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

  • Jui-Hung KaoEmail author
  • Feipei Lai
  • Bo-Cheng Lin
  • Wei-Zen Sun
  • Kuan-Wu Chang
  • Ta-Chien Chan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 375)


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.


Out-of-hospital cardiac arrest Cardiopulmonary resuscitation Geographic information systems Spatial statistics Public health interventions 



This research was supported by grant entitled “Multidisciplinary Health Cloud Research Program: Technology Development and Application of Big Health Data” from the Academia Sinica. We would also like to express our sincere gratitude to Mr. Kent M. Suárez for his English editing.

Competing Interests

The authors declare that we do not have any competing interests related to this study.


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Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  • Jui-Hung Kao
    • 1
    • 2
    Email author
  • Feipei Lai
    • 1
  • Bo-Cheng Lin
    • 2
  • Wei-Zen Sun
    • 1
  • Kuan-Wu Chang
    • 3
  • Ta-Chien Chan
    • 2
  1. 1.Department of Computer Science and Information Engineering, Department of Electrical Engineering, Graduate Institute of Biomedical Electronics and BioinformaticsNational Taiwan UniversityTaipeiTaiwan
  2. 2.Center for Geographic Information Science, Research Center for Humanity and Social SciencesAcademia SinicaTaipeiTaiwan
  3. 3.Division of Emergency Medical Service, Fire DepartmentNew Taipei City GovernmentNew TaipeiTaiwan

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