Real-world Antimicrobial Stewardship Experience in a Large Academic Medical Center: Using Statistical and Machine Learning Approaches to Identify Intervention "Hotspots" in an Antibiotic Audit and Feedback Program.

ABSTRACT:

Background

Prospective audit with feedback (PAF) is an impactful strategy for antimicrobial stewardship program (ASP) activities. However, because PAF requires reviewing large numbers of antimicrobial orders on a case-by-case basis, PAF programs are highly resource intensive. The current study aimed to identify predictors of ASP intervention (ie, feedback) and to build models to identify orders that can be safely bypassed from review, to make PAF programs more efficient.

Methods

We performed a retrospective cross-sectional study of inpatient antimicrobial orders reviewed by the University of Maryland Medical Center's PAF program between 2017 and 2019. We evaluated the relationship between antimicrobial and patient characteristics with ASP intervention using multivariable log

SUBMITTER: Goodman KE 

PROVIDER: S-EPMC9297307 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature