbot assured, highlighting the company’s commitment to fairness and accuracy.
The Human Element in AI-Driven Addiction Treatment
While AI in addiction treatment offers substantial promise, industry experts agree that it should never replace the human element in care. Behavioral health is inherently personal, and AI should be used to complement the work of clinicians, not to replace them.
As Srinivasan Rajan, data governance manager at GAVS Technologies, cautioned, “Don’t jump into it just by the buzzwords without understanding the role of the human therapist and other people in this field.” AI can support decision-making and streamline tasks, but the compassionate care provided by therapists, counselors, and peer support groups is irreplaceable.
Matthew Ruble from Discovery Behavioral Health shared a similar perspective: “It’s always an equation of risks and benefits. We’re in the middle of a suicide epidemic, the opioid crisis, and fentanyl overdoses. AI gives us the ability to intervene earlier and prevent further harm.”
Conclusion: The Future of AI in Addiction Treatment
As AI technology continues to evolve, its role in addiction treatment is likely to expand. From AI relapse prevention to enhancing peer support networks, AI is changing the way care is delivered in the field of substance use disorder. By helping providers gain deeper insights into patient behaviors and enabling proactive interventions, AI may become an indispensable tool in the fight against relapse. However, it’s essential that this technology is used responsibly, with human providers leading the way in making clinical decisions and ensuring that each patient’s unique needs are met.
Ultimately, the integration of AI in addiction treatment is a powerful tool in the ongoing effort to reduce relapse rates and improve recovery outcomes. With careful consideration and continued advancements, AI could become a cornerstone of the next generation of addiction treatment, providing more personalized, proactive, and effective care for individuals in recovery.
