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Symptom burden predicts nursing home admissions among older adults

  • Author(s): Sheppard, KD
  • Brown, CJ
  • Hearld, KR
  • Roth, DL
  • Sawyer, P
  • Locher, JL
  • Allman, RM
  • Ritchie, CS
  • et al.

Published Web Location

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3748255/
No data is associated with this publication.
Abstract

Context: Symptom burden has been associated with functional decline in community-dwelling older adults and may be responsive to interventions. Known predictors of nursing home (NH) admission are often nonmodifiable. Objectives: To determine if symptom burden independently predicted NH admission among community-dwelling older adults over an eight and a half-year follow-up period. Methods: A random sample of community-dwelling Medicare beneficiaries in Alabama, stratified by race, gender, and rural/urban residence had baseline in-home assessments of sociodemographic measurements, Charlson comorbidity count, and symptoms. Symptom burden was derived from a count of 10 patient-reported symptoms. Nursing home admissions were determined from telephone interviews conducted every six months over the eight and a half years of study. Cox proportional hazard modeling was used to examine the significance of symptom burden as a predictor for NH admission after adjusting for other variables. Results: The mean ± SD age of the sample (N = 999) was 75.3 ± 6.7 years, and the sample was 51% rural, 50% African American, and 50% male. Thirty-eight percent (n = 380) had symptom burden scores ≥2. Seventy-five participants (7.5%) had confirmed dates for NH admission during the eight and a half years of follow-up. Using Cox proportional hazard modeling, symptom burden remained an independent predictor of time to NH placement (hazard ratio = 1.11; P = 0.02), even after adjustment for comorbidity count, race, sex, and age. Conclusion: Symptom burden is an independent risk factor for NH admission. Aggressive management of symptoms in older adults may reduce or delay NH admission. © 2013 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

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