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

    230242_230242.pdf (814.4Kb)
    Access Status
    Open access
    Authors
    Finch, C.
    Stephan, K.
    Shee, A.
    Hill, Keith
    Haines, T.
    Clemson, L.
    Day, L.
    Date
    2015
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Finch, C. and Stephan, K. and Shee, A. and Hill, K. and Haines, T. and Clemson, L. and Day, L. 2015. Identifying clusters of falls-related hospital admissions to inform population targets for prioritising falls prevention programmes. Injury Prevention. 21 (4): pp. 254-259.
    Source Title
    Injury Prevention
    DOI
    10.1136/injuryprev-2014-041351
    ISSN
    1353-8047
    School
    School of Physiotherapy and Exercise Science
    Remarks

    This open access article is distributed under the Creative Commons license http://creativecommons.org/licenses/by-nc/4.0/

    URI
    http://hdl.handle.net/20.500.11937/25349
    Collection
    • Curtin Research Publications
    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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