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Parameter Heterogeneity In Breast Cancer Cost Regressions - Evidence From Five European Countries.
Smith, Joel; Banks, Helen; Campbell, Harry; Douglas, Anne; Fletcher, Eilidh; McCallum, Alison; Moger, Tron Anders; Peltola, Mikko; Sveréus, Sofia; Wild, Sarah; Williams, Linda J; Forbes, John.
Afiliação
  • Smith J; Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
  • Banks H; Centre for Research on Health and Social Care Management, CERGAS, Bocconi University.
  • Campbell H; Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.
  • Douglas A; Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.
  • Fletcher E; Lothian Analytical Services, NHS Lothian, Edinburgh, UK.
  • McCallum A; NHS Lothian, Edinburgh, UK.
  • Moger TA; Department of Health Management and Health Economics, Institute of Health and Society, University of Oslo, Oslo, Norway.
  • Peltola M; Centre for Health and Social Economics (CHESS), National Institute for Health and Welfare, Helsinki, Finland.
  • Sveréus S; Medical Management Centre, Karolinska Institutet, Stockholm, Sweden.
  • Wild S; Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.
  • Williams LJ; Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.
  • Forbes J; Health Research Institute, University of Limerick, Limerick, Ireland.
Health Econ ; 24 Suppl 2: 23-37, 2015 Dec.
Article em En | MEDLINE | ID: mdl-26633866
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.
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Texto completo: 1 Temas: ECOS / Aspectos_gerais / Financiamentos_gastos Bases de dados: MEDLINE Assunto principal: Neoplasias da Mama Tipo de estudo: Diagnostic_studies / Health_economic_evaluation / Prognostic_studies Limite: Female / Humans País/Região como assunto: Europa Idioma: En Revista: Health Econ Assunto da revista: SERVICOS DE SAUDE Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Temas: ECOS / Aspectos_gerais / Financiamentos_gastos Bases de dados: MEDLINE Assunto principal: Neoplasias da Mama Tipo de estudo: Diagnostic_studies / Health_economic_evaluation / Prognostic_studies Limite: Female / Humans País/Região como assunto: Europa Idioma: En Revista: Health Econ Assunto da revista: SERVICOS DE SAUDE Ano de publicação: 2015 Tipo de documento: Article