Evidence map›Paper›PMID 19712032›Full record

Trial reportInfection control and hospital epidemiology2009

Impact of an antimicrobial utilization program on antimicrobial use at a large teaching hospital: a randomized controlled trial.

Bernard C Camins, Mark D King, Jane B Wells, Heidi L Googe, Manish Patel, Ekaterina V Kourbatova, Henry M Blumberg

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Infection control and hospital epidemiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00552838 (The Impact of an Antimicrobial Utilization Program on Antimicrobial Use in a Large Public Hospital), which is not on this map. Cited by 52 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 6 pooled it
–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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT00552838 nacompletednot on this map

The Impact of an Antimicrobial Utilization Program on Antimicrobial Use in a Large Public Hospital: A Randomized Controlled Trial

TypeinterventionalSponsorWashington University School of MedicineRan2002 to 2003Enrolled785ConditionsAntimicrobial Prescribing PracticesArmsAcademic Detailing by the Antimicrobial Utilization Team (AUT)
3 · Its place in the literature

Who cites it

52 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Bernard C CaminsDepartment of Medicine, Emory University School of Medicine, Grady Memorial Hospital, Atlanta, Georgia, USA.
Mark D King
Jane B Wells
Heidi L Googe
Manish Patel
Ekaterina V Kourbatova
Henry M Blumberg

Funding

Washington University Institute of Clinical and Translational Sciences (UL1)UL1RR024992 · NCRR · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2007 to 2011
$45.4M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
CTSA INFRASTRUCTURE FOR PEDIATRIC RESEARCHUL1RR025008 · NCRR · EMORY UNIVERSITY · PI STEPHENS, DAVID S · 2007 to 2011
$29.0M
Atlanta Clinical and Translational Science Institute (ACTSI) RenewalUL1TR000454 · NCATS · EMORY UNIVERSITY · PI STEPHENS, DAVID S · 2012 to 2016
$25.8M
Mentored Clinical Research Scholar ProgramK12RR017643 · NCRR · EMORY UNIVERSITY · PI BLUMBERG, HENRY M · 2002 to 2006
$5.1M
Improving Antimicrobial UseK23AI054371 · NIAID · EMORY UNIVERSITY · PI KING, MARK D · 2004 to 2004
$83k
NCATS NIH HHS UL1 TR000448NCATS NIH HHS UL1 TR000454NCRR NIH HHS K12 RR017643NCRR NIH HHS UL1 RR024992NCRR NIH HHS UL1RR024992NCRR NIH HHS UL1 RR025008NIAID NIH HHS K23 AI054371
6 · The paper itself

Abstract

backgroundMultidisciplinary antimicrobial utilization teams (AUTs) have been proposed as a mechanism for improving antimicrobial use, but data on their efficacy remain limited.

objectiveTo determine the impact of an AUT on antimicrobial use at a teaching hospital.

designRandomized controlled intervention trial.

settingA 953-bed, public, university-affiliated, urban teaching hospital. PATIENTS: Patients who were given selected antimicrobial agents (piperacillin-tazobactam, levofloxacin, or vancomycin) by internal medicine ward teams.

interventionTwelve internal medicine teams were randomly assigned monthly: 6 teams to an intervention group (academic detailing by the AUT) and 6 teams to a control group that was given indication-based guidelines for prescription of broad-spectrum antimicrobials (standard of care), during a 10-month study period. MEASUREMENTS: Proportion of appropriate empirical, definitive (therapeutic), and end (overall) antimicrobial usage.

resultsA total of 784 new prescriptions of piperacillin-tazobactam, levofloxacin, and vancomycin were reviewed. The proportion of antimicrobial prescriptions written by the intervention teams that was considered to be appropriate was significantly higher than the proportion of antimicrobial prescriptions written by the control teams that was considered to be appropriate: 82% versus 73% for empirical (risk ratio [RR], 1.14; 95% confidence interval [CI], 1.04-1.24), 82% versus 43% for definitive (RR, 1.89; 95% CI, 1.53-2.33), and 94% versus 70% for end antimicrobial usage (RR, 1.34; 95% CI, 1.25-1.43). In multivariate analysis, teams that received feedback from the AUT alone (adjusted RR, 1.37; 95% CI, 1.27-1.48) or from both the AUT and the infectious diseases consultation service (adjusted RR, 2.28; 95% CI, 1.64-3.19) were significantly more likely to prescribe end antimicrobial usage appropriately, compared with control teams.

conclusionsA multidisciplinary AUT that provides feedback to prescribing physicians was an effective method in improving antimicrobial use. Trial registration. ClinicalTrials.gov identifier: NCT00552838.

Indexed as

Program EvaluationAdolescentAdultAgedAged, 80 and overAnti-Bacterial AgentsChildChild, PreschoolDrug UtilizationFemaleGuideline AdherenceHospitals, TeachingHumansInternal MedicineMaleMiddle AgedAnti-Bacterial Agents

Identifiers

PMID19712032
PMCPMC2779729

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Registered trials

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.