title: Modelling the population-level impact of tai-chi on falls and fall-related injury among community-dwelling older people.
abstract: OBJECTIVE
  To model the population level impact of tai-chi on future rates of falls and fall-related injury in older people as a tool for policy development.
  
  
  METHODS
  An epidemiological and economic model for estimating population-level effectiveness of tai-chi.
  
  
  METHODS
  Australia, 2009. Patients or subjects Australian community-dwelling population aged 70+ years, ambulatory and without debilitating conditions or profound visual defects. Intervention Group-based tai-chi, for 1 h twice weekly for 26 weeks, assuming no sustained effect beyond the intervention period. Main outcome measure Total falls and fall-related hospitalisation prevented in 2009.
  
  
  RESULTS
  Population-wide tai-chi delivery would prevent an estimated 5440 falls and 109 fall-related hospitalisations, resulting in a 0.18% reduction in the fall-related hospital admission rate for community-dwelling older people. The gross costs per fall and per fall-related hospital admission prevented were $A4414 (€3013) and $A220,712 (€150,684), respectively. A total investment of $A24.01 million (€16.39 million), equivalent to 4.2% of the cost of fall-related episodes of hospital care in 2003/4, would be required to provide tai-chi for 31,998 people and achieve this effect.
  
  
  CONCLUSIONS
  Substantial investment in, and high population uptake of, tai-chi would be required to have a large effect on falls and fall-related hospitalisation rates. Although not accounted for in this study, investment in tai-chi is likely to be associated with additional significant health benefits beyond falls prevention. This approach could be applied to other interventions to assist selection of the most cost-effective falls-prevention portfolio for Australia and other countries.
authors.affiliation: Monash University Accident Research Centre, Melbourne, Australia. lesley.day@monash.edu
authors.forename: Lesley
authors.initials: L
authors.lastname: Day
authors.forename: Caroline F
authors.initials: CF
authors.lastname: Finch
authors.forename: James E
authors.initials: JE
authors.lastname: Harrison
authors.forename: Effie
authors.initials: E
authors.lastname: Hoareau
authors.forename: Leonie
authors.initials: L
authors.lastname: Segal
authors.forename: Shahid
authors.initials: S
authors.lastname: Ullah
mesh_terms: D000058:Accidental Falls / Q000191:economics / Q000517:prevention & control* / Q000706:statistics & numerical data; D000368:Aged; D001315:Australia / Q000453:epidemiology; D019317:Evidence-Based Medicine; D005260:Female; D006760:Hospitalization / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D018570:Risk Assessment; D012931:Social Environment; D026302:Tai Ji / Q000191:economics / Q000523:psychology