Journal of Clinical Epidemiology
Volume 52, Issue 3 , Pages 251-258, March 1999

Modeling of High-cost Patient Distribution within Renal Failure Diagnosis Related Group

  • C. Quantin

      Affiliations

    • Department of Biostatistics, Teaching Public Hospital of Dijon, Dijon Cedex, France
    • Corresponding Author InformationAddress correspondence to: Catherine Quantin, M.D., Ph.D., Service de Biostatistique et Informatique Médicale, C.H.U, B.P 1542, 21034 Dijon Cedex, France
  • ,
  • E. Sauleau

      Affiliations

    • Department of Biostatistics, Public Hospital of Mulhouse, Mulhouse, France
  • ,
  • P. Bolard

      Affiliations

    • Department of Biostatistics, Teaching Public Hospital of Dijon, Dijon Cedex, France
  • ,
  • C. Mousson

      Affiliations

    • Department of Nephrology, Teaching Public Hospital of Dijon, Dijon Cedex, France
  • ,
  • M. Kerkri

      Affiliations

    • Department of Biostatistics, Teaching Public Hospital of Dijon, Dijon Cedex, France
  • ,
  • P.Brunet Lecomte

      Affiliations

    • Department of Biostatistics, Teaching Public Hospital of Dijon, Dijon Cedex, France
  • ,
  • T. Moreau

      Affiliations

    • Department of Epidemiology and Biostatistics, National Institute of Medical Research (INSERM), Villejuif Cedex, France
  • ,
  • L. Dusserre

      Affiliations

    • Department of Biostatistics, Teaching Public Hospital of Dijon, Dijon Cedex, France

Accepted 3 November 1998.

Abstract 

Modeling by mixed-distribution was proposed in order to analyze heterogeneity of costs and length of stays within Diagnosis Related Groups (DRGs). A mixed-distribution model based on Weibull distributions was applied to 791 discharge abstracts of French DRG no. 450 (Health Care Financing Administration 3 DRG no. 316 “Renal failure”) from a national database. Three subgroups of cost and length of stay were identified. Except for age, clinical criteria significantly linked with the long-stay subgroup were the same as those associated with the high-cost subgroup: acute renal failure, intensive care, infectious complications, and vascular investigations. The identification of factors associated with high costs, based on the proposed model, will allow physicians to understand more accurately how their choice of specific procedures influences hospital costs.

Keywords:  DRGs, mixed-distribution model, EM algorithm, cost, renal failure

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PII: S0895-4356(98)00164-4

Journal of Clinical Epidemiology
Volume 52, Issue 3 , Pages 251-258, March 1999