Dynamic ambulance reallocation for the reduction of ambulance response times using system status management

Lam, Sean Shao Wei; Ji, Zhang; Zhang, Zhong Cheng; Oh, Hong Choon; Overton, Jerry; Ng, Yih Yng; Ong, Marcus Eng Hock

doi:10.1016/j.ajem.2014.10.044

Cited by 38 publications

(22 citation statements)

References 32 publications

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“…"Ambulance dispatch" is defined as the event when the ambulance leaves its base station whereas "arrival at the incident location" is defined as the event when the ambulance arrives on scene. This definition of the ART is one of the key performance indicator used by Singapore's national EMS provider (Ong et al, 2010;Lam et al, 2013Lam et al, , 2015Goh et al, 2014).…”

Section: Outcome Variablementioning

confidence: 98%

“…The significance of "Heavy" traffic implies a targeted effort to develop possible interventions that can help to get first-responders on-scene despite congested roads will likely help in reducing the EMS response times. Some possible ways of reducing EMS response time are to pre-position ambulances at optimal location taking into consideration projected traveling times, hence traffic congestion, across different times of the day (Lam et al, 2013(Lam et al, , 2015, and the use of motorcyclebased first responders (Goh et al, 2014). The primary objective of motorcycle-based first responders is to reach the patient and provide high quality BLS care in anticipation of the arrival of ambulances for conveyance to acute care hospitals (Soares-Oliveira et al, 2007;Nakstad et al, 2009;Goh et al, 2014).…”

Section: Insights On Key Factors Affecting Artmentioning

confidence: 99%

“…The International Standards Organization (ISO) has thus adopted EMS response times as a key performance indicator of fire and emergency services, providing a comparable and verifiable measure of EMS performance across diverse cities (I.S.O., 2014). For cities seeking to improve their EMS systems, it is imperative to examine the factors that can impact EMS response times in order to identify effective interventions (Ong et al, 2010;Lam et al, 2013Lam et al, , 2015Goh et al, 2014).…”

Section: Introductionmentioning

confidence: 98%

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Factors affecting the ambulance response times of trauma incidents in Singapore

Lam

Nguyen

et al. 2015

Accident Analysis & Prevention

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Section: Outcome Variablementioning

confidence: 98%

Section: Insights On Key Factors Affecting Artmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Factors affecting the ambulance response times of trauma incidents in Singapore

Lam

Nguyen

et al. 2015

Accident Analysis & Prevention

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“…Simulation research conducted since the late 1960s has made some advances in understanding ways of optimising emergency vehicle deployment and redeployment problems and, to some degree at least, in coupling EMS system demand patterns with available resources in order to minimise response time. [14][15][16][17][18][19][20][21] These studies, using a variety of approaches including mathematical modelling, use of geographic information systems, demand pattern analysis and dynamic allocation and reallocation of vehicles, have identified that the only way to significantly reduce response times is somehow to address the proximity problem. If this is not done, the addition of more vehicles to an EMS system can only have an impact on waiting time.…”

Section: Discussionmentioning

confidence: 99%

Meeting national response time targets for priority 1 incidents in an urban emergency medical services system in South Africa: More ambulances won’t help

2015

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Background. Response time is viewed as a key performance indicator in most emergency medical services (EMS) systems. Objective. To determine the effect of increased emergency vehicle numbers on response time performance for priority 1 incidents in an urban EMS system in Cape Town, South Africa, using discrete-event computer simulation. Method. A simulation model was created, based on input data from part of the EMS operations. Two different versions of the model were used, one with primary response vehicles and ambulances and one with only ambulances. In both cases the models were run in seven different scenarios. The first scenario used the actual number of emergency vehicles in the real system, and in each subsequent scenario vehicle numbers were increased by adding the baseline number to the cumulative total. Results. The model using only ambulances had shorter response times and a greater number of responses meeting national response time targets than models using primary response vehicles and ambulances. In both cases an improvement in response times and the number of responses meeting national response time targets was observed with the first incremental addition of vehicles. After this the improvements rapidly diminished and eventually became negligible with each successive increase in vehicle numbers. The national response time target for urban areas was never met, even with a seven-fold increase in vehicle numbers. Conclusion. The addition of emergency vehicles to an urban EMS system improves response times in priority 1 incidents, but alone is not capable of the magnitude of response time improvement needed to meet the national response time targets.

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“…The importance of intervention methods are increasing in health, crime, fire and natural disasters (Paraskevi et al, 2010;Konstantinos et al, 2000, Zhang et al, 2016Lam et al, 2015). Responding to emergency call needs to be managed effectively using decision support systems to save human life and DOI: 10.15317/Scitech.2017.69 F. SARI 48 provide public security (Bandyopadhyay and Singh, 2016).…”

Section: Introductionmentioning

confidence: 99%

A Gis Based New Navigation Approach for Reducing Emergency Vehicle S Response Time

Sarı¹

2017

Scitech

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ABSTRACT:Recently, for ensuring human life and safety, routing and intervening emergency vehicles as soon as possible an important subject. Ambulance, firefighter, police and other emergency vehicles are the main object of the intervention. Reaching the emergency area as soon as possible is important for saving human life and preventing economic loss. Directing and routing emergency vehicles from the moment they receive an emergency call to the event location must be considered carefully. In this study, ensuring the shortest response time for the emergency vehicles, obstacles like speed bumps, traffic lights, parking status of the streets, railroad crossings and crossroads which reduce the speed of emergency vehicles and increasing the intervention time are detected. In order to determine the effect of obstacles, a new Segment Effect Value (SEV) formula is developed. Values are assigned to the street segments according to obstacles in particular streets. SEV formula makes possible to determine the routes that provides the shortest intervention time. Results are compared with the shortest route and the shortest time route. Key Words: Emergency response time, Network analyst, Geographical information systems, Navigation systems Acil Müdahale Araçlarının Müdahale Zamanını Azaltmak İçin Cbs Tabanlı Bir Navıgasyon YaklaşımÖZ: İnsan yaşamını ve güvenliğini sağlamak için acil durum araçlarının olabildiğince hızlı müdahalesi önemli bir konu haline gelmiştir. Ambulans, itfaiye, polis ve diğer araçları acil durum müdahale araçlarının başında gelmektedir. Yaşam kayıplarının ve ekonomik kayıpların önüne geçmek için hızlı müdahale büyük önem taşımaktadır. İhbar alınmasından itibaren olay yerine gidene kadarki yönlendirme dikkatle yapılmalıdır. Müdahale zamanını kısaltmak için hız bariyerleri, trafik ışıkları, park etmiş araçlar, demiryolu geçitleri ve kavşaklar gibi hız kesici engellerin bilinmesi gerekmektedir. Bu engellerin etkisini ortaya koymak için Segment Etki Değeri (SED) isimli bir formül geliştirilmiştir ve bu formül ile her bir cadde segmentine değer atanmıştır. Böylece araçların bu engellerle karşılaşmayacakları en hızlı güzergah üzerinden gitmelerinin sağlanması amaçlanmıştır. En kısa yol ve en hızlı yol arasındaki farklar paylaşılmıştır.

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Dynamic ambulance reallocation for the reduction of ambulance response times using system status management

Cited by 38 publications

References 32 publications

Factors affecting the ambulance response times of trauma incidents in Singapore

Factors affecting the ambulance response times of trauma incidents in Singapore

Meeting national response time targets for priority 1 incidents in an urban emergency medical services system in South Africa: More ambulances won’t help

A Gis Based New Navigation Approach for Reducing Emergency Vehicle S Response Time

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