ArticleBMC health services research2018
Real and predicted mortality under health spending constraints in Italy: a time trend analysis through artificial neural networks.
Article in BMC health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Assessing the Relationships of Expenditure and Health Outcomes in Healthcare Systems: A System Design Approach.Healthcare (Basel, Switzerland) · 2025Article
- Analyzing the 20-year declining trend of hospital length-of-stay in European countries with different healthcare systems and reimbursement models.International journal of health economics and management · 2024Article
- Regional and sex inequalities of avoidable mortality in Italy: A time trend analysis.Public health in practice (Oxford, England) · 2023Article
- Article
- Health system characteristics and COVID-19 performance in high-income countries.BMC health services research · 2023Article
- How International Health System Austerity Responses to the 2008 Financial Crisis Impacted Health System and Workforce Resilience - A Realist Review.International journal of health policy and management · 2023Review
- Editorial: Patterns of all-cause and cause-specific mortality during the SARS-CoV-2 pandemic: The impact of health policies and interventions.Frontiers in public health · 2022Article
- Examining the Economic Perspective of Treatable Mortality: The Role of Health Care Financing and the Importance for Economic Prosperity.Frontiers in public health · 2021Article
- Gender Inequalities in Health and Their Effect on the Economic Prosperity Represented by the GDP of Selected Developed Countries-Empirical Study.International journal of environmental research and public health · 2020Article
- Health Care Financing Systems and Their Effectiveness: An Empirical Study of OECD Countries.International journal of environmental research and public health · 2019Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundAfter 2008 global economic crisis, Italian governments progressively reduced public healthcare financing. Describing the time trend of health outcomes and health expenditure may be helpful for policy makers during the resources' allocation decision making process. The aim of this paper is to analyze the trend of mortality and health spending in Italy and to investigate their correlation in consideration of the funding constraints experienced by the Italian national health system (SSN).
methodsWe conducted a 20-year time-series study. Secondary data has been extracted from a national, institution based and publicly accessible retrospective database periodically released by the Italian Institute of Statistics. Age standardized all-cause mortality rate (MR) and health spending (Directly Provided Services - DPS, Agreed-Upon Services - TAUS, and private expenditure) were reviewed. Time trend analysis (1995-2014) through OLS and Multilayer Feed-forward Neural Networks (MFNN) models to forecast mortality and spending trend was performed. The association between healthcare expenditure and MR was analyzed through a fixed effect regression model. We then repeated MFNN time trend forecasting analyses on mortality by adding the spending item resulted significantly related with MR in the fixed effect analyses.
resultsDPS and TAUS decreased since 2011. There was a mismatch in mortality rates between real and predicted values. DPS resulted significantly associated to mortality (p < 0.05). In repeated mortality forecasting analysis, predicted MR was found to be lower when considering the pre-constraints health spending trend.
conclusionsBetween 2011 and 2014, Italian public health spending items showed a reduction when compared to prior years. Spending on services directly provided free of charge appears to be the financial driving force of the Italian public health system. The overall mortality was found to be higher than the predicted trend and this scenario may be partially attributable to the healthcare funding constraints experienced by the SSN.
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