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

• Published in: The American journal of emergency medicine Vol. 33; no. 2; pp. 159 - 166
• Main Authors: Lam, Sean Shao Wei, PhD, Zhang, Ji, MSc, Zhang, Zhong Cheng, BEng, Oh, Hong Choon, PhD, Overton, Jerry, MPA, Ng, Yih Yng, MBBS, MPH, MBA, Ong, Marcus Eng Hock, MBBS, MPH
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.02.2015; Elsevier Limited
• Subjects: Ambulance services; Ambulances - organization & administration; Ambulances - standards; Compliance; Emergencies; Emergency; Emergency medical care; Geographic Information Systems; Hospitals; Humans; Mathematical programming; Quality Improvement; Resource Allocation - methods; Response time; Singapore; Systems Analysis; Time Factors; Singapore
• ISSN: 0735-6757; 1532-8171
• DOI: 10.1016/j.ajem.2014.10.044

Abstract Objectives Dynamically reassigning ambulance deployment locations throughout a day to balance ambulance availability and demands can be effective in reducing response times. The objectives of this study were to model dynamic ambulance allocation plans in Singapore based on the system status management (SSM) strategy and to evaluate the dynamic deployment plans using a discrete event simulation (DES) model. Methods The geographical information system–based analysis and mathematical programming were used to develop the dynamic ambulance deployment plans for SSM based on ambulance calls data from January 1, 2011, to June 30, 2011. A DES model that incorporated these plans was used to compare the performance of the dynamic SSM strategy against static reallocation policies under various demands and travel time uncertainties. Results When the deployment plans based on the SSM strategy were followed strictly, the DES model showed that the geographical information system–based plans resulted in approximately 13-second reduction in the median response times compared to the static reallocation policy, whereas the mathematical programming–based plans resulted in approximately a 44-second reduction. The response times and coverage performances were still better than the static policy when reallocations happened for only 60% of all the recommended moves. Conclusions Dynamically reassigning ambulance deployment locations based on the SSM strategy can result in superior response times and coverage performance compared to static reallocation policies even when the dynamic plans were not followed strictly.