Cognitive Dysfunction, Dementia
Conditions
Brief summary
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).
Detailed 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.
Interventions
OTHERToolboxDetect
The clinician or staff member will identify the patient by either scanning a barcode or entering his/her name, age and medical record number on an administrative screen (allowing for proper routing of test results). After completing the test, a 'submit' button will automatically generate a secure HL7 message, sharing 1) a binary classification of the results ('impaired cognition' or 'normal function'), 2) the quantitative ToolboxDetect score, and 3) brief clinical decision support to rule out any reversible causes. These results will be linked to a discrete, queriable, Epic SmartData element. As patients undergo multiple AWVs over time, ToolboxDetect quantitative scores will be displayed in Epic Synopsis Activity, a graphical display that can visualize trend data (e.g. patient vitals) and calculate a percentage change from the prior year. This will allow a clinician to establish a patient's own baseline (instead of using normative data only) for reference.
Sponsors
Northwestern University
ACCESS Community Health Network
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SCREENING
Masking
DOUBLE (Investigator, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
65 Years to No maximum
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Rate of detected impairment | Up to 3 years | This will be operationalized as either results of an any administered cognitive test suggesting impairment ('detected'), or having any relevant ICD 10 classification code recorded in a patient's record after the trial launch date and throughout follow-up observation period ('diagnosis'). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Rate of cognitive testing | Up to 3 years | Extraction from the enterprise data warehouse (EDW) of elements used to document cognitive assessment |
| Rate of detected cases with mild impairment | Up to 3 years | Mild vs. other impairment rates will be compared across trial arms, operationalized by ICD code groupings. |
| Rate of cognition-related referrals | Up to 3 years | Extraction from the electronic data warehouse for whether or not a cognitive-related referral was made (medical or non-medical) following a "detected" cognitive screen |
| Caregiver involvement | Up to 3 years | Text search of clinic note from any follow-up visit post AWV, wellness visit mention of accompanying family member/caregiver; extraction from EDW to determine if proxy access to patient's MyChart portal has been shared. |
Countries
United States
Outcome results
None listed