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    Identifying clusters of falls-related hospital admissions to inform population targets for prioritising falls prevention programmes.

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    Author
    Finch, CF; Stephan, K; Shee, AW; Hill, K; Haines, TP; Clemson, L; Day, L
    Date
    2015-08
    Source Title
    Injury Prevention
    Publisher
    BMJ
    University of Melbourne Author/s
    Finch, Caroline
    Affiliation
    Physiotherapy
    Metadata
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    Document Type
    Journal Article
    Citations
    Finch, C. F., Stephan, K., Shee, A. W., Hill, K., Haines, T. P., Clemson, L. & Day, L. (2015). Identifying clusters of falls-related hospital admissions to inform population targets for prioritising falls prevention programmes.. Inj Prev, 21 (4), pp.254-259. https://doi.org/10.1136/injuryprev-2014-041351.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/257292
    DOI
    10.1136/injuryprev-2014-041351
    Open Access at PMC
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4518748
    Abstract
    BACKGROUND: There has been limited research investigating the relationship between injurious falls and hospital resource use. The aims of this study were to identify clusters of community-dwelling older people in the general population who are at increased risk of being admitted to hospital following a fall and how those clusters differed in their use of hospital resources. METHODS: Analysis of routinely collected hospital admissions data relating to 45 374 fall-related admissions in Victorian community-dwelling older adults aged ≥65 years that occurred during 2008/2009 to 2010/2011. Fall-related admission episodes were identified based on being admitted from a private residence to hospital with a principal diagnosis of injury (International Classification of Diseases (ICD)-10-AM codes S00 to T75) and having a first external cause of a fall (ICD-10-AM codes W00 to W19). A cluster analysis was performed to identify homogeneous groups using demographic details of patients and information on the presence of comorbidities. Hospital length of stay (LOS) was compared across clusters using competing risks regression. RESULTS: Clusters based on area of residence, demographic factors (age, gender, marital status, country of birth) and the presence of comorbidities were identified. Clusters representing hospitalised fallers with comorbidities were associated with longer LOS compared with other cluster groups. Clusters delineated by demographic factors were also associated with increased LOS. CONCLUSIONS: All patients with comorbidity, and older women without comorbidities, stay in hospital longer following a fall and hence consume a disproportionate share of hospital resources. These findings have important implications for the targeting of falls prevention interventions for community-dwelling older people.

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