Rangraz Jeddi Fatemeh, Nickfarjam Ali Mohammad, Sharif Reihane, Heydarian Saeedeh, Holl Felix
Health Information Management Research Center, Department of Health Information Management & Technology, School of Allied Health Professions, Kashan University of Medical Sciences, Kashan, Iran.
DigiHealth Institute, Neu-Ulm University of Applied Sciences, Neu-Ulm, Germany.
Stud Health Technol Inform. 2025 Apr 8;323:81-85. doi: 10.3233/SHTI250053.
Dementia is a major cause of disability among the elderly, imposing significant financial burdens on healthcare systems. Traditional care approaches contribute to rising costs, especially in high-income countries. Artificial intelligence (AI) offers potential solutions by enhancing various areas of dementia care.
This scoping review follows the Arksey and O'Malley framework, identifying studies from PubMed, Scopus, and Web of Science that examine AI applications in dementia care with economic impacts. Eight studies met criteria, focusing on cost reduction in diagnosis, monitoring, personalized care, and resource management.
AI reduces healthcare costs by enabling timely interventions, optimizing resources, and tailoring care. Technologies, including machine learning for diagnosis and wearable devices for monitoring, showed significant cost-saving potential.
AI holds promise for reducing dementia care costs, though challenges like data privacy, bias, and system integration remain. Addressing these and further research is essential to maximize AI's impact on dementia care.
痴呆症是老年人残疾的主要原因,给医疗保健系统带来了巨大的经济负担。传统的护理方法导致成本不断上升,尤其是在高收入国家。人工智能通过改善痴呆症护理的各个领域提供了潜在的解决方案。
本范围综述遵循阿克西和奥马利框架,从PubMed、Scopus和科学网中识别研究人工智能在痴呆症护理中的应用及其经济影响的研究。八项研究符合标准,重点关注诊断、监测、个性化护理和资源管理方面的成本降低。
人工智能通过实现及时干预、优化资源和定制护理来降低医疗保健成本。包括用于诊断的机器学习和用于监测的可穿戴设备在内 的技术显示出显著的成本节约潜力。
人工智能有望降低痴呆症护理成本,尽管数据隐私、偏差和系统集成等挑战仍然存在。解决这些问题并进行进一步研究对于最大化人工智能对痴呆症护理的影响至关重要。