Background: Frailty is increasingly recognized as a useful measure of vulnerability in older adults. Multiple claims-based frailty indices (CFIs) can readily identify individuals with frailty, but whether 1 CFI improves prediction over another is unknown. We sought to assess the ability of 5 distinct CFIs to predict long-term institutionalization (LTI) and mortality in older Veterans.
Methods: Retrospective study conducted in U.S. Veterans ≥65 years without prior LTI or hospice use in 2014. Five CFIs were compared: Kim, Orkaby (Veteran Affairs Frailty Index [VAFI]), Segal, Figueroa, and the JEN-FI, grounded in different theories of frailty: Rockwood cumulative deficit (Kim and VAFI), Fried physical phenotype (Segal), or expert opinion (Figueroa and JFI). The prevalence of frailty according to each CFI was compared. CFI performance for the coprimary outcomes of any LTI or mortality from 2015 to 2017 was examined. Because Segal and Kim include age, sex, or prior utilization, these variables were added to regression models to compare all 5 CFIs. Logistic regression was used to calculate model discrimination and calibration for both outcomes.
Results: A total of 3 million Veterans were included (mean age 75, 98% male participants, 80% White, and 9% Black). Frailty was identified for between 6.8% and 25.7% of the cohort with 2.6% identified as frail by all 5 CFIs. There was no meaningful difference between CFIs in the area under the receiver operating characteristic curve for LTI (0.78-0.80) or mortality (0.77-0.79).
Conclusions: Based on different frailty constructs, and identifying different subsets of the population, all 5 CFIs similarly predicted LTI or death, suggesting each could be used for prediction or analytics.
Published by Oxford University Press on behalf of The Gerontological Society of America 2023.