Elsevier

Computers & Operations Research

Volume 78, February 2017, Pages 349-368
Computers & Operations Research

Review
Emergency medical services and beyond: Addressing new challenges through a wide literature review

https://doi.org/10.1016/j.cor.2016.09.016Get rights and content

Abstract

One of the most important health care services is emergency medical service as it plays a vital role in saving people's lives and reducing the rate of mortality and morbidity. Over the last years, many review papers have discussed emergency medical services (EMS) location problems, however, only few review papers consider the full range of EMS systems. This review paper tries to fill this gap. Our review introduces the concept of emergency care pathway following the current trend in health care systems, i.e., shifting the central role from health care providers to patients. Considering the emergency care pathway, we provide a broad literature review and analysis in order to identify emerging challenges for future research.

Introduction

Emergency medical service is one of the most important health care services as it plays a vital role in saving people's lives and reducing the rate of mortality and morbidity. The importance and sensitivity of decision making in the emergency medical services (EMS) field have been recognized by operations research scientists, EMS planners, and health care practitioners who studied many problems arising in the management of EMS systems since the 1960s.

Locating EMS vehicles has been widely studied as is shown by numerous review papers that appeared over the last years. One of the first review papers that addressed EMS location models is the paper of ReVelle et al. [1]. Brotcorne et al. [2] presented a review paper on ambulance location and relocation problems, and classified the existing models in three main groups: static and deterministic models, probabilistic models, and dynamic models. Goldberg [3] surveyed operations research models for the deployment of EMS vehicles while focusing on modeling aspects and problems assumptions. In these review papers, challenges posed by real world applications, potentials gaps in the literature, and new trends have been addressed.

In a recent review paper, [4] studied papers addressing different types of covering models for EMS planning (set covering, maximal covering, maximum expected covering, maximum availability, gradual coverage, and cooperative coverage), hypercube queuing models, and dynamic allocation and relocation models. They also discussed the solution methods used for solving the aforementioned models. Finally, Baser et al. [5] presented a taxonomic framework for the EMS location problem. Considering 84 papers published in major journals, they developed their classification based on three major features including problem type, modeling, and methodologies. For the problem type, they divided the models into four general groups based on the type of emergency, model structure (deterministic or stochastic), variation in time (static or dynamic), and the number of objectives. For the modeling, they considered five major sub-classes of models differing in the definition of the objective function, the parameters involved and the mathematical programming type (integer, non-linear, dynamic programming, etc.). They categorized the methodologies into exact solution methods, heuristics, metaheuristics, and simulation.

Amongst the review papers on EMS systems, there are only a few review papers that have a broader view on the management of an EMS system. Green and Kolesar [6] surveyed the role of operations research and management science in improving emergency responsiveness over time, which lead to new policies and practices. They also studied the relationship between historical events (terrorism attacks) and the evolution of emergency response models and methods. Henderson [7] presented a discussion on challenges in EMS, highlighting the role of system-status management (redeployment strategies) in improving EMS systems. Finally, Ingolfsson [8] surveyed research on planning and management for EMS, emphasizing four topics: (i) demand forecasting, response times, and workload; (ii) measuring performance; (iii) choosing station locations; and (iv) allocating ambulances to stations based on predictable and unpredictable changes in demand and travel times.

In EMS studies, an important question that should be addressed is whether the current direction of research is consistent with the main aims in EMS systems. As Sorensen and Church [9, p. 9] mentioned “the recent EMS location literature has diverged, at least to some extent, from the goals of many EMS agencies”. A possible explanation for this divergence could be the difficulty of modeling the increasingly complex system that EMS has become over time. In order to manage an EMS system, relevant data should be forecasted, complex situations should be modeled, efficient solution methods should be designed, and accurate dispatching policies should be implemented. The main purpose of this review is to account for such a complexity through a broad literature review in order to address new challenges. This will indicate relevant research opportunities for researchers in this field and will show practitioners how EMS systems can benefit from this research.

The structure of our review is based on the concept of emergency care pathway (ECP). In doing so, we follow the current trend in health care systems, i.e., shifting the central role from health care providers to patients. The main concept of clinical pathways (CPs) in health care systems shifts the attention from single departments to the entire health care chain, which increases patient's safety and satisfaction, and optimizes the use of resources. Campbell et al. [10] defines the CPs as “health-care structured multidisciplinary plans that describe spatial and temporal sequences of activities to be performed, based on the scientific and technical knowledge and the organizational, professional and technological available resources”.

In EMS management, many decision problems are connected to each other. Therefore, decisions taken in one step of the ECP can affect decisions in subsequent steps of the ECP. An example of such a decision is the relationship between Emergency Department (ED) overcrowding and ambulance diversion, as discussed in Section 5.1.

Fig. 1 depicts a possible ECP composed of five main steps and its relationships with related management and organizational problems. The ECP starts when the EMS receives an emergency request. After determining the urgency of the incident, an ambulance is dispatched. The ambulance should reach the emergency scene as soon as possible to provide first-aid and to transport the patient to the ED of a hospital. Once the patient is discharged from the hospital, the ECP finishes.

Some of the problems highlighted in Fig. 1 have already been introduced above, such as the ambulance location and relocation problems. In addition, ambulance fleet management should also decide upon a dispatching policy and routing of the vehicles. The next problem in line is the interplay with the National Health Service (NHS). EMS can be viewed as an entry point of NHS which contributes to ED overcrowding. In turn, overcrowding influences the throughput of the ECP and the outcome of patients in the ECP. Therefore, the interplay with the NHS system is a problem that should be addressed.

One of the prerequisites to guarantee an efficient and fair management of the entire ECP is a good forecast of, for example, emergency demand, travel time and workload. These forecasts are needed to ensure that enough resources are available to fulfil the emergency demand. These resources consist of, for example, EMS vehicles, paramedics and medical doctors. Composing sufficient workforces and determining proper rosters is essential to deliver high quality health care.

In order to determine whether the care provided for the entire ECP is good enough in terms of efficiency, effectiveness, and fairness, evaluation metrics are needed. For ambulance location problems, several metrics in terms of coverage and response times exists as described in Section 2, however, evaluation of the entire ECP is also needed. Related to this is the validation of the model outcomes resulting from simplifying assumptions in the modeling phase.

Following the lines depicted in Fig. 1, the review is organized as follows. Section 2 is devoted to the analysis of ambulance location problems and classifies the existing literature on two key concepts with respect to the analysis of an ECP, namely equity and uncertainty. Section 3 provides an overview of ambulance relocation models. Section 4 is devoted to the analysis of dispatching and routing policies. In Section 5, we investigate the complex interplay between the EMS system and other components of the NHS, and in particular with other emergency health care delivery systems. The literature concerning the evaluation and validation of an EMS system is surveyed in Section 6. Forecasting techniques to determine demand, travel time and workload of an EMS are reviewed in Section 7. Workforce management with respect to forecasted demand is reviewed in Section 8. Finally, Section 9 provides a discussion on the main challenges that EMS systems should face in the future.

Section snippets

Location of ambulances

The majority of operations research studies in the field of EMS focus on the issue of designing comprehensive EMS systems in which early response to emergency calls is provided. This critical challenge reveals the outstanding role of locational decision making in EMS. This has resulted in the provision of a rich and vast literature on location problems in EMS, providing a wide variety of models, solution methods, and real case studies.

Interestingly, as a by-product, the progress in location

Relocation of ambulances

Most existing models in the EMS literature belong to the class of static strategic problems in which long-term and mid-term decisions are taken for establishing base stations, assigning EMS vehicles to base stations, and determining the fleet size. Unlike other applications of location models, EMS location models must include relocating EMS vehicles to deal with variations in demand. In this setting, the repositioning of idle EMS vehicles to back-up busy EMS vehicles (also called redeployment)

Dispatching and routing policies

Important real-time operational problems in EMS management are dispatching and routing. Dispatching is the act of choosing appropriate EMS vehicles to respond to emergency calls based on the nature and location of calls. Routing decisions are concerned with defining the exact route that a dispatched ambulance should follow to reach a patient.

Interplay with other emergency health care delivery systems

The EMS can be viewed as an entry point of the National Health Service (NHS), which plays a fundamental role in the delivery of emergency care. As a consequence, it is important to investigate the interplay of the EMS system with other components of the emergency care system since the performance of the EMS system can be affected by any of them. In this section, we consider three components that are important in the ECP, namely the EDs, the location of static emergency devices, and the care

Evaluation and validation

The evaluation of the performance of EMS systems should be based on practical performance measures such as health outcomes. By developing a unitary evaluation framework, different ECPs can be compared. Such an evaluation framework can also provide insight in the effect of simplifying assumptions on the accuracy of the model when applied in practice [6]. In this section, we consider ways to evaluate EMS systems, to validate models and to determine the accuracy of solutions obtained by the models.

Forecasting

Usually, EMS systems can provide huge amounts of data to be used for forecasting since they are obliged to collect data for each call and EMS vehicle. The collected data usually contains information on the time a call is received, answered and finished, the location of the incident, the outcome of the triage evaluation, etc. For the EMS vehicles, the collected data contains information on the time of dispatching, arrival at the scene, departure from the scene, arrival at the hospital, etc. The

Workforce management

Workforce management is closely related to personnel scheduling and rostering (see, e.g., [168], [169]). In healthcare, the nurse scheduling problem is probably the most studied problem in the field of workforce management (see review of [170]). Even though many models have been published in this field, the application of these models in practice is limited as argued by [171]. However, there are only a few papers that consider workforce management in the field of EMS systems.

Bradbeer et al.

Big EMS, big data, big challenge

In the previous sections, many challenges were highlighted such as those arising when dealing with the problem of incorporating equity and uncertainty aspects, the need for reliable forecasts and new methodological hybridizations.

In our opinion, the biggest challenge is to adopt a holistic outcome-based approach for the ECP, which should be conceived as a methodology that details all decisions, treatments, and reports related to a patient. From this point of view, one of the main difficulties

Acknowledgments

The authors would like to thank the numerous colleagues who suggested useful references. In particular, we would like to thank Rosa Meo for helping us in identifying the link between data mining techniques and EMS forecasts, Vito “Franco” Fragnelli for his useful suggestions in the field of game theory, Derya Demirtas for introducing the authors to the AED location problem and Angela Testi and Elena Tànfani for introducing the authors to the Health Technology Assessment. Further, the authors

Glossary

ALS
advanced life support
ABS
agent-based simulation
ADP
approximate dynamic programming
AED
automated external defibrillator
BLS
basic life support
CP
clinical pathway
DES
discrete event simulation
DSM
double standard model
DDSMt
dynamic DSM at time t
ECDS
emergency care delivery system
ECP
emergency care pathway
ED
emergency department
ELS
emergency life support
EMS
emergency medical service
EED
European Emergency Data Project
FGP
fuzzy goal programming
GIS
geographical information system
GPS
global positioning system
HTA
Health

References (190)

  • R.A. Takeda et al.

    Analysis of ambulance decentralization in an urban emergency medical service using the hypercube queueing model

    Comput Oper Res

    (2007)
  • A.P. Iannoni et al.

    An optimization approach for ambulance location and the districting of the response segments on highways

    Eur J Oper Res

    (2009)
  • A. Shariat-Mohaymany et al.

    Linear upper-bound unavailability set covering models for locating ambulancesapplication to Tehran rural roads

    Eur J Oper Res

    (2012)
  • V. Marianov et al.

    The queueing maximal availability location problema model for the siting of emergency vehicles

    Eur J Oper Res

    (1996)
  • R. Church et al.

    The maximal covering location problem

    Pap Reg Sci Assoc

    (1974)
  • P. Beraldi et al.

    Designing robust emergency medical service via stochastic programming

    Eur J Oper Res

    (2004)
  • P. Beraldi et al.

    A probabilistic model applied to emergency service vehicle location

    Eur J Oper Res

    (2009)
  • Z.-H. Zhang et al.

    A robust counterpart approach to the bi-objective emergency medical service design problem

    Appl Math Model

    (2014)
  • C. Araz et al.

    A fuzzy multi-objective covering-based vehicle location model for emergency services

    Comput Oper Res

    (2007)
  • M. Gendreau et al.

    Solving an ambulance location model by tabu search

    Locat Sci

    (1997)
  • M. Gendreau et al.

    A dynamic model and parallel tabu search heuristic for real-time ambulance relocation

    Parallel Comput

    (2001)
  • V. Schmid et al.

    Ambulance location and relocation problems with time-dependent travel times

    Eur J Oper Res

    (2010)
  • C.J. Jagtenberg et al.

    An efficient heuristic for real-time ambulance redeployment

    Oper Res Health Care

    (2015)
  • P.L. van den Berg et al.

    Time-dependent MEXCLP with start-up and relocation cost

    Eur J Oper Res

    (2015)
  • J. Naoum-Sawaya et al.

    A stochastic optimization model for real-time ambulance redeployment

    Comput Oper Res

    (2013)
  • H.K. Rajagopalan et al.

    A multiperiod set covering location model for dynamic redeployment of ambulances

    Comput Oper Res

    (2008)
  • V. Marianov et al.

    The queueing probabilistic location set covering problem and some extensions

    Socio-Econ Plan Sci

    (1994)
  • V. Schmid

    Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming

    Eur J Oper Res

    (2012)
  • V. Bélanger et al.

    An empirical comparison of relocation strategies in real-time ambulance fleet management

    Comput Ind Eng

    (2016)
  • S. Lee

    The role of centrality in ambulance dispatching

    Decis Supp Syst

    (2012)
  • M. Zarkeshzadeh et al.

    A novel hybrid method for improving ambulance dispatching response time through a simulation study

    Simul Model Pract Theory

    (2016)
  • A. Jotshi et al.

    Dispatching and routing of emergency vehicles in disaster mitigation using data fusion

    Socio-Econ Plann Sci

    (2009)
  • L. Talarico et al.

    Ambulance routing for disaster response with patient groups

    Comput Oper Res

    (2015)
  • C. ReVelle et al.

    Facility locationa review of context-free and EMS models

    Health Serv Res

    (1977)
  • J.B. Goldberg

    Operations research models for the deployment of emergency services vehicles

    EMS Manag J

    (2004)
  • X. Li et al.

    Covering models and optimization techniques for emergency response facility location and planninga review

    Math Methods Oper Res

    (2011)
  • A. Basar et al.

    A taxonomy for emergency service station location problem

    Optim Lett

    (2012)
  • L.V. Green et al.

    Improving emergency responsiveness with management science

    Manag Sci

    (2004)
  • Henderson SG. Wiley Encyclopedia of operations research and management science. In: Operations research tools for...
  • Ingolfsson A. EMS planning and management. In: Operations research and health care policy. International series in...
  • H.H.R. Campbell et al.

    Integrated care pathways

    Br Med J

    (1998)
  • L.A. McLay et al.

    Evaluating emergency medical service performance measures

    Health Care Manag Sci

    (2010)
  • E. Erkut et al.

    Ambulance location for maximum survival

    Nav Res Logist

    (2008)
  • H.K. Smith et al.

    Bicriteria efficiency/equity hierarchical location models for public service application

    J Oper Res Soc

    (2013)
  • S. Khodaparasti et al.

    Balancing efficiency and equity in location-allocation models with an application to strategic EMS design

    Optim Lett

    (2016)
  • S. Chanta et al.

    Improving emergency service in rural areasa bi-objective covering location model for EMS systems

    Ann Oper Res

    (2014)
  • K. Miettinen

    Nonlinear multiobjective optimization

    (1999)
  • S. Chanta et al.

    The minimum p-envy location problema new model for equitable distribution of emergency resources

    IIE Trans Healthc Syst Eng

    (2011)
  • M.S. Daskin

    Network and discrete location: models, algorithms, and applications

    (1995)
  • S.A. Broverman

    Actex study manual, course 1, examination of the society of actuaries, exam 1 of the casualty actuarial society

    (2001)
  • Cited by (0)

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