92 Predictors of Response Times for Collegiate Emergency Medical Services

Abstract

Study Objectives: One measure of the quality of emergency medical services (EMS) is response time to the patient's location. Collegiate-based emergency medical services (CBEMS) are unique EMS services that are dedicated to providing out-ofhospital care on specific college or university campus. It is unknown what factors affect response time for CBEMS organizations. Our objective is to determine which organizational characteristics are associated with response times, and thus the quality of out-of-hospital care provided on university campuses.Methods: We performed a retrospective study of 200 CBEMS organizations in the United States and Canada. Survey data was collected between 1993 and 2015 by the National Collegiate Emergency Medical Services Foundation (NCEMSF). Regression modeling was utilized to predict mean response times from covariates. Log transformations of variables were taken where appropriate. Covariates that had an P > 0.1 were dropped from the stepwise multiple regression model. Analyses were conducted with Stata v. 13 software (Austin, Texas) with a 2-sided significance threshold of P < .05.Results: Annual call volume, population increases, annual budget, and student enrollment are associated with response time. When there is a 10% increase in their annual call volume, the data predicts that a CBEMS organization will experience a 5% increase in their mean response time. An annual budget increase of 10% will lead to a 1.3% decrease in response time. A population increase of 10% will increase the average response time by 9.5%, while an increase in student enrollment at the institution of 10% will lead to a decrease the response time by 12.3% (see Table 1). There was a statistically significant correlation with a one-unit increase in automated external defibrillators (AEDs) and a 10.8% decrease in average response times. The remaining characteristics of the CBEMS organizations, like number of ambulances and number of members, have no statistically significant predictive value on the average response time.Conclusion: There are multiple factors that affect response times for CBEMS organizations. Both population increases and annual call volume increases lead to longer response times, and are likely directly related to one another. CBEMS organizations may be able to mitigate this effect by increasing their annual budget. Student enrollment was also associated with decreasing response times, likely because of an increase in the number of responders geographically distributed throughout campuses. This study provides insight into factors affecting the quality of out-of-hospital care provided by CBEMS organizations.

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

“…18 One retrospective study determined that annual call volume increases lead to longer response times, and that they are likely directly correlated to one another. 16 Another large systematic review of Utah EMS data estimates a strong relationship between response time and mortality, but it did not reach statistical significance. Higher response times did lead to a statistically higher probability of hospital admission.…”

“…Other studies have measured other metrics as a burden related to increasing call volumethe most popular being EMS response time. [16][17][18][19] Response time has been liberally used as a process indicator to assess EMS performance internationally. It is quantifiable, objective, and easily comprehended by the public and policymakers.…”