Researchers from Corewell Health™ and Michigan State University are the first in the state to use de-identified electronic health records of more than 1.5 million patients to determine the incidence rates and risk factors of mild cognitive impairment, or MCI, in rural and urban areas across the West to analyze. Michigan.
The results showed that many cases could go undetected among those living in rural communities in the area, and researchers will now use the findings to develop AI tools that can detect MCI earlier in patients across the country.
The retrospective study, which includes ten years of historical patient data, has now been published in the journal Alzheimer’s and dementia: translational research and clinical interventions and it is the first large-scale analysis that represents most of Western Michigan’s population, with some findings surprising the study’s authors.
While we had our suspicions about what we would find; We did not expect the potential rate of underdiagnosis of MCI in some rural areas of West Michigan to be so high.”
Bin Chen, Ph.D., associate professor at MSU College of Human Medicine and co-principal investigator of the study
According to Chen, individuals typically experience MCI before developing dementia. Yet the study found that patients who progressed directly to dementia without a prior MCI diagnosis, referred to in the study as MCI skippers, were three times more common than those initially identified with MCI.
“This tells us that MCI may go unreported in some patients,” Chen said.
David Chesla, co-principal investigator and senior director of research data management at Corewell Health Research Institute in Grand Rapids, Michigan, agreed and said this underreporting may be causing the MCI incidence rates to be so much lower.
“Our hypothesis from the beginning of this work was that there would be underreporting of cognitive impairment in Western Michigan communities; we just didn’t know to what extent,” Chesla said. “Our suspicion was initially derived from national data reporting a growing incidence of MCI within our aging US population. Our patient data reflects a subset of the national data; however, the incidence of our patient MCI in West Michigan is significantly lower than national averages .
National averages can range from 10% to 18% depending on race, age and time frame in which the data was collected.
Chesla also indicated that the research team decided to delve deeper into the geographic distribution of patients, which allowed them to distinguish whether patients were urban or rural, something he said has not been done before. This provided further evidence that there is potential under-reporting, with the ratio of MCI skippers to diagnosed MCI cases being 4.3 times higher in rural areas, compared to 2.8 times in urban areas.
While the lack of access to care in these communities, along with other reasons, could account for the higher rate of underreporting, Chesla said a limitation of the study was that it had to use information from a decade ago, when electronic recording systems were still in place. found to be at an early stage.
“Today, electronic health records are integrated into most healthcare systems, but because our work goes back in time, there may be fragmentation of the records that may also be the cause of the underreporting,” Chesla said.
Additional findings showed that although risk factors for MCI were similar between rural and urban populations, urban areas showed a greater range of risks, including being African American, hearing loss, inflammatory bowel disease, obstructive sleep apnea, and insomnia. The most common risk factors for MCI are diabetes, stroke, Parkinson’s disease and older age.
According to the researchers, the massive amount of data now gives them the opportunity to use artificial intelligence, or AI, to build powerful machine learning models that can identify higher-risk patients earlier across the state and potentially across the country. Early diagnosis has been shown to be key to potentially reversing or slowing the progression of cognitive impairment.
“The goal is to integrate this tool into healthcare systems everywhere so that it can help physicians identify and treat MCI patients more effectively,” Chen said.
But for now, Chesla suggests that if people experience symptoms such as hearing loss, mood swings, or other more common symptoms, they should not hesitate to contact their doctor or a healthcare provider for help.
“We are in an era where there are care plans and rehabilitation services that can help slow or even reverse cognitive impairment when caught early,” Chesla said.
The study was co-led by Xiaodan Zhang, a data scientist at the MSU College of Human Medicine, and Martin Witteveen-Lane, a data engineer at Corewell Health, and supported by the Corewell Health-MSU Alliance and the National Institutes of Health.