Factors influencing the adoption of Internet of Medical Things for remote patient monitoring: A systematic literature review
Dalal Alshehri, Nasimul Noman, Raymond Chiong, Shah Jahan Miah, Aaron L. Sverdlov, D. Ngo
Abstract
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.