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Updated: Apr 17, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Brain health care accelerator: A primary care-centered model for scaling dementia diagnosis and care
Jeffrey M Burns1,2,3, Jill K Morris1,2, Eric D Vidoni1,2
1Department of Neurology, University of Kansas Medical Center, Kansas City, Kansas, USA.
Abstract:
Plasma biomarkers and disease-modifying therapies for early Alzheimer's disease have created an urgent need for scalable care models. In this Perspectives, we describe how a health system is adapting dementia care delivery through a primary care provider (PCP)-centered initiative designed to improve diagnostic readiness and care capacity. The program integrates (1) blood-based biomarker testing into clinical workflows, (2) a Cognitive Assessment Visit (CAV) supported by Electronic Health Record-embedded decision tools, and (3) memory care co-management. Early implementation demonstrates that PCPs can be empowered to diagnose and manage cognitive impairment through structured workflows, targeted training, and specialist collaboration. In the first 26 weeks, 1,331 plasma p-tau217 tests were ordered by 104 clinicians, including 58 PCPs; 59 CAVs were completed by nine PCPs; and more than 330 asynchronous e-consults expanded specialist access. These results highlight the feasibility and challenges of integrating biomarker-informed dementia care within primary care workflows.
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