A new study shows that using artificial intelligence (AI) to screen hospital patients for opioid addiction can help doctors identify those in need of addiction care and reduce the chances of patients returning to the hospital after discharge. The findings, published in Nature Medicine, suggest that this technology could save lives and lower health care costs at the same time.
Opioid use disorder is a serious condition that often goes unnoticed in busy hospital settings. Many hospitals struggle to consistently screen for addiction, and patients may leave without receiving proper care. This is a major issue, as people with untreated opioid addiction are much more likely to experience an overdose after leaving the hospital.
To address this problem, researchers at the University of Wisconsin School of Medicine and Public Health developed and tested an AI screening tool. The tool was designed to analyze patient records and flag signs of opioid addiction. When the AI detected possible opioid use disorder, it alerted doctors and recommended referring the patient to an addiction specialist.
The study compared the AI-based approach to the traditional method where doctors decide on their own whether to consult addiction specialists. The clinical trial took place at University Hospital in Madison, Wisconsin, over several years.
Between March 2021 and October 2022, doctors used their own judgment to request consultations. From March to October 2023, the AI system was used hospital-wide to support the care process.
The trial included 51,760 adult hospital stays. About two-thirds of those occurred before the AI tool was used. During the whole study, there were 727 addiction medicine consultations.
The AI tool worked by scanning patient records—including doctors’ notes and medical histories—in real time. It used this information to spot patterns linked to opioid use disorder. If the tool saw warning signs, it sent an alert when a doctor opened the patient’s chart, suggesting that the patient might benefit from addiction care and withdrawal monitoring.
The results were promising. The AI-based screening was just as effective as the doctor-only approach at getting patients referred to addiction specialists. In fact, slightly more patients (1.51%) were referred with the help of the AI, compared to 1.35% without it.
What made the AI tool especially useful was its impact on hospital readmissions. Only 8% of patients in the AI group returned to the hospital within 30 days of discharge, compared to 14% in the doctor-only group.
This 47% drop in readmissions meant fewer people needed repeat hospital care. It also translated into big savings—about $109,000 in health care costs during the eight-month period when the AI tool was used, even after accounting for the cost of running the software.
The average cost of a single readmission is around $16,300. By avoiding 16 readmissions, the hospital system saved thousands of dollars and likely improved patient outcomes.
Dr. Majid Afshar, the study’s lead author, said this research shows that AI can work in real hospital settings, not just in theory. “Our study represents one of the first real-world examples of an AI screening tool actually being used in addiction care,” he explained.
Experts like Dr. Nora Volkow, director of the National Institute on Drug Abuse, praised the results. She pointed out that addiction care often gets overlooked, especially in overwhelmed hospitals. AI can help fill that gap by providing timely alerts and recommendations.
Still, the researchers acknowledge some challenges. Hospital staff might experience “alert fatigue” from too many notifications, and the system still needs to be tested in more hospitals to ensure it works everywhere. Also, changes in the opioid crisis over time could affect how well the tool works, so ongoing updates and testing are needed.
The opioid crisis remains a major issue in the U.S. Between 2022 and 2023, emergency visits for substance use rose nearly 6%, reaching 7.6 million. Opioids were the second leading cause of these visits after alcohol. But even with this growing need, hospitals often fail to screen and treat opioid use disorder consistently.
This study shows that AI could play an important role in solving that problem. It can help hospitals identify patients who need addiction care, reduce readmissions, and lower costs—all while maintaining quality of care.
With further improvements and broader testing, AI screening tools may become a regular part of hospital systems trying to respond to the ongoing opioid crisis.
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The research findings can be found in Nature Medicine.
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