A generic and flexible simulation-based analysis tool for EMS management

Emergency medical services (EMS) are dedicated to provide urgent medical care to any person requiring it and to ensure their transport to a hospital or care facility, if required. Moreover, in many contexts, EMS also have to provide transportation services for patients need to go from one hospital to another or between their home and the hospital. For such organisations, efficient strategies for managing the ambulance fleet at their disposal have to be selected, but the highly random and dynamic nature of the system under study makes this a challenging task. Most of the published studies which have considered these issues have done it focusing on a specific EMS context, one city or one territory for instance. However, it is possible to identify several common characteristics and processes from one EMS context to another. This is the purpose of the generic discrete event simulation-based analysis tool proposed here, which can be adapted to a wide range of EMS contexts. In particular, it explicitly considers the two types of tasks that can compose the mission of an EMS: serving emergency requests and providing transports between care units/hospitals/patients’ homes.

[1]  E. S. Savas,et al.  Simulation and Cost-Effectiveness Analysis of New York's Emergency Ambulance Service , 1969 .

[2]  Ilan Vertinsky,et al.  A simulation-based methodology for optimization of ambulance service policies , 1973 .

[3]  Geoffrey N. Berlin,et al.  Mathematical analysis of emergency ambulance location , 1974 .

[4]  G. Shedler,et al.  Simulation of Nonhomogeneous Poisson Processes by Thinning , 1979 .

[5]  Michael Pidd,et al.  Computer Simulation in Management Science (3rd Edition) , 1998 .

[6]  Charles ReVelle,et al.  Concepts and applications of backup coverage , 1986 .

[7]  Kapil Kumar Gupta,et al.  Ambulance deployment analysis: A case study of Bangkok , 1987 .

[8]  Marek Lubicz,et al.  Simulation modelling of emergency medical services , 1987 .

[9]  Jui-Tine Lee,et al.  A Simulation Of A Hospital Emergency Call System Using SLAMII , 1988, Simul..

[10]  Charles ReVelle,et al.  Review, extension and prediction in emergency service siting models , 1989 .

[11]  P. Trudeau,et al.  AN OPERATIONS RESEARCH APPROACH FOR THE PLANNING AND OPERATION OF AN AMBULANCE SERVICE , 1989 .

[12]  J. Goldberg,et al.  A simulation model for evaluating a set of emergency vehicle base locations: development, validation, and usage. , 1990, Socio-economic planning sciences.

[13]  Jack P. C. Kleijnen,et al.  EUROPEAN JOURNAL OF OPERATIONAL , 1992 .

[14]  John J. Bernardo,et al.  Developing and validating a decision support system for locating emergency medical vehicles in Louisville, Kentucky , 1994 .

[15]  Vladimir Marianov,et al.  Siting Emergency Services , 1995 .

[16]  Gilbert Laporte,et al.  Solving an ambulance location model by tabu search , 1997 .

[17]  Michel Gendreau,et al.  A dynamic model and parallel tabu search heuristic for real-time ambulance relocation , 2001, Parallel Comput..

[18]  S I Harewood,et al.  Emergency ambulance deployment in Barbados: a multi-objective approach , 2002, J. Oper. Res. Soc..

[19]  Erhan Erkut,et al.  Simulation of single start station for Edmonton EMS , 2003, J. Oper. Res. Soc..

[20]  Gilbert Laporte,et al.  Ambulance location and relocation models , 2000, Eur. J. Oper. Res..

[21]  J. Goldberg.  Operations Research Models for the Deployment of Emergency Services Vehicles , 2004 .

[22]  Peter Värbrand,et al.  Decision support for efficient ambulance logistics , 2005 .

[23]  Shane G. Henderson,et al.  Ambulance Service Planning: Simulation and Data Visualisation , 2005 .

[24]  Michel Gendreau,et al.  The maximal expected coverage relocation problem for emergency vehicles , 2006, J. Oper. Res. Soc..

[25]  Guillaume Carpentier,et al.  La conception et la gestion d'un réseau de service ambulancier , 2007 .

[26]  Tayfur Altiok,et al.  Simulation Modeling and Analysis with ARENA , 2007 .

[27]  Cem Saydam,et al.  A multiperiod set covering location model for dynamic redeployment of ambulances , 2008, Comput. Oper. Res..

[28]  Michel Gendreau,et al.  Waiting Strategies for Regular and Emergency Patient Transportation , 2009 .

[29]  Thomas Hanne,et al.  Bringing Robustness to Patient Flow Management Through Optimized Patient Transports in Hospitals , 2009, Interfaces.

[30]  Gilbert Laporte,et al.  Dynamic transportation of patients in hospitals , 2010, OR Spectr..

[31]  Jean-Charles Billaut,et al.  A tabu search heuristic for the dynamic transportation of patients between care units , 2011, Eur. J. Oper. Res..

[32]  Sophie N. Parragh.  Introducing heterogeneous users and vehicles into models and algorithms for the dial-a-ride problem , 2011, Transportation research. Part C, Emerging technologies.

[33]  Verena Schmid,et al.  Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming , 2012, Eur. J. Oper. Res..

[34]  Angel B. Ruiz,et al.  Déploiement et Redéploiement des Véhicules Ambulanciers dans la Gestion d'un Service Préhospitalier d'Urgence , 2012, INFOR Inf. Syst. Oper. Res..

[35]  Zied Jemaï,et al.  A review on simulation models applied to emergency medical service operations , 2013, Comput. Ind. Eng..

[36]  Andrew Mason,et al.  Simulation and Real-Time Optimised Relocation for Improving Ambulance Operations , 2013 .

[37]  Armann Ingolfsson,et al.  EMS Planning and Management , 2013 .

[38]  Averill M. David Kelton Law.  Simulation modelling & analysis. , 2014 .

[39]  Lu Zhen,et al.  A simulation optimization framework for ambulance deployment and relocation problems , 2014, Comput. Ind. Eng..