REDUCING AMBULANCE RESPONSE TIME USING SIMULATION: THE CASE OF VALDE-MARNE DEPARTMENT EMERGENCY MEDICAL SERVICE

被引:0
|
作者
Aboueljinane, Lina [1 ]
Jemai, Zied [1 ]
Sahin, Evren [1 ]
机构
[1] Ecole Cent Paris, F-92295 Chatenay Malabry, France
关键词
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The French Emergency Medical service, known as SAMU, is responsible for providing permanent phone support and dispatching the proper response for emergency requests. The response time required for an ambulance's arrival at the scene following a call is an important performance indicator in determining the quality of the SAMU system since this may be directly related to patient's survival. In this paper, discrete simulation techniques are used to model the SAMU of the Val-de-Marne department ( France) in order to investigate several alternative configurations for potential improvements. Scenarios consist of adding more resources, relocating existing teams and reducing processing times in order to improve response time. We found that repositioning part of the existing teams into potential stations increased average percentage of calls covered within the 20-minutes criterion up to 4.8%. This improvement in coverage reaches 5.2% when reducing the regulation processing time by 20%.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Using simulation and optimisation to characterise durations of emergency department service times with incomplete data
    Guo, Hainan
    Goldsman, David
    Tsui, Kwok-Leung
    Zhou, Yu
    Wong, Shui-Yee
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2016, 54 (21) : 6494 - 6511
  • [32] COVID-19 Outbreak Response for an Emergency Department Using In Situ Simulation
    Jee, Marcus
    Khamoudes, Daniel
    Brennan, Aoife M.
    O'Donnell, John
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2020, 12 (04)
  • [33] Exploring emergency areas for medical service using microscopic traffic simulation model
    Kim B.
    Spatial Information Research, 2016, 24 (2) : 75 - 84
  • [34] Ergonomics demands associated with combinations of manual and powered emergency medical service cots and ambulance loading systems: A work simulation study
    Potvin, Jim R.
    Potvin, Aidan W.
    INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS, 2019, 73
  • [35] Improving Emergency Department Services Using Simulation: Case Study of Kuwait Hospital
    Oueida, Soraia
    Kadry, Seifeddine
    Char, Pierre Abi
    Ionescu, Sorin
    2017 9TH IEEE-GCC CONFERENCE AND EXHIBITION (GCCCE), 2018,
  • [36] Optimization of the emergency department in hospitals using simulation and experimental design: Case study
    Aroua, Abdeljelil
    Abdulnour, Georges
    28TH INTERNATIONAL CONFERENCE ON FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING (FAIM2018): GLOBAL INTEGRATION OF INTELLIGENT MANUFACTURING AND SMART INDUSTRY FOR GOOD OF HUMANITY, 2018, 17 : 878 - 885
  • [37] OPTIMIZATION OF THE EMERGENCY DEPARTMENT IN HOSPITALS USING SIMULATION AND EXPERIMENTAL DESIGN: CASE STUDY
    Aroua, Abdeljelil
    Abdulnour, Georges
    2017 WINTER SIMULATION CONFERENCE (WSC), 2017, : 4511 - 4513
  • [38] Decreasing Lab Turnaround Time Improves Emergency Department Throughput and Decreases Emergency Medical Services Diversion: A Simulation Model
    Storrow, Alan B.
    Zhou, Chuan
    Gaddis, Gary
    Han, Jin H.
    Miller, Karen
    Klubert, David
    Laidig, Andy
    Aronsky, Dominik
    ACADEMIC EMERGENCY MEDICINE, 2008, 15 (11) : 1130 - 1135
  • [39] Accuracy of emergency medical service telephone triage of need for an ambulance response in suspected COVID-19: an observational cohort study
    Marincowitz, Carl
    Stone, Tony
    Hasan, Madina
    Campbell, Richard
    Bath, Peter A.
    Turner, Janette
    Pilbery, Richard
    Thomas, Benjamin David
    Sutton, Laura
    Bell, Fiona
    Biggs, Katie
    Hopfgartner, Frank
    Mazumdar, Suvodeep
    Petrie, Jennifer
    Goodacre, Steve
    BMJ OPEN, 2022, 12 (05): : e058628
  • [40] Factors Influencing the Emergency Medical Service Response Time for Cardiovascular Disease in Guangzhou, China
    Xiao-qian Chen
    Zi-feng Liu
    Shi-kun Zhong
    Xing-tang Niu
    Yi-xiang Huang
    Ling-ling Zhang
    Current Medical Science, 2019, 39 : 463 - 471