Literature DB >> 23139096

Identifying older people at high risk of future falls: development and validation of a screening tool for use in emergency departments.

Anne Tiedemann1, Catherine Sherrington, Teresa Orr, Jamie Hallen, Donna Lewis, Ann Kelly, Constance Vogler, Stephen R Lord, Jacqueline C T Close.   

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.

Entities:  

Keywords:  accidental falls; aged; assessment; emergency department

Mesh:

Year:  2012        PMID: 23139096     DOI: 10.1136/emermed-2012-201783

Source DB:  PubMed          Journal:  Emerg Med J        ISSN: 1472-0205            Impact factor:   2.740


  12 in total

1.  Using Chief Complaint in Addition to Diagnosis Codes to Identify Falls in the Emergency Department.

Authors:  Brian W Patterson; Maureen A Smith; Michael D Repplinger; Michael S Pulia; James E Svenson; Michael K Kim; Manish N Shah
Journal:  J Am Geriatr Soc       Date:  2017-06-21       Impact factor: 5.562

2.  Exposure to anticholinergic and sedative medicines as indicators of high-risk prescriptions in the elderly.

Authors:  Elodie Jean-Bart; Claire Moutet; Virginie Dauphinot; Pierre Krolak-Salmon; Christelle Mouchoux
Journal:  Int J Clin Pharm       Date:  2017-10-31

3.  Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits.

Authors:  Brian W Patterson; Collin J Engstrom; Varun Sah; Maureen A Smith; Eneida A Mendonça; Michael S Pulia; Michael D Repplinger; Azita G Hamedani; David Page; Manish N Shah
Journal:  Med Care       Date:  2019-07       Impact factor: 2.983

4.  Using the Hendrich II Inpatient Fall Risk Screen to Predict Outpatient Falls After Emergency Department Visits.

Authors:  Brian W Patterson; Michael D Repplinger; Michael S Pulia; Robert J Batt; James E Svenson; Alex Trinh; Eneida A Mendonça; Maureen A Smith; Azita G Hamedani; Manish N Shah
Journal:  J Am Geriatr Soc       Date:  2018-03-06       Impact factor: 5.562

Review 5.  Predicting geriatric falls following an episode of emergency department care: a systematic review.

Authors:  Christopher R Carpenter; Michael S Avidan; Tanya Wildes; Susan Stark; Susan A Fowler; Alexander X Lo
Journal:  Acad Emerg Med       Date:  2014-10-07       Impact factor: 3.451

6.  Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.

Authors:  Gwen Costa Jacobsohn; Margaret Leaf; Frank Liao; Apoorva P Maru; Collin J Engstrom; Megan E Salwei; Gerald T Pankratz; Alexis Eastman; Pascale Carayon; Douglas A Wiegmann; Joel S Galang; Maureen A Smith; Manish N Shah; Brian W Patterson
Journal:  Healthc (Amst)       Date:  2021-12-16

7.  Can an Emergency Department-Initiated Intervention Prevent Subsequent Falls and Health Care Use in Older Adults? A Randomized Controlled Trial.

Authors:  Elizabeth M Goldberg; Sarah J Marks; Linda J Resnik; Sokunvichet Long; Hannah Mellott; Roland C Merchant
Journal:  Ann Emerg Med       Date:  2020-08-25       Impact factor: 5.721

8.  Older adult falls prevention behaviors 60 days post-discharge from an urban emergency department after treatment for a fall.

Authors:  Kalpana Narayan Shankar; Nicole J Treadway; Alyssa A Taylor; Alan H Breaud; Elizabeth W Peterson; Jonathan Howland
Journal:  Inj Epidemiol       Date:  2017-06-19

9.  Evaluating a Two-Level vs. Three-Level Fall Risk Screening Algorithm for Predicting Falls Among Older Adults.

Authors:  Thelma J Mielenz; Sneha Kannoth; Haomiao Jia; Kristin Pullyblank; Julie Sorensen; Paul Estabrooks; Judy A Stevens; David Strogatz
Journal:  Front Public Health       Date:  2020-08-13

10.  Two-Item Fall Screening Tool Identifies Older Adults at Increased Risk of Falling after Emergency Department Visit.

Authors:  Christopher J Solie; Morgan B Swanson; Kari Harland; Christopher Blum; Kevin Kin; Nicholas Mohr
Journal:  West J Emerg Med       Date:  2020-08-20
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