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一种用于基于离散事件模拟的优化重症监护工作流程的健康数字孪生框架。

A health digital twin framework for discrete event simulation based optimised critical care workflows.

作者信息

Kuruppu Appuhamilage Gayan Dihantha Kuruppu, Hussain Maqbool, Zaman Mohsin, Ali Khan Wajahat

机构信息

School of Computing, College of Science and Engineering, University of Derby, Kedleston Road, Derby, UK, DE22 1GB.

Northampton General Hospital NHS Trust, Cliftonville, Northampton, UK, NN1 5BD.

出版信息

NPJ Digit Med. 2025 Jun 19;8(1):376. doi: 10.1038/s41746-025-01738-4.

Abstract

Digital twins have been used in industries and is now gaining traction in healthcare, particularly in precision medicine. Discrete Event Simulation is a modelling methodology for simulating processes and workflows in healthcare. This paper presents a methodology that integrates these technologies to optimise critical care workflows based on real-time state changes, emphasising patient safety, operational efficiency, and sustainability. This study proposes a novel dual-layer architecture to monitor physical and conceptual entities in the Critical Care Unit. In the current scope, this study aims to establish a methodology using Azure cloud to track treatment workflows in real-time. The results indicated that by reviewing observation forms alone successfully tracked 72% of staff-performed tasks in real-time. This study underscores the potential of digital twins to transform precision care in critical care delivery by bridging the gap between actual and ideal clinical practices.

摘要

数字孪生已在工业中得到应用,目前在医疗保健领域正越来越受到关注,尤其是在精准医疗方面。离散事件模拟是一种用于模拟医疗保健过程和工作流程的建模方法。本文提出了一种整合这些技术的方法,以根据实时状态变化优化重症监护工作流程,强调患者安全、运营效率和可持续性。本研究提出了一种新颖的双层架构,用于监测重症监护病房中的物理实体和概念实体。在当前范围内,本研究旨在建立一种使用Azure云实时跟踪治疗工作流程的方法。结果表明,仅通过审查观察表就能成功实时跟踪72%的员工执行任务。本研究强调了数字孪生通过弥合实际临床实践与理想临床实践之间的差距,在重症监护中变革精准护理的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbc6/12179303/6536ee8ab03a/41746_2025_1738_Fig1_HTML.jpg

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