Based on Real Time Remote Health Monitoring Systems: A New Approach for Prioritization “Large Scales Data” Patients with Chronic Heart Diseases Using Body Sensors and Communication Technology

  • Naser Kalid
  • A. A. Zaidan
  • B. B. Zaidan
  • Omar H. Salman
  • M. Hashim
  • O. S. Albahri
  • A. S. Albahri
Systems-level Quality Improvement
Part of the following topical collections:
  1. Systems-Level Quality Improvement


This paper presents a new approach to prioritize “Large-scale Data” of patients with chronic heart diseases by using body sensors and communication technology during disasters and peak seasons. An evaluation matrix is used for emergency evaluation and large-scale data scoring of patients with chronic heart diseases in telemedicine environment. However, one major problem in the emergency evaluation of these patients is establishing a reasonable threshold for patients with the most and least critical conditions. This threshold can be used to detect the highest and lowest priority levels when all the scores of patients are identical during disasters and peak seasons. A practical study was performed on 500 patients with chronic heart diseases and different symptoms, and their emergency levels were evaluated based on four main measurements: electrocardiogram, oxygen saturation sensor, blood pressure monitoring, and non-sensory measurement tool, namely, text frame. Data alignment was conducted for the raw data and decision-making matrix by converting each extracted feature into an integer. This integer represents their state in the triage level based on medical guidelines to determine the features from different sources in a platform. The patients were then scored based on a decision matrix by using multi-criteria decision-making techniques, namely, integrated multi-layer for analytic hierarchy process (MLAHP) and technique for order performance by similarity to ideal solution (TOPSIS). For subjective validation, cardiologists were consulted to confirm the ranking results. For objective validation, mean ± standard deviation was computed to check the accuracy of the systematic ranking. This study provides scenarios and checklist benchmarking to evaluate the proposed and existing prioritization methods. Experimental results revealed the following. (1) The integration of TOPSIS and MLAHP effectively and systematically solved the patient settings on triage and prioritization problems. (2) In subjective validation, the first five patients assigned to the doctors were the most urgent cases that required the highest priority, whereas the last five patients were the least urgent cases and were given the lowest priority. In objective validation, scores significantly differed between the groups, indicating that the ranking results were identical. (3) For the first, second, and third scenarios, the proposed method exhibited an advantage over the benchmark method with percentages of 40%, 60%, and 100%, respectively. In conclusion, patients with the most and least urgent cases received the highest and lowest priority levels, respectively.


Real-time remote monitoring Telemedicine Patient prioritisation Large-scale data Multi-criterion decision making 



This study was funded by FRGS No: MMUE/140083.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Naser Kalid
    • 1
  • A. A. Zaidan
    • 1
  • B. B. Zaidan
    • 1
  • Omar H. Salman
    • 2
  • M. Hashim
    • 1
  • O. S. Albahri
    • 1
  • A. S. Albahri
    • 1
  1. 1.Department of Computing, Faculty of Arts, Computing and Creative IndustryUniversiti Pendidikan Sultan IdrisTanjong MalimMalaysia
  2. 2.Al- Iraqia UniversityBaghdadIraq

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