Yeneneh Tamirat Negash , Faradilah Hanum , Liria Salome Calahorrano Sarmiento
{"title":"Smart product service systems for remote patient monitoring under uncertainty: A hierarchical framework from a healthcare provider perspective","authors":"Yeneneh Tamirat Negash ,&nbsp;Faradilah Hanum ,&nbsp;Liria Salome Calahorrano Sarmiento","doi":"10.1016/j.cmpbup.2024.100174","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>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.</div></div><div><h3>Objectives</h3><div>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.</div></div><div><h3>Methods</h3><div>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.</div></div><div><h3>Results</h3><div>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.</div></div><div><h3>Conclusion</h3><div>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.</div></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"7 ","pages":"Article 100174"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer methods and programs in biomedicine update","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666990024000417","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

背景本研究有助于将智能产品服务系统(smart PSS)整合到远程患者监护(RPM)中。将智能产品服务系统集成到 RPM 中,可实现个性化护理计划,并为智能 RPM 塑造以患者为中心的工作流程,从而改善服务的提供。然而,在确定智能 RPM 属性和了解其相互关系方面还存在差距。此外,先前对 RPM 的研究结果不一,有些研究显示了积极影响,有些研究则显示对患者健康没有影响,甚至有负面影响。目标首先,通过定性评估验证所提出的智能 RPM 开发标准。其次,分析智能 RPM 属性之间的相互关系。方法采用模糊德尔菲法(FDM)、模糊决策试验和评估实验室(FDEMATEL)以及分析网络过程(ANP)相结合的混合方法,建立智能 RPM 属性的分层模型。30 位专门从事慢性病管理的医疗行业专家参与了研究。结果原因组包括运营效率、增强分析和可持续服务管理,而影响组包括患者满意度和平台技术。驱动标准包括个性化治疗方案、实时监控、移动应用开发和可及性。所开发的分层框架为医疗机构实施和优化智能 RPM 系统提供了路线图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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, 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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
5.90
自引率
0.00%
发文量
0
审稿时长
10 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信