Analysis of Medical Imaging Devices in Türkiye Using the Malmquist Productivity Index

Year 2025, Volume: 59 Issue: 4, 769 - 786, 08.10.2025

Yavuz Selim Küçük

https://doi.org/10.51551/verimlilik.1710968

Abstract

Purpose: The aim of this study is to analyze the total factor productivity (TFP) of medical imaging devices in 12 regions of Türkiye for the period 2013–2022 using the Malmquist Productivity Index and to determine whether there are statistically significant differences in the TFP indicators of these devices by region and year.
Methodology: Secondary data from the Ministry of Health’s Health Statistics Yearbooks were analyzed using DEAP software with constant returns to scale (CRS) input-oriented Malmquist Productivity Index. Descriptive statistics of the data and correlations between variables were calculated with the SPSS 21.0 program, and the Mann-Whitney U test was applied to statistically test regional and temporal differences.
Findings: CT, MRI, and Doppler USG devices showed higher productivity, while ECHO and mammography exhibited lower levels. Productivity was higher in northern and western regions and lower in the south and east, with no consistent improvement observed from 2013 to 2022.
Originality: This study contributes to the literature by analyzing the TFP of medical imaging devices in 12 regions of Türkiye using the Malmquist Index, and introduces a novel approach by combining it with the Mann-Whitney U test to assess regional and temporal differences.

Keywords

Malmquist Productivity Index , Data Envelopment Analysis , Medical Imaging Devices

Ethical Statement

It was declared by the author that the tools and methods used in the study do not require the permission of the Ethics Committee. It was declared by the author that scientific and ethical principles have been followed in this study and all the sources used have been properly cited.

Supporting Institution

Any specific grant has not been received from funding agencies in the public, commercial, or not-for-profit sectors.

Project Number

-

Malmquist Verimlilik İndeksi ile Türkiye’deki Tıbbi Görüntüleme Cihazlarının Analizi

Abstract

Amaç: Bu çalışmanın amacı, Malmquist Verimlilik İndeksi ile Türkiye’deki 12 bölgede 2013–2022 dönemine ait tıbbi görüntüleme cihazlarının toplam faktör verimliliğini (TFP) analiz etmek ve Türkiye’deki tıbbi görüntüleme cihazlarının toplam faktör verimlilik göstergelerinde bölgelere ve yıllara göre istatistiksel bir fark olup olmadığını belirlemektir.
Yöntem: Sağlık Bakanlığı Sağlık İstatistikleri Yıllıklarından (2013-2022) ikincil veriler, ölçeğe göre sabit getiri (CRS) girdi odaklı Malmquist Verimlilik Endeksi ile DEAP yazılımı kullanılarak analiz edilmiştir. Verilerin tanımlayıcı istatistikleri ve değişkenler arası korelasyonlar SPSS 21.0 programı ile hesaplanmış, bölgesel ve zamansal farkların istatistiksel olarak test edilmesi amacıyla Mann-Whitney U testi uygulanmıştır.
Bulgular: BT, MR ve Doppler USG cihazları daha yüksek verimlilik gösterirken, EKO ve mamografi daha düşük verimlilik göstermektedir. Verimlilik kuzey ve batı bölgelerinde daha yüksek, güney ve doğuda ise daha düşük verimlilik göstergesine sahip ve 2013'ten 2022'ye kadar istikrarlı bir iyileşme gözlemlenmemiştir.
Özgünlük: Bu çalışma, Türkiye'nin 12 bölgesinde (2013-2022) tıbbi görüntüleme cihazlarının TFP'sini Malmquist İndeksi kullanarak analiz ederek literatüre katkıda bulunmak ve bölgesel ve zamansal farklılıkları değerlendirmek için Mann-Whitney U testi ile birleştirerek yeni bir yaklaşım ortaya koymaktır.

Keywords

Malmquist Verimlilik İndeksi , Veri Zarflama Analizi , Tıbbi Görüntüleme Cihazları

Ethical Statement

Yazar tarafından çalışmada kullanılan araç ve yöntemlerin Etik Kurul izni gerektirmediği beyan edilmiştir. Yazar tarafından bu çalışmada bilimsel ve etik ilkelere uyulduğu ve kullanılan tüm kaynakların uygun şekilde gösterildiği beyan edilmiştir.

Supporting Institution

Kamu, ticari veya kar amacı gütmeyen sektörlerdeki fonlama kuruluşlarından herhangi bir özel hibe alınmamıştır.

Project Number

-

References

• Adugna, M., Dinsa, G. and Khuzwayo, N. (2024). “Can Performance-Based Financing Improve Efficiency of Health Centers in Ethiopia? A Malmquist Productivity Index Analysis”, BMC Health Services Research, 24(1), 8, Article 696. https://doi.org/10.1186/s12913-024-11127-4
• Arhin, K. and Asante-Darko, D. (2023). “Performance Evaluation of National Healthcare Systems in the Prevention and Treatment of Non-Communicable Diseases in Sub-Saharan Africa”, PLoS One, 18(11). https://doi.org/https://doi.org/10.1371/journal.pone.0294653
• Banker, R.D., Charnes, A. and Cooper, W.W. (1984). “Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis”, Management Science, 30(9), 1078-1092.
• Charnes, A., Cooper, W.W. and Rhodes, E. (1978). “Measuring the efficiency of decision making units”, European Journal of Operational Research, 2(6), 429-444. https://doi.org/https://doi.org/10.1016/0377-2217(78)90138-8
• Charnes, A., Cooper, W. W. and Rhodes, E. (1981). “Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through”, Management Science, 27(6), 668-697.
• Chern, J-Y. and Wan, T.T. (2000). “The Impact of the Prospective Payment System on the Technical Efficiency of Hospitals”, Journal of Medical Systems, 24, 159-172.
• Coelli, T.J., Rao, D.S.P., O'donnell, C. J. and Battese, G. E. (2005). “An Introduction to Efficiency and Productivity Analysis”, Springer Science & Business Media.
• Färe, R., Grosskopf, S., Norris, M. and Zhang, Z. (1994). “Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries”, The American Economic Review, 84(1), 66-83.
• Farrell, M.J. (1957). “The Measurement of Productive Efficiency”, Royal Statistical Society Journal Series A: General, 120(3), 253-281. https://doi.org/10.2307/2343100
• Gong, Y. H., Ma, D. and Feng, W. (2024). Study on the allocation efficiency of medical and health resources in Hainan Province: Based on the super-efficiency SBM-Malmquist model. PLoS One, 19(2), 12, Article e0294774. https://doi.org/10.1371/journal.pone.0294774
• Hollingsworth, B. (2008). “The Measurement of Efficiency and Productivity of Health Care Delivery”. Health Economics, 17(10), 1107-1128.
• Huang, R., Li, W., Shi, B. G., Su, H., Hao, J., Zhao, C. J. and Chai, J. H. (2024). “Evaluating China's Primary Healthcare Services' Efficiency and Spatial Correlation: A Three-Stage DEA-Malmquist Model”, Frontiers in Public Health, 12, 16, Article 1366327. https://doi.org/10.3389/fpubh.2024.1366327
• Huang, X., Wei, Y., Sun, H., Huang, J., Chen, Y. and Cheng, J. (2023). “Assessment of Equity and Efficiency of Magnetic Resonance Imaging Services in Henan Province, China”, Cost Effectiveness and Resource Allocation, 21, 32. https://doi.org/10.1186/s12962-023-00440-0
• İlgün, G., Sönmez, S. and Koca, G. (2021). “An Evaluation on Medical Device Usage Status: A Study on Turkey and European Union Countries”, Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, (60), 381-398. https://doi.org/10.18070/erciyesiibd.874217
• İlgün, G., Sönmez, S., Konca, M. and Çakmak, C. (2022). “Evaluation of Factors Affecting the Efficiency of Medical Imaging Devices in Turkey: Two-Stage Data Envelopment Analysis”, Manisa Celal Bayar University Health Sciences Institute Journal, 9(4), 492-500. https://doi.org/10.34087/cbusbed.994765
• Li, M., Guo, J.M. and Dong, S.P. (2024). “The Regional Total Factor Productivity Changes of Healthcare Delivery in China: A Bootstrap Malmquist Data Envelopment Analysis”, Inquiry-The Journal of Health Care Organization Provision and Financing, 61. https://doi.org/10.1177/00469580241266373
• Li, Z., Zhang, W., Kong, A., Ding, Z., Wei, H. and Guo, Y. (2021). “Configuration Analysis of Influencing Factors of Technical Efficiency Based on DEA and fsQCA: Evidence from China’s Medical and Health Institutions”, Risk Management and Healthcare Policy, 14, 49-65. https://doi.org/10.2147/RMHP.S282178
• Lindaas, N.A., Anthun, K.S. and Magnussen, J. (2024). “New Public Management and Hospital Efficiency: The Case of Norwegian Public Hospital Trusts”, BMC Health Services Research, 24, 36. https://doi.org/10.1186/s12913-023-10479-7
• Medarevic, A. and Vukovic, D. (2021). “Efficiency and Productivity of Public Hospitals in Serbia Using DEA-Malmquist Model and Tobit Regression Model, 2015-2019”, International Journal of Environmental Research and Public Health, 18(23), 22, 12475. https://doi.org/10.3390/ijerph182312475
• Nak, H. and Sağbaş, İ. (2020). “Analysis of Regional Distribution of Medical Imaging Devices within Health Expenditures”, Journal of Public Finance Studies, 63, 77-92. https://doi.org/10.26650/mcd2020-822594 Ozcan, Y.A. (2008). “Health Care Benchmarking and Performance Evaluation”. Springer.
• Republic of Turkey Ministry of Health. (2024). “Ministry of Health of Turkey Health Statistics Yearbook 2022”, https://dosyasb.saglik.gov.tr/Eklenti/48055/0/siy2022eng050420241pdf.pdf, (Accessed:11.08.2025).
• Singh, S., Bala, M.M., Kumar, N. and Janor, H. (2021). “Application of DEA-Based Malmquist Productivity Index on Health Care System Efficiency of ASEAN Countries”, International Journal of Health Planning and Management, 36(4), 1236-1250. https://doi.org/10.1002/hpm.3169
• Soares, T.C. and Lopes, L.S. (2024). “Decreasing Productivity in the Primary Healthcare: A Study of the Brazilian Case”, The Journal of Developing Areas, 58(4), 43-60. https://doi.org/10.1353/jda.2024.a931315
• Sun, M., Ye, Y., Zhang, G., Shang, X. and Xue, Y. (2023). “Healthcare Services Efficiency and Its Intrinsic Drivers in China: Based on the Three-Stage Super-Efficiency SBM Model”, BMC Health Services Research, 23, 1-17. https://doi.org/https://doi.org/10.1186/s12913-023-09820-x
• Trakakis, A., Nektarios, M., Tziaferi, S. and Prezerakos, P. (2021). “Total Productivity Change of Health Centers in Greece in 2016-2018: A Malmquist Index Data Envelopment Analysis Application for the Primary Health System of Greece”, Cost Effectiveness and Resource Allocation, 19, 72. https://doi.org/10.1186/s12962-021-00326-z
• Visintin, F., Aloini, D., Gitto, S., Vannelli, S. and Di Feo, D. (2024). “Efficiency in Radiology Departments: A Two-Stage Analysis”, Flexible Services and Manufacturing Journal, 36(2), 481-502. https://doi.org/10.1007/s10696-023-09499-6
• World Health Organization. (2011). “Health Technology Assessment of Medical Devices”, World Health Organization.
• Xu, X., Yasmeen, R. and Shah, W.U.H. (2024). “Efficiency Evaluation, Regional Technological Heterogeneity and Determinant of Total Factor Productivity Change in China’s Healthcare System”, Scientific Reports, 14(1), 19606. https://doi.org/https://doi.org/10.1038/s41598-024-70736-5
• Yüksel, O. (2023). “Efficiency of Medical Imaging Techniques in Hospitals by Sector”, Munzur University Journal of Social Sciences, 12(2), 133-152.
• Zeng, Z., Yu, X., Tao, W., Feng, W. and Zhang, W. (2024). “Efficiency Evaluation and Promoter Identification of Primary Health Care System in China: An Enhanced DEA-Tobit Approach”, BMC Health Services Research, 24, 1-11. https://doi.org/https://doi.org/10.1186/s12913-024-11244-0
• Zhou, J.X., Peng, R., Chang, Y.J., Liu, Z.J., Gao, S.H., Zhao, C.J., Li, Y.X., Feng, Q.M. and Qin, X.J. (2023). “Analyzing the Efficiency of Chinese Primary Healthcare Institutions Using the Malmquist-DEA Approach: Evidence from Urban and Rural Areas”, Frontiers in Public Health, 11, 1073552. https://doi.org/10.3389/fpubh.2023.1073552