title: Identifying clusters of falls-related hospital admissions to inform population targets for prioritising falls prevention programmes.
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.
authors.affiliation: Australian Centre for Research into Injury In Sport and its Prevention (ACRISP), Federation University Australia, Ballarat, Victoria, Australia.
authors.forename: Caroline F
authors.identifier: http://orcid.org/0000-0003-1711-1930
authors.initials: CF
authors.lastname: Finch
authors.affiliation: Monash Injury Research Institute (MIRI), Monash University, Clayton, Victoria, Australia.
authors.forename: Karen
authors.initials: K
authors.lastname: Stephan
authors.affiliation: Australian Centre for Research into Injury In Sport and its Prevention (ACRISP), Federation University Australia, Ballarat, Victoria, Australia.
authors.forename: Anna Wong
authors.initials: AW
authors.lastname: Shee
authors.affiliation: Faculty of Health Sciences, School of Physiotherapy and Exercise Science, Curtin University, Perth, Western Australia, Australia.
authors.forename: Keith
authors.initials: K
authors.lastname: Hill
authors.affiliation: Allied Health Research Unit, Monash Health, Monash University, Clayton, Victoria, Australia.
authors.forename: Terry P
authors.initials: TP
authors.lastname: Haines
authors.affiliation: Ageing, Work & Health Research Unit, Faculty of Health Sciences, The University of Sydney, Sydney, New South Wales, Australia.
authors.forename: Lindy
authors.initials: L
authors.lastname: Clemson
authors.affiliation: Monash Injury Research Institute (MIRI), Monash University, Clayton, Victoria, Australia.
authors.forename: Lesley
authors.initials: L
authors.lastname: Day
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control / Q000706:statistics & numerical data*; D000368:Aged; D000369:Aged, 80 and over; D016000:Cluster Analysis; D015897:Comorbidity; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D038801:International Classification of Diseases; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D012307:Risk Factors; D012737:Sex Factors; D014739:Victoria / Q000453:epidemiology