Prediction of institutionalization in the elderly. A systematic review

Age Ageing. 2010 Jan;39(1):31-8. doi: 10.1093/ageing/afp202. Epub 2009 Nov 23.

Abstract

Objective: in the past decades, many studies have examined predictors of nursing home placement (NHP) in the elderly. This study provides a systematic review of predictors of NHP in the general population of developed countries.

Design: relevant articles were identified by searching the databases MEDLINE, Web of Science, Cochrane Library and PSYNDEXplus. Studies based on population-based samples with prospective study design and identification of predictors by multivariate analyses were included. Quality of studies and evidence of predictors were determined.

Results: thirty-six studies were identified; one-third of the studies were of high quality. Predictors with strong evidence were increased age, low self-rated health status, functional and cognitive impairment, dementia, prior NHP and a high number of prescriptions. Predictors with inconsistent results were male gender, low education status, low income, stroke, hypertension, incontinence, depression and prior hospital use.

Conclusions: findings suggested that predictors of NHP are mainly based on underlying cognitive and/or functional impairment, and associated lack of support and assistance in daily living. However, the methodical quality of studies needs improvement. More theoretical embedding of risk models of NHP would help to establish more clarity in complex relationships in using nursing homes.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review
  • Systematic Review

MeSH terms

  • Activities of Daily Living
  • Aged
  • Aged, 80 and over
  • Cognition Disorders / epidemiology*
  • Cognition Disorders / psychology
  • Dementia / epidemiology*
  • Dementia / psychology
  • Female
  • Forecasting
  • Homes for the Aged / statistics & numerical data*
  • Humans
  • Institutionalization / statistics & numerical data
  • Institutionalization / trends*
  • Male
  • Nursing Homes / statistics & numerical data*
  • Psychiatric Status Rating Scales
  • Risk Factors