Trends in utilization of Emergency Medical Services (EMS) systems can be used to extrapolate future use of an EMS system, which will be valuable for the budgeting and planning of finances and resources. The best model for incorporation of seasonal and regional fluctuations in utilization to predict future utilization is unknown.

Authors aimed to trend patterns of utilization in a regional EMS system to identify the needs of a growing population and to allow for a better understanding of how the EMS system is used on a basis of call volume and frequency of EMS transportation. The authors then used a best-fitting prediction model approach to show how the studied EMS system will be used in future years.

Systems data were retrospectively extracted by using the electronic medical records of the studied EMS system and its computer-assisted dispatch (CAD) database from 2010 through 2017. All EMS dispatches entering the system’s 9-1-1 public service access point were captured. Annual utilization data were available from 2010 through 2017, while quarterly data were available only from 2013 through 2017. The 9-1-1 utilization per capita, Advanced Life Support (ALS) utilization per capita, and ALS cancel rates were calculated and trended over the study period. The methods of prediction were assessed through a best-fitting model approach, which statistically suggested that Additive Winter’s approach (SAS) was the best fit to determine future utilization and ALS cancel rates.

Total 9-1-1 call volume per capita increased by 32.46% between 2010 and 2017, with an average quarterly increase of 0.78% between 2013 and 2017. Total ALS call volume per capita increased by 1.93% between 2010 and 2017. Percent ALS cancellations (cancelled en route to scene) increased by eight percent between 2010 and 2017, with an average quarterly increase of 0.42% (2013–2017). Predictions to end of 2019 using Additive Winter’s approach demonstrated increasing trends in 9-1-1 call volume per capita (R2 = 0.47), increasing trends of ALS utilization per capita (R2 = 0.71), and increasing percent ALS cancellation (R2 = 0.93). Each prediction showed increasing future trends with a 95% confidence interval.

The authors demonstrate paramount per capita increases of 9-1-1 call volume in the studied ALS system. There are concomitant increases of ALS cancellations prior to arrival, which suggests a potential burden on this regional ALS response system.