The TREAT project: decision support and prediction using causal probabilistic networks

Leonard Leibovici*, Mical Paul, Anders D. Nielsen, Evelina Tacconelli, Steen Andreassen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

TREAT is a decision support system for antibiotic treatment in inpatients with common bacterial infections. It was tested in a randomised controlled trial in three countries and shown to improve the percentage of appropriate empirical antibiotic treatments, while at the same time reducing hospital stay and the use of broad-spectrum antibiotics. TREAT is based on a causal probabilistic network and uses a cost-benefit model for antibiotic treatment, including costs assigned to future resistance. In the present review we discuss the advantages of using causal probabilistic models for prediction and decision support, and the various decisions that were taken in the TREAT project.

Original languageEnglish
Pages (from-to)93-102
Number of pages10
JournalInternational Journal of Antimicrobial Agents
Volume30
Issue numberSUPPL. 1
DOIs
StatePublished - Nov 2007
Externally publishedYes

Keywords

  • Appropriate antibiotic treatment
  • Bacterial infection
  • Bloodstream infection
  • Computerised decision support system
  • Cost-benefit
  • Prediction
  • Resistance to antibiotic drugs

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