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Identifying Key Factors and Strategies for Optimizing Automated External Defibrillator Deployment in China

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  • Jiang Du

    (Faculty of Art and Communication, Kunming University of Science and Technology, Kunming 650031, China)

  • Yuchao Du

    (Faculty of Art and Communication, Kunming University of Science and Technology, Kunming 650031, China)

  • Yu Zhang

    (Faculty of Art and Communication, Kunming University of Science and Technology, Kunming 650031, China)

  • Yiming Liu

    (School of Software, Northwestern Polytechnical University, Xi’an 710072, China)

  • Dapeng Wei

    (College of Design and Art, Beijing Institute of Technology, Beijing 100081, China)

Abstract

The survivability of out-of-hospital cardiac arrest patients in China is notably low, at less than 1%, primarily due to difficulties in accessing nearby Automated External Defibrillator (AED) devices during emergencies. Therefore, the strategic deployment of AEDs is crucial for improving patient survival. This study adopts a novel hybrid methodology that integrates the Fuzzy Analytic Network Process (FANP) and Grey Relational Analysis (GRA) to assess and prioritize the critical factors for optimizing AED deployment in China. In the FANP model, the rate of cardiopulmonary resuscitation training among individuals in the area, the rate of AED training among individuals in the area, and records of AED device usage within the area are key factors for improving the effectiveness of AED deployment. Furthermore, in the GRA model, the factors with higher gray relational degrees are Visibility, Social Environment, and Accessibility. This analysis sheds light on which secondary indicators can have the most significant impact on improving specific primary indicators. The insights from this study can guide the optimization of AED deployment strategies in China and offer practical solutions for enhancing the deployment of relevant public medical facilities.

Suggested Citation

  • Jiang Du & Yuchao Du & Yu Zhang & Yiming Liu & Dapeng Wei, 2024. "Identifying Key Factors and Strategies for Optimizing Automated External Defibrillator Deployment in China," Mathematics, MDPI, vol. 12(18), pages 1-27, September.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:18:p:2829-:d:1476748
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    References listed on IDEAS

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    1. Kahraman, Cengiz & Ertay, Tijen & Buyukozkan, Gulcin, 2006. "A fuzzy optimization model for QFD planning process using analytic network approach," European Journal of Operational Research, Elsevier, vol. 171(2), pages 390-411, June.
    2. Jian Wan & Chia-Liang Lin, 2023. "Research on the Service Quality Index and Alternatives Evaluation and Ranking for Online Yue Kiln Celadon Art Education in Post COVID-19 Era," Mathematics, MDPI, vol. 11(6), pages 1-20, March.
    3. Timothy C. Y. Chan & Derya Demirtas & Roy H. Kwon, 2016. "Optimizing the Deployment of Public Access Defibrillators," Management Science, INFORMS, vol. 62(12), pages 3617-3635, December.
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