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Does prospective payment increase hospital (in)efficiency? Evidence from the Swiss hospital sector

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  • Philippe K. Widmer

Abstract

Several European countries have followed the United States in introducing prospective payment for hospitals with the expectation of achieving cost efficiency gains. This article examines whether theoretical expectations of cost efficiency gains can be empirically confirmed. In contrast to previous studies, the analysis of Switzerland provides a comparison of a retrospective per diem payment system with a prospective global budget and a payment per patient case system. Using a sample of approximately 90 public financed Swiss hospitals during the years 2004 to 2009 and Bayesian inference of a standard and a random parameter frontier model, cost efficiency gains are found, particularly with a payment per patient case system. Payment systems designed to put hospitals at operating risk are more effective than retrospective payment systems. However, hospitals are heterogeneous with respect to their production technologies, making a random parameter frontier model the superior specification for Switzerland.

Suggested Citation

  • Philippe K. Widmer, 2011. "Does prospective payment increase hospital (in)efficiency? Evidence from the Swiss hospital sector," ECON - Working Papers 053, Department of Economics - University of Zurich.
  • Handle: RePEc:zur:econwp:053
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    1. Chalkley, Martin & Malcomson, James M., 1998. "Contracting for health services when patient demand does not reflect quality," Journal of Health Economics, Elsevier, vol. 17(1), pages 1-19, January.
    2. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    3. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    4. Mehdi Farsi & Massimo Filippini, 2006. "An Analysis of Efficiency and Productivity in Swiss Hospitals," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 142(I), pages 1-37, March.
    5. Biorn, Erik & Hagen, Terje P. & Iversen, Tor & Magnussen, Jon, 2002. "The Effect of Activity-Based Financing on Hospital Efficiency: A Panel Data Analysis of DEA Efficiency Scores 1992-2000," MPRA Paper 8099, University Library of Munich, Germany.
    6. Margit Sommersguter-Reichmann, 2000. "The impact of the Austrian hospital financing reform on hospital productivity: empirical evidence on efficiency and technology changes using a non-parametric input-based Malmquist approach," Health Care Management Science, Springer, vol. 3(4), pages 309-321, September.
    7. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980, October.
    8. Erik Biørn & Terje Hagen & Tor Iversen & Jon Magnussen, 2010. "How different are hospitals’ responses to a financial reform? The impact on efficiency of activity-based financing," Health Care Management Science, Springer, vol. 13(1), pages 1-16, March.
    9. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    10. Chalkley, Martin & Malcomson, James M., 2000. "Government purchasing of health services," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 15, pages 847-890, Elsevier.
    11. Borden, James P., 1988. "An assessment of the impact of diagnosis-related group (DRG)-based reimbursement on the technical efficiency of New Jersey hospitals using data envelopment analysis," Journal of Accounting and Public Policy, Elsevier, vol. 7(2), pages 77-96.
    12. Biorn, Erik & Hagen, Terje P. & Iversen, Tor & Magnussen, Jon, 2006. "Heterogeneity in Hospitals' Responses to a Financial Reform: A Random Coefficient Analysis of The Impact of Activity-Based Financing on Efficiency," MPRA Paper 8169, University Library of Munich, Germany.
    13. Jim Griffin & Mark Steel, 2007. "Bayesian stochastic frontier analysis using WinBUGS," Journal of Productivity Analysis, Springer, vol. 27(3), pages 163-176, June.
    14. Mehdi Farsi & Massimo Filippini & William Greene, 2006. "Application Of Panel Data Models In Benchmarking Analysis Of The Electricity Distribution Sector," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 77(3), pages 271-290, September.
    15. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    16. Peter Zweifel & Ming Tai-Seale, 2009. "An economic analysis of payment for health care services: The United States and Switzerland compared," International Journal of Health Economics and Management, Springer, vol. 9(2), pages 197-210, June.
    17. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    18. repec:pra:mprapa:8100 is not listed on IDEAS
    19. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    20. Philippe K Widmer & Peter Zweifel & Mehdi Farsi, 2010. "Accounting For Heterogeneity In The Measurement of Hospital Performance," Economics Discussion / Working Papers 10-21, The University of Western Australia, Department of Economics.
    21. O'Reilly, Jacqueline & Busse, Reinhard & Häkkinen, Unto & Or, Zeynep & Street, Andrew & Wiley, Miriam, 2012. "Paying for hospital care: the experience with implementing activity-based funding in five European countries," Health Economics, Policy and Law, Cambridge University Press, vol. 7(1), pages 73-101, January.
    22. L. Steinmann & P. Zweifel, 2003. "On the (in)efficiency of Swiss hospitals," Applied Economics, Taylor & Francis Journals, vol. 35(3), pages 361-370.
    23. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    24. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
    25. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    26. A. J. Culyer & J. P. Newhouse (ed.), 2000. "Handbook of Health Economics," Handbook of Health Economics, Elsevier, edition 1, volume 1, number 1.
    27. Joseph P. Newhouse, 1996. "Reimbursing Health Plans and Health Providers: Efficiency in Production versus Selection," Journal of Economic Literature, American Economic Association, vol. 34(3), pages 1236-1263, September.
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    Cited by:

    1. Braendle, Thomas & Colombier, Carsten, 2016. "What drives public health care expenditure growth? Evidence from Swiss cantons, 1970–2012," Health Policy, Elsevier, vol. 120(9), pages 1051-1060.
    2. Remers, Toine E.P. & Wackers, Erik M.E. & van Dulmen, Simone A. & Jeurissen, Patrick P.T., 2022. "Towards population-based payment models in a multiple-payer system: the case of the Netherlands," Health Policy, Elsevier, vol. 126(11), pages 1151-1156.
    3. Widmer, Philippe K., 2016. "SwissDRG: Ein Vergütungssystem mit ungleichen finanziellen Risiken für die Spitäler?," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 70(3), pages 210-226.
    4. Cristian Barra & Raffaele Lagravinese & Roberto Zotti, 2022. "Exploring hospital efficiency within and between Italian regions: new empirical evidence," Journal of Productivity Analysis, Springer, vol. 57(3), pages 269-284, June.
    5. Philippe K. Widmer & Maria Trottmann & Peter Zweifel, 2018. "Choice of reserve capacity by hospitals: a problem for prospective payment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(5), pages 663-673, June.
    6. Stefan Meyer, 2015. "Payment schemes and cost efficiency: evidence from Swiss public hospitals," International Journal of Health Economics and Management, Springer, vol. 15(1), pages 73-97, March.
    7. Cavalieri, M. & Guccio, C. & Lisi, D. & Pignataro, G., 2015. "Does the Extent of Per-Case Payment System Affect Hospital Efficiency? Evidence from the Italian NHS," Health, Econometrics and Data Group (HEDG) Working Papers 15/29, HEDG, c/o Department of Economics, University of York.
    8. Alejandro Arvelo-Martín & Juan José Díaz-Hernández & Ignacio Abásolo-Alessón, 2019. "Hospital productivity bias when not adjusting for cost heterogeneity: The case of Spain," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-17, June.
    9. Carine Milcent & Saad Zbiri, 2022. "Supplementary private health insurance: The impact of physician financial incentives on medical practice," Health Economics, John Wiley & Sons, Ltd., vol. 31(1), pages 57-72, January.

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    More about this item

    Keywords

    Hospital inefficiency; prospective payment system; Bayesian inference; stochastic frontier analysis;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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