Dissemin is shutting down on January 1st, 2025

Published in

Wiley, Australasian Journal on Ageing, 1(43), p. 199-204, 2023

DOI: 10.1111/ajag.13245

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Findings from three methods to identify falls in hospitals: Results from the Ambient Intelligent Geriatric Management system fall prevention trial

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

AbstractObjectiveTo (a) compare characteristics of patients who fall with those of patients who did not fall; and (b) characterise falls (time, injury severity and location) through three fall reporting methods (incident system reports, medical notes and clinician reports).MethodsA substudy design within a stepped‐wedge clinical trial was used: 3239 trial participants were recruited from two inpatient Geriatric Evaluation and Management Units and one general medicine ward in two Australian states. To compare the characteristics of patients who had fallen with those who had not, descriptive tests were used. To characterise falls through three reporting methods, bivariate logistic regressions were used.ResultsPatients who had fallen were more likely than patients who had not fallen to be cognitively impaired (51% vs. 29%, p < 0.01), admitted with falls (38% vs. 28%, p = 0.01) and have poor health outcomes such as prolonged length of stay (24 [16–34] vs. 12 [8–19] days [IQR], p < 0.01) and less likely to be discharged directly to the community (62% vs. 47%, p < 0.01). Most falls were captured from medical notes (93%), with clinician (71%) and incident reports (68%) missing 21%–25% of falls. The proportion of injurious falls identified through incident reports was higher than medical records or clinician reports (40% vs. 34% vs. 37%).ConclusionsThis study reaffirms the need to improve reporting falls in incident systems and at clinical handover to the team leader. Research should continue to use more than one method of identifying falls, but include data from medical records. Many falls cause injury, resulting in poor health outcomes.