Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

We investigate parameter heterogeneity in breast cancer 1-year cumulative hospital costs across five European countries as part of the EuroHOPE project. The paper aims to explore whether conditional mean effects provide a suitable representation of the national variation in hospital costs. A cohort of patients with a primary diagnosis of invasive breast cancer (ICD-9 codes 174 and ICD-10 C50 codes) is derived using routinely collected individual breast cancer data from Finland, the metropolitan area of Turin (Italy), Norway, Scotland and Sweden. Conditional mean effects are estimated by ordinary least squares for each country, and quantile regressions are used to explore heterogeneity across the conditional quantile distribution. Point estimates based on conditional mean effects provide a good approximation of treatment response for some key demographic and diagnostic specific variables (e.g. age and ICD-10 diagnosis) across the conditional quantile distribution. For many policy variables of interest, however, there is considerable evidence of parameter heterogeneity that is concealed if decisions are based solely on conditional mean results. The use of quantile regression methods reinforce the need to consider beyond an average effect given the greater recognition that breast cancer is a complex disease reflecting patient heterogeneity.

Original publication

DOI

10.1002/hec.3274

Type

Journal

Health Econ

Publication Date

12/2015

Volume

24 Suppl 2

Pages

23 - 37

Keywords

breast cancer, cost distribution, parameter heterogeneity, quantile regression, Breast Neoplasms, Europe, Female, Hospital Costs, Humans, Models, Econometric, Regression Analysis