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A decision support tool for antibiotic therapy

R S Evans1, D C Classen, S L Pestotnik

  • 1LDS Hospital, Salt Lake City, Utah, USA.

Proceedings. Symposium on Computer Applications in Medical Care
|January 1, 1995
PubMed
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A new antibiotic decision support tool reduced costs by $87 per patient and lowered adverse drug events. This clinical decision support system aids physicians in antibiotic selection and dosing, improving patient outcomes.

Area of Science:

  • Medical Informatics
  • Clinical Pharmacy
  • Intensive Care Medicine

Background:

  • Physicians require assistance in selecting appropriate antibiotic therapies.
  • Optimizing antibiotic selection is crucial for patient outcomes and cost-effectiveness.
  • Intensive care units (ICUs) present complex challenges for antibiotic management.

Purpose of the Study:

  • To evaluate the impact of a novel decision support tool on antibiotic prescribing practices.
  • To assess the tool's effect on antibiotic costs and adverse drug events (ADEs) in an ICU setting.

Main Methods:

  • A 7-month pilot study implemented a decision support tool for all antibiotic orders in a Shock/Trauma/Respiratory Intensive Care Unit (STRICU).
  • Clinical data from the study period were compared to a 12-month control period.

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  • The tool provided patient information, suggested antibiotic regimens, doses, and intervals.

    • Main Results:

    • The decision support tool was used for 588 antibiotic orders; suggested regimens were used 37% of the time.
    • Computer-suggested dosages were utilized over 90% of the time.
    • Mean antibiotic cost per patient decreased by $87.00 (p < 0.04).
    • Antibiotic adverse drug events (ADEs) were lower during the study period (0.9%) compared to the control period (2.4%), though not statistically significant (p = 0.164).

    Conclusions:

    • The decision support tool effectively assists physicians in antibiotic selection and dosing.
    • Implementation of the tool led to significant cost savings in antibiotic therapy.
    • The tool shows potential for reducing adverse drug events in critical care settings.