Real-time ambulance redeployment approach to improve service coverage with fair and restricted workload for EMS providers

Emergency Medical Services (EMS) managers are concerned with providing maximum possible coverage in their service area. As emergency calls arrive into the EMS system, some ambulances become unavailable. Redeployment deals with a dynamic relocation of available ambulances so as to compensate for the loss in coverage due to busy ambulances. Unsystematic redeployment can impose superfluous workload and result in unnecessary fatigue for EMS personnel. This paper develops a real-time approach to maximize coverage with minimum possible total travel time, considering accumulated workload restrictions for personnel in a shift. While in the past real-time redeployment has been hindered due to computational issues, we find a solution to this problem by combining two computationally inexpensive models into a single framework. The proposed approach requires only knowledge of the current state of the system in a real-time manner and, due to very short run time, is applicable in practice. The performance of our real-time approach is evaluated by a discrete-event simulation developed for a large real dataset and is compared with two benchmarks in the literature; an existing dynamic redeployment approach and a static policy. The results show statistically significant improvement in average coverage, while restricting accumulated workload for EMS personnel as well as providing more evenly distributed workload between ambulances in a shift.

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

[2]  Cem Saydam,et al.  The dynamic redeployment coverage location model , 2013 .

[3]  S. Bhulai,et al.  A dynamic ambulance management model for rural areas , 2017, Health care management science.

[4]  Yun Yuan,et al.  A Chance Constrained Programming Model for Reliable Emergency Vehicles Relocation Problem , 2013 .

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

[6]  C. J. Jagtenberg,et al.  Dynamic ambulance dispatching: is the closest-idle policy always optimal? , 2017, Health care management science.

[7]  Sandjai Bhulai,et al.  An efficient heuristic for real-time ambulance redeployment , 2015 .

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

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

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

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

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

[13]  Maria E. Mayorga,et al.  A nested-compliance table policy for emergency medical service systems under relocation , 2016 .

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

[15]  Lara Wiesche,et al.  Time-dependent ambulance allocation considering data-driven empirically required coverage , 2015, Health care management science.

[16]  Bülent Çatay,et al.  A taxonomy for emergency service station location problem , 2012, Optim. Lett..

[17]  Reinaldo Morabito,et al.  Emergency service systems: The use of the hypercube queueing model in the solution of probabilistic location problems , 2008, Int. Trans. Oper. Res..

[18]  Joseph S. Pliskin,et al.  A geographic information system simulation model of EMS: reducing ambulance response time. , 2004, The American journal of emergency medicine.

[19]  B. Williams,et al.  The Exploration of Physical Fatigue, Sleep and Depression in Paramedics: A Pilot Study , 2011 .

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

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

[22]  Tonguç Ünlüyurt,et al.  Estimating the performance of emergency medical service location models via discrete event simulation , 2016, Comput. Ind. Eng..

[23]  Xiaoyan Zhu,et al.  Covering models and optimization techniques for emergency response facility location and planning: a review , 2011, Math. Methods Oper. Res..

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

[25]  Angel B. Ruiz,et al.  An empirical comparison of relocation strategies in real-time ambulance fleet management , 2016, Comput. Ind. Eng..

[26]  Michael Ragone,et al.  Are we ready for the future? Where EMS stands now & where it's prepared to go. , 2011, JEMS : a journal of emergency medical services.

[27]  J. Studnek,et al.  Factors associated with back problems among emergency medical technicians. , 2007, American journal of industrial medicine.

[28]  Maria E. Mayorga,et al.  Joint location and dispatching decisions for Emergency Medical Services , 2013, Comput. Ind. Eng..

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

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

[31]  M. E. Bruni,et al.  Emergency medical services and beyond: Addressing new challenges through a wide literature review , 2017, Comput. Oper. Res..

[32]  Bülent Çatay,et al.  A multi-period double coverage approach for locating the emergency medical service stations in Istanbul , 2011, J. Oper. Res. Soc..

[33]  Susan R. Hunter,et al.  A Bound on the Performance of an Optimal Ambulance Redeployment Policy , 2014, Oper. Res..

[34]  Pieter L. van den Berg,et al.  Time-dependent MEXCLP with start-up and relocation cost , 2015, Eur. J. Oper. Res..

[35]  Mohammad Hossein Fazel Zarandi,et al.  The large-scale dynamic maximal covering location problem , 2013, Math. Comput. Model..

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

[37]  Sandjai Bhulai,et al.  The effect of ambulance relocations on the performance of ambulance service providers , 2016, Eur. J. Oper. Res..

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

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