Dynamic Ambulance Deployment to Reduce Ambulance Response Times Using Geographic Information Systems: A Case Study of Odunpazari District of Eskisehir Province, Turkey

Abstract

Background and ObjectiveAmbulances should always reach patients in the shortest time possible whenever they are called upon so as to increase patient survival chances especially in cardiac related medical cases. The placement of ambulances directly affects the time ambulances reach patients. The objective of the study was to find optimal stations to deploy ambulances so as to reduce ambulance response times and increase patient survival chances as a result. Data and MethodsTo reduce ambulance response times for Odunpazari district, the study employed system status management technique and maximal coverage location problem optimization model, to deploy ambulances according to ambulance demand and ensure maximum ambulance demand coverage is realized with a small ambulance fleet size, respectively. ArcGIS network analyst location allocation tool was used to find optimal ambulance stations from where ambulance demand areas can be reached within 5minutes of drive time. Four different ambulance deployment plans were modeled for periods ranging from 00:00 to 06:00hrs, 06:00 to 12:00hrs, 12:00 to 18:00hrs and 18:00 to 24:00hrs. The study used a total of 20,260 ambulance demand calls’ data for Odunpazari district collected from January 1st to December 31st 2014. ResultsThe Odunpazari district fleet of 17 ambulances was deployed differently for every six hours; between 00:00 to 06:00hrs, 06:00 to 12:00hrs, 12:00 to 18:00hrs and 18:00 to 24:00hrs to match ambulance demand and as a result, 77.6% of ambulance demand areas were located within 5minutes of drive time from the nearest ambulance station. ConclusionThe study found out that moving ambulances closer to ambulance demand areas reduces ambulance response times and dynamic ambulance deployment is by far a more effective ambulance deployment strategy than static ambulance deployment.