School of Sociology, Politics, and International Studies (SPAIS), University of Bristol, Bristol BS8 1TU, UK.
Department of Infection, Immunity and Cardiovascular Disease (IICD), University of Sheffield, Sheffield S10 2RX, UK.
Sensors (Basel). 2023 Jul 12;23(14):6333. doi: 10.3390/s23146333.
A digital twin is a computer-based "virtual" representation of a complex system, updated using data from the "real" twin. Digital twins are established in product manufacturing, aviation, and infrastructure and are attracting significant attention in medicine. In medicine, digital twins hold great promise to improve prevention of cardiovascular diseases and enable personalised health care through a range of Internet of Things (IoT) devices which collect patient data in real-time. However, the promise of such new technology is often met with many technical, scientific, social, and ethical challenges that need to be overcome-if these challenges are not met, the technology is therefore less likely on balance to be adopted by stakeholders. The purpose of this work is to identify the facilitators and barriers to the implementation of digital twins in cardiovascular medicine. Using, the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework, we conducted a document analysis of policy reports, industry websites, online magazines, and academic publications on digital twins in cardiovascular medicine, identifying potential facilitators and barriers to adoption. Our results show key facilitating factors for implementation: preventing cardiovascular disease, in silico simulation and experimentation, and personalised care. Key barriers to implementation included: establishing real-time data exchange, perceived specialist skills required, high demand for patient data, and ethical risks related to privacy and surveillance. Furthermore, the lack of empirical research on the attributes of digital twins by different research groups, the characteristics and behaviour of adopters, and the nature and extent of social, regulatory, economic, and political contexts in the planning and development process of these technologies is perceived as a major hindering factor to future implementation.
数字孪生是一种基于计算机的“虚拟”复杂系统表示，使用来自“真实”孪生体的数据进行更新。数字孪生在产品制造、航空和基础设施中得到了广泛应用，并在医学领域引起了极大关注。在医学领域，数字孪生有望通过一系列物联网 (IoT) 设备来改善心血管疾病的预防，并通过实时收集患者数据来实现个性化医疗。然而，新技术的前景常常伴随着许多技术、科学、社会和伦理方面的挑战，如果这些挑战得不到解决，那么这项技术就不太可能被利益相关者所采用。本研究旨在确定在心血管医学中实施数字孪生的促进因素和障碍。我们使用非采用、放弃、扩展、传播和可持续性（NASSS）框架，对心血管医学中数字孪生的政策报告、行业网站、在线杂志和学术出版物进行了文件分析，以确定采用数字孪生的潜在促进因素和障碍。研究结果显示了实施的关键促进因素：预防心血管疾病、计算机模拟和实验以及个性化护理。实施的关键障碍包括：建立实时数据交换、感知到的专业技能要求、对患者数据的高需求以及与隐私和监控相关的伦理风险。此外，不同研究小组对数字孪生属性、采用者特征和行为以及这些技术规划和开发过程中的社会、监管、经济和政治背景的性质和程度缺乏实证研究，被认为是未来实施的主要障碍。
