Research on the Home and Community-Based Elderly Care Service Ecosystem Driven by Digital-Intelligence Empowerment
DOI:
https://doi.org/10.4108/eetpht.11.14232Keywords:
home and community-based elderly care, digital-intelligence, service ecosystem, demand-service matching, coordinated careAbstract
INTRODUCTION: Fragmented demand records, invisible provider capacity, and weak closure verification reduce the responsiveness of home and community-based elderly care.
OBJECTIVES: This paper specifies and evaluates a lightweight digital-intelligence workflow system rather than a predictive medical-diagnosis tool. The system links multi-channel demand intake, rule-based priority scoring, provider eligibility filtering, work-order state tracking, delivery verification, exception logging, and feedback closure. The architecture retains a core-provider layer, a beneficiary layer, and a four-module support system, but implements them through minimum data fields, explicit state transitions, and auditable scoring rules.
METHODS: An eight-week AB/BA pilot was conducted at two community centers with 42 adults aged 65–82 and 386 valid service requests.
RESULTS: Compared with the routine workflow, the supported workflow reduced mean demand-to-confirmation time from 58.4 to 36.9 min and staff coordination time from 8.9 to 6.2 min per request. On-time completion increased from 79.2% to 89.1%, while matching accuracy increased from 83.8% to 91.6%.
CONCLUSION: The configuration uses ordinary tablets, office computers, spreadsheet-compatible records, role-based access, and human fallback channels, providing an implementable coordination mechanism for community elderly care.
Downloads
References
[1] National Bureau of Statistics of China, Communique of the Seventh National Population Census (No. 5): Age Composition of the Population, Beijing, China, 2021.
[2] World Health Organization, National Programmes for Age-Friendly Cities and Communities: A Guide. Geneva, Switzerland: WHO, 2023.
[3] State Council of the People's Republic of China, The 14th Five-Year Plan for National Aging Development and Elderly Care Services, Beijing, China, 2022.
[4] Vargo SL, Lusch RF. Institutions and axioms: an extension and update of service-dominant logic. Journal of the Academy of marketing Science. 2016 Jan;44(1):5-23. https://doi.org/10.1007/s11747-015-0456-3
[5] Vink J, Koskela-Huotari K, Tronvoll B, Edvardsson B, Wetter-Edman K. Service ecosystem design: Propositions, process model, and future research agenda. Journal of Service Research. 2021 May;24(2):168-86.
[6] Airola E. Learning and use of eHealth among older adults living at home in rural and nonrural settings: systematic review. Journal of medical Internet research. 2021 Dec 2;23(12):e23804. https://doi.org/10.2196/23804
[7] Kunonga TP, Spiers GF, Beyer FR, Hanratty B, Boulton E, Hall A, Bower P, Todd C, Craig D. Effects of digital technologies on older people’s access to health and social care: umbrella review. Journal of medical Internet research. 2021 Nov 24;23(11):e25887. https://doi.org/10.2196/25887
[8] Oh SS, Kim KA, Kim M, Oh J, Chu SH, Choi J. Measurement of digital literacy among older adults: systematic review. Journal of medical Internet research. 2021 Feb 3;23(2):e26145. https://doi.org/10.2196/26145
[9] Xie L, Zhang S, Xin M, Zhu M, Lu W, Mo PK. Electronic health literacy and health-related outcomes among older adults: a systematic review. Preventive medicine. 2022 Apr 1;157:106997. https://doi.org/10.1016/j.ypmed.2022.106997
[10] Ehn M, Richardson MX, Landerdahl Stridsberg S, Redekop K, Wamala-Andersson S. Mobile safety alarms based on GPS technology in the care of older adults: systematic review of evidence based on a general evidence framework for digital health technologies. Journal of medical Internet research. 2021 Oct 11;23(10):e27267. https://doi.org/10.2196/27267
[11] Dong Q, Liu T, Liu R, Yang H, Liu C. Effectiveness of digital health literacy interventions in older adults: single-arm meta-analysis. Journal of Medical Internet Research. 2023 Jun 28;25:e48166. https://doi.org/10.2196/48166
[12] Shah SG, Nogueras D, van Woerden HC, Kiparoglou V. Evaluation of the effectiveness of digital technology interventions to reduce loneliness in older adults: systematic review and meta-analysis. Journal of medical Internet research. 2021 Jun 4;23(6):e24712. https://doi.org/10.2196/24712
[13] Governance OS. Challenges and the Way Forward. Organisation for Economic Co-Operation and Development: Paris, France. 2023.
[14] International Organization for Standardization, ISO 9241-210:2019, Ergonomics of Human-System Interaction—Part 210: Human-Centred Design for Interactive Systems. Geneva, Switzerland: ISO, 2019.
[15] International Organization for Standardization, ISO/IEC 27001:2022, Information Security Management Systems—Requirements. Geneva, Switzerland: ISO, 2022.
[16] International Organization for Standardization, ISO/IEC 25010:2023, Systems and Software Engineering—Systems and Software Quality Requirements and Evaluation. Geneva, Switzerland: ISO, 2023.
[17] Ministry of Industry and Information Technology, Ministry of Civil Affairs, and National Health Commission of China, Action Plan for the Development of the Smart Health and Elderly Care Industry (2021–2025), Beijing, China, 2021.
[18] Kaneko S. Estimating Family Preference for Home Elderly-care Services: Large-scale Conjoint Survey Experiment in Japan. RePEc: Research Papers in Economics. 2019 Jan 1.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Jiao Xu, Liping Fu, Xinyan Xu, Yonggang Wang, Ying Xu, Zizhu Liu
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
