Silvia Francisci1, Stefano Guzzinati2, Giulia Capodaglio3, Daniela Pierannunzio1, Sandra Mallone1, Andrea Tavilla1, Tania Lopez1, Susanna Busco4, Walter Mazzucco5,6, Catia Angiolini7, Manuel Zorzi8, Diego Serraino9, Alessandro Barchielli10, Mario Fusco11, Fabrizio Stracci12, Fortunato Bianconi12, Massimo Rugge13, Silvia Iacovacci14, Antonio Giampiero Russo15, Rosanna Cusimano16, Anna Gigli17. 1. National Centre for Disease Prevention and Health Promotion, National Institute of Health, Rome, Italy. 2. Veneto Tumour Registry, Azienda Zero, Padua, Italy. stefano.guzzinati@azero.veneto.it. 3. Regional Epidemiology Service, Azienda Zero, Padua, Italy. 4. UOC Programmazione e Controllo di Gestione, ASL Latina, Latina, Italy. 5. Sciences for Health Promotion and Mother and Child (PROSAMI) Department, University of Palermo, Palermo, Italy. 6. Clinical Epidemiology and Cancer Registry Unit, Palermo University Hospital "P. Giaccone", Palermo, Italy. 7. Breast Oncology, Careggi University Hospital, Florence, Italy. 8. Veneto Tumour Registry, Azienda Zero, Padua, Italy. 9. SOC Epidemiologia Oncologica, Centro di Riferimento Oncologico, IRCCS, Aviano, Italy. 10. Tuscany Cancer Registry, Institute for Cancer Study and Prevention, Florence, Italy. 11. Registro Tumori ASL Napoli 3 sud, Naples, Italy. 12. Umbria Cancer Registry, Public Health Section, Department Experimental Medicine, University of Perugia, Perugia, Italy. 13. Department of Medicine, Surgical Pathology Unit, University of Padua, Padua, Italy. 14. Dipartimento di Prevenzione ASL Latina, Latina, Italy. 15. Epidemiology Unit, Agency for Health Protection of Milan, Milan, Italy. 16. Local Health Unit 6, Palermo, Italy. 17. Institute for Research on Population and Social Policies, National Research Council, Rome, Italy.
Abstract
OBJECTIVES: To estimate total direct health care costs associated to diagnosis and treatment of women with breast cancer in Italy, and to investigate their distribution by service type according to the disease pathway and patient characteristics. METHODS: Data on patients provided by population-based Cancer Registries are linked at individual level with data on health-care services and corresponding claims from administrative databases. A combination of cross-sectional approach and a threephase of care decomposition model with initial, continuing and final phases-of-care defined according to time occurred since diagnosis and disease outcome is adopted. Direct estimation of cancer-related costs is obtained. RESULTS: Study cohort included 49,272 patients, 15.2% were in the initial phase absorbing 42% of resources, 79.7% in the continuing phase absorbing 44% of resources and 5.1% in the final phase absorbing 14% of resources. Hospitalization was the most important cost driver, accounting for over 55% of the total costs. CONCLUSIONS: This paper represents the first attempt in Italy to estimate the economic burden of cancer at population level taking into account the entire disease pathway and using multiple current health care databases. The evidence produced by the study can be used to better plan resources allocation. The model proposed is replicable to countries with individual health care information on services and claims.
OBJECTIVES: To estimate total direct health care costs associated to diagnosis and treatment of women with breast cancer in Italy, and to investigate their distribution by service type according to the disease pathway and patient characteristics. METHODS: Data on patients provided by population-based Cancer Registries are linked at individual level with data on health-care services and corresponding claims from administrative databases. A combination of cross-sectional approach and a threephase of care decomposition model with initial, continuing and final phases-of-care defined according to time occurred since diagnosis and disease outcome is adopted. Direct estimation of cancer-related costs is obtained. RESULTS: Study cohort included 49,272 patients, 15.2% were in the initial phase absorbing 42% of resources, 79.7% in the continuing phase absorbing 44% of resources and 5.1% in the final phase absorbing 14% of resources. Hospitalization was the most important cost driver, accounting for over 55% of the total costs. CONCLUSIONS: This paper represents the first attempt in Italy to estimate the economic burden of cancer at population level taking into account the entire disease pathway and using multiple current health care databases. The evidence produced by the study can be used to better plan resources allocation. The model proposed is replicable to countries with individual health care information on services and claims.
Entities:
Keywords:
Administrative data; Breast cancer; Cost analysis; Health care utilization; Real world data
Authors: Claire De Oliveira; Reka Pataky; Karen E Bremner; Jagadish Rangrej; Kelvin K W Chan; Winson Y Cheung; Jeffrey S Hoch; Stuart Peacock; Murray D Krahn Journal: Healthc Policy Date: 2017-02