Comparing Dementia Classification by Self-Report and Administrative Records in the National Core Indicators-Aging and Disability Survey: A Predictive Modeling Approach

Abstract

Policymakers are interested in the long-term services and supports (LTSS) needs of people living with dementia. The National Core Indicators-Aging and Disability (NCI-AD) survey is conducted to evaluate LTSS care needs. However, dementia reporting in NCI-AD varies across states, and is either obtained from state administrative records or self-reported during the survey. We explored the implications of identifying dementia from administrative records versus self-report. We analyzed 24,569 NCI-AD respondents age 65+, of which 22.4% had dementia. To assess dementia accuracy by data source, we fit separate logistic regression models using the administrative and self-reported subsamples. We applied model coefficients to the population whose dementia status came from the opposite source. Using the administrative model to predict self-reported dementia resulted in higher sensitivity than using the self-report model to predict administrative dementia (43.8% vs. 37.9%). The self-report model’s diminished sensitivity suggests administrative records may capture cases of dementia missed by self-report.