Reimagining Resilience in Aging: Leveraging AI/ML, Big Data Analytics, and Systems Innovation

Area of Science:

• Gerontology and Public Health
• Health Systems Research
• Sociology of Aging

Background:

• Growing aging population necessitates integrated support systems for older adults.
• Existing healthcare and social services often operate in silos, leading to care gaps and health disparities.
• Resilience is crucial for older adults, families, and communities to navigate adversity.

Purpose of the Study:

• To introduce the SUNSHINE (Seniors Uniting Nationwide to Support Health, INtegrated Care, and Evolution) framework.
• To promote whole-person health, interdisciplinary collaboration, and technology adoption for aging populations.
• To enhance the well-being of older adults and family caregivers through systems integration and multi-sector collaboration.

Main Methods:

• Utilizing Theory of Change modeling to guide framework development.
• Emphasizing systems integration supported by research infrastructure and multi-sector collaboration.
• Identifying opportunities for leveraging artificial intelligence and machine learning (AI/ML) for personalized care.

Main Results:

• The SUNSHINE framework aligns various stakeholders to foster resilience in older adults.
• It prioritizes mental health, social connection, and prevention to address health disparities.
• AI/ML technologies are identified as critical for optimizing decision-making and care delivery.

Conclusions:

• SUNSHINE offers a model for advancing resilience and well-being in the aging population.
• The framework promotes equity in health opportunities and outcomes for older adults.
• It guides the redesign and evaluation of health and social systems for a healthier future of aging.