Smart product service systems for remote patient monitoring under uncertainty: A hierarchical framework from a healthcare provider perspective
Background: This study contributes to the integration of smart product service systems (smart PSSs) for remote patient monitoring (RPM). Integrating smart PSSs into RPM improves service delivery by enabling personalized care plans and shaping a patient-centered workflow for intelligent RPM. However,...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
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| Series: | Computer Methods and Programs in Biomedicine Update |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666990024000417 |
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| Summary: | Background: This study contributes to the integration of smart product service systems (smart PSSs) for remote patient monitoring (RPM). Integrating smart PSSs into RPM improves service delivery by enabling personalized care plans and shaping a patient-centered workflow for intelligent RPM. However, a gap exists in identifying intelligent RPM attributes and understanding their interrelationships. In addition, prior studies of RPM have yielded mixed results, with some studies demonstrating positive impacts and others showing no effect or even negative consequences on patient health. This inconsistency highlights the need for further investigation into how RPM systems are designed and utilized. Objectives: First, the proposed intelligent RPM development criteria are validated through a qualitative assessment. Second, the interrelationships among intelligent RPM attributes are analyzed. Finally, the driving factors of intelligent RPM development are identified. Methods: A hybrid methodology that combines the fuzzy Delphi method (FDM), the fuzzy decision-making trial and evaluation laboratory (FDEMATEL), and an analytical network process (ANP) is introduced to establish a hierarchical model of intelligent RPM attributes. Thirty healthcare industry experts specializing in chronic disease management participated in the study. Linguistic variables were utilized to manage the uncertainty inherent in expert opinions. Results: The cause group encompassed operational efficiency, enhanced analytics, and sustainable service management, whereas the effect group comprised patient satisfaction and platform technology. The driving criteria included personalized treatment plans, real-time monitoring, mobile app development, and accessibility. Conclusion: This study advances the understanding of how smart PSSs can be integrated into healthcare delivery. The developed hierarchical framework provides a roadmap for healthcare providers to implement and optimize intelligent RPM systems. |
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| ISSN: | 2666-9900 |