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ToolBox Detect: Low Cost Detection of Cognitive Decline in Primary Care Settings
Sponsor: Northwestern University
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).
Key Details
Gender
All
Age Range
65 Years - Any
Study Type
INTERVENTIONAL
Enrollment
41500
Start Date
2022-08-25
Completion Date
2026-05
Last Updated
2026-03-06
Healthy Volunteers
No
Conditions
Interventions
ToolboxDetect
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.
Locations (1)
Northwestern University
Chicago, Illinois, United States