Author: Le Lay, J.; Augusto, V.; Xie, X. L.; Alfonso-Lizarazo, E.; Bongue, B.; Celarier, T.; Gonthier, R.; Masmoudi, M.; Ieee,
Title: Impact of Covid-19 Epidemics on Bed Requirements in a Healthcare Center Using Data-driven Discrete-event Simulation Cord-id: 6sd72st0 Document date: 2020_1_1
ID: 6sd72st0
Snippet: Bed occupancy ratio reflects the state of the hospital at a given time. It is important for management to keep track of this figure to proactively avoid overcrowding and maintain a high level of quality of care. The objective of this work consists in proposing a decision-aid tool for hospital managers allowing to decide on the bed requirements for a given hospital or network of hospitals on a short-medium term horizon. To that extent we propose a new data-driven discrete-event simulation model b
Document: Bed occupancy ratio reflects the state of the hospital at a given time. It is important for management to keep track of this figure to proactively avoid overcrowding and maintain a high level of quality of care. The objective of this work consists in proposing a decision-aid tool for hospital managers allowing to decide on the bed requirements for a given hospital or network of hospitals on a short-medium term horizon. To that extent we propose a new data-driven discrete-event simulation model based on data from a French university hospital to predict bed and staff requirements. We propose a case study to illustrate the tool's ability to monitor bed occupancy in the recovery unit given the admission rate of ED patients during the pandemic of Sars-Cov-2. These results give an interesting insight on the situation, providing decision makers with a powerful tool to establish an enlightened response to this situation.
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