首页> 外文会议>International conference on frontier computing: theory, technologies and applications >Application of Cloud Computing for Emergency Medical Services: A Study of Spatial Analysis and Data Mining Technology
【24h】

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

机译:云计算在紧急医疗服务中的应用:空间分析和数据挖掘技术的研究

获取原文

摘要

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:医院外心脏骤停(OHCA)是重要的医学和公共卫生问题。入院前的紧急急救服务是评估紧急医疗服务质量的重要指标。 OHCA经常在没有预警的情况下发生,并且在紧急急救中有明确的步骤处理OHCA患者时,如果他们不能及时获得紧急急救服务,他们的生存能力就会降低。使用卡方检验,逻辑回归和决策树等统计方法对影响因素进行分析和提取。此外,结合了三种独立的空间聚类分析方法的优势,即用于发现空间聚类的全局Moran指数,局部Moran指数和空间自相关分析Getis-Ord Gi〜*算法,这是一种新颖的汇总方法。确定高风险的OHCA区域。 OHCA事件发生地点的全球Moran指数为0.025861,Z值为8.178045,表明OHCA事件发生地点具有显着的空间聚集现象,Getis-Ord Gi〜*覆盖了更多的城镇(城市区域),但高-高区域达到了统计水平通过“当地莫兰指数”获得的标准也出现在通过使用Getis-Ord Gi〜*搜索而发现的高聚类区域中。此外,通过决策树分析方法发现的重要因素具有更大的空间分布范围。当发生OHCA时,根据本研究的结果,派遣119号任务的值班人员可能会进一步询问心脏病或糖尿病的病史,以作为将来派遣高级技术人员的参考。基于Getis-Ord Gi〜*产生的OHCA易发热点地区,并针对OHCA患者过去的心脏病或糖尿病病史,公共卫生部门可以采用信息技术或可穿戴设备作为干预措施,以增加发生OHCA的可能性。目击者并优先将紧急援助资源分配到热区,从而提高OHCA患者的存活率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号