Italian regional health system structure and expected cancer survival

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Abstract

Background and aims.

Few studies deal with the association of socioeconomic and health system resource variables with cancer survival at the Italian regional level, where the greatest number of decisions about social and health policies and resource allocations are taken. The present study aimed to describe the causal relationships between socioeconomic and health system resource factors and regional cancer survival and to compute the expected cancer survival at provincial, regional and area levels.

Methods and study design.

Age-standardized relative survival at 5 years from diagnosis of cases incident in 1995–1998 and followed up to 2004 were derived by gender for 11 sites from the Italian Association of Cancer Registries data bank. The socioeconomic and health system resource variables, describing at a regional level the macroeconomy, demography, labor market, and health resources for 1995–2005, came from the Health for All database. A principal components factor analysis was applied to the socioeconomic and health system resource variables. For every site, linear regression models were computed considering the relative survival at 5 years as a dependent variable and the principal components factor analysis factors as independent variables.

Results.

The factors described the socioeconomic and health-related features of the regional systems and were causally related to the characteristics of the patient taken in charge. The models built by the factors allowed computation of the expected relative survival at 5 years with very good concordance with those observed at regional, macro-regional and national levels. In the regions without any cancer registry, survival was coherent with that of neighboring regions with similar socioeconomic and health system resources characteristics.

Conclusions.

The models highlighted the causal correlations between socioeconomic and health system resources and cancer survival, suggesting that they could be good evaluation tools for the efficiency of the resources allocation and use.

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