Antibiotic Outbreak, Risk Factors for Never Event, Prediction of Inappropriate Use

Midwestern University

Status: Completed

Conditions: Infectious Disease

Study type: Observational

Funder types: Other

Identifiers

NCT03489330

MWU3004_STU00205629

Details and patient eligibility

About

In order to decrease inappropriate antibiotic use, drivers of inappropriate use must be identified locally. This study will focus on the MOST inappropriate use, which are defined as 'never events'. Previous work has shown that antibiotic use clusters over time. It is hypothesized that never events also cluster over time. Using electronic data capture strategies, an algorithm will be developed to quickly and accurately identify areas of antibiotic use concern. Secondly, a framework will be developed, utilizing antimicrobial consumption data and captured signals of inappropriate antimicrobial use to provide targets for antimicrobial stewardship efforts.

Full description

Appropriateness in antimicrobial prescribing has become a focal national and international issue. It has been estimated that upwards of 50% of antibiotic use is inappropriate. With this backdrop, a national strategic goal has been set by the United States White House to decrease inappropriate antibiotic use by 20% and 50%, respectively for inpatient and outpatient settings. In order to decrease inappropriate use, drivers of incorrect use must be identified at each local setting. The actual drivers of confirmed inappropriate use have been difficult to identify except when using time and resource intense chart reviews. Even the largest contemporary antibiotic consumption studies have not assessed appropriateness as it was 'outside of study scope'. Further, there is no consensus or agreement on what constitutes inappropriate use. These apparent omissions underscore the difficulty and complexity in attributing appropriateness of use for antimicrobials. Importantly, this study will focus on the MOST inappropriate use, which are defined as 'never events'. Previous work has shown that antibiotic use clusters over time. It is hypothesized that never events also cluster over time. Using electronic data capture strategies, an algorithm will be developed to quickly and accurately identify areas of antibiotic use concern. Secondly, a framework will be developed, utilizing antimicrobial consumption data and captured signals of inappropriate antimicrobial use to provide targets for antimicrobial stewardship efforts.

Enrollment: 2,000 estimated patients

Sex: All

Ages: 18 to 90 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• receipt of inpatient intravenous vancomycin during proposed study period
• adults 18 years of age or older and less than 90 years of age

Exclusion criteria

• individuals who are not yet adults (infants, children, teenagers)
• pregnant women
• prisoners

Trial design

2,000 participants in 3 patient groups

Northwestern Memorial Hospital data

Description:

Inpatient intravenous vancomycin use

Henry Ford Hospital data

Description:

Inpatient intravenous vancomycin use

University of Michigan Hospital data

Description:

Inpatient intravenous vancomycin use