Spatial analysis and data mining techniques for identifying risk factors of Out-of-Hospital Cardiac Arrest

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• 作者：Jui-Hung Kao^a ; ^b ; ^{kao.jui.hung@gmail.com} ; Ta-Chien Chan^b ; ^{tachien@gate.sinica.edu.tw} ; Feipei Lai^a ; ^{flai@ntu.edu.tw} ; Bo-Cheng Lin^b ; ^{bclin@gate.sinica.edu.tw} ; Wei-Zen Sun^a ; ^{wzsun@ntu.edu.tw} ; Kuan-Wu Chang^c ; ^{chang.kuan.wu@gmail.com} ; Fang-Yie Leu^d ; ^{leufy@thu.edu.tw} ; Jeng-Wei Lin^e ; ^{jwlin@thu.edu.tw}
• 关键词：Out-of-Hospital Cardiac Arrest (OHCA) ; Emergency medical service (EMS) ; Factor analysis ; Spatial analysis ; Data mining
• 刊名：International Journal of Information Management
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：37
• 期：1
• 页码：1528-1538
• 全文大小：2042 K
• 卷排序：37

文摘

Out-of-Hospital Cardiac Arrest (OHCA) is a critical issue of emergency medical service (EMS). Ubiquitous computing technologies could significantly improve the survival rate of OHCA patients. Public health institutions should manage first-aid resources more efficiently and make EMS policies more effectively. New Taipei City, Taiwan was chosen as the scope of this study. Spatial Analysis and Data Mining Techniques were used. Spatial clustering of OHCA events was found. Risk factors to 2-hour survival rate after OHCA were identified.