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STUDY OBJECTIVE: The planning of regional emergency medical services is aided by accurate prediction of urgent ambulance journey times, but it is unclear whether it is appropriate to use Geographical Information System (GIS) products designed for general traffic. We examined the accuracy of a commercially available generic GIS package when predicting emergency ambulance journey times under different population and temporal conditions. METHODS: We undertook a retrospective cohort study of emergency ambulance admissions to three emergency departments (ED) serving differing population distributions in northeast England (urban/suburban/rural). The transport time from scene to ED for all the highest priority dispatches between 1 October 2009 and 30 September 2010 was compared with predictions made by generic GIS software. RESULTS: For 10,156 emergency ambulance journeys, the mean prediction discrepancy between actual and predicted journey times across all EDs was an underprediction of 1.6 min (SD 4.9). Underprediction was statistically significant at all population densities, but unlikely to be of clinical significance. Ambulances in urban areas were able to exceed general traffic speed, whereas, the opposite effect was seen in suburban and rural road networks. There were minor effects due to travel outside the busiest traffic times (mean overprediction 0.8 min) and during winter months (mean underprediction 0.4 min). CONCLUSIONS: It is reasonable to estimate emergency ambulance journey times using generic GIS software, but in order to avoid insufficient regional ambulance provision it would be necessary to make small adjustments because of the tendency towards systematic underprediction.

Original publication

DOI

10.1136/emermed-2012-202246

Type

Journal article

Journal

Emerg Med J

Publication Date

09/2014

Volume

31

Pages

758 - 762

Keywords

emergency ambulance systems, planning, Ambulances, Efficiency, Organizational, England, Geographic Information Systems, Humans, Regression Analysis, Retrospective Studies, Software, Time Factors