Innovative Cognitive Impairment Case Finding and Engagement for Diverse Participation in Alzheimer's Disease Care, Treatment, And Research

Recent studies have highlighted the potential use of electronic health record (EHR) data for scalable and less biased identification of people who may have or be at risk of developing MCI or ADRD at the population level.8,9 Using data from the EHR in advance of PC visits can systematically identify patients with undetected MCI and ADRD. At Indiana University (IU), researchers developed a Passive Digital Marker (PDM) to enable early detection of ADRD with an 80% accuracy for one-year and three-year prediction horizons.8,9 Despite the accuracy of the PDM, the feasibility, acceptability, and overall effectiveness of its use for early detection of ADRD in PC remains unclear. Building on this innovative tool and the ongoing engagement in IUH PC for early detection of ADRD, we propose a project to test the acceptability and feasibility of implementing the PDM in IUH PC to identify people with and at risk of MCI and ADRD and measure if we can increase patient engagement in research and evidence-based follow-up care with the IUH Brain Health Navigator (BHN). The BHN, is primary care based registered nurse with special training to conduct additional assessments of patients following a positive ADRD screen to identify possible underlying causes of cognitive impairment and assist the PCP to facilitate the patient's next steps for diagnostic assessment.