title: Fall prediction in inpatients by bedside nurses using the St. Thomas's Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY) instrument: a multicenter study.
abstract: 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).
authors.affiliation: Center for Health Services and Nursing Research, Department for Geriatric Medicine, Katholieke Universiteit Leuven, Leuven, Belgium. Koen.Milisen@med.kuleuven.be
authors.forename: Koen
authors.initials: K
authors.lastname: Milisen
authors.forename: Nele
authors.initials: N
authors.lastname: Staelens
authors.forename: René
authors.initials: R
authors.lastname: Schwendimann
authors.forename: Leen
authors.initials: L
authors.lastname: De Paepe
authors.forename: Jeroen
authors.initials: J
authors.lastname: Verhaeghe
authors.forename: Tom
authors.initials: T
authors.lastname: Braes
authors.forename: Steven
authors.initials: S
authors.lastname: Boonen
authors.forename: Walter
authors.initials: W
authors.lastname: Pelemans
authors.forename: Reto W
authors.initials: RW
authors.lastname: Kressig
authors.forename: Eddy
authors.initials: E
authors.lastname: Dejaeger
mesh_terms: D000058:Accidental Falls; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D007297:Inpatients; D008297:Male; D008875:Middle Aged; D009730:Nursing Assessment; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D012680:Sensitivity and Specificity