Accepted for/Published in: JMIR Aging
Date Submitted: Apr 25, 2025
Open Peer Review Period: May 6, 2025 - Jul 1, 2025
Date Accepted: Dec 8, 2025
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Leveraging Artificial Intelligence to Enhance Implementation of the Evidence-Based Age-Friendly Health Systems 4Ms Framework for Care in Older Adults
ABSTRACT
The aging population presents a pressing challenge for healthcare systems, compelling effective strategies to address the complex needs of older adults. The Department of Veterans Affairs (VA) has embraced the Age-Friendly Health Systems (AFHS) initiative from the Institute for Healthcare Improvement (IHI) to ensure safe and high-quality care for older Veterans through its Whole Health initiative. As an Age-Friendly Health System, healthcare providers consistently utilize the evidence-based "4Ms": What Matters, Medication, Mentation, and Mobility, to deliver comprehensive care for older adults in all care settings. This manuscript explores the potential of artificial intelligence (AI) in enhancing the evidence-based implementation of the Age-Friendly Health Systems (AFHS) 4Ms framework to provide optimal care for older adults. By leveraging AI technologies, such as natural language processing, machine learning, and data analytics, this manuscript delves into the opportunities and challenges in utilizing AI to support the 4Ms domains – what matters, medication, mentation, and mobility. Furthermore, it discusses the potential benefits of integrating AI-driven decision support systems and predictive analytics to personalize care, reduce polypharmacy and potentially inappropriate medications, enhance cognitive and mood assessments, and better identify mobility issues and interventions. By examining the intersection of AI and age-friendly care, this manuscript contributes to the existing literature by highlighting the transformative potential of AI in improving outcomes and the experiences for older adults across diverse healthcare settings.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.