Alshehri Dalal, Noman Nasimul, Chiong Raymond, Miah Shah J, Sverdlov Aaron L, Ngo Doan Tm
School of Information and Physical Sciences, The University of Newcastle, Callaghan, NSW, 2308, Australia; Department of Information Technology, King Abdulaziz University, Rabigh, 21911, Saudi Arabia.
School of Information and Physical Sciences, The University of Newcastle, Callaghan, NSW, 2308, Australia.
Comput Biol Med. 2025 Jun;192(Pt B):110142. doi: 10.1016/j.compbiomed.2025.110142. Epub 2025 May 14.
The Internet of Medical Things (IoMT) is a network of interconnected medical devices and applications aiming to facilitate real-time data sharing and personalised patient care. IoMT devices collect vast amounts of data, which are then analysed using advanced computational methods. Real-time patient monitoring is crucial, particularly for people with chronic diseases and older adults. Moreover, traditional in-person monitoring by healthcare providers can be resource-intensive and time-consuming. By leveraging IoMT technology for remote patient monitoring (RPM), healthcare providers can improve service quality, reduce costs and enhance patient care. To evaluate the current state of knowledge and address research gaps in IoMT adoption for RPM, we conducted a thorough systematic literature review (SLR). This SLR aims to provide a comprehensive overview of existing research, identify knowledge gaps, and analyse the factors that influence IoMT adoption. It follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) protocol. PRISMA guidelines allow us to systematically evaluate and synthesise the current state of relevant literature. After analysing the theoretical models used in previous studies on IoMT adoption for RPM, UTAUT2 was identified as the most effective framework for technology adoption in this area. Additionally, this SLR has identified the key factors influencing the adoption of IoMT technology, including privacy, trust, security, and perceived risk, and suggested their inclusion in future studies by analysing and integrating the findings of other studies. As much of the current research focuses solely on patient viewpoints, our SLR points to the necessity of giving equal weight to the opinions of both patients and healthcare professionals. To create IoMT systems that are more effective and inclusive, these deficiencies must be filled. This study will benefit researchers, healthcare professionals, policymakers and technology developers by offering insights to inform decision-making, guide future research and aid the development of effective IoMT solutions for RPM.
医疗物联网（IoMT）是一个由相互连接的医疗设备和应用程序组成的网络，旨在促进实时数据共享和个性化患者护理。IoMT设备收集大量数据，然后使用先进的计算方法进行分析。实时患者监测至关重要，特别是对于慢性病患者和老年人。此外，医疗保健提供者进行的传统面对面监测可能资源密集且耗时。通过利用IoMT技术进行远程患者监测（RPM），医疗保健提供者可以提高服务质量、降低成本并加强患者护理。为了评估IoMT用于RPM的知识现状并解决研究差距，我们进行了全面的系统文献综述（SLR）。本SLR旨在全面概述现有研究、识别知识差距并分析影响IoMT采用的因素。它遵循系统评价和荟萃分析的首选报告项目（PRISMA）协议。PRISMA指南使我们能够系统地评估和综合相关文献的现状。在分析了先前关于IoMT用于RPM的研究中使用的理论模型后，UTAUT2被确定为该领域技术采用的最有效框架。此外，本SLR确定了影响IoMT技术采用的关键因素，包括隐私、信任、安全和感知风险，并通过分析和整合其他研究的结果建议将其纳入未来研究。由于目前的许多研究仅关注患者观点，我们的SLR指出有必要同等重视患者和医疗保健专业人员的意见。为了创建更有效和更具包容性的IoMT系统，必须填补这些不足。本研究将通过提供见解以指导决策、指导未来研究并帮助开发有效的RPM的IoMT解决方案，使研究人员、医疗保健专业人员、政策制定者和技术开发者受益。
