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Improving Emergency Medical Dispatching with Emphasis on Mass-Casualty Incidents

Authors: Günter Kiechle; Martin Bernroider; Gabriel Kleinoscheg; Maria Obermayer; Harald Burgsteiner;

Improving Emergency Medical Dispatching with Emphasis on Mass-Casualty Incidents

Abstract

Dispatching ambulances is a demanding and stressful task for dispatchers. This is especially true in case of mass-casualty incidents. Therefore, the aim of this work was to investigate if and to what extent the dispatch operation of the Red Cross Salzburg can be optimized on such occasions with a computerized system. The basic problem of a dynamic multi-vehicle Dial-a-Ride Problem with time windows was enhanced according to the requirements of the Red Cross Salzburg. The general objective was to minimize the total mileage covered by ambulances and the waiting time of patients. Furthermore, in case of emergencies suitable adaptions to a plan should be carried out automatically. Consequently, the problem is solved by using the Adaptive Large Neighborhood Search. Evaluation results indicate that the system outperforms a human dispatcher by between 2.5% and 36% within 1 minute of runtime concerning total costs. Moreover, the system's response time in case that a plan has to be updated is less than 1 minute on average.

Keywords

Health Care Rationing, Emergency Medical Service Communication Systems, Ambulances, Decision Support Systems, Clinical, Efficiency, Organizational, Red Cross, Decision Support Techniques, Austria, Geographic Information Systems, Decision Support Systems, Management, Mass Casualty Incidents, Algorithms, Information Systems

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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