Abstract
Emergency services aim to use complex systems to ensure the provision of fundamental healthcare services to the patient at the appropriate time. Patients approaching the emergency department are examined in detail by healthcare providers. The care providers aim to obtain real-time data about the patients to detect the issues and quickly decide the appropriate treatment plan. Emergency Departments (EDs) are run by complex management systems and render diverse healthcare services. The assessment of the service quality in the emergency departments has improved significantly with the development of tools and systems of performance assessment in underdeveloped countries. These assessments are based on the views of the patients. In this context, the aim of this study was to formulate a highly sensitive assessment tool that is appropriate for simulation experiments. This assessment tool was validated and had a kappa value of 0.763 and a Cronbach’s alpha value of 0.827. The use of this tool for the assessment of healthcare standards resulted in the collection of valid and reliable data. The probability density distribution was used to check the accuracy of the results of the simulation experiment data, and all data adequately followed a normal distribution. Furthermore, 90% of the simulated cases were found to be within the optimal range.
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References
Gul, M., Guneri, A.F.: A comprehensive review of emergency department simulation applications for normal and disaster conditions. Comput. Ind. Eng. 83, 327–344 (2015). https://doi.org/10.1016/j.cie.2015.02.018
Ruohonen, T., Neittaanmaki, P., Teittinen, J.: Simulation model for improving the operation of the emergency department of special health care. In: Proceedings of 2006 Winter Simulation Conference, Monterey, CA, Dec 2006, pp. 453–458
Cabrera, E., Taboada, M., Iglesias, M.L., Epelde, F., Luque, E.: Simulation optimization for healthcare emergency departments. Procedia Comput. Sci. 9, 1464–1473 (2012). https://doi.org/10.1016/j.procs.2012.04.161
Ahmed, M.A., Alkhamis, T.M.: Simulation optimization for an emergency department healthcare unit in Kuwait. Eur. J. Oper. Res. 198(3), 936–942 (2009). https://doi.org/10.1016/j.ejor.2008.10.025
Carmen, R., Defraeye, M., Aydin, C.B., van Nieuwenhuyse, I.: Modeling emergency departments using discrete-event simulation: a real-life case study including patient boarding. The Faculty of Economics and Business, Leuven, FEB Res. Rep. KBI 1420, Sept 2014.
Kolker, A.: Process modeling of emergency department patient flow: effect of patient length of stay on ED diversion. J. Med. Syst. 32(5), 389–401 (2008). https://doi.org/10.1007/s10916-008-9144-x
de Angelis, V., Felici, G., Impelluso, P.: Integrating simulation and optimisation in health care centre management. Eur. J. Oper. Res. 150(1), 101–114 (2003). https://doi.org/10.1016/S0377-2217(02)00791-9
Alharethi, S., Gani, A., Othman, M.K.: Emergency departments. In: Arai, K., Kapoor, S., Bhatia, R. (eds.) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, pp. 341–358. Springer, Cham (2019)
Hoot, N.R., et al.: Forecasting emergency department crowding: a discrete event simulation. Ann. Emerg. Med. 52(2), 116–125 (2008). https://doi.org/10.1016/j.annemergmed.2007.12.011
Connelly, L.G., Bair, A.E.: Discrete event simulation of emergency department activity: a platform for system-level operations research. Acad. Emerg. Med. 11(11), 1177–1185 (2004). https://doi.org/10.1197/j.aem.2004.08.021
Oddoye, J.P., Yaghoobi, M.A., Tamiz, M., Jones, D.F., Schmidt, P.: A multi-objective model to determine efficient resource levels in a medical assessment unit. J. Oper. Res. Soc. 58(12), 1563–1573 (2007). https://doi.org/10.1057/palgrave.jors.2602315
Merkle, J.F.: Computer simulation: a methodology to improve the efficiency in the Brooke army medical center family care clinic. J. Healthcare Manage. 47(1), 58 (2002). https://doi.org/10.1097/00115514-200201000-00011
Brailsford, S.C., et al.: Overcoming the barriers: a qualitative study of simulation adoption in the NHS. J. Oper. Res. Soc. 64(2), 157–168 (2013). https://doi.org/10.1057/jors.2011.130
Zayed, S.B., Gani, A.B., Othman, M.K.: System Reengineering in Healthcare: Application for Hospital Emergency Departments. Springer, Cham (2018)
Alanazi, A.F.: Emergency medical services in Saudi Arabia: a study on the significance of paramedics and their experiences on barriers as inhibitors of their efficiency. Int. J. Appl. Basic Med. Res. 2(1), 34–37 (2012). https://doi.org/10.4103/2229-516X.96803
Robinson, S., Brooks, R., Kotiadis, K., van der Zee, D.J.: Conceptual Modeling for Discrete-Event Simulation. CRC Press, Florida (2010)
Komashie, A., Mousavi, A.: Modeling emergency departments using discrete event simulation techniques. In: Proceedings of the Winter Simulation Conference, 5p, 4 Dec 2005. IEEE
Rockwell, A.: Arena. Rockwell Automation Technologies Inc., USA (2018)
Stewart, R.: Successful Simulation—A Practical Approach to Simulation Projects. McGraw-Hill Book Company Europe, England (1994). 0-07-707622-2
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Ben Zayed, S., Gani, A.B., Gadelrab, H., Bin Othman, M.K. (2021). Ambulance Transfer and Emergency Department Processing: Modelling and Simulation. In: Operational Management in Emergency Healthcare. Studies in Systems, Decision and Control, vol 297. Springer, Cham. https://doi.org/10.1007/978-3-030-53832-3_4
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