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UPSI Digital Repository (UDRep)
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| Abstract : Perpustakaan Tuanku Bainun |
| This research aimed to develop a new algorithm for triage and priontlsation for chronic heart
disease patients in telemedicine environmental to aid decision-makers. In this study, the secondary
data from 500 patients with chronic heart disease was derived from the most relevant remote triage
and prioritisation studies and were evaluated in terms of their emergency levels based on
four main sensor measurements: electrocardiogram (ECG), oxygen saturation (SpO2), blood pressure
(BP), and text sensor. In this study, the patients were triaged as emergency patients and separated
into five categories, which are risk, urgent, sick, cold state, and normal. Then, the patients were
prioritised through the rank and order of the patients according to their emergency status.
Subsequently, the patients were triaged using evidence theory that refers to four features of the
ECG sensor, BP sensor, SpO2 sensor, and text sensor to determine the emergency level of the chronic
heart disease patients. Then, they were prioritised using the integrated Multi-layer of Analytic
Hierarchy Process (MLAHP) and the Technique for Order Performance by Similarity to Ideal Solution
(TOPSIS). For validation, objectively, the mean deviation was used to check the accuracy of the
systematic ranking. In terms of evaluation, this study has provided scenarios and benchmarking
checklists to evaluate the proposed algorithm with the existing models. The results showed that:
(I) the proposed triage and prioritisation algorithm was able to prioritise the patients
effectively as those with a high degree of emergency were prioritised first. (2) For objective
validation, the comparison indicated that the first group's score was the highest with a mean value
of 0.013, indicating that the prioritisation results were identical. (3) In the evaluation,
regarding the scenarios, the proposed algorithm has an advantage over the benchmark works that
cover either triage or prioritisation with percentage values of 34.3% and 50%, respectively. The
implications of this study are able to identify the triage level and the ranking of a large scale
of patients with chronic heart disease that could be used to provide services and treatments on the
basis of emergency status. In conclusion, the main findings showed that this study will increase
the performance of triage and prioritisation in the telemedicine environment.
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