Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC) 2012
DOI: 10.1109/wsc.2012.6465018
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Reducing ambulance response time using simulation: The case of Val-de-Marne department Emergency Medical service

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Cited by 17 publications
(29 citation statements)
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“…The fact that decentralised emergency vehicle location at holding points produced better response time performance in this model is not surprising, and it corroborates other data on the importance of emergency vehicle proximity to incidents [25][26][27][28][29][30][31], albeit using a baseline model that is more expansive and complex. Although the location of emergency vehicles at holding points and their demand-based movement between holding points requires a greater degree of organisation and control from a dispatching perspective, the benefits of this approach for response time performance have been clearly demonstrated.…”
Section: Implications Of the Results For Emergency Medical Services Ssupporting
confidence: 85%
“…The fact that decentralised emergency vehicle location at holding points produced better response time performance in this model is not surprising, and it corroborates other data on the importance of emergency vehicle proximity to incidents [25][26][27][28][29][30][31], albeit using a baseline model that is more expansive and complex. Although the location of emergency vehicles at holding points and their demand-based movement between holding points requires a greater degree of organisation and control from a dispatching perspective, the benefits of this approach for response time performance have been clearly demonstrated.…”
Section: Implications Of the Results For Emergency Medical Services Ssupporting
confidence: 85%
“…It was found that the simulation was able to achieve this because of its ability to both store attribute values and to show queuing levels at an individual product level [9]. In batch manufacturing systems, the flow of products can be monitored and optimized to propose a better layout design and work distribution using simulation models [10]. Overlong waiting time in emergency services is an important matter which has negative influence on healthcare quality [11].…”
Section: Fig 1 Stacked Fills and Cooling Tower [1]mentioning
confidence: 99%
“…System success criterion is to respond distress calls as quickly as possible; however, a number of matters such as heavy traffic, unexpected failures and lack of idle resource cause delay and affect the survival rates in possible catastrophic cases. Aboueljinane et al (2012) utilize DES to analyze seven scenarios, which comprises dynamic changes in existing Val-de-Marne department's emergency medical service with the aim of improving response time and compare results with the original organization. In a different study, Aboueljinane et al (2014) apply DES to improve the process of the same system, which aims to respond calls in 20 min, with five different strategies.…”
Section: Related Workmentioning
confidence: 99%