Measuring Efficiency and Productivity Change of Multi-Specialty Private Sector Hospitals in India : A DEA Based Malmquist Productivity Index Approach
DOI:
https://doi.org/10.17010/ijf/2018/v12i5/123691Keywords:
Efficiency
, Productivity, Private Sector Hospitals, Data Envelopment Analysis, Malmquist Productivity Index, IndiaC14
, C23, C61, D22, L25, O33Paper Submission Date
, January 20, 2018, Paper sent back for Revision, March 4, Paper Acceptance Date, April 21, 2018.Abstract
This study analyzed the efficiency of 28 un-listed standalone multi-speciality private sector hospitals in India with panel data from 2012-2013 to 2014-2015 using Malmquist data envelopment analysis. The study used number of beds, number of physicians, and number of other medical staff as input variables. Number of inpatients, number of outpatients, and number of major surgeries were used as output variables. While output oriented CCR and BCC models were used to estimate the technical and scale efficiencies, Malmquist productivity index was used to evaluate productivity changes over years in terms of technical efficiency change and technological change. The values by which inefficient hospitals should increase their outputs and/or decrease their inputs were estimated hospital wise across 3 years. The estimations presented current levels of different efficiency parameters and facilitated the overall evaluation of individual hospitals based on the values and their increase/decrease. It was found that the hospitals achieved a moderate productivity growth of 6.3% during the period of the study. The results of the study also provided critical implications for hospital managers.Downloads
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Agarwal, S., Yadav, S. P., & Singh, S. P. (2010). DEA based estimation of the technical efficiency of state transport undertakings in India. Opsearch, 47 (3), 216-230. doi: 10.1007/s12597-011-0035-4
Banker, R. D., Charnes, A., & Cooper, W.W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30 (9), 1078 - 1092. doi: 10.1287/mnsc.30.9.1078
Baru, R. V. (2006). Privatisation of health care in India: A comparative analysis of Orissa, Karnataka and Maharashtra states. United Nation Development Programme (UNDP). Retrieved from http://cmdr.ac.in/editor_v51/assets/mono-43.pdf
Baru, R. V. (2013). Challenges for regulating the private health services in India for achieving universal health care. Indian Journal of Public Health, 57 (4), 208 - 211. doi: 10.4103/0019-557X.123243
Bhat, R., Verma, B.B., & Reuben, E. (2001). Hospital efficiency: An empirical analysis of district hospitals and grant-in-aid hospitals in Gujarat. Journal of Health Management, 3 (2), 167 - 197. doi: 10.1177/097206340100300202
Charnes, A., Cooper, W. W., Lewin, A. Y., & Seiford, L. M. (1994). Introduction. In data envelopment analysis: Theory, methodology, and applications. Netherlands, NL: Springer.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429 - 444. doi: 10.1016/0377-2217(78)90138-8
Coelli, T. (1996). A guide to DEAP version 2.1: A data envelopment analysis (computer) program. Centre for Efficiency and Productivity Analysis. Australia : University of New England.
Coelli, T. J., Rao, D. P., O’Donnell, C. J., & Battese, G. E. (1998). An introduction to productivity and efficiency analysis. New York, NY: Springer Science.
Cook, W. D., & Seiford, L. M.(2009). Data envelopment analysis (DEA) – Thirty years on. European Journal of Operational Research, 192(1), 1-17. doi: 10.1016/j.ejor.2008.01.032
Cooper, W. W., Seiford, L. M., & Zhu, J. (Eds.). (2011). Handbook on data envelopment analysis (Vol. 164). New York, NY: Springer Science & Business Media.
Dash, U., Vaishnavi, S.D., & Muraleedharan, V.R. (2008). Technical efficiency in the use of health care resources: A case study of Tamil Nadu. Indian Economic Review, 43 (1), 69 - 82. Retrieved from http://www.jstor.org/stable/29793901
Dash, U., Vaishnavi, S.D., & Muraleedharan, V.R. (2010). Technical efficiency and scale efficiency of district hospitals. Journal of Health Management, 12 (3), 231 - 248. doi: 10.1177/097206341001200302
Debnath, R.M., & Sebastian, V.J. (2014). Efficiency in the Indian iron and steel industry - An application of data envelopment analysis. Journal of Advances in Management Research, 11 (1), 4 - 19. doi: 10.1108/JAMR-01-2013-0005
Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1992).Productivity changes in Swedish pharmacies 1980 - 1989 : A non-parametric Malmquist approach. Journal of Productivity Analysis, 3 (1 & 2), 85-101. doi:10.1007/BF00158770
Grilo, A., & Santos, J. (2015). Measuring efficiency and productivity growth of new technology - based firms in business incubators : The Portuguese case study of Madan Parque. The Scientific World Journal, 2015. 1-11. doi:10.1155/2015/936252
Grosskopf, S. (2003). Some remarks on productivity and its decompositions. Journal of Productivity Analysis, 20 (3), 459 - 474. doi: 10.1023/A:1027364119672
Gupta, A., & Mittal, S. (2010). Measuring retail productivity of food & grocery retail outlets using the DEA technique. Journal of Strategic Marketing, 18(4), 277 - 289. doi: 10.1080/09652540903537055
Hollingsworth, B. (2003). Non-parametric and parametric applications measuring efficiency in health care. Health Care Management Science, 6 (4), 203 - 218. doi : https://doi.org/10.1023/A:102625552
Hussey, P. S., De Vries, H., Romley, J., Wang, M. C., Chen, S. S., Shekelle, P. G., & McGlynn, E. A. (2009). A systematic review of health care efficiency measures. Health Services Research, 44 (3), 784 - 805. doi : 10.1111/j.1475-6773.2008.00942.x
India's healthcare sector to grow to $158.2 bn in 2017. (2013, December, 02). The Economic Times. Retrieved from http://articles.economictimes.indiatimes.com/2013-12- 02/news/44657410_1_healthcare-sector-healthcare-delivery-fortis
Jain, R. K., Natarajan, R., & Ghosh, A. (2016). Decision tree analysis for selection of factors in DEA: An application to banks in India. Global Business Review, 17(5), 1162 - 1178. doi: 10.1177/0972150916656682
Jat, T. R., & San Sebastian, M. (2013). Technical efficiency of public district hospitals in Madhya Pradesh, India: A data envelopment analysis. Global Health Action, 6(1), 1-6. doi: 10.3402/gha.v6i0.21742
Kirigia, J. M., & Asbu, E. Z. (2013). Technical and scale efficiency of public community hospitals in Eritrea: An exploratory study. Health Economics Review, 3 (1), 1-16. doi: 10.1186/2191-1991-3-6
Kohl, S., Schoenfelder, J., Fügener, A., & Brunner, J. O. (2018). The use of data envelopment analysis (DEA) in healthcare with a focus on hospitals. Health Care Management Science, 1- 43. doi: 10.1007/s10729-018-9436-8
Koutsoyiannis, A. (1979). Modern micro economics. London: McMillan Press Ltd.
Lakshminarayanan, S., Pai, Y. P., & Ramaprasad, B. S. (2016). Competency need assessment: A gap analytic approach. Industrial and Commercial Training, 48 (8), 423 - 430. doi: 10.1108/ICT-04-2016-0025
Liu, F. H. F.,& Wang, P. (2008). DEA Malmquist productivity measure: Taiwanese semiconductor companies. International Journal of Production Economics, 112 (1), 367-379. doi: 10.1016/j.ijpe.2007.03.015
Malmquist, S. (1953). Index numbers and indifference surfaces. Trabajos De EstadÃstica, 4 (2), 209 - 242. doi: 10.1007/bf03006863
Mathiyazhagan, M. K. (2003). People's choice of health care provider: Policy options for rural Karnataka in India. Journal of Health Management, 5 (1), 111 - 137. doi: 10.1177/097206340300500106
McKinsey & Company. (2012, January). India healthcare: Inspiring possibilities, challenging journey. Retrieved from http://www.mckinsey.com/global-themes/india/india-healthcare-inspiring-possibilities-challenging-journey
Mogha, S. K., Yadav, S. P., & Singh, S. P. (2012). Performance evaluation of Indian private hospitals using DEA approach with sensitivity analysis. International Journal of Advances in Management and Economics, 1 (2), 1-12. Retrieved from http://www.managementjournal.info/abstract.php?id=24
Mogha, S. K., Yadav, S. P., & Singh, S. P. (2014). New slack model based efficiency assessment of public sector hospitals of Uttarakhand : State of India. International Journal of System Assurance Engineering and Management, 5 (1), 32 - 42. doi: 10.1007/s13198-013-0207-0
Mogha, S. K., Yadav, S. P., & Singh, S. P. (2015). Slack based measure of efficiencies of public sector hospitals in Uttarakhand (India). Benchmarking: An International Journal, 22 (7), 1229 - 1246. doi: 10.1108/BIJ-12-2013-0122
Mudur, G. (2003). India plans to expand private sector in healthcare review. BMJ: British Medical Journal, 326 (7388), 520. doi: 10.1136/bmj.326.7388.520/d
Nandy, D. (2011). Efficiency study of Indian automobile companies using DEA technique: A case study of select companies. IUP Journal of Operations Management, 10 (4), 39 - 50.
Narayanaswamy, T., & Muthulakshmi, A. P. (2014). Efficiency of private sector banks in India. Indian Journal of Finance, 8 (10), 33 - 47. doi: 10.17010/ijf/2014/v8i10/71847
Naresh, G., Thiyagarajan, S., & Mahalakshmi, S. (2011). Analysis of performance of disinvested public sector enterprises using DEA approach. Indian Journal of Finance, 5 (12), 13 - 18. Retrieved from http://www.indianjournaloffinance.co.in/index.php/IJF/article/view/72464
O’Neill, L., Rauner, M., Heidenberger, K., & Kraus, M. (2008). A cross-national comparison and taxonomy of DEA-based hospital efficiency studies. Socio-Economic Planning Sciences, 42(3), 158 - 189. doi: 10.1016/j.seps.2007.03.001
Patel, P.M, & Ranjith, V.K (2018). Moderating influence of efficiency on variables of hospital financial performance: Evidence from Indian multi-specialty private sector hospitals. Indian Journal of Finance, 12(1), 9-23. doi: 10.17010/ijf/2018/v12i1/120737
Pelone, F., Kringos, D. S., Romaniello, A., Archibugi, M., Salsiri, C., & Ricciardi, W. (2015). Primary care efficiency measurement using data envelopment analysis: A systematic review. Journal of Medical Systems, 39 (156), 1-14. doi: 10.1007/s10916-014-0156-4
Pham, T.L. (2011). Efficiency and productivity of hospitals in Vietnam. Journal of Health Organization and Management, 25 (2), 195 - 213. doi: 10.1108/14777261111134428
Priya, G. D., & Jabarethina, G. (2016). A study on sustainable competitive advantage by managing service quality at a multi-speciality corporate hospital, Chennai. Prabandhan: Indian Journal of Management, 9 (7), 36 - 48. doi: 10.17010/pijom/2016/v9i7/97787
Ramanathan, R. (2003). An introduction to data envelopment analysis: A tool for performance measurement. Thousand Oaks, CA: Sage.
Ramanathan, R. (2005). Operations assessment of hospitals in the Sultanate of Oman. International Journal of Operations & Production Management, 25 (1), 39 - 54. doi.org/10.1108/01443570510572231
Salvatore, D. (2008). Managerial economics: Principles and worldwide applications. New York, NY: Oxford University Press.
Sengupta, A. (2010). Study of National Health System in India with regards access to healthcare and medicines. New Delhi: National Campaign Committee for Drug Policy.
Shetty, A., & Basri, S. (2018). Assessing the technical efficiency of traditional and corporate agents in Indian Life Insurance Industry: Slack-based data envelopment analysis approach. Global Business Review, 21(1), 1 - 17. doi: 10.1177/0972150917749722
Shiri, S. (2014). Stakeholder management: A universal strategic health services management approach to unlock a profitable return on investment. Prabandhan: Indian Journal of Management, 7(10), 17 - 31. doi: 10.17010/pijom/2014/v7i10/59249
Worthington, A. C. (2004). Frontier efficiency measurement in health care: a review of empirical techniques and selected applications. Medical Care Research and Review, 61(2), 135-170. doi:10.1177/1077558704263796
Zeller, T. L., Stanko, B. B., & Cleverley, W. O. (1996). A revised classification pattern of hospital financial ratios. Journal of Accounting and Public Policy, 15 (2), 161 - 182. DOI : 10.1016/0278-4254(96)00014-2
Zhu, J. (2008). Quantitative models for performance evaluation and benchmarking: Data envelopment analysis and spreadsheets (2nd edition). New York, NY: Springer.