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Mobile-Based Patient Monitoring Systems: A Prioritisation Framework Using Multi-Criteria Decision-Making Techniques

  • Systems-Level Quality Improvement
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Abstract

This study presents a prioritisation framework for mobile patient monitoring systems (MPMSs) based on multicriteria analysis in architectural components. This framework selects the most appropriate system amongst available MPMSs for the telemedicine environment. Prioritisation of MPMSs is a challenging task due to (a) multiple evaluation criteria, (b) importance of criteria, (c) data variation and (d) unmeasurable values. The secondary data presented as the decision evaluation matrix include six systems (namely, Yale–National Aeronautics and Space Administration (NASA), advanced health and disaster aid network, personalised health monitoring, CMS, MobiHealth and NTU) as alternatives and 13 criteria (namely, supported number of sensors, sensor front-end (SFE) communication, SFE to mobile base unit (MBU) communications, display of biosignals on the MBU, storage of biosignals on the MBU, intra-body area network (BAN) communication problems, extra-BAN communication problems, extra-BAN communication technology, extra-BAN communication protocols, back-end system communication technology, intended geographic area of use, end-to-end security and reported trial problems) based on the architectural components of MPMSs. These criteria are adopted from the most relevant studies and are found to be applicable to this study. The prioritisation framework is developed in three stages. (1) The unmeasurable values of the MPMS evaluation criteria in the adopted decision evaluation matrix based on expert opinion are represented by using the best–worst method (BWM). (2) The importance of the evaluation criteria based on the architectural components of the MPMS is determined by using the BWM. (3) The VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is utilised to rank the MPMSs according to the determined importance of the evaluation criteria and the adopted decision matrix. For validation, mean ± standard deviation is used to verify the similarity of systematic prioritisations objectively. The following results are obtained. (1) The BWM represents the unmeasurable values of the MPMS evaluation criteria. (2) The BWM is suitable for weighing the evaluation criteria based on the architectural components of the MPMS. (3) VIKOR is suitable for solving the MPMS prioritisation problem. Moreover, the internal and external VIKOR group decision making are approximately the same, with the best MPMS being ‘Yale–NASA’ and the worst MPMS being ‘NTU’. (4) For the objective validation, remarkable differences are observed between the group scores, which indicate the similarity of internal and external prioritisation results.

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  1. Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia

    E. M. Almahdi, A. A. Zaidan, B. B. Zaidan, M. A. Alsalem, O. S. Albahri & A. S. Albahri

  2. Department of Management Information System, College of Administration and Economic, University of Mosul, Mosul, Iraq

    M. A. Alsalem

  3. College of Engineering, University of Information Technology and Communications, Baghdad, Iraq

    A. S. Albahri

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Almahdi, E.M., Zaidan, A.A., Zaidan, B.B. et al. Mobile-Based Patient Monitoring Systems: A Prioritisation Framework Using Multi-Criteria Decision-Making Techniques. J Med Syst 43, 219 (2019). https://doi.org/10.1007/s10916-019-1339-9

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