%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 27
%N 
%P e58723
%T Are Treatment Services Ready for the Use of Big Data Analytics and AI in Managing Opioid Use Disorder?
%A Amer,Matthew
%A Gittins,Rosalind
%A Millana,Antonio Martinez
%A Scheibein,Florian
%A Ferri,Marica
%A Tofighi,Babak
%A Sullivan,Frank
%A Handley,Margaret
%A Ghosh,Monty
%A Baldacchino,Alexander
%A Tay Wee Teck,Joseph
%+ NHS Tayside, Ninewells Hospital, 1 James Arrott Drive, Dundee, DD1 9SY, United Kingdom, 44 7462884057, matthew.amer2@nhs.scot
%K machine learning
%K ML
%K artificial intelligence
%K AI
%K algorithm
%K predictive model
%K predictive analytics
%K predictive system
%K practical model
%K deep learning
%K early warning
%K early detection
%K big data
%K opioid use
%K opioid
%K opioid use disorder
%K substance use
%K substance use disorder
%D 2025
%7 28.4.2025
%9 Viewpoint
%J J Med Internet Res
%G English
%X In this viewpoint, we explore the use of big data analytics and artificial intelligence (AI) and discuss important challenges to their ethical, effective, and equitable use within opioid use disorder (OUD) treatment settings. Applying our collective experiences as OUD policy and treatment experts, we discuss 8 key challenges that OUD treatment services must contend with to make the most of these rapidly evolving technologies: data and algorithmic transparency, clinical validation, new practitioner-technology interfaces, capturing data relevant to improving patient care, understanding and responding to algorithmic outputs, obtaining informed patient consent, navigating mistrust, and addressing digital exclusion and bias. Through this paper, we hope to critically engage clinicians and policy makers on important ethical considerations, clinical implications, and implementation challenges involved in big data analytics and AI deployment in OUD treatment settings.
%R 10.2196/58723
%U https://www.jmir.org/2025/1/e58723
%U https://doi.org/10.2196/58723