Cognitive impairment related to dementia is frequently under-diagnosed in primary care settings despite the availability of numerous assessment tools. Missed detection delays treatment of reversible conditions as well as provision of support services and critical planning. This problem is more prevalent among older African- Americans and Hispanics than among older whites. Our group has two decades of experience developing tools to detect dementia in health disparate populations. Notably, we developed the Picture-based Memory Impairment Screen (PMIS) that relies on culture fair pictures and does not need to be administered by a medical professional. We also validated the Motoric Cognitive Risk syndrome (MCR). This highly accessible test relies on the presence of slow gait and cognitive self-complaints to identify individuals at high risk of converting to dementia. Both the PMIS and the MCR are highly sensitive and specific first-line assays that can be followed up with more thorough and complex cognitive testing. Building on our work, we propose to develop and validate a 5-minute screen (5-Cog) to identify persons at high risk of developing dementia and to flag them for further evaluation. We propose to do this in urban, multi-ethnic Bronx primary care populations with socio-economic challenges. The 5-Cog battery will include the PMIS, MCR syndrome diagnosis, and a 2-item depression screener. In the 18-month UG3 phase, we propose to fine-tune the components of the 5-Cog that will be tested in a health disparate population in the Bronx, and could be extended to other participating sites under this RFA. We will also test the feasibility of administering the 5-Cog by non-physicians to increase accessibility of our battery in primary care settings. In the 42-month UH3 phase, we propose a single-blind, randomized clinical trial in 1,200 older primary care patients presenting with cognitive complaints who will be randomized to receive either the 5-Cog battery (intervention group) or a 5-minute health literacy questionnaire (control group). Non-physicians will administer the intervention and control tests in primary care sites, and test results will be provided to primary care physicians for further action. ?Improved dementia care? will be measured by using a composite endpoint including new Mild Cognitive Impairment syndrome (MCI) or dementia diagnoses, laboratory investigations to rule out reversible causes of cognitive impairment, new dementia medication prescriptions, and specialist or social work referrals. The outcome events will be tracked using our electronic health record system. We will also conduct health care utilization and cost effectiveness analysis of the 5-Cog intervention in real-world settings. By the end of the UH3 phase, we will create a web registry to make 5-Cog test items and procedures available for download by health care professionals. The 5-Cog battery will overcome many of the implementation barriers of previous cognitive screens; it will be fast, low cost, easy to implement (requires only pen, paper and stopwatch), can be administered by non- clinicians after minimal training, not educationally or culturally biased, not confounded by depression and does not require informants.

Public Health Relevance

Despite the availability of numerous cognitive assessment tools, cognitive impairment related to dementia is frequently under-diagnosed in primary care settings and is a more prevalent problem among older African-Americans and Hispanics than among older whites. To overcome the technical, cultural and logistic barriers of current cognitive screens in primary care settings we propose to develop and validate a 5-minute cognitive screen coupled with a decision tree to identify and manage persons at high risk of developing dementia in multi-ethnic primary care populations with socio-economic challenges.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Project #
1UG3NS105565-01
Application #
9482508
Study Section
Special Emphasis Panel (ZNS1)
Program Officer
Moy, Claudia S
Project Start
2017-09-25
Project End
2022-08-31
Budget Start
2017-09-25
Budget End
2018-08-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Albert Einstein College of Medicine, Inc
Department
Type
DUNS #
079783367
City
Bronx
State
NY
Country
United States
Zip Code
10461