Can computer profiling be used to inform more equitable healthcare for individuals with Alzheimer’s?
Wenbo Wu, Ph.D.
New York University Grossman School of Medicine
New York, NY - United States
According to the 2023 Alzheimer’s Association Facts and Figures report, older Black/African Americans and Hispanic/Latino Americans are disproportionately more likely than older White Americans to have Alzheimer’s or other dementias. This report also highlights that older Black/African Americans and Hispanic/Latino Americans are more likely to have a missed diagnosis of Alzheimer’s than older White Americans. However, the health system factors that are associated with and contribute to these racial/ethnic disparities in Alzheimer’s care are not yet fully understood. Dr. Wenbo Wu and colleagues believe that an advanced computer technique called deep learning could hold the key to identifying health care patterns that are associated with health care disparities in Alzheimer’s.
Dr. Wu’s team will leverage existing datasets in the United States including health care data from Medicare inpatient claims. They will first examine the difference in frequency of hospital readmissions between individuals living with Alzheimer’s across racial/ethnic groups. Next, the researchers will use deep learning techniques to identify hospitals with significant racial/ethnic disparities in their health care services for individuals with Alzheimer’s. Lastly, the team will develop computer software programs and graphing tools to share their research findings.
The results of this study may help provide insights into which health system factors are associated with racial/ethnic disparities in dementia diagnosis and care in the United States. If successful, the findings may help policymakers to focus on communities at greatest risk for Alzheimer’s and dementia and to eliminate barriers to quality health care.
Back to Top