Evaluating dynamic dispatch strategies for emergency medical services: TIFAR simulation tool

In life-threatening emergency situations, the ability of emergency medical service (EMS) providers to arrive at the emergency scene within a few minutes may make the difference between survival or death. To realize such extremely short response times at affordable cost, efficient planning of EMS systems is crucial. In this article we will discuss the Testing Interface For Ambulance Research (TIFAR) simulation tool that can be used by EMS managers and researchers to evaluate the effectiveness of different dispatch strategies. The accuracy of TIFAR is assessed by comparing the TIFAR-based performance indicators against a real EMS system in the Netherlands. The results show that TIFAR performs extremely well.

[1]  Michael O. Ball,et al.  A Reliability Model Applied to Emergency Service Vehicle Location , 1993, Oper. Res..

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

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

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

[5]  Armann Ingolfsson,et al.  A Markov Chain Model for an EMS System with Repositioning , 2013 .

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

[7]  Lei Zhang,et al.  Optimisation of Small-Scale Ambulance Move-up , 2010 .

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

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

[10]  Elise Miller-Hooks,et al.  Evaluation of Relocation Strategies for Emergency Medical Service Vehicles , 2009 .

[11]  Oded Berman,et al.  Repositioning of distinguishable urban service units on networks , 1981, Comput. Oper. Res..

[12]  Richard L. Church,et al.  The Team/Fleet Models for Simultaneous Facility and Equipment Siting , 1979 .

[13]  Marvin B. Mandell,et al.  Covering models for two-tiered emergency medical services systems , 1998 .

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

[15]  Charles S. ReVelle,et al.  The Location of Emergency Service Facilities , 1971, Oper. Res..

[16]  Mateo Restrepo,et al.  Computational methods for static allocation and real-time redeployment of ambulances , 2008 .

[17]  Oded Berman,et al.  Dynamic Repositioning of Indistinguishable Service Units on Transportation Networks , 1981 .

[18]  M. Van Buuren TIFAR Modeling Package for the Evaluation of Emergency Medical Services: With EMS modeling results for the Amsterdam area , 2011 .

[19]  Charles S. ReVelle,et al.  The Maximum Availability Location Problem , 1989, Transp. Sci..

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

[21]  Mark S. Daskin,et al.  A Maximum Expected Covering Location Model: Formulation, Properties and Heuristic Solution , 1983 .

[22]  Richard L. Church,et al.  The maximal covering location problem , 1974 .

[23]  Vtv,et al.  Referentiekader spreiding en beschikbaarheid ambulancezorg 2008 , 2009 .

[24]  Tobias Andersson Granberg,et al.  Decision support tools for ambulance dispatch and relocation , 2007, J. Oper. Res. Soc..

[25]  H. N. Post,et al.  The shortest path problem on large‐scale real‐road networks , 2006, Networks.

[26]  Ilan Vertinsky,et al.  Ambulance Location: A Probabilistic Enumeration Approach , 1973 .