Artificial intelligence is everywhere today. From the introduction of tools like ChatGPT to usage in cutting-edge medical technology, AI is changing how people work, think, and use tools. That’s also increasingly true in healthcare, where artificial intelligence can provide data processing, voice assistance, recommendations, and task automation.
While many of these applications are new and not yet common in the world, AI is rapidly becoming a part of how medical professionals treat patients. That’s also true in the world of substance abuse treatment, where rehab centers benefit from.
AI algorithms can tap into and follow data streams to detect early signs of substance abuse in recovering patients. That can result in earlier intervention and better relapse prevention. For example, it’s a well-known fact that people withdraw from social life and the people they care about before relapse, often because they’re trying not to feel guilty. An AI algorithm can monitor social media, online behavior, and even psychological data to track signs and symptoms and then to intervene when and where necessary – so that people have the support they need to stay in recovery.
Taken a step further, and substance use monitoring could become part of general self-care automation, which would be part of someone’s personal devices. For example, there’s no reason why AI cannot integrate into the smart watches people already use to track vital signs, sleep patterns, and activity – giving real-time feedback and alerts to people when they are in danger. In the same application, AI could be used to help people in recovery recognize when they are slipping up or at increased risk of relapse, giving them better tools to understand their own habits and patterns, and therefore to stay in recovery.
Predictive analytics means using a large set of data to make predictions based on previous outcomes. If X and Y meant Z happened in the past, it’s likely to mean that again. And, the more you repeat these models, the more data the AI has to make those predictions. By understanding person-specific risk-factors and triggers and knowing what to look for, AI can alert individuals and their treatment providers to get help when it’s needed. That can allow for targeted support in recovery – before relapse actually happens.
That same kind of support could come into play in preventive treatment, but most people would find that kind of support to be too invasive, so is highly unlikely to actually happen. However, especially in treatment centers and clinics, the more data collected, the better able AI is to predict actual outcomes.
An AI algorithm can use all patient data, including past medical history, past treatment history, behavioral analysis, current treatment results, treatment outcomes, genetic information, family history, etc., to develop personalized treatment plans. These would always have to be monitored and managed by a professional, capable of determining when and where the AI suggestion works and doesn’t. However, it would allow therapists and healthcare professionals to offer much more personalized care with less time investment, reducing the total cost of care and therefore increasing the accessibility of personalized treatment plans.
Here, AI would assist healthcare professionals in making data-driven decisions by analyzing data and showing predictions and outcomes. The medical professional could then use that to improve treatment outcomes, improve resource allocation, or to choose the best intervention or treatment option for the individual’s needs. And, with an AI to update and adapt the program as that person moves through treatment, it becomes much simpler and more cost-effective to continue personalizing treatment programs as the programs progress.
Digital therapy will never replace human connection and therapy. However, evidence-based interventions like CBT are increasingly being offered through digital therapy platforms and virtual environments. Paired with an AI, these programs could offer monitoring, ongoing support, and could guide users through therapy courses.
For example, AI assistants and chatbots can offer support, coping mechanisms, and virtual support – or even companionship and a reminder not to drink or use. They can also provide on-demand and cost-free or low-cost support to people who need help and guidance. And, where needed, they can flag instances to request human intervention.
While these programs will always require human monitoring and checks, AI models can provide significant and meaningful digital therapy, on-demand.
Mental healthcare, including substance abuse treatment, will always be, first-and-foremost, human-led. That’s important because a large part of substance abuse treatment is learning to socialize, to connect with people, and to find motivation to move forward and find new coping mechanisms. That requires human intervention and human connection.
In addition, it’s important to note that AI must be integrated into healthcare in a socially and ethically responsible way. Many of the potential uses of AI in substance abuse treatment necessitate having large amounts of private patient data, which means patients must opt in, must understand how their data is being used, and should know what the algorithm is doing and why. Until that transparency is made part of treatment, AI will not have a real place in medical treatment of any kind.
However, artificial intelligence could greatly improve the cost, timeline, and efficacy of determining treatment. It could also ensure that people have easy resources to turn to when they need help or are feeling down. Medical professionals could have a better idea of how their patients are actually doing out in the world, get early warnings when those people start to slip, and can provide timely preventive intervention. All of that could greatly improve the quality of care and of life for patients recovering from substance use disorders.
Still, AI is a relatively new technology and we’re not using it for substance abuse treatment yet. In the near future, we can expect to see it increasingly used to help filter and sort data. It’s also being used in diagnosis programs in other healthcare industries, so chances are high that we’ll see it used in substance use recovery for that purpose as well.
Asana Recovery is located in Orange County, California. and offers detox, residential, and outpatient addiction treatment services in our modern and comfortable addiction treatment facilities. Please contact us today to speak with one of our experienced addiction treatment team if you have any questions about our programs.