Digital Technology-Based Telemedicine for the COVID-19 Pandemic - Shen, Yu-Ting; Chen, Liang; Yue, Wen-Wen; Xu, Hui-Xiong (Frontiers in Medicine, 2021)
The coronavirus disease 2019 (COVID-19) crisis intersected with the development and maturation of several digital technologies including the internet of things (IoT) with next generation 5G networks, artificial intelligence (AI) that uses deep learning, big-data analytics, blockchain and robotic technology, in the year 2020, has resulted in an unprecedented opportunity for the progress of telemedicine. Digital technology based telemedicine platform has currently been established in many countries, incorporated into clinical workflow with four modes including “Many to One” mode, “One to Many” mode, “Consultation” mode, and “Practical Operation” mode, and shown to be feasible, effective, and efficient in sharing epidemiological data, enabling direct interactions among healthcare providers or patients across distance, minimizing the risk of disease infection, improving the quality of patient care and preserving healthcare resources. In this state-of-the-art review, we will provide a framework for the advances of telemedicine during this COVID-19 pandemic, particularly accompanied by these digital technologies, which can make a good paradigm for presenting the potential benefits of telemedicine in context of great health crisis. We also outline several new strategies for supporting the use of telemedicine at scale.