Long-Term Nursing Home Entry: A Prognostic Model for Older Adults with a Family or Unpaid Caregiver

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

To comprehensively examine factors associated with long-term nursing home (NH) entry from 6 domains of older adult and family caregiver risk from nationally representative surveys and develop a prognostic model and a simple scoring system for use in risk stratification.

Related collections

Most cited references 28

Record: found
Abstract: found
Article: found

Dementia prevention, intervention, and care

Gill Livingston, Andrew Sommerlad, Vasiliki Orgeta … (2018)

0 comments Cited 2007 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

Accountable Health Communities--Addressing Social Needs through Medicare and Medicaid.

Dawn E. Alley, Chisara N Asomugha, Patrick H Conway … (2016)

0 comments Cited 201 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Predicting nursing home admission in the U.S: a meta-analysis

Joseph Gaugler, Sue Duval, Keith Anderson … (2007)

Background While existing reviews have identified significant predictors of nursing home admission, this meta-analysis attempted to provide more integrated empirical findings to identify predictors. The present study aimed to generate pooled empirical associations for sociodemographic, functional, cognitive, service use, and informal support indicators that predict nursing home admission among older adults in the U.S. Methods Studies published in English were retrieved by searching the MEDLINE, PSYCINFO, CINAHL, and Digital Dissertations databases using the keywords: "nursing home placement," "nursing home entry," "nursing home admission," and "predictors/institutionalization." Any reports including these key words were retrieved. Bibliographies of retrieved articles were also searched. Selected studies included sampling frames that were nationally- or regionally-representative of the U.S. older population. Results Of 736 relevant reports identified, 77 reports across 12 data sources were included that used longitudinal designs and community-based samples. Information on number of nursing home admissions, length of follow-up, sample characteristics, analysis type, statistical adjustment, and potential risk factors were extracted with standardized protocols. Random effects models were used to separately pool the logistic and Cox regression model results from the individual data sources. Among the strongest predictors of nursing home admission were 3 or more activities of daily living dependencies (summary odds ratio [OR] = 3.25; 95% confidence interval [CI], 2.56–4.09), cognitive impairment (OR = 2.54; CI, 1.44–4.51), and prior nursing home use (OR = 3.47; CI, 1.89–6.37). Conclusion The pooled associations provided detailed empirical information as to which variables emerged as the strongest predictors of NH admission (e.g., 3 or more ADL dependencies, cognitive impairment, prior NH use). These results could be utilized as weights in the construction and validation of prognostic tools to estimate risk for NH entry over a multi-year period.