Integrating AI·IoT-OAHPs with existing elderly care systems

Area of Science:

• Gerontology
• Health Informatics
• Artificial Intelligence

Background:

• Current elderly care systems face challenges with integrating novel AI and IoT healthcare solutions.
• A disconnect exists between advanced technological healthcare programs and existing community/institutional care, causing service duplication and resource waste.

Purpose of the Study:

• To propose multifaceted integration strategies for AI and IoT-based older adult healthcare.
• To highlight the necessity of supportive policies for seamless integration.
• To examine international models for successful implementation.

Main Methods:

• Literature review and analysis of existing community and institutional elderly care systems.
• Examination of international case studies on integrated healthcare models.
• Conceptual framework development for AI and IoT integration.

Main Results:

• Identified significant inefficiencies and service duplication due to lack of integration.
• Demonstrated the potential of coordinated care models to enhance service delivery.
• Highlighted the critical role of policy in facilitating successful integration.

Conclusions:

• Multifaceted integration approaches are crucial for bridging the gap between AI/IoT healthcare and traditional elderly care.
• Supportive policies and international best practices are key to optimizing resource use and improving care for older adults.
• Coordinated care is essential for the future of elderly healthcare systems.