سنجش و اندازه‌گیری بهره‌وری سازمان بهداشت و درمان صنعت نفت ایران
محورهای موضوعی : مهندسی صنایعمیثم عظیمیان 1 , مهدی کرباسیان 2 , حامد رحیم پور 3 , شهرزاد فلاحی 4
1 - دکتری، مهندسی صنایع گرایش کیفیت و بهره وری، سازمان بهداشت و درمان صنعت نفت، شرکت ملی نفت ایران، تهران، ایران
2 - دانشیار گروه مهندسی صنایع، دانشگاه صنعتی مالک اشتر، اصفهان، ایران.
3 - دکتری، مدیریت خدمات بهداشتی و درمانی، سازمان بهداشت و درمان صنعت نفت، شرکت ملی نفت ایران، تهران، ایران
4 - کارشناسی ارشد، مدیریت، سازمان بهداشت و درمان صنعت نفت، شرکت ملی نفت ایران، تهران، ایران
کلید واژه: سازمان‌های ارائه دهنده خدمات سلامت, بهره‌وری, تحلیل پوششی داده‌ها, شاخص مالم‌کوئیست.,
چکیده مقاله :
درسازمان¬های ارائۀ دهندۀ خدمات سلامت، واحدهای زیرمجموعۀ متعددی وجود دارند که به صورت هم‌زمان درحال ارائۀ خدمات درمانی و پیشگیرانه به جمعیت تحت پوشش خاصی بوده و سنجش بهره¬وری از مهمترین چالش¬های پیش روی مدیران آن¬ها می¬باشد؛ لذا هدف اين مطالعه، ارائۀ رویکردی تلفیقی از تحلیل پوششی داده¬ها و شاخص بهره¬وری مالم¬کوئیست، جهت پایش بهره¬وری سازمان بهداشت و درمان صنعت نفت ایران -به عنوان یک سازمان ارائه دهندۀ خدمات سلامت- بوده¬است. دراين تحقيق، با استفاده از شاخص¬های مرتبط با کارایی و همچنین تعریف شاخص¬های اثربخشی تأثیرگذار بر عملکرد واحدهای زیرمجموعه سازمان، ميزان رشد عملکرد واحدهای زیرمجموعه با محاسبه چهار تابع مسافت و شاخص بهره¬وری مالم¬کوئیست تعیین شده¬است. براساس نتایج به‌دست آمده دراین پژوهش، تعداد 27 شاخص تخصصی درحوزه¬های درمان مستقیم، غیرمستقیم و بهداشت جهت پایش اثربخشی سازمان¬های ارائه دهندۀ خدمات سلامت پیشنهاد شده¬است. همچنین نرخ رشد بهره¬وری پانزده منطقۀ زیرمجموعۀ سازمان مورد مطالعه -در بازه زمانی 1398 تا -1400 مورد بررسی قرار گرفته¬است.¬ نوآوری مقالۀ حاضر، عبارت از تعریف شاخص¬های سنجش اثربخشی و ارائۀ یک چارچوب نظری جهت پایش نرخ رشد بهره¬وری در سازمان¬های ارائه دهندۀ خدمات سلامت می¬باشد. توسعۀ کاربردی این تحقیق در سازمان¬های مورداشاره می¬تواند برای ارتقای ظرفیت در حوزه¬های مختلف خدمات بهداشتی- درمانی و صرفه¬جویی در منابع مورداستفاده قرارگیرد.
In health care provider organizations (HCPOs), there are several sub-units, simultaneously providing health and preventive services to the population covered, in which measuring productivity is one of the most important challenges for the managers of these organizations. Hence, the purpose of this study is to provide an integrative approach of data envelopment analysis (DEA) and Malmquist productivity index (MPI) to monitor the productivity in Iranian Petroleum Industry Health Organization (PIHO) as an HCPO. In this study, using the indicators related to efficiency and defining the specialized indicators affecting the performance of the sub-units of this organization, the growth rate of the performance of the sub-units was determined through calculating four distance functions and Malmquist productivity Index. According to the results of this study, 27 specialized indicators in the fields of direct and indirect health and preventive services for monitoring the effectiveness of proposed HCPO have been presented. Also, the growth rate of productivity of the fifteen areas of the organization under study has been evaluated from 2019 to 2021. The innovative aspect of this article lies in the definition of effectiveness measurement indicators and presentation of a theoretical framework for monitoring the rate of productivity in HCPOs. The findings of this applied research in health service organizations can be used to enhance capacity in different areas of health care and save resources.
Almeida , A., Frias, R., & Fique, J. (2015). Evaluating Hospital Efficiency Adjusting for Quality Indicators: An Application to Portuguese NHS Hospitals. Health Economics & Outcome Research, 1(1), 1-5. doi:10.4172/2471-268X/1000103
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. doi:10.1016/S2212-5671(14)00301-3
Asghar , N., Ur Rehman , H., & Ali , M. (2019). Cost Productivity of Healthcare Systems in OIC’s Member Countries: An Application of Cost Malmquist Total Productivity Index. Review of Economics and Development Studies, 5(3), 461-468. doi:10.26710/reads.v5i3.696
Azimian, M., & Akhavan, P. (2018). Performance Analysis of PIHO Family Health Teams: Integrative Approach of DEA and Malmquist. Health Informantion Management, 15(4), 155-161 . doi:10.22122/him.v15i4.3530
Azimian, M., Bardi, M., & Javadi, H. (2013). Sensistivity Analysis of Project Efficiency in a Multi-Project Environment Based on Data Envelopment Analysis. International of Engineering Sciences, 2(7), 259-265. doi:10.1.1.678.9238&rep=rep1&type=pdf
Azimian, M., Karbasian, M., & Atashgar, K. (2022). Developing a Novel Mathematical Approach toward Minimizing Sustainable Circular Economy Costs of One-shot Systems. Production Engineering, 16(1), 627-634. doi:10.1007/s11740-022-01122-1
Azimian, M., Karbasian, M., Atashgar, K., & Kabir, G. (2021). A New Approach to Select the Reliable Suppliers for One-shot Devices. Production Engineering, 15,371–382.doi:10.1007/s11740-021-01032-8
Castro Lobo, M., Ozcan, Y., Silva, A., Estellita Lins, M., & Fiszman , R. (2010). Financing Reform and Productivity Change in Brazilian Teaching Hospitals: Malmquist Approach. Central European Journal of Operations Research, 18(2), 141–152. doi:10.1007/s10100-009-0097-z
Chang, S.-J., Hsiao, H.-C., Huang, L.-H., & Chang, H. (2011). Taiwan Quality Indicator Project and Hospital Productivity Growth. OMEGA, 39(1), 14-22. doi:10.1016/j.omega.2010.01.006
Cheng, Z., Toa, H., Cia, M., Lin, H., Lin, X., Shu, Q., & Zhang, R.-n. (2015). Technical Efficiency and Productivity of Chines Courty Hospitals: An Exploratory Study in Henan Province, China. BMJ, 5(9), 1-10. doi:10.1136/bmjopen-2014-007267
Chowdhury, H., Zeleyuk, V., Laporte, A., & Pwodchis, W. (2014). Analysis of Productivity, Efficiency and Technological Changes in Hospital Servies in Ontario: How does Case-Mix Matter? International Journal of Production Economics, 150, 74-82. doi:10.1016/j.ijpe.2013.12.003
Dabagh, R., Kohi, B., Javaherian, L., & Latifi, M. (2015). Evaluation of Technical Efficiency and Productivity of West Azerbaijan Industries using Parametric and Non-parametric Methods. Parliament and Strategy, 22(83), 305-333. [In Pershian]. Retrieved from https://sid.ir/paper/224633/fa
Ghahremanloo, M., Hasani, A., Amiri, M., Hashemi-Tabatabaei, M., Keshavarz-Ghorabaee, M., & Ustinovičius, L. (2020). A Novel DEA Model for Hospital Performance Evaluation Based on the Measurement of Efficiency, Effectiveness, and Productivity. Engineering Management in Production and Services, 12(1), 7-19. doi:10.2478/emj-2020-0001
Guo, H., Zhao, Y., Niv, T., & Tsui, K.-L. (2017). Hong Kong Hospital Authority Resource Efficiency Evaluation: Via a Novel DEA-Malmquist Model and Tobit Regression Model. PLOS, 12(9), 1-24. doi:10.1371/journal.pone.0184211
Habib, A., & Shahwan, T. (2020). Measuring the Operational and Financial Efficiency Using a Malmquist Data Envelopment Analysis : A Case of Eqyption Hospitals. Benchmarking: An International Journal, 27(9):2521-2536. doi:10.1108/BIJ-01-2020-0041
Hollingsworth, B. (2003). Non-Parametric and Parametric Applications Measuring Efficiency in Health Care. Health Care Management Science, 6(4), 203-218. doi:10.1023/a:1026255523228.PMID:14686627
Kalantari, N., Mohammadi Pour, R., Seidi, M., Shiri, A., & Azizkhani, M. (2018). Fuzzy Goal Programming Model to Rolling Performance Based Budgeting by Productivity Approach (Case Study: Gas Refiner-ies in Iran). Advances in Mathematical Finance and Applications, 3(3), 95-107. doi:10.22034/amfa.2018.544952
Kawaguchi, H., Tone, K., & Tsutsui, M. (2014). Estimation of the Efficiency of Japanese Hospitals Using a Dynamic and Network DEA Model. Health Care Manag Sci, 17(2), 101-112. doi:10.1007/s10729-013-9248-9
Kim, Y., Oh, D.-h., & Kang, M. (2016). Productivity Changes in OECD Healthcare Systems: Bias-corrected Malmquist Productivity Approach. International Journal of Health Planning and Management, 31(4), 537-553. doi:10.1002/hpm.2333
Laupland, K., Edwards, F., & Dhanani , J. (2021). Determinants of Research Productivity During Postgraduate Medical Education: A Structured Review. BMC Medical Education volume, 21(1). doi:10.1186/s12909-021-03010-1
Li, H., & Dong, S. (2015). Measuring and Benchmarking Technical Efficiency of Public Hospitals in Tianjin, China: A Bootstrep-Data Envelopment Analysis Approach. The Journal of Health care Organization, Provision and Financing, 1-5. doi:10.1177/0046958015605487
Liu, W., Xia, Y., & Hou, J. (2019). Health Expenditure Efficiency in Rural China Using the Super-SBM Model and the Malmquist Productivity Index. International Journal for Equity in Health, 18(1). doi:10.1186/s12939-019-1003-5
Masri, M., & Asbu , E. (2018). Productivity Change of National Health Systems in the WHO Eastern Mediterranean Region: Application of DEA-based Malmquist Productivity Index. Global Health Research and Policy, 3(22). doi:10.1186/s41256-018-0077-8
McCann, P., & Vorley, T. (2020). Productivity Perspectives. USA: Edward Elgar Publishing. 1-392. doi:10.4337/9781788978804
Mollahaliloglu, S., Kavuncubasi, S., Younis, M., Simsek, F., Kostak, M., Yildirim, S., & Nwagwu, E. (2018). Impact of Health Sector Reforms in Hospital Productivity in Turkey: Malmquist Index Approach. International Journal of Organization Theory & Behavior, 21(2), 72-84. doi:10.1108/IJOTB-2018-0025
Naeem, M., & Ozuem, W. (2021). "Exploring the Use of Social Media Sites for Health Professionals' Engagement and Productivity in Public Sector Hospitals. Employee Relations, 43(5), 1029-1051. doi:10.1108/ER-08-2020-0391
NG, Y. (2011). The Productive Efficiency of Chines Hospitals. China Economic Review, 23, 428-439. doi:10.1016/j.chieco.2011.06.001
Ozan, Y., & Luke, R. (2011). Health Care Delivery Restructuring and Productivity Change: Assessing the Veterans Integrated Service Network (VISNs) using the Malmquist Approach. Medical Care Research and Review Supplement, 68(1), 20-35. doi:10.1177/1077558710369912
Pestana, M., Pereira, R., & Moro, S. (2020). Improving Health Care Management in Hospitals Through a Productivity Dashboard. Journal of Medical Systems, 44(4), 87. doi:10.1007/s10916-020-01546-1
Peykani, P., Seyed Esmaeili , F., Rostamy-Malkhalifeh , M., & Hosseinzadeh Lotfi, F. (2018). Measuring Productivity Changes of Hospitals in Tehran: The Fuzzy Malmquist Productivity Index. International Journal of Hospital Research, 7(3), 1-16. doi: LBL_COMMENTED_AT/ijhr.2018.92566
PN, M., & JM, K. (2016). Productivity and Efficiency Changes in Referral Hospitals in Uganda: An Application of Mamquist Total Productivity Index. Heath System and Policy Research, 3, 1-9.
Raei, B., Yousefi, M., Rahmani, K., Afshari, S., & 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. doi:10.21767/AMJ.2017.3094
Rays, Y., & Lemqeddem, H. (2021). Data Envelopment Analysis and Malmquist Index Application: Efficiency of Primary Health Care in Morocco and Covid-19. Turkish Journal of Computer and Mathematics Education, 12(5), 971-983.
Singh, S., Bala, M., Kumar, N., & 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. doi:10.1002/hpm.3169
Stefko, R., Gavurora, B., & Koronys, S. (2016). Efficiency Measurement in Healthcare Work Management Using Malmquist Indices. Journal of Management Studies, 13(1), 168-180. doi:10.17512/pjms.2016.13.1.16
Trakakis, A., Nektarios, M., Tziaferi , S., & 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). doi:10.1186/s12962-021-00326-z
Wang, T., Wang, Y., & McLeod, A. (2018). Do Health Information Technology Investments Impact Hospital Financial Performance and Productivity? International Journal of Accounting Information Systems, 28, 1-13. doi:10.1016/j.accinf.2017.12.002
Xenos, P., Nektarios, M., Constantopoulos, A., & Yfantopoulos, J. (2016). Two-Stage Hospital Efficiency Analysis Including Qualitative Evidence: A Greek Case. Journal of Hospital Administration, 5(3), 1-9. doi:10.5430/jha.v5n3p1
Yang, J., & Zeng, W. (2014). The Trade-Offs Between Efficiency and Quality in the Hospital Production: Some Evidence from Shenzen, China. China Economic Review, 13, 166-184. doi:10.1016/j.chieco.2014.09.005
Yi-Chung, H. (2013). The Efficiency of Government Spending in Health: Evidence from Europe and Central Asia. The Social Science Journal, 50(4), 665-673. doi:10.1016/j.soscij.2013.09.005