ABSTRACTS
sing Geographic Information Systems (GIS) to Assess Diffuse Response Intervals for Community Bystander-Driven (Tier-1) Emergency Medical Services Integrated with Emergency Medical Dispatch in Mwanza, TanzaniaAuthor: Jason Friesen, MPH, EMT-P | | Associate Authors: Peter G. Delaney, MD, Zachary J. Eisner, MD, Haleigh Pine, MD, Krishnan Raghavendran, MD, Marko Hingi, MD
Introduction The global injury burden disproportionately affects low- and middle-income countries, which lack robust emergency medical services (EMS). Where formal, professionally staffed, ambulance-driven (Tier 2) EMS is not financially feasible, the World Health Organization recommends community bystander–driven (Tier 1) EMS as the first step toward formal EMS. The Global Prehospital Consortium determined Tier 1 response intervals are not well understood and are a priority for investigation. On-scene response intervals for Tier 2 EMS systems vary by density of centralized responder dispatch sites per population, whereas Tier 1 EMS system community bystander responders are mobile, diffuse, and noncentrally dispatched. We used GIS to analyze prospectively collected data from a Tier 1 dispatch-enabled EMS program in Tanzania to assess response intervals. We hypothesized Tier 1 EMS response intervals would not be geographically related due to inherent responder diffusion and mobile emergency medical dispatch (EMD) coordination. Methods In 2015, the Tanzania Rural Health Movement launched a Tier1 layperson first-responder program integrated with Beacon, a mobile EMD platform for responder coordination in Mwanza, Tanzania. Chief complaint characteristics, diurnal emergency variation, and response intervals (for emergencies with 67% data compliance) were prospectively recorded for descriptive analysis. GIS software (ArcGIS Pro 2.8) used recorded latitude/longitude for compliant entries with available data for analysis of response interval and distance from Mwanza, plotted on a logarithmic distribution for correlation. Results A total of 1,397 data entries were catalogued (2017–2022). From that dataset, 192 simulated incidents and 701 data entries lacking 67% data compliance were filtered, leaving 504 entries for analysis. Of chief complaints, 77.6% were road traffic injury related, 5.23% were fall related, 5.12% were burn related, and 11.98% were other. The median on-scene response interval was 1 minute, 47 seconds (mean = 7 minutes, 50 seconds) (n = 497). Forty-nine percent of emergencies occur between Friday and Sunday, with 66.3% occurring between 6 a.m. and 6 p.m. There is no correlation between response interval and distance from Mwanza (r = 0.0053957; n = 355). Conclusion A community bystander–driven Tier 1 EMS system with integrated mobile EMD demonstrates on-scene response intervals that are irrespective of distance, suggesting response intervals are not geographically dependent, which may be due to inherent Tier 1 responder diffusion and EMD coordination. Tier 1 EMS expansion may facilitate faster on-scene response intervals than traditional Tier 2 EMS in certain settings.
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