Towards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department context

Las salas de emergencia son espacios propensos a congestionarse por el alto número de pacientes. Este problema conocido como overcrowding, tiene efectos negativos en el tiempo de espera de los pacientes. Una de las alternativas para mitigar dichos efectos es analizar el flujo de pacientes mediante l...

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Autores:: Mogollón Plazas, Juan David

Tipo de recurso:

Fecha de publicación:: 2022

Institución:: Universidad de los Andes

Repositorio:: Séneca: repositorio Uniandes

Idioma:: eng

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dc.title.none.fl_str_mv	Towards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department context
title	Towards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department context
spellingShingle	Towards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department context Input Data Management Discrete events simulation Stochastic processes Servicios médicos de urgencias Pacientes de hospitales Métodos de simulación Simulación por computadores digitales Aplicaciones Web Computación en la nube Ingeniería
title_short	Towards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department context
title_full	Towards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department context
title_fullStr	Towards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department context
title_full_unstemmed	Towards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department context
title_sort	Towards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department context
dc.creator.fl_str_mv	Mogollón Plazas, Juan David
dc.contributor.advisor.none.fl_str_mv	Guio, Roland de Goepp, Virginie Ávila Cifuentes, Oscar Javier
dc.contributor.author.none.fl_str_mv	Mogollón Plazas, Juan David
dc.contributor.jury.none.fl_str_mv	Avila Cifuentes, Oscar Javier Garcés Pernett, Kelly Johany Barbieri, Giacomo Goeep, Virginie
dc.subject.keyword.none.fl_str_mv	Input Data Management Discrete events simulation Stochastic processes
topic	Input Data Management Discrete events simulation Stochastic processes Servicios médicos de urgencias Pacientes de hospitales Métodos de simulación Simulación por computadores digitales Aplicaciones Web Computación en la nube Ingeniería
dc.subject.armarc.none.fl_str_mv	Servicios médicos de urgencias Pacientes de hospitales Métodos de simulación Simulación por computadores digitales Aplicaciones Web Computación en la nube
dc.subject.themes.es_CO.fl_str_mv	Ingeniería
description	Las salas de emergencia son espacios propensos a congestionarse por el alto número de pacientes. Este problema conocido como overcrowding, tiene efectos negativos en el tiempo de espera de los pacientes. Una de las alternativas para mitigar dichos efectos es analizar el flujo de pacientes mediante la Simulación de Eventos Discretos (DES), la cual es una poderosa herramienta para modelar la operación de un sistema a través de una secuencia de eventos. Esta técnica requiere datos de entrada de alta calidad, por lo que estos datos deben ser gestionados previamente en un proceso complejo de preparación conocido como Input Data Management (IDM). El objetivo del presente estudio es determinar cómo automatizar eficientemente el proceso de IDM requerido para los modelos DES que atacan el problema de overcrowding en salas de emergencia de hospitales y clínicas, de manera que se pueda validar la calidad de datos, reproducir y versionar los datos de entrada para un modelo DES, garantizando la seguridad y la disponibilidad de la información de los usuarios. Para abordar este problema fue necesario realizar un caso de estudio con datos reales para contextualizar el problema y evaluar los métodos estadísticos requeridos, así como realizar un ejercicio de comparación de características de las herramientas actuales para establecer las brechas entre las funcionalidades ofrecidas y las requeridas en este contexto. A partir de estos resultados, se planteó y desarrolló un prototipo que permitió satisfacer los requerimientos identificados mediante una aplicación web basada en una arquitectura cloud que da respuesta al problema planteado.
publishDate	2022
dc.date.accessioned.none.fl_str_mv	2022-02-18T19:03:52Z
dc.date.available.none.fl_str_mv	2022-02-18T19:03:52Z
dc.date.issued.none.fl_str_mv	2022-01-31
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
dc.type.coarversion.fl_str_mv	http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/masterThesis
dc.type.content.spa.fl_str_mv	Text
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url	http://hdl.handle.net/1992/54942
identifier_str_mv	instname:Universidad de los Andes reponame:Repositorio Institucional Séneca repourl:https://repositorio.uniandes.edu.co/
dc.language.iso.es_CO.fl_str_mv	eng
language	eng
dc.relation.references.es_CO.fl_str_mv	T. Anderson and L. Goodman, "Statistical inference about markov chains," The Annals of Mathematical Statistics, vol. 28, 03 1957. C. Duguay and F. Chetouane, "Modeling and Improving Emergency Department Systems using Discrete Event Simulation," Simulation, vol. 83, no. 4, pp. 311-320, 2007. A. Komashie and A. Mousavi, "Modeling emergency departments using discrete event simulation techniques," Proceedings - Winter Simulation Conference, vol. 2005, pp. 2681-2685, 2005 C. M. Rodriguez, "Evaluation of the DESI interface for discrete event simulation input data management automation," International Journal of Modelling and Simulation, vol. 35, no. 1, pp. 13-18, 2015. A. Skoogh and B. Johansson, "A methodology for input data management in discrete event simulation projects," in 2008 Winter Simulation Conference, 2008, pp. 1727-1735. N. Robertson and T. Perera, "Automated data collection for simulation" Simulation Practice and Theory, vol. 9, no. 6-8, pp. 349-364, 2002. A. Skoogh, B. Johansson, and J. Stahre, "Automated input data management: Evaluation of a concept for reduced time consumption in discrete event simulation," Simulation, vol. 88, no. 11, pp. 1279-1293, 2012. P. Barlas and C. Heavey, "Automation of input data to discrete event simulation for manufacturing: A review," International Journal of Modeling, Simulation, and Scientific Computing, vol. 7, no. 1, 2016. A. Skoogh, J. Michaloski, and N. Bengtsson, "Towards continuously updated simulation models: Combining automated raw data collection and automated data processing," 01 2011, pp. 1678-1689. C. Rodriguez, "An integrated framework for automated data collection and processing for discrete event simulation models," Ph.D. dissertation, Electronic Theses and Dissertations, 2004-2019., 2015. P. Barlas and C. Heavey, "Ke tool: An open source software for automated input data in discrete event simulation projects," 12 2016, pp. 472-483. Centeno, Giachetti, Linn, and Ismail, "A simulation-ilp based tool for scheduling er sta," in Proceedings of the 2003 Winter Simulation Conference, 2003., vol. 2, 2003, pp. 1930-1938 vol.2. K. Ghanes, O. Jouini, Z. Jemai, M. Wargon, R. Hellmann, V. Thomas, and G. Koole, "A comprehensive simulation modeling of an emergency department: A case study for simulation optimization of staing levels," Proceedings - Winter Simulation Conference, vol. 2015-Janua, pp. 1421-1432, 2015. S. M. Mahdi Seyed Ghafouri and B. Haji, "Utilizing a simulation approach for analysis of patient ow in the emergency department: A case study," in 2019 15th Iran International Industrial Engineering Conference (IIIEC), 2019, pp. 151-157. S. Samaha, W. S. Armel, and D. W. Starks, "The use of simulation to reduce the length of stay in an emergency department," Winter Simulation Conference Proceedings, vol. 2, pp. 1907-1911, 2003. O. G. Batarseh, E. J. Goldlust, and T. E. Day, "SysML for conceptual modeling and simulation for analysis: A case example of a highly granular model of an emergency department," Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013, pp. 2398-2409, 2013. A. Aroua and G. Abdulnour, "Optimization of the emergency department in hospitals using simulation and experimental design: Case study," Procedia Manufacturing, vol. 17, no. Mdc, pp. 878-885, 2018. S. Levin and M. Garifullin, "Simulating wait time in healthcare: Accounting for transition process variability using survival analyses," Proceedings - Winter Simulation Conference, vol. 2016-Febru, pp. 1252-1260, 2016. Y. H. Kuo, J. M. Leung, and C. A. Graham, "Simulation with data scarcity: Developing a simulation model of a hospital emergency department," Proceedings - Winter Simulation Conference, 2012. S. A. Paul, M. C. Reddy, and C. J. Deitch, "A systematic review of simulation studies investigating emergency department overcrowding," Simulation, vol. 86, no. 8-9, pp. 559-571, 2010. S. Saghafian, G. Austin, and S. J. Traub, "Operations research/management contributions to emergency department patient flow optimization: Review and research prospects," IIE Transactions on Healthcare Systems Engineering, vol. 5, no. 2, pp. 101- 123, 2015. H. Salmon, S. Rachuba, S. Briscoe, and M. Pitt, "A structured literature review of simulation modeling applied to emergency departments: Current patterns and emerging trends," Operations Research for Health Care, vol. 19, 01 2018. J. Jihene, A. El Mhamedi, and H. Chabchoub, "Simulationmodel of emergency department," Proceedings - ICSSSM'07: 2007 International Conference on Service Systems and Service Management, pp. 7-11, 2007. J. Bokrantz, A. Skoogh, D. L amkull, A. Hanna, and T. Perera, "Data quality problems in discrete event simulation of manufacturing operations," Simulation, vol. 94, no. 11, pp. 1009-1025, 2018. N. Robertson and T. Perera, "Feasibility for automatic data collection," in Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304), vol. 2, 2001, pp. 984-990 vol.2. N. Furian, D. Neubacher, M. O'Sullivan, C. Walker, and C. Pizzera, "GEDMod Towards a generic toolkit for emergency department modeling," Simulation Modelling Practice and Theory, vol. 87, no. July, pp. 239{273, 2018. [Online]. Available: https://doi.org/10.1016/j.simpat.2018.07.010 Y.-T. Lee, F. Riddick, and B. Johansson, "Core manufacturing simulation data a manufacturing simulation integration standard: Overview and case studies," International Journal of Computer Integrated Manufacturing, vol. 24, pp. 689-709, 08 2011. V. Silva, M. Kirikova, and G. Alksnis, "Containers for virtualization: An overview," Applied Computer Systems, vol. 23, pp. 21-27, 05 2018. D. Merkel, "Docker: lightweight linux containers for consistent development and deployment," Linux journal, vol. 2014, no. 239, p. 2, 2014. P. Jamshidi, C. Pahl, N. Mendon¿ca, J. Lewis, and S. Tilkov, "Microservices: The journey so far and challenges ahead," IEEE Software, vol. 35, pp. 24-35, 05 2018. I. Karabey Aksakalli, T. C¿ Celik, A. Can, and B. Tekinerdogan, "Deployment and communication patterns in microservice architectures: A systematic literature review," Journal of Systems and Software, vol. 180, p. 111014, 06 2021. A. Bandaru, "Amazon web services," 12 2020. S. Ross, STOCHASTIC PROCESSES, 2ND ED, ser. Wiley series in probability and mathematical statistics. Wiley India Pvt. Limited, 2008. [Online]. Available: https://books.google.com.co/books?id=HVHqPgAACAAJ INTRODUCTION TO STOCHASTIC PROCESSES. John Wiley Sons, Ltd, 2012, ch. 9, pp. 339{415. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10. 1002/9781118344972.ch9 M. Skuriat-Olechnowska, "Statistical inference and hypothesis testing for markov chains with interval censoring," 2005. [Online]. Available: https://bit.ly/3qofpOA C. Chateld, \Statistical Inference Regarding Markov Chain Models," Journal of the Royal Statistical Society Series C, vol. 22, no. 1, pp. 7{20, March 1973. [Online]. Available: https://ideas.repec.org/a/bla/jorssc/v22y1973i1p7-20.html W. T. Scherer and D. M. Glagola, "Markovian models for bridge maintenance management," Journal of Transportation Engineering-asce, vol. 120, pp. 37-51, 1994. S. K. Thompson, "Sample size for estimating multinomial proportions," The American Statistician, vol. 41, pp. 42-46, 1987. W. Conover, Practical nonparametric statistics, 3rd ed., ser. Wiley series in probability and statistics. New York, NY [u.a.]: Wiley, 1999. [Online]. Available: http://gso.gbv.de/DB=2.1/CMD-ACT=SRCHA&SRT=YOP&IKT= 1016&TRM=ppn+24551600X&sourceid=fbw bibsonomy I. Kononenko and M. Kukar, Machine Learning and Data Mining: Introduction to Principles and Algorithms. Horwood Publishing Limited, 2007. Z. Bosnjak, O. Grljevic, and S. Bosnjak, "Crisp-dm as a framework for discovering knowledge in small and medium sized enterprises' data," 06 2009, pp. 509-514. P. Sharma, "Discrete-event simulation," International journal of scientific & technology research, vol. 4, no. 4, pp. 136-140, 2015. J. Knoil and J. Helm, "Ensuring the successful adoption of discrete event simulation in a manufacturing environment," in 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165), vol. 2, 2000, pp. 1297-1304 vol.2. L. M. S. Dias, A. A. C. Vieira, G. A. B. Pereira, and J. A. Oliveira, "Discrete simulation ftware ranking a top list of the worldwide most popular and used tools," in 2016 Winter Simulation Conference (WSC), 2016, pp. 1060-1071. G. Dagkakis and C. Heavey, "A review of open source discrete event simulation software for operations research," Journal of Simulation, vol. 10, 06 2015. S. Lang, T. Reggelin, M. M uller, and A. Nahhas, "Open-source discrete-event simulation software for applications in production and logistics: An alternative to commercial tools" Procedia Computer Science, vol. 180, pp. 978-987, 01 2021. A. Vieira, L. Dias, M. Santos, G. Pereira, and J. Oliveira, "A ranking of the most known freeware and open source discrete-event simulation tools," in "", 01 2019, pp. 200-2019. V. Narasayya and S. Chaudhuri, "Cloud data services: Workloads, architectures and multi-tenancy," Foundations and Trends' in Databases, vol. 10, no. 1, pp. 1-107, 2021. [Online]. Available: http://dx.doi.org/10.1561/1900000060 G. Kulkarni, "Cloud computing-software as service," International Journal of Cloud Computing and Services Science, vol. 1, no. 1, p. 11, 2012. C. Fisher, "Cloud versus on-premise computing," American Journal of Industrial and Business Management, vol. 08, pp. 1991-2006, 01 2018. L. Qian, Z. Luo, Y. Du, and L. Guo, "Cloud computing: An overview," vol. 5931, 01 2009, pp. 626-631. L. Bass, P. Clements, and R. Kazman, Software Architecture in Practice, 3rd ed. Addison-Wesley Professional, 2012. Plotly, "Dash." [Online]. Available: https://es.reactjs.org/ Sebastian Ramirez, "Fastapi." [Online]. Available: https://github.com/tiangolo/fastapi Facebook, "React." [Online]. Available: https://es.reactjs.org/ C. Sievert, Interactive Web-Based Data Visualization with R, plotly, and shiny, 01 2020.
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spelling	Al consultar y hacer uso de este recurso, está aceptando las condiciones de uso establecidas por los autores.http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Guio, Roland de9c1202e8-6a1c-4264-af44-db743178bff1600Goepp, Virginieda2baf8f-924f-405e-a7f5-0b72a9a0c2a7600Ávila Cifuentes, Oscar Javiervirtual::5906-1Mogollón Plazas, Juan David4317ceec-9fea-4114-b3e6-f267df4b83af600Avila Cifuentes, Oscar JavierGarcés Pernett, Kelly JohanyBarbieri, GiacomoGoeep, Virginie2022-02-18T19:03:52Z2022-02-18T19:03:52Z2022-01-31http://hdl.handle.net/1992/54942instname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/Las salas de emergencia son espacios propensos a congestionarse por el alto número de pacientes. Este problema conocido como overcrowding, tiene efectos negativos en el tiempo de espera de los pacientes. Una de las alternativas para mitigar dichos efectos es analizar el flujo de pacientes mediante la Simulación de Eventos Discretos (DES), la cual es una poderosa herramienta para modelar la operación de un sistema a través de una secuencia de eventos. Esta técnica requiere datos de entrada de alta calidad, por lo que estos datos deben ser gestionados previamente en un proceso complejo de preparación conocido como Input Data Management (IDM). El objetivo del presente estudio es determinar cómo automatizar eficientemente el proceso de IDM requerido para los modelos DES que atacan el problema de overcrowding en salas de emergencia de hospitales y clínicas, de manera que se pueda validar la calidad de datos, reproducir y versionar los datos de entrada para un modelo DES, garantizando la seguridad y la disponibilidad de la información de los usuarios. Para abordar este problema fue necesario realizar un caso de estudio con datos reales para contextualizar el problema y evaluar los métodos estadísticos requeridos, así como realizar un ejercicio de comparación de características de las herramientas actuales para establecer las brechas entre las funcionalidades ofrecidas y las requeridas en este contexto. A partir de estos resultados, se planteó y desarrolló un prototipo que permitió satisfacer los requerimientos identificados mediante una aplicación web basada en una arquitectura cloud que da respuesta al problema planteado.Emergency rooms are spaces prone to congestion due to the high number of patients. This problem, known as overcrowding, has negative effects on patient waiting time. One of the alternatives to mitigate such effects is to analyze patient flow using Discrete Event Simulation (DES), which is a powerful tool to model the operation of a system through a sequence of events. This technique requires high-quality input data, so this data must be previously managed in a complex preparation process known as Input Data Management (IDM). The objective of the present study is to determine how to efficiently automate the IDM process required for DES models that tackle the problem of overcrowding in hospital and clinic emergency rooms in order to validate data quality, reproduce and version the input data for a DES model, guaranteeing the security and availability of user information. To address this problem, it was necessary to conduct a case study with real data to contextualize the problem and evaluate the required statistical methods, as well as to perform a comparison exercise of the characteristics of the current tools to establish the gaps between the functionalities offered and those required in this context. Based on these results, a prototype was designed and developed to satisfy the requirements identified through a web application based on a cloud architecture that responds to the problem posed.Magíster en Ingeniería de SoftwareMaestría99 hojasapplication/pdfengUniversidad de los AndesMaestría en Ingeniería de SoftwareFacultad de IngenieríaDepartamento de Ingeniería de Sistemas y ComputaciónTowards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department contextTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesishttp://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/TMInput Data ManagementDiscrete events simulationStochastic processesServicios médicos de urgenciasPacientes de hospitalesMétodos de simulaciónSimulación por computadores digitalesAplicaciones WebComputación en la nubeIngenieríaT. Anderson and L. Goodman, "Statistical inference about markov chains," The Annals of Mathematical Statistics, vol. 28, 03 1957.C. Duguay and F. Chetouane, "Modeling and Improving Emergency Department Systems using Discrete Event Simulation," Simulation, vol. 83, no. 4, pp. 311-320, 2007.A. Komashie and A. Mousavi, "Modeling emergency departments using discrete event simulation techniques," Proceedings - Winter Simulation Conference, vol. 2005, pp. 2681-2685, 2005C. M. Rodriguez, "Evaluation of the DESI interface for discrete event simulation input data management automation," International Journal of Modelling and Simulation, vol. 35, no. 1, pp. 13-18, 2015.A. Skoogh and B. Johansson, "A methodology for input data management in discrete event simulation projects," in 2008 Winter Simulation Conference, 2008, pp. 1727-1735.N. Robertson and T. Perera, "Automated data collection for simulation" Simulation Practice and Theory, vol. 9, no. 6-8, pp. 349-364, 2002.A. Skoogh, B. Johansson, and J. Stahre, "Automated input data management: Evaluation of a concept for reduced time consumption in discrete event simulation," Simulation, vol. 88, no. 11, pp. 1279-1293, 2012.P. Barlas and C. Heavey, "Automation of input data to discrete event simulation for manufacturing: A review," International Journal of Modeling, Simulation, and Scientific Computing, vol. 7, no. 1, 2016.A. Skoogh, J. Michaloski, and N. Bengtsson, "Towards continuously updated simulation models: Combining automated raw data collection and automated data processing," 01 2011, pp. 1678-1689.C. Rodriguez, "An integrated framework for automated data collection and processing for discrete event simulation models," Ph.D. dissertation, Electronic Theses and Dissertations, 2004-2019., 2015.P. Barlas and C. Heavey, "Ke tool: An open source software for automated input data in discrete event simulation projects," 12 2016, pp. 472-483.Centeno, Giachetti, Linn, and Ismail, "A simulation-ilp based tool for scheduling er sta," in Proceedings of the 2003 Winter Simulation Conference, 2003., vol. 2, 2003, pp. 1930-1938 vol.2.K. Ghanes, O. Jouini, Z. Jemai, M. Wargon, R. Hellmann, V. Thomas, and G. Koole, "A comprehensive simulation modeling of an emergency department: A case study for simulation optimization of staing levels," Proceedings - Winter Simulation Conference, vol. 2015-Janua, pp. 1421-1432, 2015.S. M. Mahdi Seyed Ghafouri and B. Haji, "Utilizing a simulation approach for analysis of patient ow in the emergency department: A case study," in 2019 15th Iran International Industrial Engineering Conference (IIIEC), 2019, pp. 151-157.S. Samaha, W. S. Armel, and D. W. Starks, "The use of simulation to reduce the length of stay in an emergency department," Winter Simulation Conference Proceedings, vol. 2, pp. 1907-1911, 2003.O. G. Batarseh, E. J. Goldlust, and T. E. Day, "SysML for conceptual modeling and simulation for analysis: A case example of a highly granular model of an emergency department," Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013, pp. 2398-2409, 2013.A. Aroua and G. Abdulnour, "Optimization of the emergency department in hospitals using simulation and experimental design: Case study," Procedia Manufacturing, vol. 17, no. Mdc, pp. 878-885, 2018.S. Levin and M. Garifullin, "Simulating wait time in healthcare: Accounting for transition process variability using survival analyses," Proceedings - Winter Simulation Conference, vol. 2016-Febru, pp. 1252-1260, 2016.Y. H. Kuo, J. M. Leung, and C. A. Graham, "Simulation with data scarcity: Developing a simulation model of a hospital emergency department," Proceedings - Winter Simulation Conference, 2012.S. A. Paul, M. C. Reddy, and C. J. Deitch, "A systematic review of simulation studies investigating emergency department overcrowding," Simulation, vol. 86, no. 8-9, pp. 559-571, 2010.S. Saghafian, G. Austin, and S. J. Traub, "Operations research/management contributions to emergency department patient flow optimization: Review and research prospects," IIE Transactions on Healthcare Systems Engineering, vol. 5, no. 2, pp. 101- 123, 2015.H. Salmon, S. Rachuba, S. Briscoe, and M. Pitt, "A structured literature review of simulation modeling applied to emergency departments: Current patterns and emerging trends," Operations Research for Health Care, vol. 19, 01 2018.J. Jihene, A. El Mhamedi, and H. Chabchoub, "Simulationmodel of emergency department," Proceedings - ICSSSM'07: 2007 International Conference on Service Systems and Service Management, pp. 7-11, 2007.J. Bokrantz, A. Skoogh, D. L amkull, A. Hanna, and T. Perera, "Data quality problems in discrete event simulation of manufacturing operations," Simulation, vol. 94, no. 11, pp. 1009-1025, 2018.N. Robertson and T. Perera, "Feasibility for automatic data collection," in Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304), vol. 2, 2001, pp. 984-990 vol.2.N. Furian, D. Neubacher, M. O'Sullivan, C. Walker, and C. Pizzera, "GEDMod Towards a generic toolkit for emergency department modeling," Simulation Modelling Practice and Theory, vol. 87, no. July, pp. 239{273, 2018. [Online]. Available: https://doi.org/10.1016/j.simpat.2018.07.010Y.-T. Lee, F. Riddick, and B. 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Towards a cloud-based web application for automated input data management for discrete event simulation models in an emergency department context

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