DigitAS Project, Population and Behavioural Science Division, School of Medicine, University of St Andrews, St Andrews.
Forward Leeds and Humankind Charity, Durham, UK.
Curr Opin Psychiatry. 2023 Jul 1;36(4):308-315. doi: 10.1097/YCO.0000000000000870. Epub 2023 Apr 25.
Opioid overdose events are a time sensitive medical emergency, which is often reversible with naloxone administration if detected in time. Many countries are facing rising opioid overdose deaths and have been implementing rapid opioid overdose response Systems (ROORS). We describe how technology is increasingly being used in ROORS design, implementation and delivery.
Technology can contribute in significant ways to ROORS design, implementation, and delivery. Artificial intelligence-based modelling and simulations alongside wastewater-based epidemiology can be used to inform policy decisions around naloxone access laws and effective naloxone distribution strategies. Data linkage and machine learning projects can support service delivery organizations to mobilize and distribute community resources in support of ROORS. Digital phenotyping is an advancement in data linkage and machine learning projects, potentially leading to precision overdose responses. At the coalface, opioid overdose detection devices through fixed location or wearable sensors, improved connectivity, smartphone applications and drone-based emergency naloxone delivery all have a role in improving outcomes from opioid overdose. Data driven technologies also have an important role in empowering community responses to opioid overdose.
This review highlights the importance of technology applied to every aspect of ROORS. Key areas of development include the need to protect marginalized groups from algorithmic bias, a better understanding of individual overdose trajectories and new reversal agents and improved drug delivery methods.
目的综述：阿片类药物过量事件是一个需要及时处理的医疗紧急情况，如果及时发现，通常可以通过纳洛酮给药来逆转。许多国家都面临着阿片类药物过量死亡人数上升的问题，并一直在实施快速阿片类药物过量反应系统（ROORS）。我们描述了技术如何越来越多地被应用于 ROORS 的设计、实施和交付中。
最新发现：技术可以在 ROORS 的设计、实施和交付方面做出重大贡献。基于人工智能的建模和模拟以及污水流行病学可以用于为纳洛酮获取法律和有效纳洛酮分配策略提供决策依据。数据链接和机器学习项目可以支持服务交付组织动员和分配社区资源，以支持 ROORS。数字表型是数据链接和机器学习项目的一个进步，可能会导致精确的过量反应。在最前线，通过固定位置或可穿戴传感器的阿片类药物过量检测设备、改进的连接性、智能手机应用程序和基于无人机的紧急纳洛酮输送都在改善阿片类药物过量的结果方面发挥作用。数据驱动技术也在增强社区对阿片类药物过量的反应方面发挥着重要作用。
总结：本综述强调了将技术应用于 ROORS 各个方面的重要性。发展的重点包括需要保护边缘化群体免受算法偏见的影响、更好地了解个体过量轨迹以及新的逆转剂和改进的药物输送方法。
