Amer Matthew, Gittins Rosalind, Millana Antonio Martinez, Scheibein Florian, Ferri Marica, Tofighi Babak, Sullivan Frank, Handley Margaret, Ghosh Monty, Baldacchino Alexander, Tay Wee Teck Joseph
NHS Tayside, Ninewells Hospital, Dundee, United Kingdom.
DigitAS Project, Population and Behavioural Science Research Division, School of Medicine, University of St Andrews, St Andrews, United Kingdom.
J Med Internet Res. 2025 Apr 28;27:e58723. doi: 10.2196/58723.
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.
在本文中,我们探讨了大数据分析和人工智能(AI)的应用,并讨论了在阿片类药物使用障碍(OUD)治疗环境中对其进行符合伦理、有效且公平使用所面临的重要挑战。凭借我们作为OUD政策和治疗专家的集体经验,我们讨论了OUD治疗服务为充分利用这些快速发展的技术而必须应对的8个关键挑战:数据和算法透明度、临床验证、新的从业者与技术接口、收集与改善患者护理相关的数据、理解和回应算法输出、获得患者知情同意、应对不信任以及解决数字排斥和偏差问题。通过本文,我们希望促使临床医生和政策制定者认真思考在OUD治疗环境中部署大数据分析和人工智能所涉及的重要伦理考量、临床影响和实施挑战。