Modeling the Patients Flow Behavior in Hilla Emergency Departments

  • Abstract
  • Keywords
  • References
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  • Abstract

    Emergency department (ED) represents a crucial and suitable for most patients' emergency cases at any time. It is extremely associated health services dedicated mostly to treat the arriving patient's with uncertain illnesses and without previousappointment.Patient flow sequences representa very complex processdue to the different uncertain requirements and different possible paths that patients may guide to complete their treatment.  An Agent Based Modeling (ABM) approach is implemented and appliedin an emergency department in Hilla hospital as a case studyin this paper.Thisstudy combinesABM with queuing and discrete events simulationas an evaluation process for the patients flow behavior and staff utilization in an emergency department. ABM is a flexible tool that can be created to imitatecertain complex environment. It can offer certain level of supports for managers to consider the relative influence of current or suggested strategies. It provides a suitablesituation in studying andpredicting the interactions and behavior's in ED operations. This study aims to maximize the patient's throughput, minimize their waitingtimesand optimize the resources utilization. The methodology that followed in this study is to estimate the optimal required number of ED staff's, which involves doctors, triage nurses, and receptionist, lab and x-raytechnician. Patients were modeled as agents having an ability to interact with others and with staffs and to select whether to wait and stay in the system or to leave at any stage of treatment. The simulation results is implemented according to the real collected data and the managers experiences about the averages of arrival and service rates with flow sequence probabilities. Waiting and idle times for the patients and staffs showed a good indication about the quality of services. 



  • Keywords

    Healthcare, agent-based modeling, discrete event simulation, emergency department.

  • References

      [1] Ahmed, M. A. and Alkhamis, T. M. (2009) ‘Simulation optimization for an emergency department healthcare unit in Kuwait’, European Journal of Operational Research. Elsevier B.V., 198(3), pp. 936–942. doi: 10.1016/j.ejor.2008.10.025.

      [2] Cabrera, E. et al. (2011) ‘Optimization of healthcare emergency departments by agent-based simulation’, Procedia Computer Science, 4, pp. 1880–1889. doi: 10.1016/j.procs.2011.04.204.

      [3] Cabrera, E. et al. (2012) ‘Simulation optimization for healthcare emergency departments’, Procedia Computer Science. Elsevier Masson SAS, 9, pp. 1464–1473. doi: 10.1016/j.procs.2012.04.161.

      [4] Liu, Z. et al. (2014) ‘A Generalized Agent-Based Model to Simulate Emergency Departments’, The Sixth International Conference on Advances in System Simulation, (c), pp. 65–70. Available at:

      [5] Mustapha, K. and Frayret, J.-M. (2016) ‘Agent-based modeling and simulation software architecture for health care’, SIMULTECH 2016 - Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, (September), pp. 89–100. doi: 10.5220/0005972600890100.

      [6] Nahhas, A., Awaldi, A. and Reggelin, T. (2017) ‘Simulation and the Emergency Department Overcrowding Problem’, Procedia Engineering. The Author(s), 178, pp. 368–376. doi: 10.1016/j.proeng.2017.01.068.

      [7] Taboada, M. et al. (2013) ‘Using an agent-based simulation for predicting the effects of patients derivation policies in emergency departments’, Procedia Computer Science. Elsevier B.V., 18, pp. 641–650. doi: 10.1016/j.procs.2013.05.228.

      [8] Yousefi, M. et al. (2018) ‘Simulating the behavior of patients who leave a public hospital emergency department without being seen by a physician: A cellular automaton and agent-based framework’, Brazilian Journal of Medical and Biological Research, 51(3), pp. 1–10. doi: 10.1590/1414-431X20176961.

      [9] Yousefi, M. and Ferreira, R. P. M. (2017) ‘An agent-based simulation combined with group decision-making technique for improving the performance of an emergency department’, Brazilian Journal of Medical and Biological Research, 50(5), pp. 1–10. doi: 10.1590/1414-431x20175955.

      [10] Zeinali, F., Mahootchi, M. and Sepehri, M. M. (2015) ‘Resource planning in the emergency departments: A simulation-based metamodeling approach’, Simulation Modelling Practice and Theory. Elsevier B.V., 53, pp. 123–138. doi: 10.1016/j.simpat.2015.02.002.




Article ID: 28000
DOI: 10.14419/ijet.v7i4.19.28000

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