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Hospital selection framework for remote MCD patients based on fuzzy q-rung orthopair environment

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Abstract

This research proposes a novel mobile health-based hospital selection framework for remote patients with multi-chronic diseases based on wearable body medical sensors that use the Internet of Things. The proposed framework uses two powerful multi-criteria decision-making (MCDM) methods, namely fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score method for criteria weighting and hospital ranking. The development of both methods is based on a Q-rung orthopair fuzzy environment to address the uncertainty issues associated with the case study in this research. The other MCDM issues of multiple criteria, various levels of significance and data variation are also addressed. The proposed framework comprises two main phases, namely identification and development. The first phase discusses the telemedicine architecture selected, patient dataset used and decision matrix integrated. The development phase discusses criteria weighting by q-ROFWZIC and hospital ranking by q-ROFDOSM and their sub-associated processes. Weighting results by q-ROFWZIC indicate that the time of arrival criterion is the most significant across all experimental scenarios with (0.1837, 0.183, 0.230, 0.276, 0.335) for (q = 1, 3, 5, 7, 10), respectively. Ranking results indicate that Hospital (H-4) is the best-ranked hospital in all experimental scenarios. Both methods were evaluated based on systematic ranking and sensitivity analysis, thereby confirming the validity of the proposed framework.

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Acknowledgements

The authors would like to acknowledge Universiti Pendidikan Sultan Idris (UPSI) for the unconditional support.

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Authors and Affiliations

  1. Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, 35900, Tanjung Malim, Malaysia

    A.H. Alamoodi

  2. Computer Techniques Engineering Department, Mazaya University College, Nassiriya, Thi-Qar, Iraq

    O.S. Albahri

  3. Faculty of Engineering & IT, The British University in Dubai, Dubai, United Arab Emirates

    A.A. Zaidan

  4. Department of Business Administration, College of Administrative Science, The University of Mashreq, 10021, Baghdad, Iraq

    H.A. Alsattar

  5. Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin, 64002, Taiwan

    B.B. Zaidan

  6. Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq

    A.S. Albahri

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  1. A.H. Alamoodi
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Alamoodi, A., Albahri, O., Zaidan, A. et al. Hospital selection framework for remote MCD patients based on fuzzy q-rung orthopair environment. Neural Comput & Applic 35, 6185–6196 (2023). https://doi.org/10.1007/s00521-022-07998-5

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