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Colón-Emeric CS, Huang J, Pieper CF, Bettger JP, Roth DL, Sheehan OC. Cost trajectories as a measure of functional resilience after hospitalization in older adults. Aging Clinical and Experimental Research. 2020 Feb 14.
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Abstract: BACKGROUND: Administrative data sets lack functional measures. AIM: We examined whether trajectories of cost can be used as a marker of functional recovery after hospitalization. METHODS: Secondary analysis of the National Health and Aging Trends Study merged with Centers for Medicare and Medicaid Services data. Community-dwelling participants with a first hospitalization occurring after any annual survey were included (N? = 937). Monthly total cost trajectories were constructed for the 3 months before and 3 months following hospitalization. Growth mixture models identified groups of patients with similar trajectories. The association of cost classes with five functional outcomes was examined using multivariate models, controlling for pre-hospitalization function and lead time. RESULTS: Four cost trajectory classes describing common recovery patterns were identified-persistently high, persistently moderate, low-spike-recover, and low variable. Cost class membership was significantly associated with change in Activities of Daily Living (ADL), instrumental ADL, Short Physical Performance Battery, and grip strength (p? < 0.005), but not gait speed (p? = 0.08). The proportion of patients who maintained or improved SPPB score was 46.8% in the persistently high, 49.2% in the persistently moderate, 52.7% in the low-spike-recover, and 57.2% in the low-variable groups. In models adjusted for known predictors of functional outcome, the magnitude and direction of association was maintained but significance was lost, indicating that cost trajectories'' mirror is mediated by predictors of recovery not available in administrative data. CONCLUSION: Cost trajectories and total costs are associated with functional recovery following hospitalization in older adults. Cost may be useful as a measure of recovery in administrative data.

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