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New computer-based tools for empiric antibiotic decision support

H Warner1, S R Blue, D Sorenson

  • 1Division of Infectious Disease, University of Utah Medical Center, Sunquest Information Systems, Inc., Salt Lake City, USA.

Proceedings : a Conference of the American Medical Informatics Association. AMIA Fall Symposium
|January 1, 1997
PubMed
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This study introduces Q-ID, an infectious disease decision-support model. Q-ID aids in selecting empirical antibiotic treatments and optimizing current therapies by analyzing patient data and microbial resistance patterns.

Area of Science:

  • Infectious Diseases
  • Medical Informatics
  • Clinical Decision Support Systems

Background:

  • Empirical antibiotic therapy is crucial for managing infectious diseases.
  • Optimizing antibiotic selection requires considering disease specifics, patient factors, and local resistance patterns.
  • Existing decision-support tools may not fully integrate these complex variables.

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