Fall prediction in inpatients by bedside nurses using the St. Thomas's Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY) instrument: a multicenter study.

Journal Article (Academic Article)

OBJECTIVE: To assess the predictive value of the St. Thomas's Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY) instrument, a simple fall-risk assessment tool, when administered at a patient's hospital bedside by nurses. METHODS: Prospective multicenter study. METHODS: Six Belgian hospitals. METHODS: A total of 2,568 patients (mean age+/-standard deviation 67.2+/-18.4; 55.3% female) on four surgical (n=875, 34.1%), eight geriatric (n=687, 26.8%), and four general medical wards (n=1,006, 39.2%) were included in this study upon hospital admission. All patients were hospitalized for at least 48 hours. METHODS: Nurses completed the STRATIFY within 24 hours after admission of the patient. Falls were documented on a standardized incident report form. RESULTS: The number of fallers was 136 (5.3%), accounting for 190 falls and an overall rate of 7.3 falls per 1,000 patient days for all hospitals. The STRATIFY showed good sensitivity (> or = 84%) and high negative predictive value (> or = 99%) for the total sample, for patients admitted to general medical and surgical wards, and for patients younger than 75, although it showed moderate (69%) to low (52%) sensitivity and high false-negative rates (31-48%) for patients admitted to geriatric wards and for patients aged 75 and older. CONCLUSIONS: Although the STRATIFY satisfactorily predicted the fall risk of patients admitted to general medical and surgical wards and patients younger than 75, it failed to predict the fall risk of patients admitted to geriatric wards and patients aged 75 and older (particularly those aged 75-84).

Full Text

Duke Authors

Cited Authors

  • Milisen, K; Staelens, N; Schwendimann, R; De Paepe, L; Verhaeghe, J; Braes, T; Boonen, S; Pelemans, W; Kressig, RW; Dejaeger, E

Published Date

  • May 2007

Published In

Volume / Issue

  • 55 / 5

Start / End Page

  • 725 - 733

PubMed ID

  • 17493192

International Standard Serial Number (ISSN)

  • 0002-8614

Digital Object Identifier (DOI)

  • 10.1111/j.1532-5415.2007.01151.x

Language

  • English