Literature DB >> 29169934

Sustained reduction in rates of hospital-onset Clostridium difficile infection using an automated electronic health record protocol.

Jad Antoine Khoury1, William W Sistrunk2, Frances Hixson3, Mary Duncan4, Ann Perry4, Amanda Varble4, Alex M Bryant5.   

Abstract

BACKGROUND: An automated protocol was designed within our electronic medical record (EMR) to help curb the Clostridium difficile problem at our institution. The protocol will identify patients at high risk for C difficile, improve the timing of testing of patients infected on admission, and enhance the appropriateness of C difficile testing throughout the patient's hospitalization.
METHODS: Admitted patients with 2 of the following 3 criteria were labeled as high risk for C difficile: admission to a medical institution in the preceding 90 days, administration of antibiotics in the preceding 90 days, or a history of C difficile. High-risk patients with diarrhea in the first 3 days of admission are identified in the EMR, and prompt testing for C difficile is done. After day 3, if diarrhea develops, a series of questions is presented to help test the appropriate patients for C difficile.
RESULTS: A statistically significant reduction in rates of hospital-onset C difficile was achieved after implementation of the protocol.
CONCLUSIONS: Implementation of an automated protocol for targeted testing of high-risk patients for C difficile was successful at reducing rates of hospital-onset C difficile by improving timing and appropriateness of testing.
Copyright © 2018 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Clostridium difficile

Mesh:

Year:  2017        PMID: 29169934     DOI: 10.1016/j.ajic.2017.09.029

Source DB:  PubMed          Journal:  Am J Infect Control        ISSN: 0196-6553            Impact factor:   2.918


  2 in total

1.  Preventable Patient Harm: a Multidisciplinary, Bundled Approach to Reducing Clostridium difficile Infections While Using a Glutamate Dehydrogenase/Toxin Immunochromatographic Assay/Nucleic Acid Amplification Test Diagnostic Algorithm.

Authors:  Katherine Schultz; Emily Sickbert-Bennett; Ashley Marx; David J Weber; Lauren M DiBiase; Stacy Campbell-Bright; Lauren E Bode; Mike Baker; Tom Belhorn; Mark Buchanan; Sherie Goldbach; Jacci Harden; Emily Hoke; Beth Huenniger; Jonathan J Juliano; Michael Langston; Heather Ritchie; William A Rutala; Jason Smith; Shelley Summerlin-Long; Lisa Teal; Peter Gilligan
Journal:  J Clin Microbiol       Date:  2018-08-27       Impact factor: 5.948

2.  Improving Appropriate Diagnosis of Clostridioides difficile Infection Through an Enteric Pathogen Order Set With Computerized Clinical Decision Support: An Interrupted Time Series Analysis.

Authors:  Catherine Liu; Kristine Lan; Elizabeth M Krantz; H Nina Kim; Jacqlynn Zier; Chloe Bryson-Cahn; Jeannie D Chan; Rupali Jain; John B Lynch; Steven A Pergam; Paul S Pottinger; Ania Sweet; Estella Whimbey; Andrew Bryan
Journal:  Open Forum Infect Dis       Date:  2020-08-21       Impact factor: 3.835

  2 in total

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