Yang Chih-Hao, Chen Yen-Chi, Hsu Wei, Chen Yu-Hui
Department of Accounting, Ming Chuan University, Shilin, Taipei, 111005 Taiwan, ROC.
Department of Accounting Information, National Taipei University of Business, Zhongzheng, Taipei, 100025 Taiwan, ROC.
Ann Oper Res. 2023 Apr 29:1-32. doi: 10.1007/s10479-023-05358-7.
A globally aging population results in the long-term care of people with chronic illnesses, affecting the living quality of the elderly. Integrating smart technology and long-term care services will enhance and maximize healthcare quality, while planning a smart long-term care information strategy could satisfy the variety of care demands regarding hospitals, home-care institutions, and communities. The evaluation of a smart long-term care information strategy is necessary to develop smart long-term care technology. This study applies a hybrid Multi-Criteria Decision-Making (MCDM) method, which uses the Decision-Making Trial and Evaluation Laboratory (DEMATEL) integrated with the Analytic Network Process (ANP) for ranking and priority of a smart long-term care information strategy. In addition, this study considers the various resource constraints (budget, network platform cost, training time, labor cost-saving ratio, and information transmission efficiency) into the Zero-one Goal Programming (ZOGP) model to capture the optimal smart long-term care information strategy portfolios. The results of this study indicate that a hybrid MCDM decision model can provide decision-makers with the optimal service platform selection for a smart long-term care information strategy that can maximize information service benefits and allocate constrained resources most efficiently.
全球人口老龄化导致对慢性病患者的长期护理，影响老年人的生活质量。整合智能技术和长期护理服务将提高并最大化医疗质量，而规划智能长期护理信息战略可以满足医院、家庭护理机构和社区的各种护理需求。评估智能长期护理信息战略对于开发智能长期护理技术是必要的。本研究应用一种混合多准则决策（MCDM）方法，该方法使用决策试验与评价实验室（DEMATEL）并结合网络分析法（ANP）对智能长期护理信息战略进行排序和确定优先级。此外，本研究将各种资源约束（预算、网络平台成本、培训时间、劳动力成本节省率和信息传输效率）纳入零一目标规划（ZOGP）模型，以获取最优的智能长期护理信息战略组合。本研究结果表明，混合MCDM决策模型可以为决策者提供智能长期护理信息战略的最优服务平台选择，该战略能够最大化信息服务效益并最有效地分配有限资源。
