Predicting 3-year mortality and admission to acute-care hospitals, skilled nursing facilities, and long-term care facilities in Medicare beneficiaries.

Kurichi JE, Bogner HR, Streim JE, Xie D, Kwong PL, Saliba D, Hennessy S. Predicting 3-year mortality and admission to acute-care hospitals, skilled nursing facilities, and long-term care facilities in Medicare beneficiaries. Archives of Gerontology and Geriatrics. 2017 Nov 1; 73:248-256.

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Abstract:

PURPOSE: The ability to predict mortality and admission to acute care hospitals, skilled nursing facilities (SNFs), and long-term care (LTC) facilities in the elderly and how it varies by activity of daily living (ADL) and instrumental ADL (IADL) status could be useful in measuring the success or failure of economic, social, or health policies aimed at disability prevention and management. We sought to derive and assess the predictive performance of rules to predict 3-year mortality and admission to acute care hospitals, SNFs, and LTC facilities among Medicare beneficiaries with differing ADL and IADL functioning levels. METHODS: Prospective cohort using Medicare Current Beneficiary Survey data from the 2001 to 2007 entry panels. In all, 23,407 community-dwelling Medicare beneficiaries were included. Multivariable logistic models created predicted probabilities for all-cause mortality and admission to acute care hospitals, SNFs, and LTC facilities, adjusting for sociodemographics, health conditions, impairments, behavior, and function. RESULTS: Sixteen, 22, 14, and 14 predictors remained in the final parsimonious model predicting 3-year all-cause mortality, inpatient admission, SNF admission, and LTC facility admission, respectively. The C-statistic for predicting 3-year all-cause mortality, inpatient admission, SNF admission, and LTC facility admission was 0.779, 0.672, 0.753, and 0.826 in the ADL activity limitation stage development cohorts, respectively, and 0.788, 0.669, 0.748, and 0.799 in the ADL activity limitation stage validation cohorts, respectively. CONCLUSIONS: Parsimonious models can identify elderly Medicare beneficiaries at risk of poor outcomes and can aid policymakers, clinicians, and family members in improving care for older adults and supporting successful aging in the community.