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Exploring health outcomes by stochastic multi-objective acceptability analysis: an application to Italian regions

Author

Listed:
  • Raffaele Lagravinese
  • Paolo Liberati
  • Giuliano Resce

Abstract

This paper introduces the Stochastic Multi-Objective Acceptability Analysis (SMAA) in order to investigate the evolution of mortality rates in the Italian regions over the period 1990-2013. We propose to explore the overall outcome of health care by a Composite Index (CI) of mortality based on the combination of standardized mortality rates for seventeen different diseases. From a methodological standpoint, we propose to overcome the arbitrary of the weighting process, by using the SMAA, which is a methodology that allows to rank regions considering the whole set of possible vectors of weights. Moreover, we explore the spatial segregation in health using the multidimensional generalization of the Gini index, and introducing the multidimensional generalization of ANOGI. The unprecedented use of SMAA in health sector allows to explore regional multidimensional paths beyond the order of importance given to the single dimensions. Our analysis shows that in the 24 years considered there has been no convergence path in terms of health care outcome in Italy, neither between nor within regions.

Suggested Citation

  • Raffaele Lagravinese & Paolo Liberati & Giuliano Resce, 2017. "Exploring health outcomes by stochastic multi-objective acceptability analysis: an application to Italian regions," Working Papers. Collection B: Regional and sectoral economics 1703, Universidade de Vigo, GEN - Governance and Economics research Network.
    • Handle: RePEc:gov:wpregi:1703
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    File URL: http://infogen.webs.uvigo.es/WPB/WP1703.pdf
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    2. Dino Rizzi & Michele Zanette, 2021. "Potential efficiency gains and expenditure savings in the Italian Regional Healthcare Systems," Politica economica, Società editrice il Mulino, issue 2, pages 187-214.
    3. Cavalieri, Marina & Ferrante, Livio, 2020. "Convergence, decentralization and spatial effects: An analysis of Italian regional health outcomes," Health Policy, Elsevier, vol. 124(2), pages 164-173.

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    More about this item

    Keywords

    Stochastic Multi-Objective Acceptability Analysis; Composite Indicators; Health; Spatial Inequality; ANOGI;
    All these keywords.

    JEL classification:

    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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