Where patients with cancer die in South Australia, 1990-1999: a population-based review

Med J Aust. 2001 Nov 19;175(10):526-9. doi: 10.5694/j.1326-5377.2001.tb143710.x.


Objective: To determine the place of death of South Australians who die of cancer.

Design: A population-based, cross-sectional study of data from the South Australian Cancer Registry.

Participants: 29,230 patients with cancer dying in 1990-1999.

Main outcome measures: Place of death; patient demography; year of death; survival from diagnosis; and type of cancer.

Results: 25.0% of patients died in a metropolitan public hospital, 19.9% in a hospice, 16.9% in a country hospital, 15.8% at a private residence, 12.7% in a metropolitan private hospital, and 9.7% in a nursing home. Although the change in place of death was not marked, multivariate logistic regression showed a secular trend away from metropolitan public hospitals towards metropolitan private hospitals and, in 1998-1999, towards nursing homes. Patients dying of cancer in a metropolitan public hospital were more likely to be younger, males, born outside Australia, and residents of lower socioeconomic areas of Adelaide. They were also more likely to have died within three months of diagnosis, and to have a haematological malignancy or a cancer of the upper digestive tract, lung or female breast. In contrast, patients dying at a private residence tended to be under 70 years and comprise longer-term survivors. Country residents were less likely than Adelaide residents to die in a hospice.

Conclusion: The proportion of patients dying in different settings have health service implications. The relatively low use of hospice facilities by country patients may reflect differences in access to hospice facilities.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Analysis of Variance
  • Cross-Sectional Studies
  • Female
  • Health Facilities / statistics & numerical data*
  • Home Nursing / statistics & numerical data*
  • Hospices / statistics & numerical data
  • Hospitals, Rural / statistics & numerical data
  • Hospitals, Urban / statistics & numerical data
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Neoplasms / mortality*
  • Nursing Homes / statistics & numerical data
  • Socioeconomic Factors
  • South Australia / epidemiology
  • Statistics, Nonparametric
  • Terminal Care*