Emergency Medical Services and beyond: Addressing new challenges through a wide literature review (Summary)
By investigating the work that has been done in EMS during the most recent years, the purpose of this summary is to contribute to new solutions and innovations of EMS as well as to participate in the discussion around the challenges in EMS.
Different scientists have analysed and discussed the full spectrum of EMS systems in order to identify new challenges and research gaps. Described as “the most important health care service, as it plays a vital role in saving people’s lives and reducing the rate of mortality and morbidity”1, EMS received attention already in 1960s when practitioners and EMS planners investigated the problems of the EMS management.
EMS vehicles and EMS location models have been widely investigated and researchers have been focused on ambulance location and relocation problems and categorised the different models as:
- statistic and deterministic
- probabilistic
- dynamic
The challenges related to EMS models involve the problem of incorporating equity and uncertainty aspects, the need for reliable forecasts and new methodological hybridizations. This summary will discuss some among the aforementioned challenges.
The most relevant problems and challenges identified through an in-depth literature review of the EMS location models can be summarised under the two concepts of equity and uncertainty.
The equity aspect is not only common in EMS systems but also in other fields of healthcare for the evaluations of the fairness in the allocation of the resources devoted to the patients. It is referred to the importance of ensuring lack of disparities in the mean response time of different demand zones (urban areas vs. rural areas).
As the authors of the article underline, there have been many attempts in the last few years in trying to incorporate equity in EMS systems. However, many other areas have not been deserved much attention and proper investigation.
Focus has been on different aspects of equity as well as defining equity metrics to develop equity-based models in EMS planning. The metrics used in the geographical position has been that of evaluating the quality of service in urban zones. Moreover, given the fact that EMS systems are “subject to dynamic pressures and often the actual configuration does not comply with the original design of the system”2, it is important to consider all the temporal aspects related to equity concepts.
Moreover, uncertainty is important when it comes to the EMS sector. For instance, uncertainty is related to the amount and location of demand, travel times, gravity of incidents or to the availability of emergency vehicles, as well as to many other factors, such as the length of stay at the emergency departments. Consequently, only a structured approach can play upon strategic and uncertain information. A review of the literature on this topic has focused on the occurrence of three approaches: probabilistic paradigm, stochastic programming approach, the robust counterpart and the fuzzy framework.
Without delving deeper into the analysis of different types of approaches, it is relevant to underline that each of such approaches attempt to capture uncertainty in different occurrences and each of them have their own advantages.
However, the uncertainty in EMS planning and particularly in demand, availability of EMS vehicles and response time, has been investigated and such analysis has resulted in adopting a combination of all the four aforementioned approaches which can help in building a more realistic model a complete overview of the system.
The uncertainty in the risk aversion in EMS location models has not been deeply studied yet and the authors convey in addressing the future research to this aspect. Besides, future investigations should also focus on the increasing need for developing models that can simultaneously incorporate realistic information and find solutions for all the aspects.
Dispatching and routing are operational problems related to EMS management. Dispatching is “the act of choosing appropriate EMS vehicles to respond to emergency calls based on the nature and location of calls”3. While, routing is described as the “exact route that a dispatched ambulance should follow to reach a patient”4. Both dispatching and routing should include equity adopting an emergency priority approach. How? Communication technologies will help to “to dynamically update the priority of assigned calls and to reroute EMS vehicles if necessary”5. However, as it has been demonstrated, researchers and scientists have not applied this method yet, although the practical value has been recognised. Moreover, when it comes to disaster management, decision-makers are required to handle the respond to several calls in the waiting list resulting in “drastic fluctuations in vehicle availability”6. That it is why priority-based dispatching policies must be designed for disaster responses.
The routing decisions instead, mainly depend on a better communication between the drivers and the call centre, as well as on solution methods that may determine excellent routes in real-time.
Interplay with other emergency health care delivery systems
For emergency health care delivery systems is intended everything from the EDs (Emergency Departments), the location of static emergency devices and the care systems dealing with First Hour Quintet care delivery (i.e. cardiac arrests, acute coronary syndromes, severe trauma etc..). If considered all together, all these components play a crucial role in delivering on-time care.
The challenge related to the emergency health delivery systems is the need of the development of a model that considers all the components in order to provide adequate solutions for all stakeholders.
Conclusion
Finally, the big challenge in EMS is the adoption of a holistic outcome-based approach for the ECP (Emergency Care Pathway), “which should be conceived as a methodology that details all decisions, treatments, and reports related to a patient”7. This leads to the difficulty in collecting the information regarding all events involving the patient before, during and after the EMS intervention. EMS systems often collect a large amount of data. However, this does not involve the retrieve of data on what happens before and after the involvement of an EMS vehicle.
Consequently, the main challenge is to develop new reliable models, able to serve the “inherent complexity behind the definition of an ECP”8.
Note: This short summary is based on the scientific paper “Emergency Medical Services and beyond: Addressing new challenges through a wide literature review”.
Author: Aringhieri, M.E. Bruni, S. Khodaparasti and J.T. van Essen
References
[1] Aringhieri, R., Bruni, M. E., Khodaparasti, S., & van Essen, T. (2017). Emergency medical services and beyond: Addressing new challenges through a wide literature review. Computers & Operations Research
[2] Ibidem
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[4] Ibidem
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[8] Ibidem
Aringhieri, R., Bruni, M. E., Khodaparasti, S., & van Essen, T. (2017). Emergency medical services and beyond: Addressing new challenges through a wide literature review. Computers & Operations Research, 78, 349-368. Available at https://doi.org/10.1016/j.cor.2016.09.016
Keywords
Emergency Medical Service, Emergency Department, Operations Research, Data Mining, Health Technology Assessment, Clinical Pathway.