• ISSN: 2148-2225 (online)

Ulaştırma ve Lojistik Kongreleri

alphanumeric journal

The Journal of Operations Research, Statistics, Econometrics and Management Information Systems

Benchmarking healthcare systems of OECD countries: A DEA - based Malmquist Productivity Index Approach

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Ayhan Aydın


Abstract

Along with technological innovations and developments experienced in the second half of the twentieth century, very important changes have occurred in healthcare. Many different, complex and economically expensive services are being tried to be carried out together. For this reason, it is finally crucial that the health services delivered by providers to scarce resources are delivered effectively and efficiently to people without sacrificing quality. Today, the most important problem of the production of healthcare services is the resource shortage as it is in other sectors. Efficiency, quality and competition are important criteria in the production and delivery of health services. Reducing costs in the production of health services is one of the main health policies for many world countries. These policies have made it necessary for international competitiveness, product and service sectors to continually improve their performance. The objective of this paper is to identify the efficiency of healthcare services using the healthcare data of OECD countries through the years 2000 – 2015. Also, this paper examines the fluctuations in total factor productivity, which is obtained by multiplying technical and technological changes in efficiency measurements by years. Using the Malmquist Total Productivity Analysis method, the most efficient healthcare systems are found in Chile, Denmark, Iceland, Israel, Japan, Korea, Mexico, Slovenia, Sweden, and Turkey both technical efficiency and scale efficiency all years.

Keywords: Data Envelopment Analysis, Efficiency, Healthcare, Malmquist, OECD

Jel Classification: C01


Suggested citation

Aydın, A. (). Benchmarking healthcare systems of OECD countries: A DEA - based Malmquist Productivity Index Approach. Alphanumeric Journal, 10(1), 25-40. https://doi.org/10.17093/alphanumeric.1057559

References

  • Koopmans, T. C. (1951). Efficient allocation of resources. Econometrica: Journal of the Econometric Society, 455-465.
  • Hollingsworth, B., & Parkin, D. (2001). The efficiency of the delivery of neonatal care in the UK. Journal of Public Health, 23(1), 47-50.
  • Harrison, J. P., Coppola, M. N., & Wakefield, M. (2004). Efficiency of federal hospitals in the United States. Journal of medical systems, 28(5), 411-422.
  • Ehreth, J. L. (1994). The development and evaluation of hospital performance measures for policy analysis. Medical care, 568-587.
  • Worthington, A. C. (2004). Frontier efficiency measurement in health care: a review of empirical techniques and selected applications. Medical care research and review, 61(2), 135-170.
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253-281.
  • Şenel, T., & Gümüştekin, S. (2015). Samsun'daki Hastanelerin Etkinliklerinin Değerlendirilmesinde Veri Zarflama Analizi Kullanılması. International Anatolia Academic Online Journal Sciences Journal, 3(2).
  • Wilson, G. W., & Jadlow, J. M. (1982). Competition, profit incentives, and technical efficiency in the provision of nuclear medicine services. The Bell Journal of Economics, 472-482.
  • Nunamaker, T. R. (1983). Measuring routine nursing service efficiency: a comparison of cost per patient day and data envelopment analysis models. Health services research, 18(2 Pt 1), 183.
  • Sherman, H. D. (1984). Hospital efficiency measurement and evaluation: empirical test of a new technique. Medical care, 922-938.
  • Register, C. A., & Bruning, E. R. (1987). Profit incentives and technical efficiency in the production of hospital care. Southern Economic Journal, 899-914.
  • Grosskopf, S., & Valdmanis, V. (1987). Measuring hospital performance: A non-parametric approach. Journal of health Economics, 6(2), 89-107.
  • Cullinane, K., Song, D. W., Ji, P., & Wang, T. F. (2004). An application of DEA windows analysis to container port production efficiency. Review of network Economics, 3(2).
  • Zare Ahmadabadi, H., Masoudian, S., & Zare Banadkouki, M. R. (2019). Evaluating the technical efficiency of Yazd City health centers with a combined approach of DEA and GT. SSU_Journals, 26(8), 717-732.
  • Li, Y., Lei, X., & Morton, A. (2019). Performance evaluation of nonhomogeneous hospitals: the case of Hong Kong hospitals. Health care management science, 22(2), 215-228.
  • Palmer, S., & Torgerson, D. J. (1999). Definitions of efficiency. Bmj, 318(7191), 1136.
  • Lameire, N., Joffe, P., & Wiedemann, M. (1999). Healthcare systems—an international review: an overview. Nephrology Dialysis Transplantation, 14(suppl_6), 3-9.
  • Chou, S. Y., Liu, J. T., & Hammitt, J. K. (2003). National health insurance and precautionary saving: evidence from Taiwan. Journal of Public Economics, 87(9-10), 1873-1894.
  • Wendt, C., Frisina, L., & Rothgang, H. (2009). Healthcare system types: a conceptual framework for comparison. Social Policy & Administration, 43(1), 70-90.
  • Anderson, L. M., Scrimshaw, S. C., Fullilove, M. T., Fielding, J. E., Normand, J., & Task Force on Community Preventive Services. (2003). Culturally competent healthcare systems: A systematic review. American journal of preventive medicine, 24(3), 68-79.
  • Abolghasem, S., Toloo, M., & Amézquita, S. (2019). Cross-efficiency evaluation in the presence of flexible measures with an application to healthcare systems. Health care management science, 22(3), 512-533.
  • Sherman, H. D. (1984). Hospital efficiency measurement and evaluation: empirical test of a new technique. Medical care, 922-938.
  • Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1992). Productivity changes in Swedish pharamacies 1980–1989: A non-parametric Malmquist approach. Journal of productivity Analysis, 3(1), 85-101.
  • Falavigna, G., Ippoliti, R., & Manello, A. (2013). Hospital organization and performance: a directional distance function approach. Health Care Management Science, 16(2), 139-151.
  • Çağlar, A. (2003). Veri zarflama analizi ile belediyelerin etkinlik ölçümü. Hacettepe Üniversitesi Fen Bilimleri Enstitüsü, Yayımlanmamış Doktora Tezi, Ankara.
  • Ngo, T., & Nguyen, L. T. P. (2012). Total factor productivity of Thai banks in 2007-2010: An application of DEA and Malmquist index. Journal of Applied Finance and Banking, 2(5), 27-42.
  • de Araújo Junior, J. N., Justo, W. R., de Lima, J. R. F., FERREIRA, M. D. O., Araújo, J. L. P., & Pereira, A. F. C. (2019). Analysis on the Technical Efficiency of Northeast Municipal Expenditure with Basic Education: A DEA Approach and Malmquist's Index. Embrapa Semiárido-Artigo em periódico indexado (ALICE).
  • Malmquist, S. (1953). Index numbers and indifference surfaces. Trabajos de estadística, 4(2), 209-242.
  • Caves, D. W., Christensen, L. R., & Diewert, W. E. (1982). The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica: Journal of the Econometric Society, 1393-1414.
  • Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1994). Productivity developments in Swedish hospitals: a Malmquist output index approach. In Data envelopment analysis: Theory, methodology, and applications (pp. 253-272). Springer, Dordrecht.
  • Rezitis, A. N. (2006). Productivity growth in the Greek banking industry: A non-parametric approach. Journal of Applied economics, 9(1), 119-138.
  • Kök, R., & Şimşek, N. (2006). Endüstri-içi dış ticaret, patentler ve uluslararası teknolojik yayılma. Türkiye Ekonomi Kurumu Uluslararası Ekonomi Konferansı, 11, 13.
  • Wu, W. Y., Tsai, H. J., Cheng, K. Y., & Lai, M. (2006). Assessment of intellectual capital management in Taiwanese IC design companies: using DEA and the Malmquist productivity index. R&D Management, 36(5), 531-545.
  • Al‐Shammari, M. (1999). A multi‐criteria data envelopment analysis model for measuring the productive efficiency of hospitals. International Journal of Operations & Production Management.
  • Zavras, A., Andreopoulos, N., Katsikeris, N., Zavras, D., Cartsos, V., & Vamvakidis, A. (2002). Oral cancer treatment costs in Greece and the effect of advanced disease. BMC Public Health, 2(1), 1-8.
  • Mirmirani, S., Li, H. C., & Ilacqua, J. A. (2008). Health care efficiency in transition economies: an application of data envelopment analysis. International Business & Economics Research Journal (IBER), 7(2).
  • Caballer-Tarazona, M., Moya-Clemente, I., Vivas-Consuelo, D., & Barrachina-Martínez, I. (2010). A model to measure the efficiency of hospital performance. Mathematical and computer modelling, 52(7-8), 1095-1102.
  • Varabyova, Y., & Schreyögg, J. (2013). International comparisons of the technical efficiency of the hospital sector: panel data analysis of OECD countries using parametric and non-parametric approaches. Health policy, 112(1-2), 70-79.
  • Moran, V., & Jacobs, R. (2013). An international comparison of efficiency of inpatient mental health care systems. Health Policy, 112(1-2), 88-99.
  • Popescu, C., Asandului, L., & Fatulescu, P. (2014). A data envelopment analysis for evaluating Romania's health system. Procedia-Social and Behavioral Sciences, 109, 1185-1189.
  • Asandului, L., Roman, M., & Fatulescu, P. (2014). The efficiency of healthcare systems in Europe: A data envelopment analysis approach. Procedia Economics and Finance, 10, 261-268.
  • Daştan, İ., & Çetinkaya, V. (2015). OECD ülkeleri ve Türkiye’nin sağlık sistemleri, sağlık harcamaları ve sağlık göstergeleri karşılaştırması. SGD-Sosyal Güvenlik Dergisi, 5(1), 104-134.
  • Bekaroglu, C. (2015). “A Multi-Stage Efficiency Analysis of OECD Healthcare and the Impact of Technical Change”. University of Connecticut, Doktora tezi.
  • Berenguer, G., Iyer, A. V., & Yadav, P. (2016). Disentangling the efficiency drivers in country-level global health programs: An empirical study. Journal of Operations Management, 45, 30-43.
  • Campos, M. S., Fernández-Montes, A., Gavilan, J. M., & Velasco, F. (2016). Public resource usage in health systems: a data envelopment analysis of the efficiency of health systems of autonomous communities in Spain. Public health, 138, 33-40.
  • Öztürk, E. G. (2016). Health System Performance in OECD Countries: Data Envelopment Analysis. Sosyal Bilimler Enstitüsü, Yüksek Lisans Tezi.
  • Kara, N. O., Yeşilaydın, G., & Hancıoğlu, Y. A STUDY ON GRADUATE THESIS ABOUT COMPETITION IN TURKEY. CIEP 2017 PROCEEDINGS BOOK, 185.
  • Herwartz, H., & Schley, K. (2018). Improving health care service provision by adapting to regional diversity: an efficiency analysis for the case of Germany. Health Policy, 122(3), 293-300.
  • Zhong, K., Chen, L., Cheng, S., Chen, H., & Long, F. (2020). The efficiency of primary health care institutions in the Counties of Hunan province, China: Data from 2009 to 2017. International journal of environmental research and public health, 17(5), 1781.
  • Kuosmanen, T. (2009). Data envelopment analysis with missing data. Journal of the Operational Research Society, 60(12), 1767-1774.

Volume 10, Issue 1, 2022

2022.10.01.OR.02

alphanumeric journal

Volume 10, Issue 1, 2022

Pages 25-40

Received: Jan. 13, 2022

Accepted: June 6, 2022

Published: June 30, 2022

Full Text [809.2 KB]

2022 Aydın, A.

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