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Rendering hospital budgets volume based and open ended to reduce waiting lists: Does it work?

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  • van de Vijsel, Aart R.
  • Engelfriet, Peter M.
  • Westert, Gert P.
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    Abstract

    In the past decades fixed budgets for hospitals were replaced by reimbursement based on outputs in several countries in order to bring down waiting lists. This was also the case in the Netherlands where fixed global budgets were replaced by budgets that are to a large extent volume based and in practice open-ended. The objective of this study was to examine the effectiveness of this Dutch policy measure, which was implemented in 2001. We carried out a statistical analysis and interpretation of trends in Dutch hospital admission rates. We observed a significant turn in the development of in-patient admission rates after the abolition of budget caps in 2001: decreasing admission rates turned into an internationally exceptional increase of more than 3% per year. Day care admissions had already been rising explosively for two decades, but the pace increased after 2001. The increase in the number of admissions includes a broad range of patient categories that were not in the first place associated with long waiting times. The growth was attributable for a large part to admissions for observation of the patient and the evaluation of symptoms, not resulting in a definite medical diagnosis. We considered several factors, other than the availability of more resources, to explain the growth: the ageing of the population, making up for waiting list arrears, ditto for "under consumption" of unplanned care and, as to the growth of day care, substitution for inpatient care. However, these factors were all found to fall short as an explanation. Although waiting times have dropped since the change in the budget system, they continue to be long for several procedures. Our study indicates that making available more resources to admit patients, or otherwise an increase in hospital activity, do not in itself lead to equilibrium between demand and supply because the volume and composition of demand are partly induced by supply. We conclude that abolishing budget caps to solve waiting list problems is not efficient. Instead of a generic measure, a more focused approach is necessary. We suggest ingredients for such an approach.

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    Bibliographic Info

    Article provided by Elsevier in its journal Health Policy.

    Volume (Year): 100 (2011)
    Issue (Month): 1 (April)
    Pages: 60-70

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    Handle: RePEc:eee:hepoli:v:100:y:2011:i:1:p:60-70

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    Web page: http://www.elsevier.com/locate/healthpol

    Related research

    Keywords: Hospital Admissions Case mix Reimbursement mechanisms Payment systems Waiting lists;

    References

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    1. Davis, Carolyne K. & Rhodes, Deborah J., 1988. "The impact of DRGs on the cost and quality of health care in the United States," Health Policy, Elsevier, vol. 9(2), pages 117-131, April.
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    4. McGuire, Thomas G., 2000. "Physician agency," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 9, pages 461-536 Elsevier.
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    6. J. Oostenbrink & F. Rutten, 2006. "Cost assessment and price setting of inpatient care in the Netherlands. The DBC case-mix system," Health Care Management Science, Springer, vol. 9(3), pages 287-294, August.
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    8. Reinhard Busse & Jonas Schreyögg & Peter Smith, 2006. "Editorial: Hospital case payment systems in Europe," Health Care Management Science, Springer, vol. 9(3), pages 211-213, August.
    9. Luigi Sicilani & Jeremy Hurst, 2004. "Explaining Waiting-time Variations for Elective Surgery Across OECD Countries," OECD Economic Studies, OECD Publishing, vol. 2004(1), pages 95-123.
    10. Hanning, Marianne & Spangberg, Ulrika Winblad, 2000. "Maximum waiting time -- a threat to clinical freedom?: Implementation of a policy to reduce waiting times," Health Policy, Elsevier, vol. 52(1), pages 15-32, May.
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    12. Iversen, Tor, 1993. "A theory of hospital waiting lists," Journal of Health Economics, Elsevier, vol. 12(1), pages 55-71, April.
    13. Duckett, Stephen J., 1995. "Hospital payment arrangements to encourage efficiency: the case of Victoria, Australia," Health Policy, Elsevier, vol. 34(2), pages 113-134, November.
    14. Mikkola, Hennamari & Keskimaki, Ilmo & Hakkinen, Unto, 2002. "DRG-related prices applied in a public health care system--can Finland learn from Norway and Sweden?," Health Policy, Elsevier, vol. 59(1), pages 37-51, January.
    15. Martine Bellanger & Laurent Tardif, 2006. "Accounting and reimbursement schemes for inpatient care in France," Health Care Management Science, Springer, vol. 9(3), pages 295-305, August.
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    Cited by:
    1. de Meijer, Claudine & O’Donnell, Owen & Koopmanschap, Marc & van Doorslaer, Eddy, 2013. "Health expenditure growth: Looking beyond the average through decomposition of the full distribution," Journal of Health Economics, Elsevier, vol. 32(1), pages 88-105.
    2. Schut, Frederik T. & Varkevisser, Marco, 2013. "Tackling hospital waiting times: The impact of past and current policies in the Netherlands," Health Policy, Elsevier, vol. 113(1), pages 127-133.
    3. Wong, Albert & Wouterse, Bram & Slobbe, Laurentius C.J. & Boshuizen, Hendriek C. & Polder, Johan J., 2012. "Medical innovation and age-specific trends in health care utilization: Findings and implications," Social Science & Medicine, Elsevier, vol. 74(2), pages 263-272.
    4. Rudy Douven & Remco Mocking & Ilaria Mosca, 2012. "The Effect of Physician Fees and Density Differences on Regional Variation in Hospital Treatments," CPB Discussion Paper 208, CPB Netherlands Bureau for Economic Policy Analysis.
    5. Claudine de Meijer & Marc Koopmanschap & Owen O'Donnell & Eddy van Doorslaer, 2012. "Health Expenditure Growth: Looking beyond the Average through Decomposition of the Full Distribution," Tinbergen Institute Discussion Papers 12-051/3, Tinbergen Institute.
    6. Jan Boone & Rudy Douven, 2014. "Provider competition and over-utilization in health care," CPB Discussion Paper 275, CPB Netherlands Bureau for Economic Policy Analysis.

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