Digital Detection of Dementia (D Cubed) Studies: D3
Status: Recruiting
Location: See location...
Intervention Type: Other
Study Type: Interventional
Study Phase: Not Applicable
SUMMARY
The specific aim of the pragmatic trial is to evaluate the practical utility and effect of the PDM, the QDRS, and the combined approach (PDM + QDRS) in improving the annual rate of new documented ADRD diagnosis in primary care practices.
Eligibility
Participation Requirements
Sex: All
Minimum Age: 65
Healthy Volunteers: f
View:
• 65 years or older
• At least one visit to primary care practice within the past year
• Ability to provide informed consent
• Ability to communicate in English or Spanish
• Available EHR data from at least the past three years
Locations
United States
Florida
University of Miami School of Medicine
RECRUITING
Boca Raton
Contact Information
Primary
Malaz Boustani, MD, MPH
mboustan@iu.edu
317-274-8536
Backup
Katrina Coppedge, BA
kcoppedg@iu.edu
317-278-1602
Time Frame
Start Date: 2023-11-08
Estimated Completion Date: 2025-11-08
Participants
Target number of participants: 3150
Treatments
No_intervention: Annual Well Visit or any other visit to Primary Care Doctor
Annual Well Visit or any other visit to Primary Care Doctor: This is the usual care arm. Electronic Health Record Data for patients from the clinics randomized to usual care will be collected for comparison with the other 2 arms. Patients from these primary care clinics must have had a visit to their doctor either as an annual well visit (AWV) or any other type of visit. These clinics will not have to do anything for the study but run their business as usual without altering anything.
Experimental: Passive Digital Marker (PDM)
Passive Digital Marker (PDM): Electronic Health Record Data from those clinics randomized to PDM will be run through the PDM, a machine learning algorithm which can predict ADRD one year and three years prior to its onset.
Active_comparator: Passive Digital Marker (PDM) + Quick Dementia Rating Scale (QDRS)
Patients in the primary care clinics randomized to PDM+QDRS will have Electronic Health Record Data of their patients run through the PDM, a machine learning algorithm which can predict ADRD one year and three years prior to its onset. In addition, patients from these clinics will have their patients complete the QDRS, a validated patient reported outcome (PRO) tool. This combined approach will assess the value of early detection of ADRD and if the annual well visit can overcome the barriers related to early detection of ADRD.
Related Therapeutic Areas
Sponsors
Collaborators: National Institute on Aging (NIA)
Leads: Indiana University