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Computer-assisted decision support for the diagnosis and treatment of infectious diseases in intensive care units

  • C.A.M. Schurink*
  • , P.J.F. Lucas
  • , I.M. Hoepelman
  • , M.J.M. Bonten
  • *Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

Abstract

Diagnosing nosocomial infections in critically ill patients admitted to intensive care units (ICUs) is a challenge because signs and symptoms are usually non-specific for a particular infection. In addition, the choice of treatment, or the decision not to treat, can be difficult. Models and computer-based decision-support systems have been developed to assist ICU physicians in the management of infectious diseases. We discuss the historical development, possibilities, and limitations of various computer-based decision-support models for infectious diseases, with special emphasis on Bayesian approaches. Although Bayesian decision-support systems are potentially useful for medical decision making in infectious disease management, clinical experience with them is limited and prospective evaluation is needed to determine whether their use can improve the quality of patient care.

Original languageEnglish
Pages (from-to)305-312
Number of pages8
JournalThe Lancet infectious diseases
Volume5
Issue number5
DOIs
Publication statusPublished - May 2005
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • n/a OA procedure

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