新冠肺炎大流行背景下数字双胞胎的范围综述

IF 2.3 Q3 ENGINEERING, BIOMEDICAL Biomedical Engineering and Computational Biology Pub Date : 2022-01-01 DOI:10.1177/11795972221102115
Asiya Khan, M. Milne-Ives, E. Meinert, G. Iyawa, Ray B Jones, A. N. Josephraj
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引用次数: 8

摘要

背景:数字双胞胎(DT)是物理实体的虚拟副本,是帮助管理和预测新冠肺炎疫情的一种很有前途的工具。通过提供每个患者的详细模型,可以使用DTs来确定哪种护理方法对该患者最有效。患者体验和护理服务的改善将有助于减少对医疗服务的需求,并改善医院管理。目的:本研究的目的是解决两个研究问题:(1)DTs在预测和管理新冠肺炎等传染病方面的有效性如何?以及(2)在医疗保健中使用DTs的前景和挑战是什么?方法:根据系统评价的首选报告项目和范围界定评价的荟萃分析扩展(PRISMA-ScR)框架构建综述。PubMed、IEEE Xplore、Scopus、ScienceDirect和Google Scholar中参考文献的标题和摘要使用选定的关键词(与数字双胞胎、医疗保健和新冠肺炎有关)进行搜索。根据纳入和排除标准对这些论文进行了筛选,因此所有以英语发表的与数字双胞胎在医疗保健中的使用有关的论文都被纳入其中。采用叙述性综合法对所收录的论文进行分析。结果:18篇论文符合入选标准,被纳入评审。纳入的论文中没有一篇研究了在新冠肺炎或一般传染病暴发的背景下使用DTs。关于DT技术在医疗保健领域的应用、机遇和挑战的学术研究普遍处于早期阶段。结论:该综述确定了对DTs在医疗保健中的使用进行进一步研究的必要性,特别是在传染病爆发的情况下。基于审查期间确定的框架,本文提出了在新冠肺炎疫情期间使用DTs进行医院管理的初步概念框架,以解决这一研究空白。
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A Scoping Review of Digital Twins in the Context of the Covid-19 Pandemic
Background: Digital Twins (DTs), virtual copies of physical entities, are a promising tool to help manage and predict outbreaks of Covid-19. By providing a detailed model of each patient, DTs can be used to determine what method of care will be most effective for that individual. The improvement in patient experience and care delivery will help to reduce demand on healthcare services and to improve hospital management. Objectives: The aim of this study is to address 2 research questions: (1) How effective are DTs in predicting and managing infectious diseases such as Covid-19? and (2) What are the prospects and challenges associated with the use of DTs in healthcare? Methods: The review was structured according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) framework. Titles and abstracts of references in PubMed, IEEE Xplore, Scopus, ScienceDirect and Google Scholar were searched using selected keywords (relating to digital twins, healthcare and Covid-19). The papers were screened in accordance with the inclusion and exclusion criteria so that all papers published in English relating to the use of digital twins in healthcare were included. A narrative synthesis was used to analyse the included papers. Results: Eighteen papers met the inclusion criteria and were included in the review. None of the included papers examined the use of DTs in the context of Covid-19, or infectious disease outbreaks in general. Academic research about the applications, opportunities and challenges of DT technology in healthcare in general was found to be in early stages. Conclusions: The review identifies a need for further research into the use of DTs in healthcare, particularly in the context of infectious disease outbreaks. Based on frameworks identified during the review, this paper presents a preliminary conceptual framework for the use of DTs for hospital management during the Covid-19 outbreak to address this research gap.
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