Our study objective is to widely implement and evaluate a user-centered, scalable, electronic health record (EHR)-linked strategy for the routine detection of cognitive decline among diverse primary care settings. We will conduct a large-scale, primary care practice-randomized trial to implement and comprehensively evaluate ToolboxDetect as a standard of care with AWVs, linked to an EHR (Epic). Diverse, academic and community settings are included to optimize future dissemination efforts.
ToolboxDetect is an iPad-based, self-administered assessment that leverages two well validated measures from the NIH Toolbox Cognition Battery: Dimensional Change Card Sorting (for executive function) and the Picture Sequence Memory (for episodic memory). It takes approximately 7-8 minutes to administer, and for practices randomized to the ToolboxDetect arm, this will be used as the practice standard to fulfill the requirement for cognitive testing as part of the Medicare Annual Wellness Visit (AWV).
The aims of our investigation are to:
1. Evaluate the effectiveness of ToolboxDetect, compared to enhanced usual care, to promote timely detection of cognitive decline and its care management.
2. Disseminate and implement ToolboxDetect among a large Federally Qualified Health Center Network and assess its feasibility and acceptability for use;
3. Investigate the fidelity of ToolboxDetect, and identify any patient, caregiver, healthcare provider and/or system barriers to its optimal, sustained implementation;
4. Determine costs associated with implementing ToolboxDetect from a primary care perspective.
