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Developing Reliable Digital Healthcare Service Using Semi-Quantitative Functional Resonance Analysis

Zhengshu Zhou*, Yutaka Matsubara, Hiroaki Takada

Graduate School of Informatics, Nagoya University, Nagoya, 464-8601, Japan

* Corresponding Author: Zhengshu Zhou. Email: email

Computer Systems Science and Engineering 2023, 45(1), 35-50. https://doi.org/10.32604/csse.2023.030848

Abstract

Since entering the era of Industry 4.0, the concept of Healthcare 4.0 has also been put forward and explored by researchers. How to use Information Technology (IT) to better serve people’s healthcare is one of the most featured emerging directions in the academic circle. An important field of Healthcare 4.0 research is the reliability engineering of healthcare service. Because healthcare systems often affect the health and even life of their users, developers must be very cautious in the design, development, and operation of these healthcare systems and services. The problems to be solved include the reliability of business process, system functions, and personal healthcare data. The Functional Resonance Analysis Method (FRAM) has been applied in reliability engineering for safety-critical systems in available studies, using both qualitative and quantitative approaches. However, the method has not been applied in the field of digital healthcare services development. Therefore, to narrow the gap, we present in this paper a semi-quantitative functional resonance analysis method to develop reliable healthcare services for diabetics. Moreover, this paper has tried to improve the reliability design of the service-oriented architecture (SOA) of traditional insulin pump therapy by system thinking.

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Cite This Article

Z. Zhou, Y. Matsubara and H. Takada, "Developing reliable digital healthcare service using semi-quantitative functional resonance analysis," Computer Systems Science and Engineering, vol. 45, no.1, pp. 35–50, 2023.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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