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量化医疗系统的恢复力:熵与网络科学视角

Quantifying the Resilience of a Healthcare System: Entropy and Network Science Perspectives.

作者信息

Klemann Désirée, Winasti Windi, Tournois Fleur, Mertens Helen, van Merode Frits

机构信息

Department of Gynecology and Obstetrics, Maastricht University Medical Centre+, Maastricht University, 6229 HX Maastricht, The Netherlands.

Care and Public Health Research Institute, Maastricht University, 6200 MD Maastricht, The Netherlands.

出版信息

Entropy (Basel). 2023 Dec 24;26(1):21. doi: 10.3390/e26010021.

Abstract

In this study, we consider the human body and the healthcare system as two complex networks and use theories regarding entropy, requisite variety, and network centrality metrics with resilience to assess and quantify the strengths and weaknesses of healthcare systems. Entropy is used to quantify the uncertainty and variety regarding a patient's health state. The extent of the entropy defines the requisite variety a healthcare system should contain to be able to treat a patient safely and correctly. We use network centrality metrics to visualize and quantify the healthcare system as a network and assign the strengths and weaknesses of the network and of individual agents in the network. We apply organization design theories to formulate improvements and explain how a healthcare system should adjust to create a more robust and resilient healthcare system that is able to continuously deal with variations and uncertainties regarding a patient's health, despite possible stressors and disturbances at the healthcare system. In this article, these concepts and theories are explained and applied to a fictive and a real-life example. We conclude that entropy and network science can be used as tools to quantify the resilience of healthcare systems.

摘要

在本研究中,我们将人体和医疗保健系统视为两个复杂网络,并运用关于熵、必要多样性以及具有恢复力的网络中心性指标的理论,来评估和量化医疗保健系统的优势与劣势。熵用于量化患者健康状态的不确定性和多样性。熵的程度定义了医疗保健系统为能够安全且正确地治疗患者而应包含的必要多样性。我们使用网络中心性指标将医疗保健系统可视化为网络并进行量化,同时确定网络以及网络中各个主体的优势与劣势。我们应用组织设计理论来制定改进措施,并解释医疗保健系统应如何进行调整,以创建一个更强大且具有恢复力的医疗保健系统,该系统能够持续应对患者健康方面的变化和不确定性,尽管医疗保健系统可能存在压力源和干扰。在本文中,这些概念和理论将通过一个虚构示例和一个实际示例进行解释与应用。我们得出结论,熵和网络科学可作为量化医疗保健系统恢复力的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/bc5de0551029/entropy-26-00021-g001.jpg

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