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Evaluation of an Algorithm to Reduce Antibiotic Prescribing for Acute Bronchitis

NCT00981994 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 3300

Last updated 2016-11-28

No results posted yet for this study

Summary

Inappropriate use of antibiotics to treat patients with acute bronchitis is a significant factor contributing to the selection of antimicrobial drug resistant pathogens, which threaten the effectiveness of available therapies to treat common community-acquired bacterial infections. A key factor driving overuse of antibiotics is inaccurate estimation of pneumonia risk among patients with acute cough illnesses. This study will use a cluster randomized trial design within the Geisinger Health System's integrated clinic network to measure the efficacy of an algorithm driven clinical decision support tool to safely reduce the frequency of unnecessary antibiotic prescriptions for adult patients with lower respiratory tract infections.

Conditions

  • Acute Respiratory Tract Infection

Interventions

BEHAVIORAL

Decision Support for ARI Management

Use of history and physical examination findings to estimate probability of pneumonia in patients with acute respiratory infections and thereby guide treatment decisions

Sponsors & Collaborators

Principal Investigators

  • Joshua P Metlay, MD, PhD · University of Pennsylvania

  • Ralph Gonzales, MD,MS · University of California, San Francisco

Study Design

Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
16 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2009-10-31
Primary Completion
2011-05-31
Completion
2012-09-30

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT00981994 on ClinicalTrials.gov