Emergency Medical Services Utilization Is Associated With Community Deprivation in Children.

BACKGROUND: Pediatric emergency medical services (EMS) utilization is costly and resource intensive; significant variation exists across large-scale geographies. Less is known about variation at smaller geographic levels where factors including lack of transportation, low health literacy, and decreased access to medical homes may be more relevant. Our objective was to determine whether pediatric EMS utilization varied across Hamilton County, Ohio, census tracts and whether such utilization was associated with socioeconomic deprivation. METHODS: This was a retrospective analysis of children living in Hamilton County, Ohio, transported by EMS to the Cincinnati Children's emergency department between July 1, 2014, and July 31, 2016. Participants' addresses were assigned to census tracts and an EMS utilization rate and deprivation index were calculated for each. Pearson's correlation coefficients evaluated relationships between tract-level EMS utilization and deprivation. Tract-level deprivation was used as a predictor in patient-level evaluations of acuity. RESULTS: During the study period, there were 4,877 pediatric EMS transports from 219 of the 222 county census tracts. The county EMS utilization rate during the study period was 2.4 transports per 100 children (range 0.2-11). EMS utilization rates were positively correlated with increasing deprivation (r = 0.72, 95% confidence interval [CI], 0.65-0.77). Deprivation was associated with lower illness severity at triage, fewer transports resulting in resuscitation suite use, and fewer transports resulting in hospitalizations (all p < 0.05). CONCLUSIONS: EMS utilization varied substantially across census tracts in Hamilton County, Ohio. A deeper understanding into why certain socioeconomically deprived areas contribute to disproportionately high rates of EMS utilization could support development of targeted interventions to improve use.

Temporal Trends and Future Predictions of Regional EMS System Utilization Using Statistical Modeling.

INTRODUCTION: 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. PROBLEM: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.