Stochastic league tables: An application to diabetes interventions in the Netherlands

Raymond C.W. Hutubessy, Louis W. Niessen, Rob F. Dijkstra, Ton F. Casparie, Frans F. Rutten

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The aim of this paper is to discuss the use of stochastic league tables approach in cost-effectiveness analysis of diabetes interventions. It addresses the common grounds and differences with other methods of presenting uncertainty to decision-makers. This comparison uses the cost-effectiveness results of medical guidelines for Dutch diabetes type 2 patients in primary and secondary care. Stochastic league tables define the optimum expansion pathway as compared to baseline, starting with the least costly and most cost-effective intervention mix. Multi-intervention cost-effectiveness acceptability curves are used as a way to represent uncertainty information on the cost-effectiveness of single interventions as compared to a single alternative. The stochastic league table for diabetes interventions shows that in case of low budgets treatment of secondary care patients is the most likely optimum choice. Current care options of diabetes complications are shown to be inefficient compared to guidelines treatment. With more resources available one may implement all guidelines and improve efficiency. The stochastic league table approach and multi-intervention cost-effectiveness acceptability curves in uncertainty analysis lead to similar results. In addition, the stochastic league table approach provides policy makers with information on affordability by budget level. It fulfils more adequately the information requirements to choose between interventions, using the efficiency criterion.

Original languageEnglish (US)
Pages (from-to)445-455
Number of pages11
JournalHealth economics
Volume14
Issue number5
DOIs
StatePublished - May 2005
Externally publishedYes

Keywords

  • Cost-effectiveness analysis
  • Decision-making analysis
  • Diabetes mellitus
  • Uncertainty analysis

ASJC Scopus subject areas

  • Health Policy

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