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OBJECTIVE: To determine health system expenditure on cancers by time since diagnosis using data for an entire country. METHODS: New Zealand cancer registry data was linked to hospitalization, pharmaceutical, outpatient, general practice, laboratory, and other datasets, with costs ascribed to each event occurring in 2006-2011. "Excess" cancer costs were estimated by subtracting "expected costs" for citizens without cancer from the "total cost" for cancer patients ($2011 inflation-adjusted). Gamma regressions were used to estimate costs per person-month. RESULTS: For first adult cancer diagnosed that the excess cost per person was between US$3400 and US$4300 in the first month postdiagnosis (varied by sex and age), fell to US$50-US$150 per month at 2 or more years postdiagnosis (excluding those within a year of death), but increased again if dying from their cancer (US$3800-US$8300 in the last month of life). Such patterns varied by cancer, for example, in the first month postdiagnosis for 65 year olds it varied 20-fold from US$800 for prostate to US$15,900 for brain cancer. Per diagnosed case, total excess costs varied from US$5000 (melanoma) to US$66,000 (bone and connective tissue) [Corrected]. Excess cancer costs made up 6.5% of total Vote:Health expenditure in 2010-2011, with colorectal (14.7%), breast (14.4%) being the top 2 contributors, and prostate, non-Hodgkin lymphoma, leukemia, and lung each contributing about 6%. CONCLUSIONS: Costs vary substantially by time since diagnosis and cancer type. The results and regression equations reported in this paper can be used in modeling requiring cancer costs by time since diagnosis and proximity to death.

Original publication

DOI

10.1097/MLR.0000000000000330

Type

Journal article

Journal

Med Care

Publication Date

04/2015

Volume

53

Pages

302 - 309

Keywords

Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Child, Child, Preschool, Female, Health Care Costs, Humans, Incidence, Infant, Male, Middle Aged, Models, Economic, Neoplasms, New Zealand, Sex Factors, Time Factors, Young Adult