Virtua Health was selected to participate in the Davos Alzheimer’s Collaborative Healthcare System Preparedness U.S. Fellowship Program.
The project is led by the Davos Alzheimer’s Collaborative (DAC), a pioneering worldwide initiative seeking to cure Alzheimer’s disease and improve brain health.
Virtua is among 10 U.S. health systems selected to participate.
Virtua, in collaboration with the New Jersey Institute for Successful Aging (NJISA) at the Rowan-Virtua School of Osteopathic Medicine, will share learnings with the DAC Healthcare System Preparedness team and other health systems through early 2026.
“We are partnering with diverse health care systems nationwide to accelerate the adoption of early detection for cognitive impairment using the DAC Healthcare System Preparedness Blueprint. The program will produce a U.S.-specific early detection Blueprint, offering evidence-based training and tools to enable health systems to implement programs quickly and sustainably, ultimately improving access to cognitive evaluation for millions of Americans,” Tim MacLeod, director of DAC Healthcare System Preparedness, said.
“Virtua recognizes the growing population of individuals 65 and older and is committed to expanding our clinical capacities and developing programs that reflect their distinct needs,” Dr. Jennifer Khelil, Virtua’s executive vice president and chief clinical officer, said. “Virtua’s inclusion in DAC and academic affiliation with Rowan University support our goal of attaining IHI Age-Friendly Health System designation for Virtua’s five hospitals and its 36 primary care practices.”
DAC’s goal is to end Alzheimer’s Disease by mirroring the success of global efforts against infectious diseases such as HIV/AIDS, COVID-19, and malaria. The project is designed to support health systems in implementing early detection of cognitive impairment and Alzheimer’s disease in primary care settings across the United States. The 10 participating health systems intentionally represent a diverse cross-section of healthcare delivery models, geographic regions, and patient populations.
