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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.


DOI:10.3390/e26010021
PMID:38248147
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10814470/
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
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/e87285286207/entropy-26-00021-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/bc5de0551029/entropy-26-00021-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/102b9ef1aacd/entropy-26-00021-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/ae3706be99ba/entropy-26-00021-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/8992bd9ee069/entropy-26-00021-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/9cc707974502/entropy-26-00021-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/f605ac5ed979/entropy-26-00021-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/9f7bf38fd836/entropy-26-00021-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/ebc852d48d88/entropy-26-00021-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/b0b3b11e51bf/entropy-26-00021-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/ae5e6e35f046/entropy-26-00021-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/f39f9f177884/entropy-26-00021-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/58b940df0113/entropy-26-00021-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/5a42743ef735/entropy-26-00021-g013a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/278080fe4f50/entropy-26-00021-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/e87285286207/entropy-26-00021-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/bc5de0551029/entropy-26-00021-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/102b9ef1aacd/entropy-26-00021-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/ae3706be99ba/entropy-26-00021-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/8992bd9ee069/entropy-26-00021-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/9cc707974502/entropy-26-00021-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/f605ac5ed979/entropy-26-00021-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/9f7bf38fd836/entropy-26-00021-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/ebc852d48d88/entropy-26-00021-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/b0b3b11e51bf/entropy-26-00021-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/ae5e6e35f046/entropy-26-00021-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/f39f9f177884/entropy-26-00021-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/58b940df0113/entropy-26-00021-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/5a42743ef735/entropy-26-00021-g013a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/278080fe4f50/entropy-26-00021-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e8/10814470/e87285286207/entropy-26-00021-g015.jpg

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引用本文的文献

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本文引用的文献

[1]
Molecular biomarkers, network biomarkers, and dynamic network biomarkers for diagnosis and prediction of rare diseases.

Fundam Res. 2022-8-9

[2]
Hospital Organizational Structure and Information Processing: An Entropy Perspective.

Entropy (Basel). 2023-2-26

[3]
The problem with making Safety-II work in healthcare.

BMJ Qual Saf. 2022-5

[4]
Health and Disease Are Dynamic Complex-Adaptive States Implications for Practice and Research.

Front Psychiatry. 2021-3-29

[5]
The Human Organism as an Integrated Interaction Network: Recent Conceptual and Methodological Challenges.

Front Physiol. 2020-12-21

[6]
Resilience in Clinical Care: Getting a Grip on the Recovery Potential of Older Adults.

J Am Geriatr Soc. 2019-9-9

[7]
Revisiting redundancy in hospitals-A case-based research study.

Health Care Manage Rev. 2021

[8]
Quantifying resilience of humans and other animals.

Proc Natl Acad Sci U S A. 2018-10-29

[9]
Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery.

BMC Med. 2018-9-7

[10]
Adaptive expertise in medical decision making.

Med Teach. 2018-7-23

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