Predictability of buprenorphine-naloxone treatment retention: A multi-site analysis combining electronic health records and machine learning.
Fateme Nateghi HaredashtSajjad FouladvandSteven TateMin Min ChanJoannas Jie Lin YeowKira GriffithsIvan LopezJeremiah W BertzAdam S MinerTina Hernandez-BoussardChwen-Yuen Angie ChenHuiqiong DengKeith N HumphreysAnna LembkeL Alexander VanceJonathan H ChenPublished in: Addiction (Abingdon, England) (2024)
US patients with opioid use disorder or opioid dependence treated with buprenorphine-naloxone prescriptions appear to have a high (∼60%) treatment attrition by 6 months. Machine learning models trained on diverse electronic health record datasets appear to be able to predict treatment continuity with accuracy comparable to that of clinical experts.