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

Indiana University3,454 enrolled

Overview

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.

Study Type

INTERVENTIONAL

Allocation

Purpose

SCREENING

Masking

NONE

Enrollment

3,454

Conditions

Mild Cognitive Impairment (MCI)

Interventions

Acceptability and Feasibility of Twistle messaging for PDM+ patientsBEHAVIORAL

PC patients identified by the PDM as high risk for developing or having undetected MCI or ADRD will receive the patient-informed message developed in Aim 2. The patient-informed message will include instructions for completing validated questions about subjective memory concerns. In addition, interested patients will have the option to schedule a visit with the BHN, or enroll in research opportunities.

Eligibility

Sex: ALLMin age: 65 Years

Medical Language ↔ Plain English

Inclusion Criteria: * 65 years and older; established patients of 12 selected clinics at IU Health PC who are identified by the PDM as high risk for developing or having undetected MCI or ADRD. Exclusion Criteria: * Patients younger than 65 years; new patients to IUH (less than 12 months); individuals whose primary language is neither English nor Spanish; and current diagnosis of ADRD or MCI.

Outcomes

Primary Outcomes

Implementation of the PDM to identify at risk patients

Implement the PDM, using IUH EHR data, to identify primary care patients aged 65 or older who a have undetected MCI or ADRD or who are at risk. Measured by the percentage of patients with subjective cognitive concerns, and their MoCA scores in comparison to match the epidemiological rates in the literature on undetected MCI and ADRD in PC (\~11-60%).