Dr. Shanna Burke, assistant professor in the School of Social Work at the FIU Robert Stempel College of Public Health & Social Work, received a $99,994 grant funded by the Florida Department of Health through the Ed and Ethel Moore Alzheimer’s Disease Research Program.
[Photo: Dr. Shanna Burke]
Researchers at any university or research institute in Florida were eligible to apply and in the end, a total of twenty-seven research grants were awarded through a peer-reviewed, competitive process based on recommendations by the Alzheimer’s Disease Research Grant Advisory Board.
Collaborating with Christopher Barnes and Kevin Hanson from the Translational Science Information Technology Department in the University of Florida Clinical and Translational Science Institute, Dr. Burke aims to:
Dr. Burke’s study has the potential to affect the health of Floridians by increasing the precision of neurodegenerative diagnosis related to the Alzheimer’s disease continuum. In under-resourced and understaffed health care settings, the proposed technology has the potential to allow free-standing memory disorder and primary care clinics to provide the expert detection and diagnostic services generally delivered by University Centers. Given that the Alzheimer’s disease pathophysiological process likely begins 10-20 years prior to any observable symptoms, it is crucial to identify the early contributing risk factors, which may be revealed through an algorithm that can quickly and precisely simultaneously account for multiple variables. Diagnostic services are especially necessary in Florida where 53 of 67 of counties have an above-average share of people 65 and older (Pew Research Center, 2015). This project has the potential to affect a large share of the current aging population in Florida, as the State continues to attract older adults in the winter months and as a prime retirement destination.
This study aims to make a significant contribution to the Alzheimer’s disease field by applying an algorithmic diagnosis to the records obtained from observations of over 33,000 people in the United States. Diagnostic classification using an algorithm will allow researchers and physicians to more precisely define and delineate risk factors associated with each cognitive status. The idea is that further definition of each cognitive status and its associated factors will contribute to early detection of potential mild cognitive impairment and/or probable Alzheimer’s disease.
Speaking about this research, Dr. Burke stated: “This grant provides the opportunity to revise the original algorithmic diagnosis to incorporate neuropsychological assessments that are used by more than 60-80 percent of the Alzheimer’s Disease Centers in the United States and are likely to be used by most free-standing memory disorders clinics. Some Centers utilize a consensus approach to a cognitive status assessment, while others utilize an algorithm to ensure continuity between the diagnosis of the physician/medical consensus team and the neuropsychiatrist performing the cognitive testing. The current study seeks to attempt to computerize that ‘conversation’ by taking into account a large number of factors simultaneously and applying the diagnostic algorithm to arrive at a consistently accurate diagnosis. An accurate diagnosis the first time will allow for the correct treatment plan to commence in a timely fashion.”