Azimi Ali, Bagheri Nasser, Mostafavi Sayyed Mostafa, Furst Mary Anne, Hashtarkhani Soheil, Amin Fateme Hashemi, Eslami Saeid, Kiani Fatemeh, VafaeiNezhad Reza, Akbari Toktam, Golabpour Amin, Kiani Behzad
Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Center for Mental Health Research College of Health and Medicine, Australian National University, Canberra, Australian Capital Territory, Australia.
BMC Public Health. 2021 Jan 4;21(1):7. doi: 10.1186/s12889-020-10064-1.
Response time to cardiovascular emergency medical requests is an important indicator in reducing cardiovascular disease (CVD) -related mortality. This study aimed to visualize the spatial-time distribution of response time, scene time, and call-to-hospital time of these emergency requests. We also identified patterns of clusters of CVD-related calls.
This cross-sectional study was conducted in Mashhad, north-eastern Iran, between August 2017 and December 2019. The response time to every CVD-related emergency medical request call was computed using spatial and classical statistical analyses. The Anselin Local Moran's I was performed to identify potential clusters in the patterns of CVD-related calls, response time, call-to-hospital arrival time, and scene-to-hospital arrival time at small area level (neighborhood level) in Mashhad, Iran.
There were 84,239 CVD-related emergency request calls, 61.64% of which resulted in the transport of patients to clinical centers by EMS, while 2.62% of callers (a total of 2218 persons) died before EMS arrival. The number of CVD-related emergency calls increased by almost 7% between 2017 and 2018, and by 19% between 2017 and 2019. The peak time for calls was between 9 p.m. and 1 a.m., and the lowest number of calls were recorded between 3 a.m. and 9 a.m. Saturday was the busiest day of the week in terms of call volume. There were statistically significant clusters in the pattern of CVD-related calls in the south-eastern region of Mashhad. Further, we found a large spatial variation in scene-to-hospital arrival time and call-to-hospital arrival time in the area under study.
The use of geographical information systems and spatial analyses in modelling and quantifying EMS response time provides a new vein of knowledge for decision makers in emergency services management. Spatial as well as temporal clustering of EMS calls were present in the study area. The reasons for clustering of unfavorable time indices for EMS response requires further exploration. This approach enables policymakers to design tailored interventions to improve response time and reduce CVD-related mortality.
对心血管紧急医疗请求的响应时间是降低心血管疾病(CVD)相关死亡率的一项重要指标。本研究旨在可视化这些紧急请求的响应时间、现场时间和呼叫至医院时间的时空分布。我们还确定了与CVD相关呼叫的聚集模式。
本横断面研究于2017年8月至2019年12月在伊朗东北部的马什哈德进行。使用空间和经典统计分析计算每个与CVD相关的紧急医疗请求呼叫的响应时间。运用安塞林局部莫兰指数(Anselin Local Moran's I)来识别伊朗马什哈德小区域层面(社区层面)与CVD相关呼叫、响应时间、呼叫至医院到达时间以及现场至医院到达时间模式中的潜在聚集区。
共有84239次与CVD相关的紧急请求呼叫,其中61.64%的呼叫导致患者被紧急医疗服务(EMS)送往临床中心,而2.62%的呼叫者(共2218人)在EMS到达之前死亡。2017年至2018年期间,与CVD相关的紧急呼叫数量增加了近7%,2017年至2019年期间增加了19%。呼叫的高峰时间是晚上9点至凌晨1点,凌晨3点至上午9点记录的呼叫数量最少。就呼叫量而言,周六是一周中最繁忙的一天。马什哈德东南部地区与CVD相关呼叫的模式存在统计学上的显著聚集区。此外,我们发现在研究区域内,现场至医院到达时间和呼叫至医院到达时间存在很大的空间差异。
在建模和量化EMS响应时间时使用地理信息系统和空间分析为紧急服务管理中的决策者提供了新的知识脉络。研究区域内存在EMS呼叫的空间和时间聚集现象。EMS响应不利时间指标聚集的原因需要进一步探索。这种方法使政策制定者能够设计针对性的干预措施,以改善响应时间并降低与CVD相关的死亡率。