{"title":"Developing a minimum dataset for smart aged care service platforms in China.","authors":"Tianchang Liu, Xiaoyu Zhang, Xiaokang Song, Qinghua Zhu","doi":"10.1177/18333583251327663","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background:</b> While the smart aged care service platform in China significantly enhances aged care services in China by integrating resources, it struggles with \"data silo\" issues due to the absence of data standards, leading to poor data integration, limited data-sharing and fragmented system functions. <b>Objective</b>: The study aimed to develop a minimum dataset (MDS) for smart aged care service platforms that constitutes core data to support real-time demand analysis and cross-regional cooperation, as well as to provide a foundation for the construction of a smart aged care data resource framework. <b>Method:</b> The study was developed in three phases: (1) bidding documents, policies, standards and literature were collected; (2) by analysing the content of the documents, the study constructed the structure of the MDS and extracted data elements afterward; and (3) a two-round Delphi process with 26 specialists was subsequently performed to revise the draft, and 24 institution staff invited to review and determine the MDS prototype. <b>Results:</b> Smart aged care service platforms included three types of users: older adults and their families; aged care organisations and regulatory authorities. The final MDS contained 122 items (26 optional items) with 6 first-level categories and 17 second-level categories. The most recognised sub-categories were nursing diagnosis, demographics and medical history. The data of government regulatory agencies was also important. <b>Conclusion:</b> The developed MDS provides a standardised framework for data integration and sharing in smart aged-care service platforms. <b>Implications for health information management:</b> The MDS can enhance data quality, facilitate personalised care, support evidence-based decision-making and promote research and innovation in aged care.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"18333583251327663"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health information management : journal of the Health Information Management Association of Australia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/18333583251327663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: While the smart aged care service platform in China significantly enhances aged care services in China by integrating resources, it struggles with "data silo" issues due to the absence of data standards, leading to poor data integration, limited data-sharing and fragmented system functions. Objective: The study aimed to develop a minimum dataset (MDS) for smart aged care service platforms that constitutes core data to support real-time demand analysis and cross-regional cooperation, as well as to provide a foundation for the construction of a smart aged care data resource framework. Method: The study was developed in three phases: (1) bidding documents, policies, standards and literature were collected; (2) by analysing the content of the documents, the study constructed the structure of the MDS and extracted data elements afterward; and (3) a two-round Delphi process with 26 specialists was subsequently performed to revise the draft, and 24 institution staff invited to review and determine the MDS prototype. Results: Smart aged care service platforms included three types of users: older adults and their families; aged care organisations and regulatory authorities. The final MDS contained 122 items (26 optional items) with 6 first-level categories and 17 second-level categories. The most recognised sub-categories were nursing diagnosis, demographics and medical history. The data of government regulatory agencies was also important. Conclusion: The developed MDS provides a standardised framework for data integration and sharing in smart aged-care service platforms. Implications for health information management: The MDS can enhance data quality, facilitate personalised care, support evidence-based decision-making and promote research and innovation in aged care.