Validation of Claims Algorithms to Identify Alzheimer's Disease and Related Dementias.

TitleValidation of Claims Algorithms to Identify Alzheimer's Disease and Related Dementias.
Publication TypeJournal Article
Year of Publication2022
AuthorsMcCarthy, EP, Chang, C-H, Tilton, N, Kabeto, MU, Langa, KM, Bynum, JPW
JournalThe Journals of Gerontology, Series A
ISSN Number1758-535X
KeywordsAccuracy, algorithm, Dementia, Diagnosis, Medicare

BACKGROUND: Using billing data generated through healthcare delivery to identify individuals with dementia has become important in research. To inform tradeoffs between approaches, we tested the validity of different Medicare claims-based algorithms.

METHODS: We included 5,784 Medicare-enrolled, Health and Retirement Study participants aged >65 years in 2012 clinically assessed for cognitive status over multiple waves and determined performance characteristics of different claims-based algorithms.

RESULTS: Positive predictive value (PPV) of claims ranged from 53.8-70.3% and was highest using a revised algorithm and 1-year of observation. The trade-off of greater PPV was lower sensitivity; sensitivity could be maximized using 3-years of observation. All algorithms had low sensitivity (31.3-56.8%) and high specificity (92.3-98.0%). Algorithm test performance varied by participant characteristics, including age and race.

CONCLUSIONS: Revised algorithms for dementia diagnosis using Medicare administrative data have reasonable accuracy for research purposes, but investigators should be cognizant of the trade-offs in accuracy among the approaches they consider.

Citation Key12060
PubMed ID34919686
PubMed Central IDPMC9159657