UPDATE: A groundbreaking new AI tool has just been confirmed to enhance the early detection of Alzheimer’s disease and related dementias (ADRD) in primary care settings. Researchers at the Indiana University School of Medicine, along with partners from the Regenstrief Institute, Eskenazi Health, University of Miami, and Lamar University, have developed a fully digital, zero-cost method that could transform how dementia is diagnosed in busy clinics.
In a randomized clinical trial involving over 5,300 patients, this innovative approach combines the Quick Dementia Rating System (QDRS) with a Passive Digital Marker (PDM) powered by machine learning. The results are staggering: the incidence rate of ADRD diagnoses surged by 31% within just 12 months, all without requiring any additional time or effort from healthcare providers.
Researchers assert that this dual approach represents a significant leap in integrating artificial intelligence and patient-reported outcomes into everyday clinical practice. By utilizing existing electronic health records (EHRs), the tool identifies crucial factors such as memory issues and vascular concerns, making it easier to flag patients who need further evaluation.
“This is the most scalable approach to early detection that I know of,” stated Malaz A. Boustani, MD, a research scientist at Regenstrief and co-developer of the PDM. Unlike traditional methods that typically require at least five minutes of a clinician’s time, this new system operates seamlessly within the existing EHR framework, requiring no extra clinician involvement or associated costs.
The trial, conducted across nine federally qualified health centers in Indianapolis, demonstrated how technology can alleviate burdens on primary care teams while improving outcomes for older adults. Patients aged 65 and older participated in the study, which utilized the QDRS survey embedded in their patient portal. The PDM continuously analyzed clinical data to identify at-risk individuals, delivering results directly to clinicians’ EHR inboxes only when action was needed.
The impact of this approach extends beyond detection: it also led to a remarkable 41% increase in follow-up diagnostic assessments, such as neuroimaging and cognitive testing. This suggests that early detection can lead to more timely and accessible dementia care for underserved populations, addressing a critical gap in healthcare.
In their published paper in JAMA Network Open, Boustani and his colleagues noted that over 50% of older adults in primary care never receive a timely diagnosis of ADRD. The challenges of limited consultation time and the stigma surrounding dementia often result in missed opportunities for early intervention.
“This work represents the next phase of our half-century legacy at Regenstrief,” Boustani added. “We’ve shown that it’s possible to bring the power of AI and patient-reported outcomes directly into the clinic—seamlessly, affordably, and at scale.”
The QDRS, designed to empower patients and families to report cognitive changes quickly, combined with the PDM, opens new avenues for early detection of dementia. As healthcare systems worldwide face increasing demands, this digital solution could level the playing field, ensuring equitable access to critical diagnostic services.
As this urgent development unfolds, healthcare providers and policymakers are encouraged to explore the integration of these innovative tools into their practices. The potential benefits for patient outcomes are profound, paving the way for a brighter future in dementia care.
Stay tuned for further updates on how this AI tool reshapes the landscape of early dementia detection across the globe.
