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Predicting change in functional status over quarterly intervals for older adults enrolled in the PACE community-based long-term care program

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Abstract

Background and aims: Many frail older adults experience multiple changes in activities of daily living (ADL) functioning over the course of a year. Accurate predictions of ADL status over quarterly intervals may improve the precision of care planning for older adults who seek long-term care in the community. The study sought to develop and validate a model that predicts older adults’ ADL status over quarterly intervals. Methods: The study included 3127 enrollees from 11 Program of All Inclusive Care for the Elderly (PACE) sites. Nurses assessed ADL status quarterly. Potential predictors included baseline assessment of age, sex, race, and living situation and quarterly assessments of prior functioning, co-morbidities, prior hospitalizations, and mental status. Results: Change in level of functioning occurred for 30% of quarterly observations. Predictors of functioning at the end of a quarter were prior ADL change, prior hospitalization, living with others, impaired mental status, cancer, dementia, coronary artery disease, congestive heart failure and chronic obstructive pulmonary disease. When the model was applied to the validation observations, 93% of predictions were within one level and 72% of the predictions were the same level of ADL functioning observed at the end of the quarter. Conclusions: In a sample of community-living ADL-disabled older adults, changes in functional status over a quarter were common and associated with functional and health status at the beginning of the quarter. Further validation of the model may result in an index that helps clinicians better predict future ADL needs of community-living older adults who need long-term care.

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Authors and Affiliations

  1. School of Nursing, Purdue University, West Lafayette, IN, USA

    Laura P. Sands PhD

  2. Center on Aging and the Life Course, Purdue University, West Lafayette, IN, USA

    Laura P. Sands PhD & Bruce A. Craig

  3. Department of Statistics, Purdue University, West Lafayette, IN, USA

    Huiping Xu & Bruce A. Craig

  4. OnLok Senior Health Services, San Francisco, USA

    Catherine Eng

  5. Division of Geriatrics, University of California at San Francisco, San Francisco, USA

    Catherine Eng & Kenneth E. Covinsky

  6. UCSF/ Mt. Zion Center on Aging, San Francisco, USA

    Kenneth E. Covinsky

  7. San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA

    Kenneth E. Covinsky

Authors
  1. Laura P. Sands PhD
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  2. Huiping Xu
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  3. Bruce A. Craig
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  4. Catherine Eng
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  5. Kenneth E. Covinsky
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Correspondence to Laura P. Sands PhD.

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Sands, L.P., Xu, H., Craig, B.A. et al. Predicting change in functional status over quarterly intervals for older adults enrolled in the PACE community-based long-term care program. Aging Clin Exp Res 20, 419–427 (2008). https://doi.org/10.1007/BF03325147

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  • DOI: https://doi.org/10.1007/BF03325147

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