A generic method to develop simulation models for ambulance systems

Abstract In this paper, we address the question of generic simulation models and their role in improving emergency care around the world. After reviewing the development of ambulance models and the contexts in which they have been applied, we report the construction of a reusable model for ambulance systems. Further, we describe the associated parameters, data sources, and performance measures, and report on the collection of information, as well as the use of optimisation to configure the service to best effect. Having developed the model, we have validated it using real data from the emergency medical system in a Brazilian city, Belo Horizonte. To illustrate the benefits of standardisation and reusability we apply the model to a UK context by exploring how different rules of engagement would change the performance of the system. Finally, we consider the impact that one might observe if such rules were adopted by the Brazilian system.

[1]  Takehiro Furuta,et al.  Hypercube simulation analysis for a large-scale ambulance service system , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[2]  Rosbi Mamat,et al.  Impact of Ambulance Dispatch Policies on Performance of Emergency Medical Services , 2011, IEEE Transactions on Intelligent Transportation Systems.

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

[4]  R. Vukmir,et al.  Survival from prehospital cardiac arrest is critically dependent upon response time. , 2006, Resuscitation.

[5]  Chih-Hao Lin,et al.  Managing emergency department overcrowding via ambulance diversion: a discrete event simulation model. , 2015, Journal of the Formosan Medical Association = Taiwan yi zhi.

[6]  K. Siddharthan,et al.  A priority queuing model to reduce waiting times in emergency care. , 1996, International journal of health care quality assurance.

[7]  Michael C. Fu,et al.  Feature Article: Optimization for simulation: Theory vs. Practice , 2002, INFORMS J. Comput..

[8]  Reinaldo Morabito,et al.  A multiple dispatch and partial backup hypercube queuing model to analyze emergency medical systems on highways , 2007 .

[9]  Roberto Berchi,et al.  A five steps methodology for ambulance planning , 2010, 2010 IEEE Workshop on Health Care Management (WHCM).

[10]  Luiz Ricardo Pinto,et al.  Emergency medical systems analysis by simulation and optimization , 2010, Proceedings of the 2010 Winter Simulation Conference.

[11]  Patricio Donoso,et al.  Assessing an ambulance service with queuing theory , 2008, Comput. Oper. Res..

[12]  W Falk,et al.  A study of waiting time in an emergency department. , 1973, Canadian Medical Association journal.

[13]  Mathew W. McLean,et al.  Forecasting emergency medical service call arrival rates , 2011, 1107.4919.

[14]  Kevin P. Hwang,et al.  Using a discrete-event simulation to balance ambulance availability and demand in static deployment systems. , 2009, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[15]  John W. Fowler,et al.  Optimal control policies for ambulance diversion , 2014, Eur. J. Oper. Res..

[16]  Reinaldo Morabito,et al.  Analysis of ambulance decentralization in an urban emergency medical service using the hypercube queueing model , 2007, Comput. Oper. Res..

[17]  Paul R. Harper,et al.  Simulation in health-care: lessons from other sectors , 2012, Oper. Res..

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

[19]  P. Pons,et al.  Paramedic response time: does it affect patient survival? , 2005, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[20]  Michael Pidd,et al.  Discrete event simulation for performance modelling in health care: a review of the literature , 2010, J. Simulation.

[21]  Takehiro Furuta,et al.  Optimization model and simulation for improving ambulance service system , 2013 .

[22]  Sascha Ossowski,et al.  Dynamic coordination of ambulances for emergency medical assistance services , 2014, Knowl. Based Syst..

[23]  Laura A McLay,et al.  Evaluating emergency medical service performance measures , 2010, Health care management science.

[24]  John W. Fowler,et al.  Design of centralized Ambulance Diversion policies using Simulation-Optimization , 2011, Proceedings of the 2011 Winter Simulation Conference (WSC).

[25]  T. Kirsch,et al.  The effects of ambulance diversion: a comprehensive review. , 2006, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[26]  Rocío Sánchez-Mangas,et al.  The probability of death in road traffic accidents. How important is a quick medical response? , 2010, Accident; analysis and prevention.

[27]  Ray J. Paul,et al.  Can health care benefit from modeling and simulation methods in the same way as business and manufacturing has? , 2007, 2007 Winter Simulation Conference.

[28]  O. Koch,et al.  Modeling ambulance service of the Austrian Red Cross , 2003, Proceedings of the 2003 Winter Simulation Conference, 2003..

[29]  Terry Young,et al.  Three critical challenges for modeling and simulation in healthcare , 2009, Proceedings of the 2009 Winter Simulation Conference (WSC).

[30]  Reinaldo Morabito,et al.  Non-homogeneous servers in emergency medical systems: Practical applications using the hypercube queueing model , 2008 .

[31]  Tillal Eldabi,et al.  Proceedings of the 2007 Winter Simulation Conference , 2007 .

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

[33]  Marcus Eng Hock Ong,et al.  Geographical variation in ambulance calls is associated with socioeconomic status. , 2012, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[34]  James A. Fitzsimmons,et al.  An emergency medical system simulation model , 1971, WSC '71.

[35]  John W. Fowler,et al.  Comparison of ambulance diversion policies via simulation , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[36]  Roberto Aringhieri An integrated DE and AB simulation model for EMS management , 2010, 2010 IEEE Workshop on Health Care Management (WHCM).

[37]  Matthew S. Maxwell,et al.  Approximate Dynamic Programming for Ambulance Redeployment , 2010, INFORMS J. Comput..

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

[39]  Karl F. Doerner,et al.  Ambulance location and relocation problems with time-dependent travel times , 2010, Eur. J. Oper. Res..

[40]  Zied Jemaï,et al.  A simulation study to improve the performance of an emergency medical service: Application to the French Val-de-Marne department , 2014, Simul. Model. Pract. Theory.

[41]  Syi Su,et al.  Modeling an emergency medical services system using computer simulation , 2003, Int. J. Medical Informatics.

[42]  John W. Fowler,et al.  Bi-criteria analysis of ambulance diversion policies , 2010, Proceedings of the 2010 Winter Simulation Conference.

[43]  Shane G. Henderson,et al.  Estimating ambulance requirements in Auckland, New Zealand , 1999, WSC '99.

[44]  Reinaldo Morabito,et al.  An optimization approach for ambulance location and the districting of the response segments on highways , 2009, Eur. J. Oper. Res..

[45]  David E. Allen,et al.  Optimal planning of an emergency ambulance service , 1969 .

[46]  J A Fitzsimmons,et al.  Establishing the level of service for public emergency ambulance systems. , 1979, Socio-economic planning sciences.

[47]  Mohammad Mehdi Sepehri,et al.  Two new models for redeployment of ambulances , 2014, Comput. Ind. Eng..

[48]  Martin Pitt,et al.  An analysis of the academic literature on simulation and modelling in health care , 2009, J. Simulation.

[49]  J. Kaufman,et al.  Response time effectiveness: comparison of response time and survival in an urban emergency medical services system. , 2002, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[50]  Qi-Ming He,et al.  A Markovian queueing model for ambulance offload delays , 2013, Eur. J. Oper. Res..

[51]  G. Bevan,et al.  "Systematic" , 1966, Comput. J..

[52]  Markus Reuber,et al.  Pre-hospital care after a seizure: Evidence base and United Kingdom management guidelines , 2015, Seizure.

[53]  Jon Nicholl,et al.  Role of ambulance response times in the survival of patients with out-of-hospital cardiac arrest , 2010, Emergency Medicine Journal.

[54]  Samir Elhedhli,et al.  A stochastic optimization model for real-time ambulance redeployment , 2013, Comput. Oper. Res..

[55]  Michael C. Fu,et al.  Optimization for Simulation: Theory vs. Practice , 2002 .