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Forecasting the Emergency Department Patients Flow

Abstract : Emergency department (ED) have become the patient’s main point of entrance in modern hospitals causing it frequent overcrowding, thus hospital managers are increasingly paying attention to the ED in order to provide better quality service for patients. One of the key elements for a good management strategy is demand forecasting. In this case, forecasting patients flow, which will help decision makers to optimize human (doctors, nurses…) and material(beds, boxs…) resources allocation. The main interest of this research is forecasting daily attendance at an emergency department. The study was conducted on the Emergency Department of Troyes city hospital center, France, in which we propose a new practical ED patients classification that consolidate the CCMU and GEMSA categories into one category and innovative time-series based models to forecast long and short term daily attendance. The models we developed for this case study shows very good performances (up to 91,24 % for the annual Total flow forecast) and robustness to epidemic periods.
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Journal articles
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https://hal-utt.archives-ouvertes.fr/hal-02493675
Contributor : Daniel Gavrysiak <>
Submitted on : Friday, February 28, 2020 - 8:57:56 AM
Last modification on : Saturday, February 29, 2020 - 1:35:31 AM

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ROSAS | UTT | CNRS

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Mohamed Afilal, Farouk Yalaoui, Frédéric Dugardin, Lionel Amodeo, David Laplanche, et al.. Forecasting the Emergency Department Patients Flow. Journal of Medical Systems, Springer Verlag (Germany), 2016, 40 (7), ⟨10.1007/s10916-016-0527-0⟩. ⟨hal-02493675⟩

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