Examination of Efficiency Change of Provincial Hospitals in Azerbaijan with Malmquist Index

Abstract

The level of development in health is an important criterion for countries. In a study aimed at measuring the performance of the health system in Azerbaijan on a provincial basis, the change in health efficiency of 56 cities between 2015-2019 was analyzed with the Malmquist Total Factor Productivity Index (MPI). As an input variable, the number of hospital beds, the number of health workers and the number of physicians were used in the provinces. The values used in input variables are figures per 10,000 people. As an output variable, the number of deaths of infants (under 1 year old), the number of deaths and the number of outpatient clinics were determined. The values used in the output variables are figures per 1000 people. The average MPI scores of the provinces covered by the study were 0.998 in 2015-2016, 1.002 in 2016-2017, 1.036 in 2017-2018 and 1.027 in 2018-2019. Out of the sample cluster of 56 provinces, Total Factor Productivity (TFP) increased in 36 (64.29%), remained constant in 1 (1.79%) and decreased in 19 (33.93%). Furthermore, TFP values were highest in Qazakh (20.6%), Aghdam (12,7) and Dashkesen (12,2). As a result of the study, it was found that there was an increase in productivity levels during the time period when the health performance of the provinces in Azerbaijan was evaluated. For this reason, it is proposed to develop actions and policies aimed at improving performance in low-productivity provinces and to allocate resources taking into account social needs.

Keywords

• Malmquist productivity index
• efficiency measurement
• health performance

References

1. SSCRA, The State Statistical Committee of the Republic of Azerbaijan, (2020), Regions of Azerbaijan. https://www.stat.gov.az/source/regions/, (accessed March 14, 2021). Candemir, M. and Deliktaş, E. (2006). Technical efficiency, scale efficiency, technical progress, efficiency change and productivity analysis in the state-owned agricultural enterprises in Turkey :1999-2003, Ankara: TIGEM Yayın No: 141.
2. Coelli, T. (1996). A guide to frontier version 4.1: A computer program for stochastic frontier production and cost function estimation. CEPA Working Papers, 7 (Centre for Efficiency and Productivity Analysis University of New England Armidale,Australia), 1–33.
3. Coelli, T.J., Prasada Rao D.S., O'Donnell C.J. and Battese G.E. (2005). An introduction to efficiency and productivity analysis. Second Edition. New York: Springer.
4. Dirik, C. ve Sahin, S. (2020). Efficiency and productivity analysis of health services in Turkey: A Comparison of radial and non-radial DEA and MPI models. Journal of Visioner Suleyman Demirel University, 11 (28), 790-814.
5. Fare, R., Grosskopf, S., Norris, M. and Zhang, Z. (1994). American economic association productivity growth, technical progress and efficiency change in ındustrialized countries. American Economic Association, 84(1), 66–83.
6. Flokou, A., Aletras, V. and Niakas, D. (2017). A Window-DEA based efficiency evaluation of the public hospital sector in greece during the 5-year economic crisis. PLoS ONE, 12(5), 1–26.
7. Henri, J. F. (2004). Performance measurement and organizational effectiveness: Bridging the gap. Managerial Finance, 30(6), 93–123.
8. Kutlar, A., Gülcü, A. and Karagöz, Y. (2004). The performence assessment of different faculties of Cumhuriyet University. Journal of Economics and Administrative Sciences Cumhuriyet University, 5(2), 137–157.

9. Kutlar, A. and Salamov, F. (2016). Investigation of efficiency change in Azerbaijani public hospitals: Malmquist Index approach. The Sakarya Journal of Economics, 5 (1), 18-33
10. Loeb, J. M. (2004). The current state of performance measurement in health care. International Journal for Quality in Health Care, 16(SUPPL. 1), 5–10.
11. Ozcan, Y. A. (2014). Health care benchmarking and performance evaluation an assessment using data envelopment analysis (DEA). International Series in Operations Research & Management Science. USA: Springer International Publishing.
12. Prokopenko, J. (2011). Verimlilik yönetimi uygulamalı el kitabı, Milli Prodüktivite Merkezi Yayınları: 476, 7. Baskı, Ankara.
13. Raei, B., Yousefi, M., Rahmani, K., Afshari, S., and Ameri, H. (2017). Patterns of productivity changes in hospitals by using malmquist-DEA index: A panel data analysis (2011–2016). AMJ, 10(10), 856–864.
14. Şahin, İ. (1999). Sağlık kurumlarında göreceli verimlilik ölçümü: Sağlık Bakanlığı hastanelerinin illere göre karşılaştırmalı verimlilik analizi. Amme İdaresi Dergisi, 32(2). 123-145
15. Tengilimoğlu, D., Işık, O. and Akbolat, M. (2017). Sağlık işletmeleri yönetimi. Nobel Akademik Yayıncılık Eğitim Danışmanlık Ltd. Şti., 8. Baskı, Ankara.
16. Tone, K. (2004). Malmquist productivity index: Efficiency Change Over Time: in Cooper, WW, Seiford, LM, Zhu, J. Handbook on Data Envelopment Analysis.
17. Yüksel, O. and Yiğit, V. (2020). Malmquist Total Factor Productivity Index: an application in oral and dental health centers. Suleyman Demirel University The Journal of Health Science, 11(4), 466-474.