JOURNAL ARTICLE

Pharmacist adjustment of preoperative antibiotic orders to the preferred preoperative antibiotic cefazolin for patients with penicillin allergy labeling.

  • Published In: American Journal of Health-System Pharmacy, 2023, v. 80, n. 8. P. 532 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Lessard, Sarah; Huiras, Chris; Dababneh, Ala; Palraj, Raj; Thies, Renee; Woolever, Nate; Holt, Kandi; Schwan, Brenda; Poelma, Jennifer; Tempelis, Jennifer; Sawyer, Mark 3 of 3

Abstract

This article focuses on a pharmacist-led, interdisciplinary collaborative practice agreement (CPA) implemented to optimize preoperative antibiotic use in patients with penicillin allergy labeling (PAL), including those reporting severe immunoglobulin E–mediated reactions such as hives and anaphylaxis. The CPA allowed pharmacists to independently switch nonpreferred antibiotics to cefazolin, the preferred preoperative prophylactic antibiotic, resulting in increased cefazolin use (from 86% to 96.3%) and decreased use of alternatives like clindamycin and vancomycin without any reported allergic safety events during surgery. Among 1,572 patients with PAL undergoing 10,182 procedures, those with severe reactions, including 52 with anaphylaxis, tolerated cefazolin safely. The findings support the safe and effective use of cefazolin in patients with PAL through pharmacist-led stewardship, suggesting benefits outweigh risks even in severe allergy cases.

Additional Information

  • Source:American Journal of Health-System Pharmacy. 2023/04, Vol. 80, Issue 8, p532
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2023
  • ISSN:1079-2082
  • DOI:10.1093/ajhp/zxac385
  • Accession Number:163001503
  • Copyright Statement:Copyright of American Journal of Health-System Pharmacy is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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