Evidence map›Paper›PMID 38268340›Full record

ArticleInfection control and hospital epidemiology2024

A five-year quasi-experimental study to evaluate the impact of empiric antibiotic order sets on antibiotic use metrics among hospitalized adult patients.

Wesley D Kufel, Jeffrey M Steele, Rahul Mahapatra, Mitchell V Brodey, Dongliang Wang, Kristopher M Paolino, Paul Suits, Derek W Empey, Stephen J Thomas

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In one paragraph

Article in Infection control and hospital epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Wesley D KufelBinghamton University School of Pharmacy and Pharmaceutical Sciences, Binghamton, New York.ORCID 0000-0001-7703-096X
Jeffrey M SteeleState University of New York Upstate Medical University, Syracuse, New York.
Rahul MahapatraState University of New York Upstate Medical University, Syracuse, New York.ORCID 0000-0002-8252-3715
Mitchell V BrodeyState University of New York Upstate Medical University, Syracuse, New York.
Dongliang WangState University of New York Upstate Medical University, Syracuse, New York.
Kristopher M PaolinoState University of New York Upstate Medical University, Syracuse, New York.
Paul SuitsState University of New York Upstate Medical University, Syracuse, New York.
Derek W EmpeyState University of New York Upstate University Hospital, Syracuse, New York.
Stephen J ThomasState University of New York Upstate Medical University, Syracuse, New York.ORCID 0000-0002-8368-7682

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveEvaluation of adult antibiotic order sets (AOSs) on antibiotic stewardship metrics has been limited. The primary outcome was to evaluate the standardized antimicrobial administration ratio (SAAR). Secondary outcomes included antibiotic days of therapy (DOT) per 1,000 patient days (PD); selected antibiotic use; AOS utilization;

designThis 5-year, single-center, quasi-experimental study comprised 5 phases from 2017 to 2022 over 10-month periods between August 1 and May 31.

settingThe study was conducted in a 752-bed tertiary care, academic medical center.

interventionOur institution implemented AOSs in the electronic medical record (EMR) for common infections among hospitalized adults.

resultsFor the primary outcome, a statistically significant decreases in SAAR were detected from phase 1 to phase 5 (1.0 vs 0.90;

conclusionsImplementing AOS into the EMR was associated with a statistically significant reduction in SAAR, antibiotic DOT per 1,000 PD, selected antibiotic orders, and CDI cases.

Indexed as

Anti-Infective AgentsClostridioides difficileClostridium InfectionsCross InfectionAdultAnti-Bacterial AgentsFluoroquinolonesHumansVancomycinAnti-Bacterial AgentsAnti-Infective AgentsFluoroquinolonesVancomycin

Identifiers

PMID38268340
PMCPMC11027081

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.