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How the Great Recession affects performance: a case of Pennsylvania hospitals using DEA

Author

Listed:
  • Ya Chen

    (Hefei University of Technology)

  • Justin Wang

    (Worcester Polytechnic Institute)

  • Joe Zhu

    (Nanjing Audit University
    Worcester Polytechnic Institute)

  • H. David Sherman

    (Northeastern University)

  • Shin-Yi Chou

    (Lehigh University)

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.

Suggested Citation

  • Ya Chen & Justin Wang & Joe Zhu & H. David Sherman & Shin-Yi Chou, 2019. "How the Great Recession affects performance: a case of Pennsylvania hospitals using DEA," Annals of Operations Research, Springer, vol. 278(1), pages 77-99, July.
    • Handle: RePEc:spr:annopr:v:278:y:2019:i:1:d:10.1007_s10479-017-2516-1
    DOI: 10.1007/s10479-017-2516-1
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    as
    1. Grosskopf, Shawna & Margaritis, Dimitri & Valdmanis, Vivian, 2004. "Competitive effects on teaching hospitals," European Journal of Operational Research, Elsevier, vol. 154(2), pages 515-525, April.
    2. Lee, Hsuan-Shih & Chu, Ching-Wu & Zhu, Joe, 2011. "Super-efficiency DEA in the presence of infeasibility," European Journal of Operational Research, Elsevier, vol. 212(1), pages 141-147, July.
    3. Tsekouras, Kostas & Papathanassopoulos, Fotis & Kounetas, Kostas & Pappous, Giorgos, 2010. "Does the adoption of new technology boost productive efficiency in the public sector? The case of ICUs system," International Journal of Production Economics, Elsevier, vol. 128(1), pages 427-433, November.
    4. Chang, Hsihui & Cheng, Mei-Ai & Das, Somnath, 2004. "Hospital ownership and operating efficiency: Evidence from Taiwan," European Journal of Operational Research, Elsevier, vol. 159(2), pages 513-527, December.
    5. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Chowdhury, Hedayet & Zelenyuk, Valentin & Laporte, Audrey & Wodchis, Walter P., 2014. "Analysis of productivity, efficiency and technological changes in hospital services in Ontario: How does case-mix matter?," International Journal of Production Economics, Elsevier, vol. 150(C), pages 74-82.
    8. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    9. Chen, Yao, 2005. "Measuring super-efficiency in DEA in the presence of infeasibility," European Journal of Operational Research, Elsevier, vol. 161(2), pages 545-551, March.
    10. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    11. Lawrence Pellegrini & Rosa Rodriguez-Monguio & Jing Qian, 2014. "The US healthcare workforce and the labor market effect on healthcare spending and health outcomes," International Journal of Health Economics and Management, Springer, vol. 14(2), pages 127-141, June.
    12. Grosskopf, Shawna & Margaritis, Dimitri & Valdmanis, Vivian, 2001. "The effects of teaching on hospital productivity," Socio-Economic Planning Sciences, Elsevier, vol. 35(3), pages 189-204, September.
    13. Chen, Yao, 2003. "A non-radial Malmquist productivity index with an illustrative application to Chinese major industries," International Journal of Production Economics, Elsevier, vol. 83(1), pages 27-35, January.
    14. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    15. J Harris & H Ozgen & Y Ozcan, 2000. "Do mergers enhance the performance of hospital efficiency?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(7), pages 801-811, July.
    16. Hiroyuki Kawaguchi & Kaoru Tone & Miki Tsutsui, 2014. "Estimation of the efficiency of Japanese hospitals using a dynamic and network data envelopment analysis model," Health Care Management Science, Springer, vol. 17(2), pages 101-112, June.
    17. Leleu, Hervé & Moises, James & Valdmanis, Vivian, 2012. "Optimal productive size of hospital's intensive care units," International Journal of Production Economics, Elsevier, vol. 136(2), pages 297-305.
    18. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    19. Qingxian An & Haoxun Chen & Jie Wu & Liang Liang, 2015. "Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output," Annals of Operations Research, Springer, vol. 235(1), pages 13-35, December.
    20. Cláudia Araújo & Carlos Barros & Peter Wanke, 2014. "Efficiency determinants and capacity issues in Brazilian for-profit hospitals," Health Care Management Science, Springer, vol. 17(2), pages 126-138, June.
    21. Fare, Rolf & Knox Lovell, C. A., 1978. "Measuring the technical efficiency of production," Journal of Economic Theory, Elsevier, vol. 19(1), pages 150-162, October.
    22. Chen, Ya & Li, Yongjun & Liang, Liang & Salo, Ahti & Wu, Huaqing, 2016. "Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures," European Journal of Operational Research, Elsevier, vol. 250(2), pages 543-554.
    23. Chen, Yao & Liang, Liang, 2011. "Super-efficiency DEA in the presence of infeasibility: One model approach," European Journal of Operational Research, Elsevier, vol. 213(1), pages 359-360, August.
    24. H-H Hu & Q Qi & C-H Yang, 2012. "Evaluation of China's regional hospital efficiency: DEA approach with undesirable output," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(6), pages 715-725, June.
    25. Yasar A. Ozcan, 2014. "Evaluation of Performance in Health Care," International Series in Operations Research & Management Science, in: Health Care Benchmarking and Performance Evaluation, edition 2, chapter 0, pages 3-14, Springer.
    26. Juan Du & Justin Wang & Yao Chen & Shin-Yi Chou & Joe Zhu, 2014. "Incorporating health outcomes in Pennsylvania hospital efficiency: an additive super-efficiency DEA approach," Annals of Operations Research, Springer, vol. 221(1), pages 161-172, October.
    27. G D Ferrier & V G Valdmanis, 2004. "Do mergers improve hospital productivity?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1071-1080, October.
    28. W D Cook & L Liang & Y Zha & J Zhu, 2009. "A modified super-efficiency DEA model for infeasibility," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 276-281, February.
    29. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
    30. Yasar A. Ozcan, 2014. "Health Care Benchmarking and Performance Evaluation," International Series in Operations Research and Management Science, Springer, edition 2, number 978-1-4899-7472-3, December.
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