Key result
A hybrid Multi-Criteria Decision Analysis framework combining Analytic Hierarchy Process and Additive Ratio Assessment successfully evaluated and ranked computer-based health monitoring applications.
Why the study?
Despite the anticipated benefits of computer-based health surveillance applications, concerns about performance, security, and alignment with healthcare professionals needs arise with widespread deployment.
The proposed hybrid Multi-Criteria Decision Analysis (MCDA) framework combining AHP and ARAS aims to provide a structured scientific process to evaluate and prioritize computer-based health monitoring systems.
Should not yet change which health-monitoring apps clinicians adopt; leaves open real-world validation of the hybrid ranking.
The surge in computer-based health surveillance applications, leveraging technologies like big data analytics, artificial intelligence, and the Internet of Things, aims to provide personalized and streamlined medical services. These applications encompass diverse functionalities, from portable health trackers to remote patient monitoring systems, covering aspects such as heart rate tracking, task monitoring, glucose level checking, medication reminders, and sleep pattern assessment. Despite the anticipated benefits, concerns about performance, security, and alignment with healthcare professionals' needs arise with their widespread deployment. This study introduces a Hybrid Multi-Criteria Decision Analysis (MCDA) paradigm, combining the strengths of Additive Ratio Assessment (ARAS) and Analytic Hierarchy Process (AHP), to address the intricate nature of decision-making processes. The method involves selecting and structuring criteria hierarchically, providing a detailed evaluation of application efficacy. Professional stakeholders quantify the relative importance of each criterion through pairwise comparisons, generating criteria weights using AHP. The ARAS methodology then ranks applications based on their performance concerning the weighted criteria. This approach delivers a comprehensive assessment, considering factors like real-time capabilities, surgical services, and other crucial aspects. The research results provide valuable insights for healthcare practitioners, legislators, and technologists, aiding in deciding the adoption and integration of computer-based health monitoring applications, ultimately enhancing medical services and healthcare outcomes.
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Wang et al. (2024) studied Evaluation of computer-based health monitoring applications. Hybrid Multi-Criteria Decision Analysis (MCDA) framework combining AHP and ARAS was evaluated on Ranking and evaluation of computer-based health monitoring applications. A hybrid Multi-Criteria Decision Analysis framework combining Analytic Hierarchy Process and Additive Ratio Assessment successfully evaluated and ranked computer-based health monitoring applications.
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