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Inter-Regional Performance of the Public Health System in a High-Inequality Country

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  • Maria Cristina Gramani

Abstract

Previous cross-country studies have revealed a relationship between health and socio-economic factors. However, multinational studies that use aggregate figures could obfuscate the actual situation in each individual region, or even in each individual federal unit, mainly in a developing country that spans a continent and has large socioeconomic inequalities. We conducted a within-country study, in Brazil, of health system performance that examined data in the four perspectives that most strongly affect the performance of public health systems: financial, customer, internal processes and learning&growth. After estimating the interregional health system performance from each perspective, we identified the determinants of inefficiency (i.e., the factors that have the greatest potential for improvement in each region). The results showed that the major determinants of inefficiency in the less efficient regions (N and NE) are concentrated in the perspective of learning&growth (the number of health professionals and the number of graduates with a health-related undergraduate degree) and, in the regions with the best performance (S and SE) the major determinants of inefficiency are concentrated in the financial perspective (spending on health care and the amount paid for hospitalization).

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  • Maria Cristina Gramani, 2014. "Inter-Regional Performance of the Public Health System in a High-Inequality Country," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-8, January.
    • Handle: RePEc:plo:pone00:0086687
    DOI: 10.1371/journal.pone.0086687
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    1. Varmazyar, Mohsen & Dehghanbaghi, Maryam & Afkhami, Mehdi, 2016. "A novel hybrid MCDM model for performance evaluation of research and technology organizations based on BSC approach," Evaluation and Program Planning, Elsevier, vol. 58(C), pages 125-140.
    2. Renan Felinto de Farias Aires & Camila Cristina Rodrigues Salgado, 2022. "A Multi-Criteria Approach to Assess the Performance of the Brazilian Unified Health System," IJERPH, MDPI, vol. 19(18), pages 1-13, September.
    3. Hainan Guo & Yang Zhao & Tie Niu & Kwok-Leung Tsui, 2017. "Hong Kong Hospital Authority resource efficiency evaluation: Via a novel DEA-Malmquist model and Tobit regression model," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-24, September.

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