Artificial Intelligence in Geriatrics: Riding the Inevitable Tide of Promise, Challenges, and Considerations

Abstract

In the era of technological revolution in healthcare, the integration of Artificial Intelligence (AI) stands out as a potentially transformative force (1). Clinicians often view the promises of AI with a healthy degree of skepticism (2), understanding the complexities of aging and the heterogeneity of physical and cognitive functions in older adults (3). This skepticism is necessary and healthy. AI engineers, on the other hand, sometimes struggle to fully grasp the expectations of clinicians and the intricate nature of aging (4). The future will require multidisciplinary collaboration among clinicians, AI engineers, and key stakeholders, including patient advocacy groups and older adults, to develop solutions that effectively address the complex nature of aging. As a geriatrician (P.A.) and an AI researcher (R.C.), we aim to provide insight into this burgeoning field, highlighting how AI can redefine, revitalize, and revolutionize care for older adults. In this editorial, we are also charting a course for an upcoming special issue in The Journals of Gerontology on AI-enabled wearables and sensors for older adults. This upcoming issue will aim to explore innovative ways these technologies enhance care for older adults, with a focus on practical applications and real-world impact. Geriatrics, with its focus on the health and care of older adults, presents unique challenges, including managing multiple chronic diseases, cognitive decline, and end-of-life care (5). AI’s role in geriatrics is not limited to clinical applications. It extends to enhancing the everyday lives of older adults through AI-powered assistive technologies, enabling better management of chronic conditions, and providing companionship through advanced robotics and virtual assistants (1). These innovations are crucial in addressing the psychological and social aspects of aging, thus contributing to a holistic approach to care for older adults. The future of geriatrics care is inherently collaborative, demanding a synergy among healthcare professionals, technologists, ethicists, and AI developers. The goal is to foster an environment where AI not only coexists with traditional healthcare practices but also enhances them, always keeping the well-being and dignity of older adults at the forefront. In that realm, the National Institute on Aging has allocated $60 million to establish 3 Artificial Intelligence and Technology Collaboratories for Aging Research at Johns Hopkins University, University of Pennsylvania, and a University of Massachusetts-led consortium. This initiative aims to accelerate the development of AI technologies tailored for older adults. The project brings together experts across various fields, including medicine, engineering, and business, alongside patient advocacy groups and older adults. These collaboratories seek to integrate AI into geriatric care effectively, enhancing healthcare practices while focusing on the well-being and dignity of older adults (6,7). AI has already made significant strides in the healthcare of older adults, particularly in predictive analytics and diagnostics. A notable example is Stanford Hospital’s AI algorithm (8), which assesses mortality risk. This deep-learning algorithm, trained on 2 million patient records, flags patients with a 75% or higher risk of dying within 3–12 months (9,10). This information prompts physicians to initiate advance care planning conversations, though the specific mortality risk is not disclosed to the patient or attending physician. This algorithm is intended as a tool for facilitating critical end-of-life discussions, often neglected due to busy clinical schedules and the discomfort of the topic (8,11). The utility of this algorithm extends beyond physicians to other healthcare staff. Therapists, for example, use it to guide conversations about end-of-life care, focusing on what is important to the patient in their final months. This broader involvement of nonphysician staff in such discussions represents a significant shift in the approach to terminal care (8,11). Likewise, the University of Pennsylvania Health System’s AI algorithm, which evaluates over 500 patient variables, has quadrupled the number of advance care conversations (8). This algorithm has also helped address potential biases in patient care, particularly in conversations about death among different ethnic or minority groups (12). AI’s impact on healthcare is not limited to predictive analytics. Google’s AI system for lung cancer detection, for instance, has shown promising results, outperforming radiologists in some aspects (13). The FDA has approved over 160 AI-driven products in recent years, mostly in medical imaging, reflecting AI’s growing role in this field (8). A recent project by computer scientists at the University of California, San Diego, CA, exemplifies this evolution. Funded by an Amazon Research Award, they are developing a voice assistant tailored to understand and respond to medical questions from adults over age 65 (8,14). This demographic often struggles with current voice assistants due to their conversational speech patterns. This initiative underscores the necessity to adapt AI to the user, emphasizing inclusivity in technology design. In terms of patient outcomes, AI is also helping with surgical decision making. A team from Johns Hopkins University (8) has developed an AI algorithm that uses imaging data to predict the best candidates for spinal surgery. This model, which considers spinal morphology, is potentially more accurate than traditional assessment methods based solely on general health indicators (15). The coronavirus disease 2019 (COVID-19) pandemic has further highlighted the importance of AI in healthcare. BlueDot’s AI methodologies were instrumental in tracking early cases of the outbreak. The Severe COVID-19 Adaptive Risk Predictor developed by Johns Hopkins researchers provided valuable insights for patient management during the pandemic, although challenges in data consistency and validation were noted (8). AI has also been pivotal in sepsis detection and management. Suchi Saria’s work at Johns Hopkins led to the development of an AI system that integrates patient data for early sepsis detection, potentially saving lives and reducing healthcare costs. Her startup, Bayesian Health, has made this technology accessible to thousands of healthcare providers (16). One of the emerging applications of AI in healthcare is its utility for clinicians, including geriatricians, in their day-to-day patient interactions. AI systems are increasingly being developed to review patient messages and analyze them in the context of past encounters and medical records. This capability allows for the preparation of a thorough analysis and assists doctors in crafting responses, enhancing the efficiency and effectiveness of patient communication. Additionally, AI is being employed to listen to patient encounters and prepare detailed encounter notes. This not only saves time for healthcare professionals but also ensures accuracy in medical documentation, which is critical for patient care continuity. AI’s potential in diagnosing rare syndromes and diseases is another promising application. By analyzing vast datasets and identifying patterns that might be overlooked by human clinicians, AI can aid in the early detection and diagnosis of rare conditions, significantly affecting patient outcomes (8). However, AI in healthcare faces challenges, including algorithmic biases and data quality issues. Studies have shown that AI tools can unintentionally perpetuate racial and gender biases present in healthcare data (17,18). Addressing these biases is crucial for the equitable application of AI in healthcare. The integration of AI for older adults is also not without challenges. Existing systems often reflect societal biases, particularly ageism, neglecting the needs and preferences of older adults. This issue is evident in the way older adults interact with technologies like voice assistants. In addition, and specifically in the older adult’s domain, there is a narrow focus on accessibility, often conflating aging with disability, which inadvertently excludes older adults from the wider benefits of technology (19). This perspective sidelines the rich life experiences, wisdom, and potential contributions of older adults in the realm of digital technology. There is a need for technologies that are not only usable by older adults with age-related limitations but are also useful and acceptable to the broader spectrum of older adults, many of whom do not have such limitations. There is a critical need to involve older adults as full stakeholders in digital society, and enable them to be active participants and co-designers in technology development. This inclusion can lead to innovations that better align with the varied needs and preferences of older adults, and help dispel stereotypes that often lead to the marginalization of this demographic in the tech industry. By embracing the diverse experiences and insights of older adults, we can develop AI technologies that truly enhance the lives of older adults, making the digital world more inclusive and beneficial for all age groups. Despite these challenges, AI’s role in healthcare is rapidly expanding. Big tech firms and startups are investing heavily in AI-driven healthcare solutions, anticipating significant growth in this sector. The future of AI in healthcare, particularly geriatrics care, lies in addressing these challenges and ensuring equitable access to AI tools across all patient demographics (1). In addressing the future of geriatrics and healthcare, a common concern arises: will AI replace physicians, and scientists? The reality, however, reveals a different narrative. The truth is, AI will not replace clinicians, including geriatricians, or scientists. These roles, steeped in years of training, experience, and human understanding, remain irreplaceable. What AI does is enhance these roles, offering tools and insights that were previously unimaginable. It brings a level of precision, efficiency, and predictive power to healthcare, changing how we approach diagnosis, treatment, and patient care. This power of AI does not diminish the value of healthcare professionals; rather, it elevates it. Those who embrace AI and integrate it into their practice will find themselves at the forefront of modern medicine, especially in the field of geriatrics where the complexities of care are manifold. Thus, as we navigate the inevitable tide of integrating AI into geriatrics and healthcare at large, it’s not a question of replacement but of enhancement and evolution. The key lies in harnessing AI as a powerful ally in our quest to provide the best possible care for older adults. Those who adapt, learn, and grow with these technological advancements will be the ones shaping the future of geriatrics care. They are the ones who will not be replaced, but will instead become irreplaceable. This work was supported by grants from the National Institute on Aging, part of the National Institutes of Health (P30AG073104 to Johns Hopkins University). None.

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