AI and digital tools improve early dementia detection in primary care
Integrating AI tools into electronic health records boosts follow-up assessments and ensures broader access to early dementia care.
Early detection of Alzheimer’s is often limited in primary care due to short consultations, focus on other health issues, and stigma. Researchers have now demonstrated that a fully digital, zero-cost approach can overcome these barriers without requiring additional clinician time.
A pragmatic clinical trial involving over 5,000 patients tested a dual method combining the Quick Dementia Rating System (QDRS), a ten-question patient-reported survey, with an AI-powered passive digital marker.
The approach, embedded in electronic health records, increased new dementia diagnoses by 31 percent compared with usual care and prompted 41 percent more follow-up assessments, such as cognitive tests and neuroimaging.
The passive digital marker from Regenstrief uses machine learning to analyse health records for memory issues and vascular concerns. Open-source and free, it flags at-risk patients and sends results to clinicians’ EHRs with no extra time or staff needed.
Researchers highlight that embedding these tools directly into routine care can improve equity, thereby reaching populations that the healthcare system has traditionally underserved.
Experts say that using patient-reported outcomes with AI is a scalable and efficient way to detect dementia early, without adding burden to primary care teams.
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