Abstract
Health care spending usually contributes to a large part of a developed country’s economy. In 2011, the U.S. consumed about 17.7% of its GDP on health care. As one of the most significant components of the health care industry, the hospital sector plays a key role to provide healthcare services. Healthcare services industry can be affected by many factors, of which economic downturn is a crucial one. As a result, it is worth investigating the condition and state of hospital management when economic downturn occurs. This paper aims to analyze how the Great Recession affects hospital performance in Pennsylvania during the period 2005–2012 by using data envelopment analysis (DEA). Specifically, we measure efficiency for hospitals in Pennsylvania, and use several DEA models to calculate the global Malmquist index (GMI). We find that: (1) 15.4% hospitals are always efficient while 36.9% hospitals are always inefficient for all years in 2005–2012; (2) The relative distance for a group of hospitals to the frontier is almost unchanged post-recession and pre-recession; (3) The average efficiency/GMI decreases by 2.43%/3.07% from pre-recession to post-recession. The analysis indicates that hospital performance slightly decreased due to the economic downturn in Pennsylvania.
Similar content being viewed by others
Notes
Data Accessed on June 25, 20014. Available at http://research.stlouisfed.org/fred2/categories/29613.
References
An, Q., Chen, H., Wu, J., & Liang, L. (2015). Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output. Annals of Operations Research. doi:10.1007/s10479-015-1987-1.
An, Q., Chen, H., Xiong, B., Wu, J., & Liang, L. (2016). Target intermediate products setting in a two-stage system with fairness concern. Omega. doi:10.1016/j.omega.2016.12.005.
An, Q., Wen, Y., Xiong, B., Yang, M., & Chen, X. (2017). Allocation of carbon dioxide emission permits with the minimum cost for Chinese provinces in big data environment. Journal of Cleaner Production, 142, 886–893.
Araújo, C., Barros, C. P., & Wanke, P. (2014). Efficiency determinants and capacity issues in Brazilian for-profit hospitals. Health Care Management Science, 17, 126–138.
Baker, R. M., Dixon, D. R., & Passmore, D. (2010). Role of hospitals in the Pennsylvania economy. Social science research network, February 23, 2010. http://ssrn.com/abstract=1557864. Accessed 31 March, 2015.
Chang, H., Cheng, M. A., & Das, S. (2004). Hospital ownership and operating efficiency: Evidence from Taiwan. European Journal of Operational Research, 159, 513–527.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.
Chen, Y. (2003). A non-radial Malmquist productivity index with an illustrative application to Chinese major industries. International Journal of Production Economics, 83, 27–35.
Chen, Y. (2005). Measuring super-efficiency in DEA in the presence of infeasibility. European Journal of Operational Research, 161, 545–551.
Chen, Y., Cook, W. D., Du, J., Hu, H. H., & Zhu, J. (2015). Bounded and discrete data and Likert scales in data envelopment analysis: Application to regional energy efficiency in China. Annals of Operations Research. doi:10.1007/s10479-015-1827-3.
Chen, Y., & Liang, L. (2011). Super-efficiency DEA in the presence of infeasibility: One model approach. European Journal of Operational Research, 213, 359–360.
Chen, Y., Li, Y. J., Liang, L., Salo, A., & Wu, H. Q. (2016). Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures. European Journal of Operational Research, 250(2), 543–554.
Chowdhury, H., Zelenyuk, V., Laporte, A., & Wodchis, W. P. (2014). Analysis of productivity, efficiency and technological changes in hospital services in Ontario: How does case-mix matter? International Journal of Production Economics, 150, 74–82.
Cook, W. D., Liang, L., Zha, Y., & Zhu, J. (2009). A modified super-efficiency DEA model for infeasibility. Journal of Operational Research Society, 69, 276–281.
Cook, W. D., & Seiford, L. (2009). Data envelopment analysis (DEA)—Thirty years on. European Journal of Operational Research, 192, 1–17.
Cook, W. D., Tone, K., & Zhu, J. (2014). Data envelopment analysis: Prior to choosing a model. Omega, 44, 1–4.
Cooper, W. W., Seiford, L., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references, and dea-solver software. Berlin: Springer.
Du, J., Wang, J., Chen, Y., Chou, S.-Y., & Zhu, J. (2014). Incorporating health outcomes in Pennsylvania hospital efficiency: An additive super-efficiency DEA approach. Annals of Operations Research, 221, 161–172.
Elliott, V. S. (2010a). Hospital mass layoffs matching last year’s record levels: Health systems say the economic downturn continues to take its toll. American Medical News, American Medical Association, April 5, 2010. http://www.amednews.com/article/20100405/business/304059962/7/. Accessed 17 March, 2015.
Elliott, V. S. (2010b). Recession hitting health system harder this time around: Patients are having trouble paying medical bills, a New Study Finds. American Medical News, American Medical Association, May 12, 2010. http://www.amednews.com/article/20100512/business/305129997/8/. Accessed 17 March, 2015.
Elliott, V. S. (2011). 2010 the second-worst year for hospital mass layoffs in 15 years: The highest number of layoffs occurred in April, when almost 2,000 employees filed for unemployment benefits. American Medical News, American Medical Association, Feb. 9, 2011. http://www.amednews.com/article/20110209/business/302099997/8/. Accessed 17 March, 2015.
Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1992). Productivity developments in Swedish pharmacies: A non-parametric Malmquist approach. Journal of Productivity Analysis, 3, 85–101.
Färe, R., Grosskopf, S., & Lovell, C. A. K. (1985). The measurement of efficiency of production. Dordrecht: Kluwer-Nijhoff Publishing.
Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth technical progress and efficiency changes in industrialized countries. American Economic Review, 84, 66–83.
Färe, R., & Lovell, C. A. K. (1978). Measuring the technical efficiency of production. Journal of Economic Theory, 19, 150–162.
Ferrier, G. D., & Valdmanis, V. (2004). Do mergers improve hospital productivity? Journal of the Operational Research Society, 55(10), 1071–1080.
Gong, Y. D., Zhu, J., Chen, Y., & Cook, W. D. (2016). DEA as a tool for auditing: Application to Chinese manufacturing industry with parallel network structures. Annals of Operations Research. doi:10.1007/s10479-016-2197-1.
Grosskopf, S., Margaritis, D., & Valdmanis, V. (2001). The effects of teaching on hospital productivity. Socio-Economic Planning Sciences, 35(3), 189–204.
Grosskopf, S., Margaritis, D., & Valdmanis, V. (2004). Competitive effects on teaching hospitals. European Journal of Operational Research, 154(2), 515–525.
Harrison, J. P., Coppola, M. N., & Wakefield, M. (2004). Efficiency of federal hospitals in the United States. Journal of Medical Systems, 28(5), 411–422.
Harrison, J. P., & Sexton, C. (2006). The improving efficiency frontier of religious not-for-profit hospitals. Hospital Topics, 84(1), 2–10.
Harris, J. M., Ozgen, H., & Ozcan, Y. A. (2000). Do mergers enhance the performance of hospital efficiency? Journal of the Operational Research Society, 51, 801–811.
Holahan, J., & Wang, M. (2004). Changes in health insurance coverage during the economic downturn: 2000–2002. Health Affairs. doi:10.1377/hlthaff.w4.31.
Hu, H. H., Qi, Q., & Yang, C. H. (2012). Evaluation of China’s regional hospital efficiency: DEA approach with undesirable output. Journal of the Operational Research Society, 63, 715–725.
Indivero, V. M. (2014). Hospitals recover from recession, some financial issues remain, Penn State News, Penn State University. May 12, 2014. http://news.psu.edu/story/315594/2014/05/12/research/hospitals-recover-recession-some-financial-issues-remain. Accessed 17 March, 2015.
Katz-Stone, A. (2001). Downturn adds to hospitals’ fundraising woes. Philadelphia Business Journal, 20(9), 17.
Kawaguchi, H., Tone, K., & Tsutsui, M. (2014). Estimation of the efficiency of Japanese hospitals using a dynamic and network data envelopment analysis model. Health Care Management Science, 17, 101–112.
Lee, H. S., Chu, C. W., & Zhu, J. (2011). Super-efficiency DEA in the presence of infeasibility. European Journal of Operational Research, 212, 141–147.
Lee, K., & Wan, T. T. H. (2004). Information system integration and technical efficiency in urban hospitals. International Journal of Healthcare Technology and Management, 1(3/4), 452.
Leleu, H., Moises, J., & Valdmanis, V. (2012). Optimal productive size of hospital’s intensive care units. International Journal of Production Economics, 136(2), 297–305.
Liu, J. S., Lu, L. Y. Y., Lu, W. M., & Lin, B. J. Y. (2013). A survey of DEA applications. Omega, 41, 893–902.
Miller, F., Wang, J., Zhu, J., Chen, Y., & Hockenberry, J. (2015). Investigation of the impact of the Massachusetts health care reform on hospital costs and quality of care. Annals of Operations Research. doi:10.1007/s10479-015-1856-y.
Nunamaker, T. R. (1983). Measuring routine nursing service efficiency: A comparison of cost per patient day and data envelopment analysis models. Health Services Research, 18, 183–208.
O’Neill, L. (1998). Multifactor efficiency in data envelopment analysis with an application to urban hospitals. Health Care Management Science, 1(1), 19–27.
Ozcan, Y. A. (2014). Health care benchmarking and performance evaluation: An assessment using data envelopment analysis (DEA) (2nd ed.). Berlin: Springer.
Pastor, J. T., & Lovell, C. A. K. (2005). A global Malmquist productivity index. Economics Letters, 88, 266–271.
Pellegrini, L. C., Rodriguez-monguio, R., & Qian, J. (2014). The US healthcare workforce and the labor market effect on healthcare spending and health outcomes. International Journal of Health Care Finance and Economics, 14(2), 127–141.
Seiford, L. M., & Zhu, J. (1999). Infeasibility of super-efficiency data envelopment analysis models. INFOR, 37, 174–187.
Sherman, H. D. (1984). Hospital efficiency measurement and evaluation: Empirical test of a new technique. Medical Care, 22(10), 922–938.
Sholly, C. (2009). Despite recession, HMC in black. Lebanon Daily News, June 28, 2009. http://www.ldnews.com/ci_12710336. Accessed 31 March, 2015.
Tsekouras, K., Papathanassopoulos, F., Kounetas, K., & Pappous, G. (2010). Does the adoption of new technology boost productive efficiency in the public sector? The case of ICUs system. International Journal of Production Economics, 128(1), 427–433.
Twedt, S. (2009). Survey: 80 percent of PA. hospitals weigh layoffs. Pittsburgh Post-Gazette, March 13, 2009. http://www.post-gazette.com/business/businessnews/2009/03/13/Survey-80-percent-of-Pa-hospitals-weigh-layoffs/stories/200903130144. Accessed 31 March, 2015.
Wade, M. (2009). Area hospitals forced to tighten budgets. Northeast Pennsylvania Business Journal, 24(3), 25.
Acknowledgements
The authors are grateful for the comments and suggestions from two anonymous reviewers on an earlier version of this paper. Dr. Ya Chen thanks the support by the National Natural Science Foundation of China (Grant No. 71601064) and Natural Science Foundation of Anhui Province (Grant No. 1708085QG161). Support from the Priority Academic Program Development of the Jiangsu Higher Education Institutions (China) is acknowledged.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chen, Y., Wang, J., Zhu, J. et al. How the Great Recession affects performance: a case of Pennsylvania hospitals using DEA. Ann Oper Res 278, 77–99 (2019). https://doi.org/10.1007/s10479-017-2516-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10479-017-2516-1