Abstract
We present a computational model of workflow in the hospital during a pandemic. The objective is to assist management in anticipating the load of each care unit, such as the ICU, or ordering supplies, such as personal protective equipment, but also to retrieve key parameters that measure the performance of the health system facing a new crisis. The model was fitted with good accuracy to France's data set that gives information on hospitalized patients and is provided online by the French government. The goal of this work is both practical in offering hospital management a tool to deal with the present crisis of COVID-19 and offering a conceptual illustration of the benefit of computational science during a pandemic.
Publication types
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Research Support, Non-U.S. Gov't
MeSH terms
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Computer Simulation*
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Hospital Administration / methods*
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Hospitalization / statistics & numerical data
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Humans
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Pandemics*
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Workflow*
Grants and funding
MG funded a start-up called ORintelligence, MG and GJ are respectively President and CTO of this company but not employees. The funder provided support in the form of salary for SF and to acquire research materials but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. As a matter of fact, ORintelligence is an AI driven, people friendly solution to improve clinics’ flow, efficiency, and outcomes and has no intend to work in ICU. The specific roles of these authors are articulated in the ‘author contributions’ section. This does not alter our adherence to PLOS ONE policies on sharing data and materials.