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The Correlation Between Four Input Indicators and Six Demographic and Output Indicators Within the East European Healthcare Systems

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Economy, Finance and Business in Southeastern and Central Europe

Part of the book series: Springer Proceedings in Business and Economics ((SPBE))

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Abstract

The purpose of this paper is to compare the relevance of four resource indicators (inputs), in regard to six mortality indicators (outputs) within healthcare systems in 27 East European countries.

The correlation between the following input indicators, number of GPs/100,000 population, health expenditure as % of GDP, total health expenditure PPP $/capita, pharmaceutical expenditure PPP $/capita, and the following demographic and output indicators, life expectancy at birth; reduction of life expectancy through death before 65 years; estimated infant mortality/1000 live births; maternal deaths/100,000 live births; SDR diabetes mellitus, all ages/100,000; and SDR tuberculosis, all ages/100,000, was analyzed.

WHO data was used, for the following East European countries: Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Georgia, Greece, Hungary, Latvia, Lithuania, FYROM, Moldova, Montenegro, Poland, Romania, Russia, Serbia, Slovakia, Slovenia, Turkey, and Ukraine. Data from 2011 was used.

The various degrees of correlation between the input and output indicators were analyzed using scatter diagrams and calculating Pearson linear correlation coefficient.

This type of study can be extended to other health outcome indicators as it can be also tried with other healthcare system resource indicators.

The research shows the importance of real data (money) as compared to percentage data.

Many reform projects as well as policy evaluations are based on “weak” indicators, misleading public perception, hiding policy mistakes, and ultimately leading focus to unimportant things.

The paper tries to shed light on indicators which are really significant from the point of view of policymakers. It might be also of particular interest to students who can understand better the use of indicators.

This paper will be presented as PPT.

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References

  • Market House Books Ltd. (1990a). A concise dictionary of business (p. 167). Oxford: Oxford University Press.

    Google Scholar 

  • Market House Books Ltd. (1990b). A concise dictionary of business (p. 312). Oxford: Oxford University Press.

    Google Scholar 

  • Sava, D. (2014). The correlation between two financial policy indicators and several outcome indicators, a current perspective on health sciences (pp. 690–700). 1-st Balkan congress on health sciences, Edirne.

    Google Scholar 

  • Triola, M. M., & Triola, M. F. (2006a). Correlation and regression. In Biostatistics for the biological and health sciences (p. 431). Boston: Pearson Education.

    Google Scholar 

  • Triola, M. M., & Triola, M. F. (2006b). Correlation and regression. In Biostatistics for the biological and health sciences (p. 640). Boston: Pearson Education.

    Google Scholar 

  • Triola, M. M., & Triola, M. F. (2006c). Correlation and regression. In Biostatistics for the biological and health sciences (p. 436). Boston: Pearson Education.

    Google Scholar 

  • WHO. (2016, April). European health for all database. Available at http://data.euro.who.int/hfadb/

  • World Bank indicators. (2016, April). Available at http://data.worldbank.org/indicator/SP.DYN.LE00.IN

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Acknowledgments

The author would like to thank the WHO and European Health for All database for maintaining and providing free access to a valuable database with public health indicators, pertaining to European countries.

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Correspondence to Dan Sava .

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Sava, D. (2018). The Correlation Between Four Input Indicators and Six Demographic and Output Indicators Within the East European Healthcare Systems. In: Karasavvoglou, A., Goić, S., Polychronidou, P., Delias, P. (eds) Economy, Finance and Business in Southeastern and Central Europe. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-70377-0_29

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