TY - JOUR
T1 - Spatio-temporal epidemiology of emergency medical requests in a large urban area. A scan-statistic approach
AU - Hashtarkhani, Soheil
AU - Kiani, Behzad
AU - Mohammadi, Alireza
AU - MohammadEbrahimi, Shahab
AU - Dehghan-Tezerjani, Mohammad
AU - Samimi, Tahereh
AU - Tara, Mahmood
AU - Matthews, Stephen A.
N1 - Publisher Copyright:
© the Author(s), 2021 Licensee PAGEPress, Italy.
PY - 2021/10/19
Y1 - 2021/10/19
N2 - Pre-hospital care is provided by emergency medical services (EMS) staff, the initial health care providers at the scene of disas-ter. This study aimed to describe the characteristics of EMS callers and space-time distribution of emergency requests in a large urban area. Descriptive thematic maps of EMS requests were created using an empirical Bayesian smoothing approach. Spatial, temporal and spatio-temporal clustering techniques were applied to EMS data based on Kulldorff scan statistics technique. Almost 225,000 calls were registered in the EMS dispatch centre during the study period. Approximately two-thirds of these calls were associated with an altered level of patient consciousness, and the median response time for rural and urban EMS dispatches was 12.2 and 10.1 minutes, respectively. Spatio-temporal clusters of EMS requests were mostly located in central parts of the city, par-ticularly near the downtown area. However, high-response time clustered areas had a low overlap with these general, spatial clus-ters. This low convergence shows that some unknown factors, other than EMS requests, influence the high-response times. The findings of this study can help policymakers to better allocate EMS resources and implement tailored interventions to enhance EMS system in urban areas.
AB - Pre-hospital care is provided by emergency medical services (EMS) staff, the initial health care providers at the scene of disas-ter. This study aimed to describe the characteristics of EMS callers and space-time distribution of emergency requests in a large urban area. Descriptive thematic maps of EMS requests were created using an empirical Bayesian smoothing approach. Spatial, temporal and spatio-temporal clustering techniques were applied to EMS data based on Kulldorff scan statistics technique. Almost 225,000 calls were registered in the EMS dispatch centre during the study period. Approximately two-thirds of these calls were associated with an altered level of patient consciousness, and the median response time for rural and urban EMS dispatches was 12.2 and 10.1 minutes, respectively. Spatio-temporal clusters of EMS requests were mostly located in central parts of the city, par-ticularly near the downtown area. However, high-response time clustered areas had a low overlap with these general, spatial clus-ters. This low convergence shows that some unknown factors, other than EMS requests, influence the high-response times. The findings of this study can help policymakers to better allocate EMS resources and implement tailored interventions to enhance EMS system in urban areas.
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U2 - 10.4081/gh.2021.1043
DO - 10.4081/gh.2021.1043
M3 - Article
C2 - 34726036
AN - SCOPUS:85118492204
SN - 1827-1987
VL - 16
JO - Geospatial Health
JF - Geospatial Health
IS - 2
M1 - 1043
ER -