Journal of Medical Systems

, 38:107

Time Series Modelling and Forecasting of Emergency Department Overcrowding

  • Farid Kadri
  • Fouzi Harrou
  • Sondès Chaabane
  • Christian Tahon
Systems-Level Quality Improvement

DOI: 10.1007/s10916-014-0107-0

Cite this article as:
Kadri, F., Harrou, F., Chaabane, S. et al. J Med Syst (2014) 38: 107. doi:10.1007/s10916-014-0107-0
Part of the following topical collections:
  1. Systems-Level Quality Improvement

Abstract

Efficient management of patient flow (demand) in emergency departments (EDs) has become an urgent issue for many hospital administrations. Today, more and more attention is being paid to hospital management systems to optimally manage patient flow and to improve management strategies, efficiency and safety in such establishments. To this end, EDs require significant human and material resources, but unfortunately these are limited. Within such a framework, the ability to accurately forecast demand in emergency departments has considerable implications for hospitals to improve resource allocation and strategic planning. The aim of this study was to develop models for forecasting daily attendances at the hospital emergency department in Lille, France. The study demonstrates how time-series analysis can be used to forecast, at least in the short term, demand for emergency services in a hospital emergency department. The forecasts were based on daily patient attendances at the paediatric emergency department in Lille regional hospital centre, France, from January 2012 to December 2012. An autoregressive integrated moving average (ARIMA) method was applied separately to each of the two GEMSA categories and total patient attendances. Time-series analysis was shown to provide a useful, readily available tool for forecasting emergency department demand.

Keywords

Emergency departmentOvercrowdingTime seriesARMAForecasting

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Farid Kadri
    • 1
    • 2
  • Fouzi Harrou
    • 3
  • Sondès Chaabane
    • 1
    • 2
  • Christian Tahon
    • 1
    • 2
  1. 1.Univ. Lille Nord de FranceLilleFrance
  2. 2.UVHC, TEMPO Lab., “Production, Services, Information” TeamValenciennesFrance
  3. 3.Chemical Engineering ProgramTexas A&M University at QatarDohaQatar