ToolBox Detect: Low Cost Detection of Cognitive Decline in Primary Care Settings

Northwestern University

Status: Enrolling

Conditions: Cognitive Dysfunction; Dementia

Treatments: Other: ToolboxDetect

Study type: Interventional

Funder types: Other

Identifiers

NCT04852601

R01AG069762

Details and patient eligibility

About

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. This strategy, called ToolboxDetect, will provide an efficient and sensitive cognitive screen that can be easily implemented in everyday clinical settings, and is responsive to patient, family, and caregiver concerns for potential symptoms of cognitive decline (CD) and cognitive impairment (CI).

Full description

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.

Enrollment: 41,500 estimated patients

Sex: All

Ages: 65+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. Individuals aged 65 and older will be considered.
2. Adults who may or may not have cognitive impairments.
3. Practices affiliated with Northwestern Medicine and Access Community Health Network.

Exclusion criteria

1. Severe, uncorrectable vision or hearing impairment

Trial design

Primary purpose: Screening

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Double Blind

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41,500 participants in 2 patient groups

ToolboxDetect Strategy

Experimental group

Description:

All practices randomized to the intervention arm will implement the ToolboxDetect battery as the standard of care routine cognitive assessment to fulfill the Medicare Annual Wellness Visit (AWV) requirement. The 7-8 minute ToolboxDetect battery contains self-administered versions of the NIH ToolBox Picture Sequence Memory Test (PSM) and the NIH ToolBox Dimensional Change Card Sorting (DCCS). PSM measures episodic memory and DCCS tests executive functioning. The validated ToolboxDetect application will be imparted either as an application on an iPad or on a PC desktop/laptop computer commonly found in a clinical exam room for EHR access.

Treatment:

Other: ToolboxDetect

Enhanced Usual Care

No Intervention group

Description:

At Northwestern Medicine, cognitive assessments included in Annual Wellness Visits or other routine or sick/problem-based visits vary by practice and also by clinician. However, the choice of test was limited to either a Mini-Cog©, Montreal Cognitive Assessment (MoCA), or Mini Mental Status Exam (MMSE). While we will not make any explicit recommendations to these practices with regard to their use of a cognitive assessment, we will ensure that 1) any chosen test is linked to an Epic SmartData element, which will allow the clinician to record the results of the test as discrete data (which can then be queried), and that 2) providers receive a compiled list of local medical and non-medical referrals for any detected cases of CI. The Alzheimer's Association recommendations for early detection efforts among primary care practices will also be provided to each clinic's medical leadership.