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Emerg Med J. 2003 Sep;20(5):421-5.

Predictors of falls in a high risk population: results from the prevention of falls in the elderly trial (PROFET).

Author information

1
Clinical Age Research Unit, Department of Health Care of the Elderly, Guy's, King's and St Thomas' School of Medicine, King's College, London, UK. jacqueline.close@kcl.ac.uk

Abstract

OBJECTIVES:

The prevention of falls in the elderly trial (PROFET) provides evidence of the benefits of structured interdisciplinary assessment of older people presenting to the accident and emergency department with a fall. However, the service implications of implementing this effective intervention are significant. This study therefore examined risk factors from PROFET and used these to devise a practical approach to streamlining referrals from accident and emergency departments to specialist falls services.

METHODS:

Logistic regression analysis was used in the control group to identify patients with an increased risk of falling in the absence of any intervention. The derived predictors were investigated to see whether they also predicted loss to follow up. A second regression analysis was undertaken to test for interaction with intervention.

RESULTS:

Significant positive predictors of further falls were; history of falls in the previous year (OR 1.5 (95%CI 1.1 to 1.9)), falling indoors (OR 2.4 (95%CI 1.1 to 5.2)), and inability to get up after a fall (OR 5.5 (95%CI 2.3 to 13.0)). Negative predictors were moderate alcohol consumption (OR 0.55 (95%CI 0.28 to 1.1)), a reduced abbreviated mental test score (OR 0.7 (95%CI 0.53 to 0.93)), and admission to hospital as a result of the fall (OR 0.26 (95%CI 0.11 to 0.61)). A history of falls (OR 1.2 (95%CI 1.0 to 1.3)), falling indoors (OR 3.2 (95%CI 1.5 to 6.6)) and a reduced abbreviated mental test score (OR 1.3 (95%CI 1.0 to 1.6)) were found to predict loss to follow up.

CONCLUSIONS:

The study has focused on a readily identifiable high risk group of people presenting at a key interface between the primary and secondary health care sectors. Analysis of derived predictors offers a practical risk based approach to streamlining referrals that is consistent with an attainable level of service commitment.

PMID:
12954679
PMCID:
PMC1726177
[Indexed for MEDLINE]
Free PMC Article
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