{"title":"Synergistic evaluation system of \"technology and service\" in smart elderly care institutions in China.","authors":"Xiaoyun Liu, Ka-Yin Chau, Xiaoxiao Liu, Yan Wan","doi":"10.1177/20552076251326681","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Smart elderly care faces numerous challenges while aligning with the national strategy of promoting the silver economy. Chief among these challenges is the inconsistent quality of services offered by smart elderly care institutions, which significantly impedes the industry's further development. Therefore, the objective of this paper is to develop a theoretical framework for assessing the quality of smart elderly care services, refine the evaluation index system for these services, and explore strategies to enhance their quality.</p><p><strong>Methods: </strong>Based on the Structure-Process-Outcome model, this paper has developed an integrated theoretical framework and employed a combination of modified-Delphi method and Decision-Making Trial and Evaluation Laboratory - Analytic Network Process to establish and assign weights to the service quality evaluation system for smart elderly care institutions in China.</p><p><strong>Results: </strong>This study develops a \"Technology + Service\" synergistic theoretical framework and an index system comprising four first-tier indicators, 12 second-tier indicators, and 54 third-tier indicators. The most significant indicators identified are service resources, smart elderly care infrastructure, staffing, service empathy, the rate of health file creation, 3S device coverage rate, and average living space per bed.</p><p><strong>Conclusion: </strong>The results reveal that service resources, especially the information technology infrastructure and smart equipment are the most crucial aspects of smart elderly care institutions. Additionally, institutions should focus on improving the expertise of their staff and providing psychological care for elderly adults.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"11 ","pages":"20552076251326681"},"PeriodicalIF":2.9000,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12033596/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"DIGITAL HEALTH","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/20552076251326681","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Smart elderly care faces numerous challenges while aligning with the national strategy of promoting the silver economy. Chief among these challenges is the inconsistent quality of services offered by smart elderly care institutions, which significantly impedes the industry's further development. Therefore, the objective of this paper is to develop a theoretical framework for assessing the quality of smart elderly care services, refine the evaluation index system for these services, and explore strategies to enhance their quality.
Methods: Based on the Structure-Process-Outcome model, this paper has developed an integrated theoretical framework and employed a combination of modified-Delphi method and Decision-Making Trial and Evaluation Laboratory - Analytic Network Process to establish and assign weights to the service quality evaluation system for smart elderly care institutions in China.
Results: This study develops a "Technology + Service" synergistic theoretical framework and an index system comprising four first-tier indicators, 12 second-tier indicators, and 54 third-tier indicators. The most significant indicators identified are service resources, smart elderly care infrastructure, staffing, service empathy, the rate of health file creation, 3S device coverage rate, and average living space per bed.
Conclusion: The results reveal that service resources, especially the information technology infrastructure and smart equipment are the most crucial aspects of smart elderly care institutions. Additionally, institutions should focus on improving the expertise of their staff and providing psychological care for elderly adults.