A Framework for emergency department management: a proposal based on process mining and simulation
AbstractAn emergency department (ED) face random demands from patients with different needs, which may contribute to their overcrowding. therefore, the present study designed a framework to support decision making in ED management. The framework integrates simulation techniques supported by process mining. Simulation was used in this work because it contributes to capture the randomness and complexity of patient flow in the ED and support the decision-making process. However, the data to feed a simulation model is usually collected manually from the time between patient arrivals in the ED, time for triage, interviews with experts, among others. Nevertheless, use only these collection techniques may be error-induced because they are based on human perceptions, as well as they are long. In this sense, process mining contributed to the construction of the studied ED simulation model through the discovery of the real process and the historical data of the patients registered in the event log. Through process mining, little conceptual modeling effort was used for the simulation model, which may contribute to encouraging the use of simulation in hospital environments.
. L. Vanbrabant, K. Braekers, K. Ramaekers, I. Van Nieuwenhuyse, I. Simulation of emergency department operations: A comprehensive review of KPIs and operational improvements. Computers & Industrial Engineering, 131, pp. 356-381, 2019.
. F. Pegoraro, E. A. P. Santos, E. D. F. R. Loures. A support framework for decision making in emergency department management. Computers & Industrial Engineering, 146, 106477, 2020.
. A. AROUA, G. ABDULNOUR, Optimization of the emergency department in hospitals using simulation and experimental design: Case study. In: Simulation Conference (WSC), 2017 Winter. IEEE, 2017, pp.4511-4513.
. F. Pegoraro, E. A. P. Santos, E. D. F. R. Loures, F. W. Laus. A hybrid model to support decision making in emergency department management. Knowledge-Based Systems, 203, 106148, 2020.
. P. BOCCIARELLI, A. D'AMBROGIO, A. GIGLIO, E. PAGLIA. Simulation-Based Performance And Reliability Analysis Of Business Processes. In: Proceedings Of The 2014 Winter Simulation Conference, Piscataway, Nj, Usa. IEEE Press, 2014, pp. 3012-3023.
. P. LAJOIE, J, GAUDREAULT, V. LAVOIE, J. KENDALL. Using Simulation To Assess The Performance Of A Breakthrough Wood-Drying Technology. In: Proceedings Of The 2014 Winter Simulation Conference: Piscataway, Nj, Usa. IEEE Press, 2014, pp. 4158–4159
. A. ROZINAT, M. T. WYNN, W. M. P. VAN DER AALST, A. H. TER HOFSTEDE, C. J. FIDGE. Workflow simulation for operational decision support. Data & Knowledge Engineering, vol. 68(9), pp 834-850, 2009.
. A. ROZINAT, R. S, MANS, M. SONG, W. M. P VAN DER AALST. Discovering simulation models. Information systems, vol. 34(3), pp. 305-327, 2009.
. R. S. MANS, W. M. P, VAN DER AALST, R. J. B, VANWERSCH. Process mining in healthcare: evaluating and exploiting operational healthcare processes. Heidelberg: Springer, 2015.
. H. A. REIJERS, W. M. P, VAN DER AALST. Short-term simulation: bridging the gap between operational control and strategic decision making. In Proceedings of the IASTED International Conference on Modeling and Simulation, 1999, pp. 417-421.
. M. ROVANI, F. M. MAGGI, M. Leoni, W. M. P. VAN DER AALST. Declarative process mining in healthcare. Expert Systems with Applications, vol. 42(23), pp. 9236-9251, 2015.
. W. M. P. VAN DER AALST, Process Mining – discovery, conformance and enhancement of business processes. Springer, 2011.
. I. KHODYREV, S. POPOVA. Discrete modeling and simulation of business processes using event logs. Procedia Computer Science, 2014, pp. 322-331.
. A. ROZINAT, M. WYNN, W. M. P. VAN DER AALST, A. H. TER HOFSTEDE, C. J. FIDGE. Workflow simulation for operational decision support using design, historic and state information. In International Conference on Business Process Management. Springer, Berlin, Heidelberg, 2008, pp. 196-211.
. M. T WYNN, M. DUMAS, C. J. FIDGE, A. H. TER HOFSTEDE, W. M. P. VAN DER AALST. Business process simulation for operational decision support. In International Conference on Business Process Management. Springer, Berlin, Heidelberg. 2007, pp. 66-77.
. W. ABO-HAMAD, A. RAMY, ARISHA. A hybrid process-mining approach for simulation modeling. In: Simulation Conference (WSC), Winter. IEEE, 2017. pp. 1527-1538.
. F. PEGORARO, E. A. P. SANTOS, E. F. R. LOURES, G. DA SILVA DIAS, G. L. M. DOS SANTOS, R. O. COELHO. Short-Term Simulation in Healthcare Management with Support of the Process Mining. In: World Conference on Information Systems and Technologies, Springer, Cham, 2018, pp. 724-735.
. V. AUGUSTO, X. XIE, M. PRODEL, B. JOUANETON, L. LAMARSALLE. Evaluation of discovered clinical pathways using process mining and joint agent-based discrete-event simulation. In Proceedings of the 2016 Winter Simulation Conference, IEEE Press, 2016, pp. 2135-2146.
. J. NAKATUMBA, M. WESTERGAARD, W. M. P. VAN DER AALST. Generating event logs with workload-dependent speeds from simulation models. In: International Conference on Advanced Information Systems Engineering. Springer, Berlin, Heidelberg, 2012, pp. 383-397.
. C. ALVAREZ, E. ROJAS, M. ARIAS, J. MUNOZ-GAMA, M. SEPÚLVEDA, V. HERSKOVIC, D. CAPURRO. Discovering role interaction models in the Emergency Room using Process Mining. Journal of biomedical informatics, vol. 78, pp. 60-77, 2018.
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