Using Consumer Credit Data To Identify Precursors And Consequences Of Cognitive Impairment

• PI:              Lauren Nicholas, PhD
• Funder:     The National Institute of Aging
• Status:      Ongoing

To date, the potential health uses of consumer financial data have largely been ignored, particularly for the older population. This exploratory project considers the utility of a big data resource from outside healthcare; consumer debt characteristics collected in credit reports, to predict new cases of cognitive impairment and dementia and healthcare utilization of cognitively impaired patients.

The project has three research aims: (1) to create datasets linking the Federal Reserve Bank of New York/Equifax Consumer Credit Panel to national Medicare claims and survey data; (2) to assess the utility of consumer debt characteristics as predictors of cognitive decline; (3) to assess the utility of consumer debt characteristics as predictors of hospitalization and nursing home use among patients with dementia. This type of surveillance can help to protect older adults from fraud and other financial risks and assist long-distance caregivers to know when to intervene. Findings have immediate relevance for banks and policymakers designing banking and money management solutions for the growing dementia population. This project also serves as a proof-of-concept for the utility of financial big data for clinical diagnoses and design of products to help cognitively impaired older adults.