Efficiency assessment of medical diagnostic laboratories using undesirable sustainability indicators: A network data envelopment analysis approach

Document Type : Article

Authors

1 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

3 Department of Industrial Engineering, Faculty of Engineering, KHATAM University, Tehran, Iran

Abstract

Assessing the performance of health systems assists health decision-makers to ensure the accountability for their decisions. Medical diagnostic laboratories are one of the most important and sectors in the healthcare system of all countries. Thus, an assessment of the performance of medical diagnostic laboratories is of particular importance. This paper aims to propose a network data envelopment analysis (NDEA) model to assess the performance of medical diagnostic laboratories and decomposing the efficiency of the system with intricate internal structure based on sustainable development indicators. In addition, the proposed model is designed according to the internal structure of the medical diagnostic laboratory, which includes three main laboratory processes (the pre-test, the test and the post-test) with a combination of additional inputs and outputs (including both desirable and undesirable). The proposed model is a multiplicative DEA approach to estimate and decompose the efficiencies of system. Thus, a heuristic method is used as a suitable solution to convert a multiplicative NDEA approach into an equivalent linear program. The performance proposed model is shown through a real study in Iran. The computational results demonstrate the applicability of the proposed model in determining the most efficient laboratory using undesirable sustainability indicators.

Keywords


References:
[1] Nolte, E. and McKee, M. “Measuring the health of nations: analysis of mortality amenable to health care”. Journal of Epidemiology & Community Health, 58(4), pp.326-326 (2004).
[2] The European health report 2009: health and health systems. Copenhagen, WHO Regional Office for Europe.
[3] Solnica, B., Dabrowska, M., and  Sypniewska, G. “Laboratory Medicine as a Profession and Clinical Science–How to Perform Both of them well? ”. EJIFCC, 21(3), 53 (2010).
[4] Engau, A. “Proper efficiency and tradeoffs in multiple criteria and stochastic optimization”. Mathematics of operations research, 42(1), 119-134 (2016).
[5] Charnes, A., Cooper, W. W., and Rhodes, E. “Measuring the efficiency of decision making units”. European journal of operational research, 2(6), 429-444 (1978). 
 [6] Kao, C. “Network data envelopment analysis: A review”. European journal of operational research, 239(1), 1-16 (2014). 
[7] Wei, Q., and Yan, H. “A data envelopment analysis (DEA) evaluation method based on sample decision making units”. International Journal of Information Technology & Decision Making, 9(04) 601-624 (2010).
[8] Färe, R., and Whittaker, G. “An intermediate input model of dairy production using complex survey data”.  Journal of Agricultural Economics, 46(2), 201-213 (1995). 
[9] Lewis, H. F., and Sexton, T. R. “Network DEA: efficiency analysis of organizations with complex internal structure”. Computers & Operations Research, 31(9), 1365-1410 (2004). 
[10] Färe, R., Grosskopf, S., Lovell, C. K. et al. “Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach”. The review of economics and statistics, 90-98 (1989).
[11] Rosko, M.D. and Mutter, R.L. “What have we learned from the application of stochastic frontier analysis to US hospitals?”. Medical Care Research and Review, 68(1_suppl), pp.75S-100S (2011).
[12] Nayar, P. and  Ozcan, Y.A. “Data envelopment analysis comparison of hospital efficiency and quality”. Journal of medical systems, 32(3), pp.193-199 (2008).
[13] Audibert, M., Mathonnat, J., Pelissier, A. et al. “Health insurance reform and efficiency of township hospitals in rural China: An analysis from survey data”. China Economic Review, 27, pp.326-338 (2013).
[14] Varabyova, Y. and Schreyögg, J. “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), pp.70-79 (2013).
[15] Leleu, H., Moises, J. and Valdmanis, V.G. “How do payer mix and technical inefficiency affect hospital profit? ”.A weighted DEA approach. Operations Research for Health Care, 3(4), pp.231-237 (2014).
[16] Popescu, C., Asandului, L. and Fatulescu, P. “A data envelopment analysis for evaluating Romania's health system”. Procedia-Social and Behavioral Sciences, 109, pp.1185-1189 (2014).
[17] Asandului, L., Roman, M. and Fatulescu, P. “The efficiency of healthcare systems in Europe: A data envelopment analysis approach”. Procedia Economics and Finance, 10, pp.261-268 (2014).
[18] Al-Refaie, A., Fouad, R.H. and Li, M.H. “Applying simulation and DEA to improve performance of emergency department in a Jordanian hospital”. Simulation Modelling Practice and Theory, 41, pp.59-72 (2014).
[19] Chowdhury, H. and Zelenyuk, V. “Performance of hospital services in Ontario: DEA with truncated regression approach”. Omega, 63, pp.111-122 (2016).
[20] Campos, M.S., Fernández-Montes, and A., Gavilan, J.M. “Public resource usage in health systems: a data envelopment analysis of the efficiency of health systems of autonomous communities in Spain”. Public health, 138, pp.33-40 (2016).
 [21] Johannessen, K.A., Kittelsen, S.A. and Hagen, T.P. “Assessing physician productivity following Norwegian hospital reform: A panel and data envelopment analysis”. Social Science & Medicine, 175, pp.117-126 (2017).
[22] Khushalani, J. and Ozcan, Y.A. “Are hospitals producing quality care efficiently? An analysis using Dynamic Network Data Envelopment Analysis (DEA)”. Socio-Economic Planning Sciences, 60, pp.15-23 (2017).
[23] Patra, A. and Ray, P.K. “Measurement of efficiency and productivity growth of hospital systems: a Indian case study ”. In Healthcare Systems Management: Methodologies and Applications (pp. 13-22). Springer, Singapore (2018).
[24] Şahin, B. and İlgün, G. “Assessment of the efficiency of dental services in Turkey”. Health Policy and Technology, 7(2), pp.173-181 (2018).
[25] Haghighi, S.M. and Torabi, S.A. “A novel mixed sustainability-resilience framework for evaluating hospital information systems”. International journal of medical informatics, 118, pp.16-28 (2018).
 [26] Peykani, P., Mohammadi, E., Emrouznejad, A. et al. “Fuzzy data envelopment analysis: An adjustable approach”. Expert Systems with Applications, 136, pp.439-452 (2019).
[27] Thorsen, M.L., Thorsen, A. and McGarvey, R. “Operational efficiency, patient composition and regional context of US health centers: Associations with access to early prenatal care and low birth weight”. Social Science & Medicine, 226, pp.143-152 (2019).
[28] Abolghasem, S., Toloo, M. and Amézquita, S. “A dataset of healthcare systems for cross-efficiency evaluation in the presence of flexible measure”. Data in brief, 25, p.104239 (2019).
[29] Chawla, R., Goswami, B. and Singh, B. “Evaluating laboratory performance with quality indicators”. Laboratory Medicine, 41(5), pp.297-300 (2010).
[30] Bakar, A.H.A., Hakim, I.L. and Chong, S.C. “Measuring supply chain performance among public hospital laboratories”. International journal of productivity and performance management (2010).
[31] Gumus, A.T. “Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology”. Expert systems with applications, 36(2), pp.4067-4074 (2009).
[32] Lin, M.C., Wang, C.C. and Chen, M.S. “Using AHP and TOPSIS approaches in customer-driven product design process”. Computers in industry, 59(1), pp.17-31 92008).
[33] Chen, C.T., 2000. “Extensions of the TOPSIS for group decision-making under fuzzy environment”. Fuzzy sets and systems, 114(1), pp.1-9.
[34] Aviles-Sacoto, S., Cook, W. D. and  Imanirad, R. “Two-stage network DEA: when intermediate measures can be treated as outputs from the second stage”. Journal of the Operational Research Society, 66(11), 1868-1877 (2015). 
[35] Kao, C., and Hwang, S. N. “Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan”, European journal of operational research, 185(1), 418-429 (2008). 
[36] Charnes, A., and Cooper, W. W. “Programming with linear fractional functional”, Naval Research logistics quarterly, 9(3‐4), 181-186 (1962).