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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

Author

Listed:
  • Andrew Street

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

  • Conrad Kobel

    (IMU - Innsbruck Medical University = Medizinische Universität Innsbruck)

  • Thomas Renaud

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

  • Josselin Thuilliez

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

Abstract

We set out an analytical strategy to examine variations in resource use, whether cost or length of stay, of patients hospitalised with different conditions. The methods are designed to evaluate (i) how well diagnosis-related groups (DRGs) capture variation in resource use relative to other patient characteristics and (ii) what influence the hospital has on their resource use. In a first step, we examine the influence of variables that describe each individual patient, including the DRG to which the patients are assigned and a range of personal and treatment-related characteristics. In a second step, we explore the influence that hospitals have on the average cost or length of stay of their patients, purged of the influence of the variables accounted for in the first stage. We provide a rationale for the variables used in both stages of the analysis and detail how each is defined. The analytical strategy allows us (i) to identify those factors that explain variation in resource use across patients, (ii) to assess the explanatory power of DRGs relative to other patient and treatment characteristics and (iii) to assess relative hospital performance in managing resources and the characteristics of hospitals that explain this performance.

Suggested Citation

  • Andrew Street & Conrad Kobel & Thomas Renaud & Josselin Thuilliez, 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," Post-Print halshs-00719777, HAL.
  • Handle: RePEc:hal:journl:halshs-00719777
    DOI: 10.1002/hec.2837
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    10. Bernal-Delgado, Enrique & Comendeiro-Maaløe, Micaela & Ridao-López, Manuel & Sansó Rosselló, Andreu, 2020. "Factors underlying the growth of hospital expenditure in Spain in a period of unexpected economic shocks: A dynamic analysis on administrative data," Health Policy, Elsevier, vol. 124(4), pages 389-396.
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    18. Michael M. Havranek & Josef Ondrej & Philippe K. Widmer & Stella Bollmann & Simon Spika & Stefan Boes, 2023. "Using exogenous organizational and regional hospital attributes to explain differences in case‐mix adjusted hospital costs," Health Economics, John Wiley & Sons, Ltd., vol. 32(8), pages 1733-1748, August.
    19. 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.
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    22. Mikko Peltola & on behalf of the EuroDRG group, 2012. "Patient Classification And Hospital Costs Of Care For Stroke In 10 European Countries," Health Economics, John Wiley & Sons, Ltd., vol. 21(S2), pages 129-140, August.
    23. Thanassoulis, Emmanuel & Silva Portela, Maria & Graveney, Mike, 2016. "Identifying the scope for savings at inpatient episode level: An illustration applying DEA to chronic obstructive pulmonary disease," European Journal of Operational Research, Elsevier, vol. 255(2), pages 570-582.
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    25. David Scheller‐Kreinsen & on behalf of the EuroDRG group, 2012. "How Well Do Diagnosis‐Related Group Systems Group Breast Cancer Surgery Patients?—Evidence From 10 European Countries," Health Economics, John Wiley & Sons, Ltd., vol. 21(S2), pages 41-54, August.

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