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Forecasting the Emergency Department Patients Flow

  • Systems-Level Quality Improvement
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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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Authors and Affiliations

  1. Institut Charles Delaunay, LOSI, Université de Technologie de Troyes UMR 6281, CNRS, 12 Rue Marie Curie, CS 42060, cedex, 10004, Troyes, France

    Mohamed Afilal, Farouk Yalaoui, Frédéric Dugardin & Lionel Amodeo

  2. Département d’Information Médicale, Centre Hospitalier de Troyes, 101 Avenue Anatole, 10000, Troyes, France

    David Laplanche & Philippe Blua

Authors
  1. Mohamed Afilal
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  2. Farouk Yalaoui
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Correspondence to Mohamed Afilal.

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Afilal, M., Yalaoui, F., Dugardin, F. et al. Forecasting the Emergency Department Patients Flow. J Med Syst 40, 175 (2016). https://doi.org/10.1007/s10916-016-0527-0

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