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Application of Cloud Computing for Emergency Medical Services: A Study of Spatial Analysis and Data Mining Technology

机译:云计算对应急医疗服务的应用:空间分析与数据挖掘技术研究

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Out of Hospital Cardiac Arrest (OHCA) is an important medical and public health issue. Emergency first aid service prior to hospital admission is an important indicator for the quality evaluation of the emergency medical service. OHCA frequently occurs without warning, and while there are clear steps in emergency first aid concerning the treatment of OHCA patients, their survivability diminishes if they cannot receive emergency first aid services in time. Using statistical methods such as chi-square test, logistic regression, and decision tree, the influence factors were analyzed and extracted. In addition, combining the strengths of three independent spatial clustering analysis methods, namely, the Global Moran's Index for finding the spatial clustering, as well as the Local Moran's Index and spatial autocorrelation analysis Getis-Ord Gi~* algorithm, a novel summary approach to identify high-risk OHCA areas. The Global Moran's Index of OHCA event locations were 0.025861, with a Z-score of 8.178045, indicating significance spatial clustering phenomenon of OHCA locations, Getis-Ord Gi~* covers more towns (urban areas), but the High-High area reaching statistical standards obtained through the Local Moran's Index also has also appeared in the high clusters Area found through search using the Getis-Ord Gi~*. In addition, the important factors found through the decision tree analysis method have more space distribution coverage. When OHCA occurs, based on findings in this study, the 119-dispatch duty officer may make further inquiries regarding medical history of heart disease or diabetes, which shall serve as a reference for future dispatch of senior technicians. Based on the OHCA-prone hot zone generated by the Getis-Ord Gi~* and targeting OHCA patients' past medical history of heart disease or diabetes, public health units may adopt information technology or wearable devices as intervention in order to increase the probability of eyewitnesses and prioritize the dispatch of emergency aid resources into the hot zone, thereby enhancing OHCA patient survival rates.
机译:走出医院心脏骤停的(OHCA)是一个重要的医学和公共卫生问题。之前入院急救服务是紧急医疗服务质量评价的重要指标。 OHCA频繁发生没有预兆,同时也有在急救关于OHCA患者的治疗明确步骤,其生存能力减弱,如果他们不能及时得到急救服务。使用统计方法,如卡方检验,Logistic回归,决策树,影响因素进行分析和提取。此外,结合三个独立的空间聚类分析方法,即全球莫兰指数寻找空间聚类,以及本地莫兰指数和空间自相关分析G系数-Ord Gi图〜*算法,一种新的总结方法的长处确定高风险领域OHCA。 OHCA事件地点的全球莫兰指数是0.025861,具有8.178045的Z得分,这表明OHCA位置的意义空间聚类现象,G系数-Ord Gi图〜*覆盖多个城镇(市区),但高 - 高面积达统计通过本地莫兰指数也获得标准也出现在高集群区通过搜索发现使用G系数 - 奥德GI〜*。此外,发现通过决策树分析方法的重要因素,有更多的空间分布范围。当OHCA情况下,根据本研究发现,119调度值班人员可以做出关于心脏疾病或糖尿病,这应作为高级技工的未来派遣一个参考的病史进一步调查。基于由G系数-Ord Gi图产生的OHCA多发的热区〜*,并以增加的概率瞄准OHCA患者过去的心脏疾病或糖尿病,公共卫生部门可以采取信息技术或可穿戴式设备作为干预的病史目击者和应急救援资源的调度优先进入热区,从而提高患者的OHCA存活率。

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