Estimating the Demand for Ambulances in Traffic Accidents

Background: Effective Emergency medical service delivery in road traffic accidents requires accurate resource planning that relies on operational, tactical, and strategic demand forecasts. This study aims to estimate the demand for ambulances in traffic accidents using time series modeling techniques. Methods: We conducted a retrospective cohort analysis of ambulance demands related to traffic incidents in Golestan Province, Iran. The analysis of individual time series was utilized for demand prediction. Then, we applied statistical methods to present the performance indicators. Results: This research examined ۳۷۴۰۹ calls that led to ambulance dispatch from March ۲۰۲۱ to March ۲۰۲۳. According to the examination of traffic collision data, the demand rate is greater during the daytime compared to nighttime. Nonetheless, ambulance responses to deadly accidents take place more frequently at night compared to daytime. Our analysis indicates that demand will vary between ۲۴۰۰ and ۸۰۰ with a ۹۰% confidence level. Additionally, at an ۸۰% confidence level, the demand range is expected to be between ۳۰۰ and ۲۸۰۰. Conclusion: By analyzing the historical data, we have identified a trend and seasonal patterns in the data, which suggests an increase in demand during the summer months. Forecasting the course of service recipients in the prehospital emergency service can increase situational awareness and help manage the challenges caused by overcrowding. By anticipating the surge in demand for services during peak periods, it is possible to plan and allocate resources effectively and minimize delays.

کلیدواژه ها:

Time series ، Estimating ، Traffic accidents ، Emergency medical service ، Ambulance