Free Access
RAIRO-Oper. Res.
Volume 55, 2021
Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
Page(s) S1823 - S1831
Published online 02 March 2021
  • G.E. Battese and D.S.P. Rao, Technology gap, efficiency, and a stochastic metafrontier function. Int. J. Bus. Econ. 1 (2002) 87–93. [Google Scholar]
  • G.E. Battese, D.S.P. Rao and C.J. O’Donnell, A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. J. Prod. Anal. 21 (2004) 91–103. [Google Scholar]
  • L.G. Burke, A.B. Frakt, D. Khullar, E.J. Orav and A.K. Jha, Association between teaching status and mortality in U.S. hospitals. JAMA 317 (2017) 2105–2113. [PubMed] [Google Scholar]
  • L.G. Burke, D. Khullar, J. Zheng, A.B. Frakt, E.J. Orav and A.K. Jha, Comparison of costs of care for medicare patients hospitalized in teaching and nonteaching hospitals. JAMA Netw Open. 2 (2019) e195229. [PubMed] [Google Scholar]
  • J.M. Cameron, The indirect costs of graduate medical education. New England J. Med. 312 (1985) 1233–1238. [Google Scholar]
  • C. Campbell, K. Gillespie and J. Romeis, The effects of residency training programs on the financial performance of veterans affairs medical centers. Inquiry 28 (1991) 288–299. [PubMed] [Google Scholar]
  • K. Carey and J.F. Burgress, Jr., On measuring the hospital cost-quality trade-off. Health Econ. 8 (1999) 509–520. [PubMed] [Google Scholar]
  • S.J. Chang, H.C. Hsiao, L.H. Huang and H. Chang, Taiwan quality indicator project and hospital productivity growth. Omega 39 (2011) 14–22. [PubMed] [Google Scholar]
  • K.H. Chen and H.Y. Yang, A cross-country comparison of productivity growth using the generalised metafrontier Malmquist productivity index: with application to banking industries in Taiwan and China. J. Prod. Anal. 35 (2011) 197–212. [Google Scholar]
  • K.C. Chen, L.N. Chien, Y.H. Hsu and M.M. Yu, Metafrontier frameworks for studying hospital productivity growth and quality changes. Int. J. Qual. Health Care 28 (2016) 650–656. [PubMed] [Google Scholar]
  • R. Fäare, S. Grosskopf, M. Norris and Z. Zhang, Productivity growth, technical progress, and efficiency change in industrialized countries. Am. Econ. Rev. 84 (1994) 66–83. [Google Scholar]
  • R. Fäare, S. Grosskoph and P. Roos, Productivity and quality changes in Swedish pharmacies. Int. J. Prod. Econ. 39 (1995) 137–144. [Google Scholar]
  • M. Farsi, Changes in hospital quality after conversion in ownership status. Int. J. Health Care Finance Econ. 4 (2004) 211–230. [Google Scholar]
  • G.D. Ferrier and J.S. Trivitt, Incorporating quality into the measurement of hospital efficiency: a double DEA approach. J. Prod. Anal. 40 (2013) 337–355. [Google Scholar]
  • A. Flokou, V. Aletras and D. Niakas, A window-DEA based efficiency evaluation of the public hospital sector in Greece during the 5-year economic crisis. PLoS One 12 (2017) e0177946. [Google Scholar]
  • S. Grosskopf, D. Margaritisb and V. Valdmanis, The effects of teaching on hospital productivity. Soc.-Econ. Planning Sci. 35 (2001) 189–204. [Google Scholar]
  • S. Grosskopf, D. Margaritisb and V. Valdmanis, Comparing teaching and non-teaching hospitals: a frontier approach (teaching vs. non-teaching hospitals). Health Care Manage. Sci. 4 (2001) 83–90. [Google Scholar]
  • A.J. Hartz, M.S. Gottlieb, E.M. Kuhn and A.A. Rimm, The relationship between adjusted hospital mortality and the results of peer review. Health Serv. Res. 27 (1993) 765–777. [PubMed] [Google Scholar]
  • G. Jensen and M. Morrisey, The role of physicians in hospital production. Rev. Econ. Stat. 68 (1986) 432–441. [Google Scholar]
  • S. Kumar and R.R. Russell, Technological change, technological catch-up, and capital deepening: relative contributions to growth and convergence. Am. Econ. Rev. 92 (2002) 527–548. [Google Scholar]
  • S.C. Kumbhakar and H.J. Wang, Estimation of growth convergence using a stochastic production frontier approach. Econ. Lett. 88 (2005) 300–305. [Google Scholar]
  • P. Nayar, Y.A. Ozcan, F. Yu, A.T. Nguyen, Benchmarking urban acute care hospitals. Health Care Manage. Rev. 38 (2013) 137–145. [PubMed] [Google Scholar]
  • S. Nuti, T. Grillo Ruggieri and S. Podetti, Do university hospitals perform better than general hospitals? A comparative analysis among Italian regions. BMJ Open. 6 (2016) e011426. [PubMed] [Google Scholar]
  • C. J. O’Donnell, D.S.P. Rao and G.E. Battese, Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Empir. Econ. 34 (2008) 231–255. [Google Scholar]
  • H. Pardes, The future of medical schools and teaching hospitals in the era of managed care. Acad. Med. 72 (1997) 97–102. [Google Scholar]
  • E. Rich, G. Gifford, M. Luxenberg and B. Dowd, The relationship of house staff experience to the cost and quality of inpatient care. J. Am. Med. Assoc. 263 (1990) 953–957. [PubMed] [Google Scholar]
  • D.M. Shahian, P. Nordberg, G.S. Meyer, B.B. Blanchfield, E.A. Mort, D.F. Torchiana and S.L. Normand, Contemporary performance of U.S. teaching and nonteaching hospitals. Acad Med. 87 (2012) 701–708. [Google Scholar]
  • F. Sloan, R. Feldman and B. Steinwald, Effects of teaching on hospital productivity. J. Health Econ. 2 (1983) 1–23. [PubMed] [Google Scholar]
  • V. Valencia, V.M. Arora, S.R. Ranji, C. Meza and C. Moriates, A comparison of laboratory testing in teaching vs nonteaching hospitals for 2 common medical conditions. JAMA Intern Med. 178 (2018) 39–47. [PubMed] [Google Scholar]
  • B. Walheer, Aggregation of metafrontier technology gap ratios: the case of European sectors in 1995–2015. Eur. J. Oper. Res. 269 (2018) 1013–1026. [Google Scholar]
  • J. Yang and W. Zeng, The trade-offs between efficiency and quality in the hospital production: some evidence from Shenzhen, China. Chin. Econ. Rev. 31 (2014) 166–184. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.