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Journal of Clinical Oncology, Vol 24, No 6 (February 20), 2006: pp. 856-862
© 2006 American Society of Clinical Oncology.
DOI: 10.1200/JCO.2005.02.1790

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Identification in Administrative Databases of Women Dying of Breast Cancer

Bruno Gagnon, Nancy E. Mayo, Carroll Laurin, James A. Hanley, Neil McDonald

From the Divisions of Stroke, Rehabilitation, Health Care Services, Breast Cancer, and Outcomes; Palliative Care, Ethics at the End of Life, and Communication; and Statistical Models, Methodology, and Clinical Epidemiology; and Oncology, Bioethics, Anorexia-Cachexia, and Palliative Care, McGill University, Montréal, Quebéc, Canada.

Address reprint requests to Bruno Gagnon, MD, MSC, 687 Pine Ave W, Ross 4.29, Montréal, Quebéc H3A 1A1, Canada; e-mail: bruno.gagnon{at}clinepi.mcgill.ca

PURPOSE: Palliative care is an essential component of cancer care, and population-based research is needed to monitor its impact. Administrative databases are the cornerstone of health services research. Their limitation is that cause of death is not sufficient to readily classify decedents as terminally ill for the study of the health services they received at the end of life. The study purpose is to develop and test the validity of an algorithm allowing the classification of the decedents as dying of breast cancer (BC), using administrative data.

METHODS: Validation was carried out through a chart review of 119 BC decedents extracted from hospital-based databases. This algorithm was applied to 3,384 deceased women with BC representative of the whole population. The effect of the classification by the algorithm was illustrated by the shift in the distributions of age and place of death.

RESULTS: The validation showed a sensitivity of 95%, a specificity of 89%, a positive predictive value of 98%, and negative predictive value of 77% for the classification of women dying of BC. Of the 3,384 decedents, 2,293 were classified as dying of, and 1,091 as not dying of BC. Women dying of BC were younger, died less often at home (6.9% v 17.9%), and in chronic care institutions (4.1% v 14.8%), and more often in acute-care beds (69.9% v 57.1%).

CONCLUSION: This novel way to classify decedents is conceptually based and empirically validated through chart review and impact on distribution of age and place of death.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.


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