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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月19日

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

摘要

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.