title: Demographic factors as predictors for hospital admission in patients with chronic disease.
abstract: OBJECTIVE
  To identify demographic predictors of hospital admission for chronic disease.
  
  
  METHODS
  Hospital morbidity records were extracted from the WA Data Linkage System for the period 1994-99 for specific chronic diseases based on national priorities. Poisson regression was used to estimate the effects of Aboriginal and Torres Strait Islander (ATSI) descent, co-morbidity, geography, socio-economic status and possession of health insurance on hospital admission rates.
  
  
  RESULTS
  This study has identified some of the main demographic risk factors for hospitalisation in patients with chronic disease as the following: being male, of ATSI descent, living in a relatively disadvantaged Census Collection District and having multiple co-morbidities. Depending on the disease, locational disadvantage and possession of private health insurance were also risk factors.
  
  
  CONCLUSIONS
  The study indicates that a crucial component in keeping patients with chronic disease out of hospital is ensuring quality primary care for all members of the community, equipping patients with the necessary skills to self-manage their chronic condition. Particular attention must be given to developing programs that are accessible to the more disadvantaged members of the community.
  
  
  CONCLUSIONS
  Programs aimed at keeping patients with chronic disease out of hospital must be targeted at the most vulnerable groups of the population if they are to be effective.
authors.affiliation: School of Population Health, University of Western Australia. kate.brameld@health.wa.gov.au
authors.forename: Kate J
authors.initials: KJ
authors.lastname: Brameld
authors.forename: C D'Arcy J
authors.initials: CD
authors.lastname: Holman
mesh_terms: D001315:Australia / Q000453:epidemiology; D002908:Chronic Disease; D003710:Demography; D005260:Female; D006302:Health Services Research; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D016012:Poisson Distribution; D016016:Proportional Hazards Models; D012307:Risk Factors