Abstract
BACKGROUND
Medicare fee-for-service (FFS) claims data are increasingly leveraged for dementia research. Few studies address the validity of recent claims data to identify dementia, or carefully evaluate characteristics of those assigned the wrong diagnosis in claims.
METHODS
We used claims data from 2014-2018, linked to participants administered rigorous, annual dementia evaluations in five cohorts at the Rush Alzheimer’s Disease Center. We compared prevalent dementia diagnosed through the 2016 cohort evaluation versus claims identification of dementia, applying the Bynum-standard algorithm.
RESULTS
Of 1,054 participants with Medicare Parts A and B FFS in a 3-year window surrounding their 2016 index date, 136 had prevalent dementia diagnosed during cohort evaluations; the claims algorithm yielded 217. Sensitivity of claims diagnosis was 79%, specificity 88%, positive predictive value 50%, negative predictive value 97%, and overall accuracy 87%. White participants were disproportionately represented among detected dementia cases (true-positive) versus cases missed (false-negative) by claims (90% versus 75%, respectively, p=0.04). Dementia appeared more severe in detected than missed cases in claims (mean MMSE=15.4 versus 22.0, respectively, p<0.001; 28% with no limitations in activities of daily living versus 45%, p=0.046). By contrast, those with “over-diagnosis” of dementia in claims (false-positive) had several worse health indicators than true negatives (eg, self-reported memory concerns=51% versus 29%, respectively, p<0.001; mild cognitive impairment in cohort evaluation=72% versus 44%, p<0.001; mean comorbidities=7 versus 4, p<0.001).
CONCLUSIONS
Recent Medicare claims perform reasonably well in identifying dementia; however, there are consistent differences in cases of dementia identified through claims than in rigorous cohort evaluations.