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This paper proposes a smart real-time health monitoring structured for hospitals' distributor based on wearable health data sensors. Health data were received from multiple heterogeneous wearable sensors, such as electrocardiogram (ECG), oxygen saturation sensor (SpO2), blood pressure monitor, and non-sensory measurement (text frame), from 500 patients with different symptoms. Triage level and healthcare services were identified based on the new four-level remote triage and package localization (4LRTPL). The numbers of healthcare services that represent hospital status were collected from 12 hospitals located in Baghdad city. This study constructed a decision matrix based on the crossover of “multi-healthcare services” and “hospital list” within Tier 4. The hospitals were then ranked using multi-criteria decision-making (MCDM) techniques, namely, integrated analytic hierarchy process (AHP) and vlsekriterijumskaoptimizacija i kompromisnoresenje (VIKOR). Mean ± standard deviation was computed to ensure that the hospital ranking undergoes systematic ranking for objective validation. This research provided scenarios and checklist benchmarking to evaluate the proposed and existing health recommender frameworks. Results corroborated that: 1) the integration of AHP and VIKOR effectively solved hospital selection problems; 2) in the objective validation, significant differences were recognized between the scores of groups, indicating that the ranking results were identical; 3) in evaluation, the proposed framework exhibited an advantage over the benchmark framework with a percentage of 56.25%; and 4) hospitals with multiple healthcare services received the highest ranks, whereas hospitals with fewer healthcare services received low ranks.
Albahri et al. (Tue,) studied this question.