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

Author: , AlmanasrehNadja, AndreassenSteen, CaudaRoberto, FrankUwe, LeiboviciLeonard, NielsenAnders D, PaulMical, TacconelliEvelina

Comparative StudyResearch that compares multiple groups/interventions to determine differences/similarities in outcomes/characteristics.
Journal ArticleAn article published in an academic or professional journal that reports original research or scholarly analysis.
Randomized Controlled TrialA clinical trial that randomly assigns participants to treatment and control groups to evaluate the effects of an intervention.
Research Support, Non-U.S. Gov'tResearch funding provided by government agencies outside the United States.

Overview

The study evaluated the effectiveness of a computerized decision support system for antibiotic treatment (TREAT) in improving appropriate antibiotic treatment and reducing antibiotic costs. The results showed that TREAT prescribed appropriate empirical antibiotic treatment significantly more frequently than physicians, used less broad-spectrum antibiotics, and reduced antibiotic costs. The study concluded that TREAT improved the rate of appropriate empirical antibiotic treatment while reducing antibiotic costs and the use of broad-spectrum antibiotic treatment.
Paper Details　
Original Abstract of the Article :
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 advi...See full text at original site
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引用元：
https://doi.org/10.1093/jac/dkl372

データ提供：米国国立医学図書館（NLM）

TREAT: A Computerized Decision Support System for Optimizing Antibiotic Treatment

Antibiotic resistance is a growing global health threat, emphasizing the need for judicious antibiotic use. This study investigates the effectiveness of TREAT, a computerized decision support system for antibiotic treatment, in improving antibiotic prescribing practices and reducing antibiotic costs. The study involved a prospective cohort study and a cluster randomized trial conducted in three hospitals in Israel, Germany, and Italy. The results demonstrated that TREAT significantly improved the rate of appropriate empirical antibiotic treatment compared to physicians' prescribing habits, while simultaneously reducing antibiotic costs and the use of broad-spectrum antibiotics. These findings highlight the potential of computerized decision support systems to enhance antibiotic stewardship and optimize treatment outcomes.

TREAT: A Promising Tool for Antibiotic Stewardship

The study's findings suggest that TREAT is a promising tool for improving antibiotic prescribing practices and reducing antibiotic resistance. The system's ability to guide clinicians towards appropriate and cost-effective antibiotic choices is a valuable contribution to the fight against antibiotic resistance.

Optimizing Antibiotic Treatment

Antibiotic resistance is a serious threat to public health. This study demonstrates the potential of computerized decision support systems, like TREAT, to optimize antibiotic treatment and reduce the risk of resistance. By promoting the judicious use of antibiotics, we can preserve the effectiveness of these life-saving medications for future generations.

Dr.Camel's Conclusion

This research is like finding a hidden spring of fresh water in the arid desert of antibiotic resistance! TREAT is a valuable tool for guiding clinicians towards effective and responsible antibiotic use, helping us to combat this growing threat to global health.

Date :
  1. Date Completed 2007-03-22
  2. Date Revised 2022-03-30
Further Info :

Pubmed ID

16998208

DOI: Digital Object Identifier

10.1093/jac/dkl372

Related Literature

Article Analysis
・Effective treatment of antibiotic resistance
SNS
PICO Info
in preparation
Languages

English

Positive IndicatorAn AI analysis index that serves as a benchmark for how positive the results of the study are. Note that it is a benchmark and requires careful interpretation and consideration of different perspectives.

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