Reducing Overcrowding at the Emergency Department Through a Different Physician and Nurse Shift Organisation: A Case Study

  • Roberto Aringhieri
  • Giovanni Bonetta
  • Davide DumaEmail author
Part of the AIRO Springer Series book series (AIROSS, volume 1)


Overcrowding is a widespread problem affecting the performance of an Emergency Department (ED). In this paper we deal with the overcrowding problem at the ED sited at Ospedale Sant’Antonio Abate di Cantù, Italy. Exploiting the huge amounts of data collected by the ED, we propose a new agent-based simulation model to analyse the real impact on the ED overcrowding of a different physicians and nurses shift organisations. The proposed simulation model demonstrates its capability of analysing the ED performance from a patient-centred perspective.


Emergency department Overcrowding Agent based simulation 



The authors wish to thank Alessandra Farina, Elena Scola and Filippo Marconcini of the ED at Ospedale Sant’Antonio Abate di Cantù for the fruitful collaboration and for providing us the data set and allowing their use in this paper.


  1. 1.
    Aboueljinane, L., Sahin, E., Jemai, Z.: A review on simulation models applied to emergency medical service operations. Comput. Ind. Eng. 66, 734–750 (2013)CrossRefGoogle Scholar
  2. 2.
    Aringhieri, R., Bruni, M., Khodaparasti, S., van Essen, J.: Emergency medical services and beyond: addressing new challenges through a wide literature review. Comput. Oper. Res. 78, 349–368 (2017)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Aringhieri, R., Dell’Anna, D., Duma, D., Sonnessa, M.: Evaluating the dispatching policies for a regional network of emergency departments exploiting health care big data. In: Lecture Notes in Computer Science, vol. 10710, pp. 549–561. Springer (2018)Google Scholar
  4. 4.
    Aringhieri, R., Duma, D., Fragnelli, V.: Modeling the rational behavior of individuals on an e-commerce system. Oper. Res. Perspect. 5, 22–31 (2018)CrossRefGoogle Scholar
  5. 5.
    Derlet, R.: Overcrowding in emergency departments: increased demand and decreased capacity. Ann. Emerg. Med. 39(4), 430–432 (2002)CrossRefGoogle Scholar
  6. 6.
    Derlet, R., Richards, J.: Overcrowding in the nation’s emergency departments: complex causes and disturbing effects. Ann. Emerg. Med. 35(1), 63–68 (2000)CrossRefGoogle Scholar
  7. 7.
    Duma, D., Aringhieri, R.: Mining the Patient Flow Through an Emergency Department to Deal with Overcrowding, vol. 210, pp. 49–59. Springer, New York LLC (2017)Google Scholar
  8. 8.
    Feng, Y.-Y., Wu, I.-C., Chen, T.-L.: Stochastic resource allocation in emergency departments with a multi-objective simulation optimization algorithm. Health Care Manag. Sci. 20(1), 55–75 (2017)CrossRefGoogle Scholar
  9. 9.
    George, F., Evridiki, K.: The effect of emergency department crowding on patient outcomes. Health Sci. J. 9(1), 1–6 (2015)Google Scholar
  10. 10.
    Hwang, U., Concato, J.: Care in the emergency department: how crowded is overcrowded? Acad. Emerg. Med. 11(10), 1097–1101 (2004)CrossRefGoogle Scholar
  11. 11.
    Luscombe, R., Kozan, E.: Dynamic resource allocation to improve emergency department efficiency in real time. Eur. J. Oper. Res. 255(2), 593–603 (2016)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Paul, S., Reddy, M., Deflitch, C.: A systematic review of simulation studies investigating emergency department overcrowding. Simulation 86(8–9), 559–571 (2010)CrossRefGoogle Scholar
  13. 13.
    Sinreich, D., Jabali, O., Dellaert, N.: Reducing emergency department waiting times by adjusting work shifts considering patient visits to multiple care providers. IIE Trans. (Inst. Ind. Eng.) 44(3), 163–180 (2012)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Roberto Aringhieri
    • 1
  • Giovanni Bonetta
    • 1
  • Davide Duma
    • 1
    Email author
  1. 1.Dipartimento di InformaticaUniversità degli Studi di TorinoTurinItaly

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