title: Effect of an antibiotic algorithm on the adequacy of empiric antibiotic therapy given by a medical emergency team.
abstract: BACKGROUND
  Delayed administration of effective antimicrobial therapy increases mortality in patients with septic shock. Empiric antibiotic selection in this setting can be inaccurate. The objective of this study was to determine whether an antibiotic algorithm (AA) tailored to institutional resistance patterns improves the adequacy of antimicrobial therapy.
  
  
  METHODS
  A retrospective review of our rapid response system database was performed. Patients with possible sepsis with positive microbiological culture results were enrolled. Pathogens identified by culture were used to determine adequacy of antibiotic selection before and after implementation of an AA.
  
  
  RESULTS
  A total of 234 patients with septic shock were reviewed (before AA, n = 36; after AA, n = 198). Seventy-two patients had positive cultures and were enrolled (before AA, n = 13; after AA, n = 59). Significantly more patients received adequate coverage after AA implementation (54% vs 86%, P = .02). Before AA, inadequate Gram-negative coverage was the most common reason for failure. Reasons for failure in the after-AA group were nonadherence to the algorithm (n = 5) and multidrug-resistant pathogens (n = 3). The algorithm failed in patients with vancomycin-resistant enterococci (n = 3), multidrug-resistant Klebsiella pneumoniae (n = 1), and Candida albicans (n = 1).
  
  
  CONCLUSIONS
  The use of an AA significantly improves the adequacy of empiric antimicrobial therapy.
authors.affiliation: Department of Pharmacy, Hospital of the University of Pennsylvania 19104, USA. tmiano81@gmail.com
authors.forename: Todd A
authors.initials: TA
authors.lastname: Miano
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Powell
authors.forename: William D
authors.initials: WD
authors.lastname: Schweickert
authors.forename: Steven
authors.initials: S
authors.lastname: Morgan
authors.forename: Shawn
authors.initials: S
authors.lastname: Binkley
authors.forename: Babak
authors.initials: B
authors.lastname: Sarani
mesh_terms: D000368:Aged; D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D020000:Decision Support Systems, Clinical; D004632:Emergency Medical Services; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010348:Patient Care Team; D012189:Retrospective Studies; D012772:Shock, Septic / Q000188:drug therapy*; D016896:Treatment Outcome
chemical_list: D000900:Anti-Bacterial Agents