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Identifying older people at high risk of future falls: development and validation of a screening tool for use in emergency departments
  1. Anne Tiedemann1,2,
  2. Catherine Sherrington1,2,
  3. Teresa Orr1,
  4. Jamie Hallen3,
  5. Donna Lewis4,
  6. Ann Kelly3,
  7. Constance Vogler4,2,
  8. Stephen R Lord5,
  9. Jacqueline C T Close5,6
  1. 1Musculoskeletal Division, The George Institute for Global Health, Sydney, New South Wales, Australia
  2. 2Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
  3. 3Prince of Wales Hospital, Randwick, New South Wales, Australia
  4. 4Royal North Shore Hospital, St Leonards, New South Wales, Australia
  5. 5Neuroscience Research Australia, University of Sydney, Sydney, New South Wales, Australia
  6. 6Prince of Wales Clinical School, Neuroscience Research Australia, University of New South Wales, Randwick, New South Wales, Australia
  1. Correspondence to Dr Anne Tiedemann, Musculoskeletal Division, The George Institute for Global Health, University of Sydney, PO Box M201, Missenden Rd, Camperdown, 2050 NSW, Australia; atiedemann{at}georgeinstitute.org.au

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.

  • accidental falls
  • aged
  • assessment
  • emergency department
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