Digital Detection of Dementia (D Cubed) Studies: D3

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Indiana University

Status

Enrolling

Conditions

Alzheimer Disease and Related Dementias (ADRD)

Treatments

Other: Passive Digital Marker for screening for ADRD

Study type

Interventional

Funder types

Other
NIH

Identifiers

NCT06224205
2008372812b
R01AG069765-01 (U.S. NIH Grant/Contract)

Details and patient eligibility

About

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.

Full description

Alzheimer's disease and related dementias (ADRD) negatively impact millions of Americans with an annual societal cost of more than $200 million.1 Currently, half of Americans living with ADRD never receive a diagnosis.2-7 For those who do, the diagnosis often occurs two to five years after the onset of symptoms.6-9 As stated by the National Institute on Aging (NIA) (RFA-AG-20-051) "The inability to diagnose and treat cognitive impairment results in prolonged and expensive medical care" and "early detection could help persons with dementia and their care partners plan for the future". Furthermore, if the development of disease modifying therapeutics for ADRD is successful, this may require the use of such therapeutics at a very early stage of ADRD.1 However, the current approaches of using cognitive tests or biomarkers for early detection of ADRD are not scalable due to their low acceptance, their invasive nature, their cost, or their lack of accessibility in rural or underserved areas. Thus, the NIA called out for the development of low cost, effective, and scalable approaches for early detection of ADRD (RFA-AG-20-051). In response to the RFA-AG-20-051 call for the "validation, and translation of screening and assessment tools for measuring cognitive decline a pragmatic cluster-randomized controlled comparative effectiveness (NIH Stage IV) trial will be executed in Eskenazi Health in central Indiana and one additional replicated pragmatic trial among patients from diverse rural, suburban and urban primary care practices in south Florida. The pragmatic trial will incorporate the Passive Digital Marker (PDM) and the Quick Dementia Rating Scale (QDRS) within the Medicare paid Annual Wellness Visit (AWV) for a cohort of patients from practices across the two independent sites, with practices randomized in each pragmatic trial to one of the 3 arms (AWV alone, the AWV with PDM and the PDM and the QDRS). Quick Dementia Rating Scale (QDRS)- is a validated patient reported outcome (PRO) tool. Passive Digital Marker (PDM) - is a Machine Learning (ML) algorithm which can predict ADRD one year and three years prior to its onset by using routine care electronic health record (EHR) data. The algorithm was trained using structured and unstructured data from three EHR datasets: diagnosis (Dx), prescriptions (Rx), and medical notes (Nx). Individual algorithms derived from each of the three datasets were developed and compared to a combined one that included all three datasets.

Enrollment

3,150 estimated patients

Sex

All

Ages

65+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • 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

Exclusion criteria

  • Prior ADRD or mild cognitive impairment diagnosis as determined by ICD-10 code
  • Evidence of any history of prescription for a cholinesterase inhibitors or memantine.
  • Has serious mental illness such as bipolar or schizophrenia as determined by ICD-10 code
  • Permanent resident of a nursing facility

Trial design

Primary purpose

Screening

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Double Blind

3,150 participants in 3 patient groups

Annual Well Visit or any other visit to Primary Care Doctor
No Intervention group
Description:
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.
Passive Digital Marker (PDM)
Experimental group
Description:
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.
Treatment:
Other: Passive Digital Marker for screening for ADRD
Passive Digital Marker (PDM) + Quick Dementia Rating Scale (QDRS)
Active Comparator group
Description:
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.
Treatment:
Other: Passive Digital Marker for screening for ADRD

Trial contacts and locations

1

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Central trial contact

Malaz Boustani, MD, MPH; Katrina Coppedge, BA

Data sourced from clinicaltrials.gov

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