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JAC Advance Access originally published online on September 23, 2006
Journal of Antimicrobial Chemotherapy 2006 58(6):1238-1245; doi:10.1093/jac/dkl372
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© The Author 2006. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Antimicrobial practice

Improving empirical antibiotic treatment using TREAT, a computerized decision support system: cluster randomized trial

Mical Paul1,2,*, Steen Andreassen3, Evelina Tacconelli4, Anders D. Nielsen3, Nadja Almanasreh5, Uwe Frank5, Roberto Cauda4, Leonard Leibovici1,2 and on behalf of the TREAT Study Group

1 Department of Medicine E, Rabin Medical Center Beilinson Campus, 49100 Petah-Tiqva, Israel 2 Sackler Faculty of Medicine, Tel-Aviv University Ramat-Aviv, Israel 3 Center for Model-based Medical Decision Support, Aalborg University Aalborg, Denmark 4 Department of Infectious Diseases, Gemelli Hospital in Rome, Universitá Cattolica del Sacro Cuore School of Medicine Rome, Italy 5 Department of Clinical Microbiology and Hospital Hygiene, Freiburg University Hospital, Freiburg University Freiburg, Germany

Received 12 March 2006; returned 28 June 2006; revised 13 August 2006; accepted 17 August 2006

*Corresponding author. Tel: +972-3-9376504; Fax: +972-3-9376512; E-mail: pil1pel{at}zahav.net.il

Background: Appropriate antibiotic treatment decreases mortality, while superfluous treatment is associated with antibiotic resistance. We built a computerized decision support system for antibiotic treatment (TREAT) targeting these outcomes.

Methods: Prospective cohort study comparing TREAT's advice to physician's treatment followed by a cluster randomized trial comparing wards using TREAT (intervention) versus antibiotic monitoring without TREAT (control). We included patients suspected of harbouring bacterial infections in three hospitals (Israel, Germany and Italy). The primary outcome, appropriate antibiotic treatment, was assessed among patients with microbiologically documented infections (MDI). Length of hospital stay, adverse events, mortality (interventional trial) and antibiotic costs (both studies), including costs related to future antibiotic resistance, were compared among all included patients.

Results: Among 1203 patients included in the cohort study (350 with MDI), TREAT prescribed appropriate empirical antibiotic treatment significantly more frequently than physicians (70% versus 57%, P < 0.001) using less broad-spectrum antibiotics at half physicians' antibiotic costs. The randomized trial included 2326 patients, 570 with MDI. The rate of appropriate empirical antibiotic treatment was higher in intervention versus control wards [73% versus 64%, odds ratio (OR): 1.48, 95% confidence interval (CI): 0.95–2.29, intention to treat, adjusted for location and clustering]. For patients treated according to TREAT's advice in intervention wards, the difference with controls was highly significant (OR: 3.40, 95% CI: 2.25–5.14). Length of hospital stay, costs related to future resistance and total antibiotic costs were lower in intervention versus control wards.

Conclusions: TREAT improved the rate of appropriate empirical antibiotic treatment while reducing antibiotic costs and the use of broad-spectrum antibiotic treatment.

Keywords: appropriate antibiotic treatment , antibiotic resistance , ecological antibiotic costs , decision support system


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