A new algorithm for triage and prioritisation patients in telemedecine environmental
<p>This research aimed to develop a new algorithm for triage and priontlsation for chronic heart</p><p>disease patients in telemedicine environmental to aid decision-makers. In this study, the secondary</p><p>data from 500 patient...
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Format: | thesis |
Language: | eng |
Published: |
2020
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Subjects: | |
Online Access: | https://ir.upsi.edu.my/detailsg.php?det=11452 |
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Summary: | <p>This research aimed to develop a new algorithm for triage and priontlsation for chronic heart</p><p>disease patients in telemedicine environmental to aid decision-makers. In this study, the secondary</p><p>data from 500 patients with chronic heart disease was derived from the most relevant remote triage</p><p>and prioritisation studies and were evaluated in terms of their emergency levels based on</p><p>four main sensor measurements: electrocardiogram (ECG), oxygen saturation (SpO2), blood pressure</p><p>(BP), and text sensor. In this study, the patients were triaged as emergency patients and separated</p><p>into five categories, which are risk, urgent, sick, cold state, and normal. Then, the patients were</p><p>prioritised through the rank and order of the patients according to their emergency status.</p><p>Subsequently, the patients were triaged using evidence theory that refers to four features of the</p><p>ECG sensor, BP sensor, SpO2 sensor, and text sensor to determine the emergency level of the chronic</p><p>heart disease patients. Then, they were prioritised using the integrated Multi-layer of Analytic</p><p>Hierarchy Process (MLAHP) and the Technique for Order Performance by Similarity to Ideal Solution</p><p>(TOPSIS). For validation, objectively, the mean deviation was used to check the accuracy of the</p><p>systematic ranking. In terms of evaluation, this study has provided scenarios and benchmarking</p><p>checklists to evaluate the proposed algorithm with the existing models. The results showed that:</p><p>(I) the proposed triage and prioritisation algorithm was able to prioritise the patients</p><p>effectively as those with a high degree of emergency were prioritised first. (2) For objective</p><p>validation, the comparison indicated that the first group's score was the highest with a mean value</p><p>of 0.013, indicating that the prioritisation results were identical. (3) In the evaluation,</p><p>regarding the scenarios, the proposed algorithm has an advantage over the benchmark works that</p><p>cover either triage or prioritisation with percentage values of 34.3% and 50%, respectively. The</p><p>implications of this study are able to identify the triage level and the ranking of a large scale</p><p>of patients with chronic heart disease that could be used to provide services and treatments on the</p><p>basis of emergency status. In conclusion, the main findings showed that this study will increase</p><p>the performance of triage and prioritisation in the telemedicine environment.</p><p></p> |
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