Researchers will aim to create and validate a risk calculator and screening tool to identify and test individuals with high risk of cognitive decline.
Darlene Floden, PhD
Cleveland Clinic announced they have been awarded a $2.6 million grant from the National Institute on Aging to develop and validate 2 automated tools – a risk calculator to identify patients at high risk of cognitive decline and a screening tool to test for the condition.
An interdisciplinary team at Cleveland Clinic aims to create a low-cost, time-efficient procedure that can be used in primary care settings to identify and screen patients at high risk of cognitive decline.
“Clinicians are facing an aging population, and with that comes an increased incidence of dementia,” said Cleveland Clinic neuropsychologist Darlene Floden, PhD, who led the multidisciplinary effort to obtain the grant. “There is a significant unmet need for a feasible way to efficiently screen this population on a large scale.”
While existing tests like the Montreal Cognitive Assessment (MoCA) and Mini-Cog are the current standard for screening, there are various challenges that accompany these tools. It can be time-intensive to administer within the timeframe of a typical appointment. Additionally, user error with paper-and-pencil tests has been well-documented in published studies.
The team’s five-year research project involves two phases. In the first, researchers will focus on developing and validating a low-cost risk calculator that estimates patients’ likelihood of experiencing cognitive declines over the next five years. They will collaborate with Michael Kattan, PhD, chair of the Department of Quantitative Health Sciences in Cleveland Clinic’s Lerner Research Institute. The tool uses information from the medical record, such as health status indicators, demographics and socioeconomic status, to predict who is at high risk for developing cognitive deficits.
The researchers also will test the longitudinal utility of a patient-administered tool developed by Floden and Robyn Busch, PhD. The new tool, called the Brief Assessment of Cognitive Health (BACH), is automated with auditory instructions and can be completed by the patient in the waiting room in about 15 minutes. The tool consists of a complex memory test, a formal depression screen and a medical history form.
Unlike the MoCA, the BACH also screens for several reversible causes of cognitive decline that provide avenues for treatment – depression, sleep disruption and stress – in addition to detecting cognitive problems. Moreover, the BACH is incorporated into the Epic electronic medical record platform used by Cleveland Clinic, so its results are automatically recorded in patients’ medical records. The researchers will compare the BACH to the MoCA and to neuropsychological testing to determine which is more sensitive to cognitive change over time.
For the project’s last three years, an implementation trial will be conducted to gauge the uptake and utility of the risk calculator and BACH in several primary care practices affiliated with Cleveland Clinic. “The approach will be modified during the course of this trial as we learn how these tools change physician behavior and patient treatment,” Floden said. “We will learn what works and what doesn’t and adapt as we go.”
Findings will be rolled out over the course of the trial. In addition, Floden and Busch plan to soon launch a web-based version of the BACH that people can complete at home. If these tools are validated and physicians find them useful, they hope to offer them to other large medical systems and insurers.
In addition to Kattan and Busch, other Cleveland Clinic collaborators include:
Robert Fox, MD, vice chair for research in the Neurological Institute; Kamini Krishnan, PhD, a neuropsychologist in the Lou Ruvo Center for Brain Health; Anita Misra-Hebert, MD, director of the Healthcare Delivery and Implementation Science Center; Elizabeth Pfoh, PhD, and Michael Rothberg, MD, MPH, of the Center for Value-Based Care Research; and Saket Saxena, MD, of the Center for Geriatric Medicine.