Prioritization methodology for a large scale of remote patients: a case study of chronic heart disease (IR)
This research aims to present a methodology based on Multi-Criteria Decision Making (MCDM) to aid decision-makers in prioritizing a large scale of patients in a telemedicine environment. In this study, the data from 500 patients with chronic heart disease are examined and evaluated their emergency l...
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| Main Author: | |
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| Format: | thesis |
| Language: | eng |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://ir.upsi.edu.my/detailsg.php?det=4497 |
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| Summary: | This research aims to present a methodology based on Multi-Criteria Decision Making (MCDM) to aid decision-makers in prioritizing a large scale of patients in a telemedicine environment. In this study, the data from 500 patients with chronic heart disease are examined and evaluated their emergency levels based on four main sources: electrocardiogram (ECG), oxygen saturation (SPO2), blood pressure (BP), and non- sensory measurement (text frame). The researcher of this study constructed a decision matrix based on a crossover of multiple sources and patients list according to the features of the sources. Subsequently, patients were prioritized using MCDM techniques, namely, integrated Multi-layer Analytic Hierarchy Process (MLAHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). For validation, subjectively, cardiologists are consulted to confirm the ranking results; objectively, mean ± standard deviation and T-test are used to check the accuracy of the systematic ranking. For evaluation, this study provided scenarios and checklist benchmarking to evaluate the proposed and existing prioritization methods. The following results were obtained. (1) Integrating MLAHP and Group-TOPSIS is effective for solving patient prioritization problems. (2) In subjective validation, the first five patients assigned to the doctors are the most critical cases needing the highest priority levels, whereas the last five are the least critical cases and thus given the lowest priority levels. In objective validation, significant differences were observed between the groups’ scores, indicating that the ranking results were identical. (3) In evaluation, regarding the first, second, and third scenarios, the proposed method had an advantage over the benchmark method with rates of 40%, 60%, and 100%, respectively. The implications of this study, will gain the benefits to medical organizations in provide a way to improve the priority settings processes for the healthcare manages constantly making difficult resource decisions. As well as benefits to doctors by assist medical teams through providing a decision making support for prioritizing and perform a timely and accurate treatment of their patients. Moreover, the benefits to patients are provided as the prioritization improves fairness, decreases urgent waiting times for patients with heart chronic disease. |
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