JGIS  Vol.7 No.4 , August 2015
A GIS-Based Decision Support System for Reducing Air Ambulance Response Times: A Case Study on Public Schools in Jeddah City
Author(s) Randa Alharbi
ABSTRACT
In injuries reducing ambulance response time (time from injury to hospital arrival) is an important factor for saving people’s lives. Helicopter emergency medical services can reduce out-of-hospital transport times because of their high speed and their ability to travel in straight paths unlike ground ambulance which are restricted to road network paths, as well as the ability toaccess rural or remote area injuries that are difficult to reach by ground ambulance. GIS technology aids air ambulance movement planning to reduce out-of-hospital response time based on mathematical and geographic models to support decision making which is necessary from out-of-hospital care providers. The goal of this study is to use GIS to develop an efficient DSS to outline where air ambulance can reduce response times, by using spatial analysis tools to create Euclidean distance and direction zones around receiving hospitals. The study concludes that GIS technology can be used to develop an efficient DSS to outline where air ambulance can reduce response times, by creating surfaces of Euclidean allocation, direction, and distance that can be used to improve initial response times for the civil defense air rescue and air ambulance services.

Cite this paper
Alharbi, R. (2015) A GIS-Based Decision Support System for Reducing Air Ambulance Response Times: A Case Study on Public Schools in Jeddah City. Journal of Geographic Information System, 7, 384-391. doi: 10.4236/jgis.2015.74030.
References
[1]   Ong, M.E.H., et al. (2010) Reducing Ambulance Response Times Using Geospatial-Time Analysis of Ambulance Deployment. Academic Emergency Medicine, 17, 951-957.
http://dx.doi.org/10.1111/j.1553-2712.2010.00860.x

[2]   Harmon, J.E. and Anderson, S.J. (2003) The Design and Implementation of Geographic Information Systems. John Wiley & Sons, Hobokon.

[3]   Gunes, A.E. and Kovel, J.P. (2000) Using GIS in Emergency Management Operations. Journal of Urban Planning and Development, 126, 136-149. http://dx.doi.org/10.1061/(ASCE)0733-9488(2000)126:3(136)

[4]   McGregor, J., et al. (2004) If All Ambulances Could Fly: Putting Provincial Standards of Emergency Care Access to the Test in Northern British Columbia. Canadian Journal of Rural Medicine: The Official Journal of the Society of Rural Physicians of Canada = Journal canadien de la medecine rurale: Le journal officiel de la Societe de medecine rurale du Canada, 10, 163-168.

[5]   Panahi, S. and Delavar, M. (2009) Dynamic Shortest Path in Ambulance Routing Based on GIS. International Journal of Geoinformatics, 5, 13-19.

[6]   Schuurman, N., et al. (2009) Modelling Optimal Location for Pre-Hospital Helicopter Emergency Medical Services. BMC Emergency Medicine, 9, 6. http://dx.doi.org/10.1186/1471-227X-9-6

[7]   Lerner, E.B., et al. (1999) Use of a Geographic Information System to Determine Appropriate Means of Trauma Patient Transport. Academic Emergency Medicine, 6, 1127-1133.
http://dx.doi.org/10.1111/j.1553-2712.1999.tb00115.x

[8]   Al-Rashdi, M.R. (2011) Geographic Information System Saudi Red Crescent Authority in Jeddah: Analytical and Evaluative Study. Book of Conference.

[9]   Ormsby, T., et al. (2001) Getting to Know ArcGIS Desktop. The Jste Teacher Education, 93.

[10]   McCoy, J., et al. (2001) Using ArcGIS Spatial Analyst. Environmental Systems Research Institute. Inc., Redlands.

[11]   ArcGIS, E. (2001) 8.3 of ArcMap, ArcCatalog, ArcToolbox and Spatial Analyst User’s Guide. Redlands.

[12]   Dobesova, Z. (2011) Programming Language Python for Data Processing. International Conference on Electrical and Control Engineering (ICECE), Yichang, 16-18 September 2011, 4866-4869.

 
 
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