Early and equitable detection of cognitive impairment can benefit patients and their families. Delaying diagnosis leads to poor health outcomes for patients and their care partners and limits access to resources for treatment and care management services.

The study of 204 socially and economically vulnerable older adults (average age 70 years) determined that African American individuals had more than twice the odds of unrecognized cognitive impairment (mild cognitive impairment or dementia).

Approximately 82 percent of Black patients had undiagnosed dementia or mild cognitive impairment, compared with 64 percent of White patients. Only 26 percent of all study participants had no cognitive impairment.

The study population was slightly more than half African American and predominantly female. The association between race and cognitive impairment did not differ by sex, age or years of education.

On average each study participant was receiving primary care for three chronic medical conditions such as diabetes, heart disease, hypertension or chronic obstructive pulmonary disease and they were taking five medications.

To make the diagnosis, patients and family members were interviewed, three years of the patient’s medical records were reviewed, and full comprehensive cognitive testing and neurological examinations were administered.

“We know from our previous work that there is stigma attached with diagnosis of cognitive impairment as well as fear about loss of independence. So, the patient and often their care partner are unlikely to ask that their primary care provider check on the patient’s brain health,” said study senior author Malaz Boustani, M.D., MPH. “To provide quality care and to overcome disparity as well as stigma, we have to develop scalable, timely, equitable and sustainable approaches, strategies, processes and tools for early detection of cognitive impairment in primary care in general and, specifically, in Federally Qualified Health Centers, which predominantly serve low-income and medically underserved communities.

“Early detection would allow patients and care partners access to three recent breakthroughs in brain care. One is the availability of amyloid lowering therapy that can change the trajectory of cognitive and functional decline in people with Alzheimer’s disease. Number two is the new alternative payment model from the Centers for Medicare and Medicaid Services (CMS) to help cover the expenses of providing comprehensive dementia care services, including support for care partners.

“Thirdly early detection opens the door to reduction to the risk for future cognitive impairment by implementing lifestyle changes targeting blood pressure, diabetes, cholesterol, sleep and depression as well as cognitive and physical exercises.”

Using machine learning to extract information recorded in the medical notes of a patient’s electronic health record, Dr. Boustani and colleagues have developed and are testing a low cost, scalable methodology to spot cognitive impairment or facilitate early detection of individuals at risk of developing dementia. They call it zero minute assessment at less than a dollar cost and view it as a culturally sensitive solution — a healthcare system redesign — for a problem which the healthcare system doesn’t have time or financial capital to solve.

The study authors write, “The differences in diagnoses by race are likely due to both a higher prevalence of dementia in this subgroup and a lack of embedded workflows that support detection and timely diagnosis among these patients owing to patient, physician, and health care factors that need to be addressed urgently.”

“Prevalence of Unrecognized Cognitive Impairment in Federally Qualified Health Centers” is published in JAMA Network Open. The study was funded by the National Institutes of Health’s National Institute on Aging, grant R01AG069765 (PIs: Malaz Boustani, Zina Ben Miled and James Galvin).

Regenstrief Institute study authors in addition to Dr. Boustani are Research Scientist Nicole Fowler, PhD, MHSA, and Arthur Owora, PhD, MPH, and Affiliate Scientist Zina Ben Miled, PhD.