title: Computer-assisted decision support for the diagnosis and treatment of infectious diseases in intensive care units.
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.
authors.affiliation: Department of Medicine, Division of Acute Medicine and Infectious Diseases, University Medical Centre, Utrecht, Netherlands. K.Schurink@umcutrecht.nl
authors.forename: C A M
authors.initials: CA
authors.lastname: Schurink
authors.forename: P J F
authors.initials: PJ
authors.lastname: Lucas
authors.forename: I M
authors.initials: IM
authors.lastname: Hoepelman
authors.forename: M J M
authors.initials: MJ
authors.lastname: Bonten
mesh_terms: D001499:Bayes Theorem; D003141:Communicable Diseases / Q000175:diagnosis / Q000188:drug therapy; D003428:Cross Infection / Q000175:diagnosis* / Q000188:drug therapy; D003658:Decision Making, Computer-Assisted; D005103:Expert Systems; D006801:Humans; D007362:Intensive Care Units; D016015:Logistic Models; D011014:Pneumonia / Q000175:diagnosis / Q000188:drug therapy / Q000209:etiology; D012372:ROC Curve; D012121:Respiration, Artificial / Q000009:adverse effects