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A 10-year cohort study of the burden and risk of in-hospital falls and fractures using routinely collected hospital data
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  1. C A Brand1,
  2. V Sundararajan2
  1. 1Centre of Research Excellence in Patient Safety (CREPS), Department of Preventive Medicine, Monash University, Department of Epidemiology and Preventive Medicine, Victoria, Australia
  2. 2Department of Medicine, Monash University, Southern Clinical School, Monash University, Clayton, Victoria, Australia
  1. Correspondence to Professor C A Brand, Centre of Research Excellence in Patient Safety (CREPS), Department of Preventive Medicine, Monash University, Department of Epidemiology and Preventive Medicine, Level 3, MacFarlane-Burnet Tower, 89 Commercial Road Melbourne, Victoria 3004, Australia; caroline.brand{at}med.monash.edu.au

Abstract

Objectives To document the burden of in-hospital falls and fractures, and to identify factors that may increase the risk of these events.

Design A retrospective cohort analysis

Setting The study was set in the State of Victoria, Australia.

Participants Hospital episode data collected in the Victoria Admitted Episodes Dataset, for all multiday-stay patients 18 years or more admitted to Victorian public hospitals; 1 July 1998 to 30 June 2008. Diagnoses were defined by the International Classification of Disease, 10th Revision, Australian Modification (ICD-10-AM), which includes an in-hospital diagnostic timing code. Outcome measures included rates of in-hospital falls and fractures, length of hospital stay and mortality. Variables included in risk adjustment included financial year, individual demographic and comorbidity data, and hospital characteristics.

Results There were 3 345 415 episodes: 21 250 (0.64%) in-hospital falls and 4559 (0.14%) fractures. In-hospital fall (IHF) episode rates increased over the study period, but fracture episode rates were stable. Mortality (HR 1.3, CI 1.3 to 1.5) and length of stay (median 19 days vs 5 days, p<0.0001) were increased with IHF. Risk factors for IHF included dementia (rate ratio 1.7, CI 1.6 to 1.8) and delirium (rate ratio 1.8, CI 1.6 to 2.0).

Conclusions Routinely collected data that include a hospital diagnostic timing code offer a standard method of quantifying in-hospital falls and fractures. Unselected in-hospital falls data may be subject to reporting and documentation bias. The utility of using robust selected injuries such as IHF-related fracture as a quality-of-care indicator requires further investigation.

  • Accidental falls risk management in-patients risk factors cohort study
  • adverse event
  • patient safety

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Footnotes

  • Data sharing statement The full data-extraction algorithm can be obtained on request from VS (vijaya.sundararajan{at}med.monash.edu.au)

  • Competing interests VS is a senior medical advisor to the Department of Health, Victoria.

  • Ethics approval Ethics approval was provided by Monash University, Standing Committee on Ethics in Research Involving Humans.

  • Provenance and peer review Not commissioned; externally peer reviewed.