title: Identifying older people at high risk of future falls: development and validation of a screening tool for use in emergency departments.
abstract: BACKGROUND
  Hospital emergency departments (EDs) treat a high proportion of older people, many as a direct consequence of falling.
  
  
  OBJECTIVE
  To develop and externally validate a fall risk screening tool for use in hospital EDs and to compare the tool's predictive ability to existing screening tools.
  
  
  METHODS
  This prospective cohort study involved two hospital EDs in Sydney, Australia. Potential participants were people aged 70+ years who presented to the ED after falling or with a history of 2+ falls in the previous year and were subsequently discharged. 219 people participated in the tool development study and 178 people participated in the external validation study. Study measures included number of fallers during the 6-month follow-up period, and physical status, medical history, fall history and community service use.
  
  
  RESULTS
  31% and 35% of participants fell in the development and external validation samples, respectively. The developed two-item screening tool included: 2+ falls in the past year (OR 4.18, 95% CI 2.61 to 6.68) and taking 6+ medications (OR 1.89, CI 1.18 to 3.04). The area under the receiver operating characteristic curve (AUC) was 0.70 (0.64-0.76). This represents significantly better predictive ability than the measure of 2+ previous falls alone (AUC 0.67, 0.62-0.72, p=0.02) and similar predictive ability to the FROP-Com (AUC 0.73, 0.67-0.79, p=0.25) and PROFET screens (AUC 0.70, 0.62-0.78, p=0.5).
  
  
  CONCLUSIONS
  A simple, two-item screening tool demonstrated good external validity and accurately discriminated between fallers and non-fallers. This tool could identify high risk individuals who may benefit from onward referral or intervention after ED discharge.
authors.affiliation: Musculoskeletal Division, The George Institute for Global Health, Sydney, New South Wales, Australia.
authors.forename: Anne
authors.initials: A
authors.lastname: Tiedemann
authors.forename: Catherine
authors.initials: C
authors.lastname: Sherrington
authors.forename: Teresa
authors.initials: T
authors.lastname: Orr
authors.forename: Jamie
authors.initials: J
authors.lastname: Hallen
authors.forename: Donna
authors.initials: D
authors.lastname: Lewis
authors.forename: Ann
authors.initials: A
authors.lastname: Kelly
authors.forename: Constance
authors.initials: C
authors.lastname: Vogler
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Lord
authors.forename: Jacqueline C T
authors.initials: JC
authors.lastname: Close
mesh_terms: D000058:Accidental Falls / Q000706:statistics & numerical data; D000368:Aged; D000369:Aged, 80 and over; D001315:Australia; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D015577:Geriatric Assessment / Q000379:methods*; D006801:Humans; D008297:Male; D008403:Mass Screening / Q000379:methods; D015999:Multivariate Analysis; D011446:Prospective Studies; D018570:Risk Assessment / Q000379:methods
keywords: accidental falls; aged; assessment; emergency department