Document Type : Original Article
Authors
- . Aziz Rezapour 1
- . Zeynab Foroughi 2
- . Niusha Shahidi Sadeghi 2
- . Mehran Faraji 1
- . Alireza Mazdaki 1
- . Ali Sarabi Asiabar 1
- . Noureddin Niknam 2
- . Keivan Rahmani 3
- . Saeed Mohammad-Pour 4
1 Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran
2 Department of Health Services Management, School of Management and Medical Information, Iran University of Medical Sciences, Tehran, Iran
3 Health Management and Economics Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
4 Department of Health Economics, School of Management and Medical Information, Iran University of Medical Sciences, Tehran, Iran
Abstract
CONTEXT: Selecting variables is a fundamental step in evaluating comparative efficiency because
the results of measuring efficiency depend on the used variables.
AIMS: The aim of this study is to provide a comprehensive set of input and output variables for
measuring efficiency with an emphasis on application in general hospitals in Iran.
MATERIALS AND METHODS: This study comprised a literature review followed by a Delphi survey
process. After extracting the variables from the literature review in order to reach consensus on them
and identify the native variables, the researchers used the Delphi technique in three rounds. Thirty
Iranian hospital managers, in Alborz, Saveh, Qazvin, Qom, and Hamadan universities, participated
in this study. For analysis, the interquartile range (IQR) and median were used. IQR was used to
assess the agreement of Delphi panel members.
RESULTS: After literature review, nine indicators were identified as input variables and 11 indicators
were identified as output variables. After the proposed changes by Delphi members, 24 input variables
and 24 output variables were identified to measure hospital efficacy. Finally, ten variables were
selected as inputs and ten variables were selected as outputs to measure the performance of public
hospitals in Iran by using the consensus of the members in the Delphi panel.
CONCLUSIONS: This study proposes a framework for selecting the most appropriate variables for
measuring the hospital efficiency with an emphasis on nonparametric methods. Choosing variables
to measure hospital efficiency requires infrastructure such as an intelligent information system.
Keywords
the efficiency of medical diagnostic laboratories by the method
of data envelopment analysis. J Lab Sci 2015;9:102‑9.[In Persian]
2. Kounetas K, Papathanassopoulos F. How efficient are Greek hospitals? A case study using a double bootstrap DEA approach.
Eur J Health Econ 2013;14:979‑94.
3. Afzali H, Moss J, Mahmood M. A conceptual framework for
selecting the most appropriate variables for measuring hospital
efficiency with a focus on Iranian public hospitals. Health Serv
Manage Res 2009;22:81‑91.
4. Mahfooz S, Pouragha B, Abedi Z, Satarivand S. Efficiency
evaluation of Shahid Beheshti University of Medical Sciences
hospitals in Tehran using data envelopment analysis method.
Health Promot Manage 2015;5:11‑21.[In Persian]
5. Jehu‑Appiah C, Sekidde S, Adjuik M, Akazili J, Almeida SD,
Nyonator F, et al. Ownership and technical efficiency of hospitals:
Evidence from Ghana using data envelopment analysis. Cost Eff
Resour Alloc 2014;12:9.
6. Caballer‑Tarazona M, Moya‑Clemente I, Vivas‑Consuelo D,
Barrachina‑Martínez I. A model to measure the efficiency of
hospital performance. Math Comput Model 2010;52:1095‑102.
7. Azad E, Ketabi S, Soltani I, Bagherzade M. Efficiency analysis
and allocation of resources to different parts of Shariati Hospital
in Isfahan using data envelopment analysis. Health Inf Manage
2012;8:938‑47.[In Persian]
8. Mehrtak M, Yusefzadeh H, Jaafaripooyan E. Pabon lasso and data
envelopment analysis: A complementary approach to hospital
performance measurement. Glob J Health Sci 2014;6:107‑16.
9. Mitropoulos P, Mitropoulos I, Karanikas H, Polyzos N. The
impact of economic crisis on the Greek hospitals’ productivity.
Int J Health Plann Manage 2018;33:171‑84.
10. Kohl S, Schoenfelder J, Fügener A. et al. Health Care Manag
Sci (2018). https://doi.org/10.1007/s10729‑018‑9436‑8
11. Nikokar S, Ketabi S, Moazam E. Provide a combined model of data
envelopment analysis and a spatial analysis for evaluating the
performance of hospital managers. Health Inf Manage 2011: 01‑11.
[In Persian]
12. Park J, Fowler K, Giebel S. Measuring hospital operating
efficiencies for strategic decisions. Int J Bus Soc Sci 2011,
2.13: 67‑88.
13. Salehzadeh R, Ketabi S. Measuring the efficiency of Qom hospitals
with data envelopment analysis and analytic hierarchy process.
Health Inf Manage 2011;8:479‑89.[In Persian]
14. Goudarzi R, Pourreza A, Shokoohi M, Askari R, Mahdavi M,
Moghri J, et al. Technical efficiency of teaching hospitals in Iran:
The use of stochastic frontier analysis, 1999‑2011. Int J Health
Policy Manag 2014;3:91‑7.
15. Najarzade M, Tourabipour A, GhasemzadeR, SalehiR. Evaluation
of Ahwaz hospitals efficiency by data envelopment analysis in the
years 85 to 89. J Jundishapur Health Sci 2013;4:77‑87.[In Persian]
16. Torabipour A, Najarzadeh M, Arab M, Farzianpour F,
Ghasemzadeh R. Hospitals productivity measurement using
data envelopment analysis technique. Iran J Public Health
2014;43:1576‑81.
17. Cheng Z, Cai M, Tao H, He Z, Lin X, Lin H, et al. Efficiency
and productivity measurement of rural township hospitals in
china: A bootstrapping data envelopment analysis. BMJ Open
2016;6:e011911.
18. Lobo MS, Rodrigues Hde C, André EC, de Azeredo JA, Lins MP.
Dynamic network data envelopment analysis for university
hospitals evaluation. Rev Saude Publica 2016;50:22.
19. Rahmani N, Keshavarz A, Tabatabayee S, Roohollah K. Assessing
the role of ownership on changes in total factors using indicators
Malmquist and data envelopment analysis method in Qazvin
hospitals. J Payavard Salamat 2013;6:300‑10.[In Persian]
20. Rayens MK, Hahn EJ. Building consensus using the policy Delphi
method. Policy Polit Nurs Pract 2000;1:308‑15.
21. Hsu CC, Sandford BA. The Delphi technique: Making sense of
consensus. Pract Assess Res Eval 2007;12:1‑8.
22. Jones J, Hunter D. Consensus methods for medical and health
services research. BMJ 1995;311:376‑80.
23. Crutzen R, de Nooijer J, Brouwer W, Oenema A, Brug J,
de Vries NK, et al. Internet‑delivered interventions aimed at
adolescents: A Delphi study on dissemination and exposure.
Health Educ Res 2008;23:427‑39.
24. Ramanathan R. An Introduction to Data Envelopment Analysis:
A Tool for Performance Measurement. SAGE; 2003.
25. Bowlin WF. Measuring performance: An introduction to data
envelopment analysis (DEA). J Cost Anal 1998;15:3‑27.
26. Moradi G, Piroozi B, Safari H, Esmail Nasab N,
Mohamadi Bolbanabad A, Yari A, et al. Assessment of the
efficiency of hospitals before and after the implementation of
health sector evolution plan in Iran based on Pabon–Lasso model.
Iran J Public Health 2017;46:389‑95.
27. Xu GC, Zheng J, Zhou ZJ, Zhou CK, Zhao Y. Comparative study
of three commonly used methods for hospital efficiency analysis
in Beijing Tertiary Public Hospitals, China. Chin Med J (Engl)
2015;128:3185‑90.
28. Mosadeghrad AM, Esfahani P, Nikafshar M. Hospitals’ efficiency
in Iran: A systematic review and meta‑analysis of two decades of
research. J Payavard Salamat 2017;11:318‑331.
29. Kiadaliri AA, Jafari M, Gerdtham UG. Frontier‑based techniques
in measuring hospital efficiency in Iran: A systematic review and
meta‑regression analysis. BMC Health Serv Res 2013;13:312.
)