Factors Affecting the Technical Efficiency of Health Systems: A Case Study of Economic Cooperation Organization (ECO) Countries (2004–10)

Document Type : Original Article

Authors

Department of Health Services Administration, School of Management and Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran

Abstract

Background
Improving efficiency of health sector is of particular importance in all countries. To reach this end, it is paramount to measure the efficiency. On the other hand, there are many factors that affect the efficiency of health systems. This study aimed to measure the Technical Efficiency (TE) of health systems in Economic Cooperation Organization (ECO) countries during 2004–10 and to determine the factors affecting their TE.
 
Methods
This was a descriptive-analytical and panel study. The required data were gathered using library and field studies, available statistics and international websites through completing data collection forms. In this study, the TE of health systems in 10 ECO countries was measured using their available data and Data Envelopment Analysis (DEA) through two approaches. The first approach used GDP per capita, education and smoking as its inputs and life expectancy and infant mortality rates as the outputs. The second approach, also, used the health expenditures per capita, the number of physicians per thousand people, and the number of hospital beds per thousand people as its inputs and life expectancy and under-5 mortality rates as the outputs. Then, the factors affecting the TE of health systems were determined using the panel data logit model. Excel 2010, Win4Deap 1.1.2 and Stata 11.0 were used to analyze the collected data.
 
Results
According to the first approach, the mean TE of health systems was 0.497 and based on the second one it was 0.563. Turkey and Turkmenistan had, respectively, the highest and lowest mean of efficiency. Also, the results of panel data logit model showed that only GDP per capita and health expenditures per capita had significant relationships with the TE of health systems.
 
Conclusion
In order to maximize the TE of health systems, health policy-makers should pay special attention to the proper use of healthcare resources according to the people’s needs, the appropriate management of the health system resources, allocating adequate budgets to the health sector, establishing an appropriate referral system to provide better public access to health services according to their income and needs, among many others.

Keywords

Main Subjects

References

  1.  

    1. Bankauskaite V, Dargent G. Health systems performance indicators: methodological issues. Presupuesto y Gasto Público 2007; 49: 125-37.
    2. Clayton AC. Assessing the Productive Efficiency of US Health Care: Comparison of Analytical Methods [internet]. Honors Projects 2010: 106. Available from: http://digitalcommons.iwu.edu/econ_honproj/106/
    3. Collins C, Green A. Decentralization and primary health care: some negative implications in developing countries. Int J Health Serv 1994; 24: 459-76. doi: 10.2190/g1xj-px06-1lvd-2fxq
    4. Schieber GJ. Preconditions for health reform: experiences from the OECD countries. Health Policy 1995; 32: 279-93. doi: 10.1016/0168-8510(95)00740-J
    5. Varela PS, de Andrade Martins G, Fávero LPL. Production efficiency and financing of public health: an analysis of small municipalities in the state of São Paulo—Brazil. Health Care Manag Sci  2010; 13: 112-23. doi: 10.1007/s10729-009-9114-y
    6. World Health Organization (WHO). The world health report 2000 - health systems: improving performance. Geneva: WHO; 2000.
    7. Vitaliano DF, Toren M. Hospital cost and efficiency in a regime of stringent regulation. East Econ J 1996: 22; 161-75.
    8. Mehregan MR. Quantitative models for assessment of organizations performance (DEA). Tehran: School of Management, Tehran University; 2008.
    9. Torkamani J. The impact of insurance on farmers’ technical efficiency and risk aversion: the use of stochastic frontier production functions. Journal of Agricultural and Development Economics 2009; 22: 45-8.
    10. Pinto C. Technical Efficiency in the Production of Aggregate Regional Health Outcomes in Italy. Finance Research 2013; 2: 4-11.
    11. de Cos PH, Moral-Benito E. Determinants of health-system efficiency: evidence from OECD countries. Int J Health Care Finance Econ 2014: 14; 69-93. doi: 10.1007/s10754-013-9140-7
    12. Hadad S, Hadad Y, Simon-Tuval T. Determinants of healthcare system’s efficiency in OECD countries. Eur J Health Econ 2013; 14: 253-65. doi: 10.1007/s10198-011-0366-3
    13. Afonso A, Schuknecht L, Tanzi V. Public sector efficiency: an international comparison. Public Choice 2005; 123: 321-47. doi: 10.1007/s11127-005-7165-2
    14. Ramsay CR, Grant A, Wallace S, Garthwaite P, Monk A, Russell I. Statistical assessment of the learning curves of health technologies. Health Technol Assess 2001; 5: 1-79.
    15. Wooldridge J. Econometric Analysis of Cross Section and Panel Data. Cambridge: MIT Press; 2002.
    16. Jones AM. Applied econometrics for health economists: a practical guide. 2nd edition. Oxford: Radcliffe Publishing; 2007.
    17. Gujarati DN. Basic Econometrics. 4th edition. New York: McGraw-Hill; 2003.
    18. Varabyova Y, Schreyögg J. International comparisons of the technical efficiency of the hospital sector: Panel data analysis of OECD countries using parametric and non-parametric approaches. Health Policy 2013; 112: 70-9. doi: 10.1016/j.healthpol.2013.03.003
    19. Sabbagh Kermani M, Yavari K, Basakha M, Shahtahmasbi E. Education and Health Expenditure Efficiency in OIC Countries: Using a DEA Approach. The Economic Research 2009; 9: 65-87.
    20. World Health Organization (WHO). WHO European Region: Turkey statistics summary (2002 - present) [internet]. [cited 2014  February 5]. Available from: http://apps.who.int/gho/data/node.country.country-TUR
    21. World Health Organization (WHO). WHO European Region: Turkmenistan statistics summary (2002 - present).   [cited 2014 February 5]. Available from: http://apps.who.int/gho/data/node.country.country-TKM
    22. Zhang N, Hu A, Zheng J. Using Data Envelopment Analysis approach to estimate the health production efficiencies in China. Frontiers of Economics in China 2007; 2: 1-23. doi: 10.1007/s11459-007-0001-5
    23. Gustavson KR, Lonergan SC, Ruitenbeek HJ. Selection and modeling of sustainable development indicators: a case study of the Fraser River Basin, British Columbia. Ecol Econ 1999; 28: 117-32. doi: 10.1016/s0921-8009(98)00032-9
    24. Verhoeven M, Gunnarsson V, Carcillo S. Education and Health in G7 Countries: Achieving Better Outcomes with Less Spending. Washington, DC: International Monetary Fund; 2007. doi: 10.5089/9781451868265.001
    25. Prasetyo AD, Zuhdi U. The Government Expenditure Efficiency towards the Human Development. Procedia Economics and Finance 2013; 5: 615-22. doi: 10.1016/s2212-5671(13)00072-5
    26. Sumaili FK, Milimo J. Health Sector Reform Review: A Report. Lusaka: Participatory Assessment Group (PAG); 1996.
    27. Retzlaff-Roberts D, Chang CF, Rubin RM. Technical efficiency in the use of health care resources: a comparison of OECD countries. Health Policy 2004; 69: 55-72. doi: 10.1016/j.healthpol.2003.12.002
    28. Or Z, Wang J, Jamison D. International differences in the impact of doctors on health: a multilevel analysis of OECD countries. J Health Econ 2005; 24: 531-60. doi: 10.1016/j.jhealeco.2004.09.003
    29. Aakvik A, Holmås TH. Access to primary health care and health outcomes: the relationships between GP characteristics and mortality rates. J Health Econ 2006; 25: 1139-53. doi: 10.1016/j.jhealeco.2006.04.001
    30. Macinko J, Marinho de Souza Mde F, Guanais FC, da Silva Simões CC. Going to scale with community-based primary care: an analysis of the family health program and infant mortality in Brazil, 1999–2004. Soc Sci Med 2007; 65: 2070-80. doi: 10.1016/j.socscimed.2007.06.028
    31. Monin JL, Lancellotti P, Monchi M, Lim P, Weiss E, Piérard L, et al. Risk score for predicting outcome in patients with asymptomatic aortic stenosis. Circulation 2009; 120: 69-75. doi: 10.1161/circulationaha.108.808857
    32. Starfield B, Shi L, Macinko J. Contribution of primary care to health systems and health. Milbank Q 2005; 83: 457-502. doi: 10.1111/j.1468-0009.2005.00409.x
    33. Nolte E, McKee CM. Measuring the health of nations: updating an earlier analysis. Health Aff (Millwood) 2008; 27: 58-71. doi: 10.1377/hlthaff.27.1.58
    34. Jones J, Rowan K. Is there a relationship between the volume of work carried out in intensive care and its outcome? Int J Technol Assess Health Care 1995; 11: 762-9. doi: 10.1017/s0266462300009193
    35. Javitt JC, Street DA, Tielsch JM, Wang Q, Kolb MM, Schein O, et al. National Outcomes of Cataract Extraction: Retinal Detachment and Endophthalmids after Outpatient Cataract Surgery. Ophthalmology 1994; 101: 100-6. doi: 10.1016/S0161-6420(13)31251-2
    36. Kelly JV. What do mortality studies reveal about hospital volume, teaching status, and ownership? Int J Technol Assess Health Care 1990; 6: 239-52. doi: 10.1017/s0266462300000763
    37. Borghans I, Heijink R, Kool T, Lagoe RJ, Westert GP. Benchmarking and reducing length of stay in Dutch hospitals. BMC Health Serv Res 2008; 8: 220. doi: 10.1186/1472-6963-8-220
    38. Grigoli F. Public Expenditure in the Slovak Republic: Composition and Technical Efficiency. Washington, DC: International Monetary Fund; 2012. doi: 10.5089/9781475505214.001
    39. Jafarov E, Gunnarsson V. Government spending on health care and education in Croatia: efficiency and reform options. Washington, DC: International Monetary Fund; 2008. doi: 10.5089/9781451869958.001
    40. Evans RG, Lomas J, Barer ML, Labelle RJ, Fooks C, Stoddart GL, et al. Controlling health expenditures--the Canadian reality. N Engl J Med 1989; 320: 571-7. Doi: 10.1056/nejm198903023200906

     

     

     

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