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How well do diagnosis-related groups for appendectomy explain variations in resource use? An analysis of patient-level data from 10 european countries

Author

Listed:
  • Anne Mason

    (CHE - Center for Health Economics - University of York [York, UK])

  • Zeynep Or

    (IRDES - Institut de Recherche et Documentation en Economie de la Santé - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres)

  • Thomas Renaud

    (IRDES - Institut de Recherche et Documentation en Economie de la Santé - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres)

  • Andrew Street

    (CHE - Center for Health Economics - University of York [York, UK])

  • Josselin Thuilliez

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Padraic Ward

    (CHE - Center for Health Economics - University of York [York, UK])

Abstract

Appendectomy is a common and relatively simple procedure to remove an inflamed appendix, but the rate of appendectomy varies widely across Europe. This paper investigates factors that explain differences in resource use for appendectomy. We analysed 106 929 appendectomy patients treated in 939 hospitals in 10 European countries. In stage 1, we tested the performance of three models in explaining variation in the (log of) cost of the inpatient stay (seven countries) or length of stay (three countries). The first model used only the diagnosis-related groups (DRGs) to which patients were coded, the second model used a core set of general patient-level and appendectomy-specific variables, and the third model combined both sets of variables. In stage two, we investigated hospital-level variation. In classifying appendectomy patients, most DRG systems take account of complex diagnoses and comorbidities but use different numbers of DRGs (range: 2 to 8). The capacity of DRGs and patient-level variables to explain patient-level cost variation ranges from 34% in Spain to over 60% in England and France. All DRG systems can make better use of administrative data such as the patient's age, diagnoses and procedures, and all countries have outlying hospitals that could improve their management of resources for appendectomy.

Suggested Citation

  • Anne Mason & Zeynep Or & Thomas Renaud & Andrew Street & Josselin Thuilliez & Padraic Ward, 2012. "How well do diagnosis-related groups for appendectomy explain variations in resource use? An analysis of patient-level data from 10 european countries," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00719783, HAL.
  • Handle: RePEc:hal:cesptp:halshs-00719783
    DOI: 10.1002/hec.2836
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    References listed on IDEAS

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    1. Street, Andrew & Sivey, Peter & Mason, Anne & Miraldo, Marisa & Siciliani, Luigi, 2010. "Are English treatment centres treating less complex patients?," Health Policy, Elsevier, vol. 94(2), pages 150-157, February.
    2. Andrew Street & Conrad Kobel & Thomas Renaud & Josselin Thuilliez & ON BEHALF OF THE EURODRG GROUP, 2012. "How Well Do Diagnosis‐Related Groups Explain Variations In Costs Or Length Of Stay Among Patients And Across Hospitals? Methods For Analysing Routine Patient Data," Health Economics, John Wiley & Sons, Ltd., vol. 21(S2), pages 6-18, August.
    3. Andrew Street & Conrad Kobel & Thomas Renaud & Josselin Thuilliez & ON BEHALF OF THE EURODRG GROUP, 2012. "How Well Do Diagnosis‐Related Groups Explain Variations In Costs Or Length Of Stay Among Patients And Across Hospitals? Methods For Analysing Routine Patient Data," Health Economics, John Wiley & Sons, Ltd., vol. 21(S2), pages 6-18, August.
    4. Elena Polverejan & Joseph C. Gardiner & Cathy J. Bradley & Margaret Holmes‐Rovner & David Rovner, 2003. "Estimating mean hospital cost as a function of length of stay and patient characteristics," Health Economics, John Wiley & Sons, Ltd., vol. 12(11), pages 935-947, November.
    5. Halvorsen, Robert & Palmquist, Raymond, 1980. "The Interpretation of Dummy Variables in Semilogarithmic Equations," American Economic Review, American Economic Association, vol. 70(3), pages 474-475, June.
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    Cited by:

    1. Carine Milcent, 2021. "From downcoding to upcoding: DRG based payment in hospitals," International Journal of Health Economics and Management, Springer, vol. 21(1), pages 1-26, March.
    2. Møller Dahl, Christian & Planck Kongstad, Line, 2017. "The costs of acute readmissions to a different hospital – Does the effect vary across provider types?," Social Science & Medicine, Elsevier, vol. 183(C), pages 116-125.
    3. Zuzana Kotherová & Martina Caithamlová & Juraj Nemec & Kateřina Dolejšová, 2021. "The Use of Diagnosis-Related Group-Based Reimbursement in the Czech Hospital Care System," IJERPH, MDPI, vol. 18(10), pages 1-18, May.
    4. Reinhard Busse & on behalf of the EuroDRG group, 2012. "DO DIAGNOSIS‐RELATED GROUPS EXPLAIN VARIATIONS IN HOSPITAL COSTS AND LENGTH OF STAY? – ANALYSES FROM THE EURODRG PROJECT FOR 10 EPISODES OF CARE ACROSS 10 EuroPEAN COUNTRIES," Health Economics, John Wiley & Sons, Ltd., vol. 21(S2), pages 1-5, August.
    5. Carine Milcent, 2019. "From downcoding to upcoding: DRG based payment in hospitals," Working Papers halshs-02317416, HAL.
    6. Carine Milcent, 2019. "From downcoding to upcoding: DRG based payment in hospitals," PSE Working Papers halshs-02317416, HAL.
    7. James Gaughan & Anne Mason & Andrew Street & Padraic Ward, 2012. "English Hospitals Can Improve Their Use of Resources: An Analysis of Costs and Length of Stay for Ten Treatments," Working Papers 078cherp, Centre for Health Economics, University of York.
    8. Myung Jae Jeon & Sung Pil Choo & Young Hwa Kwak & Dong Wook Kim & Eui Hyeok Kim, 2019. "The effect of diagnosis-related group payment system on the quality of medical care for pelvic organ prolapse in Korean tertiary hospitals," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-9, August.

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