Antibiotic Outbreak, Risk Factors for Never Event, Prediction of Inappropriate Use
Study Details
Study Description
Brief Summary
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.
Condition or Disease | Intervention/Treatment | Phase |
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Detailed 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.
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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Northwestern Memorial Hospital data Inpatient intravenous vancomycin use |
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Henry Ford Hospital data Inpatient intravenous vancomycin use |
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University of Michigan Hospital data Inpatient intravenous vancomycin use |
Outcome Measures
Primary Outcome Measures
- appropriateness of vancomycin use [Proposed 36 month study period]
classified as 1) never event, 2) potentially inappropriate, 3) not inappropriate
Secondary Outcome Measures
- outbreaks of never events [Proposed 36 month study period]
predictive interval thresholds that identify high proportion of never events
Eligibility Criteria
Criteria
Inclusion Criteria:
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receipt of inpatient intravenous vancomycin during proposed study period
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adults 18 years of age or older and less than 90 years of age
Exclusion Criteria:
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individuals who are not yet adults (infants, children, teenagers)
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pregnant women
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prisoners
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
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1 | Midwestern University | Downers Grove | Illinois | United States | 60515 |
Sponsors and Collaborators
- Midwestern University
- Northwestern Memorial Hospital
- University of Michigan
- Henry Ford Hospital
- Wayne State University
Investigators
- Principal Investigator: Marc H Scheetz, PharmD, MSc, Midwestern University
Study Documents (Full-Text)
More Information
Additional Information:
Publications
- Baggs J, Fridkin SK, Pollack LA, Srinivasan A, Jernigan JA. Estimating National Trends in Inpatient Antibiotic Use Among US Hospitals From 2006 to 2012. JAMA Intern Med. 2016 Nov 1;176(11):1639-1648. doi: 10.1001/jamainternmed.2016.5651.
- Cusini A, Rampini SK, Bansal V, Ledergerber B, Kuster SP, Ruef C, Weber R. Different patterns of inappropriate antimicrobial use in surgical and medical units at a tertiary care hospital in Switzerland: a prevalence survey. PLoS One. 2010 Nov 16;5(11):e14011. doi: 10.1371/journal.pone.0014011.
- Fleming-Dutra KE, Hersh AL, Shapiro DJ, Bartoces M, Enns EA, File TM Jr, Finkelstein JA, Gerber JS, Hyun DY, Linder JA, Lynfield R, Margolis DJ, May LS, Merenstein D, Metlay JP, Newland JG, Piccirillo JF, Roberts RM, Sanchez GV, Suda KJ, Thomas A, Woo TM, Zetts RM, Hicks LA. Prevalence of Inappropriate Antibiotic Prescriptions Among US Ambulatory Care Visits, 2010-2011. JAMA. 2016 May 3;315(17):1864-73. doi: 10.1001/jama.2016.4151.
- Glowacki RC, Schwartz DN, Itokazu GS, Wisniewski MF, Kieszkowski P, Weinstein RA. Antibiotic combinations with redundant antimicrobial spectra: clinical epidemiology and pilot intervention of computer-assisted surveillance. Clin Infect Dis. 2003 Jul 1;37(1):59-64. Epub 2003 Jun 23.
- Hecker MT, Aron DC, Patel NP, Lehmann MK, Donskey CJ. Unnecessary use of antimicrobials in hospitalized patients: current patterns of misuse with an emphasis on the antianaerobic spectrum of activity. Arch Intern Med. 2003 Apr 28;163(8):972-8.
- Kelesidis T, Braykov N, Uslan DZ, Morgan DJ, Gandra S, Johannsson B, Schweizer ML, Weisenberg SA, Young H, Cantey J, Perencevich E, Septimus E, Srinivasan A, Laxminarayan R. Indications and Types of Antibiotic Agents Used in 6 Acute Care Hospitals, 2009-2010: A Pragmatic Retrospective Observational Study. Infect Control Hosp Epidemiol. 2016 Jan;37(1):70-9. doi: 10.1017/ice.2015.226. Epub 2015 Oct 12.
- Magill SS, Edwards JR, Beldavs ZG, Dumyati G, Janelle SJ, Kainer MA, Lynfield R, Nadle J, Neuhauser MM, Ray SM, Richards K, Rodriguez R, Thompson DL, Fridkin SK; Emerging Infections Program Healthcare-Associated Infections and Antimicrobial Use Prevalence Survey Team. Prevalence of antimicrobial use in US acute care hospitals, May-September 2011. JAMA. 2014 Oct 8;312(14):1438-46. doi: 10.1001/jama.2014.12923.
- P.R. Yarnold, R.C. Soltysik, Maximizing Predictive Accuracy, ODA Books2016.
- P.R. Yarnold, R.C. Soltysik, Refining two-group multivariable classification models using univariate optimal discriminant analysis., Decision Sciences, 22 (1991) 1158-1164.
- Rhodes NJ, O'Donnell JN, Lizza BD, McLaughlin MM, Esterly JS, Scheetz MH. Tree-Based Models for Predicting Mortality in Gram-Negative Bacteremia: Avoid Putting the CART before the Horse. Antimicrob Agents Chemother. 2015 Nov 23;60(2):838-44. doi: 10.1128/AAC.01564-15. Print 2016 Feb.
- Rhodes NJ, Wagner JL, Gilbert EM, Crew PE, Davis SL, Scheetz MH. Days of Therapy and Antimicrobial Days: Similarities and Differences Between Consumption Metrics. Infect Control Hosp Epidemiol. 2016 Aug;37(8):971-973. doi: 10.1017/ice.2016.109. Epub 2016 May 13.
- Scheetz MH, Crew PE, Miglis C, Gilbert EM, Sutton SH, O'Donnell JN, Postelnick M, Zembower T, Rhodes NJ. Investigating the Extremes of Antibiotic Use with an Epidemiologic Framework. Antimicrob Agents Chemother. 2016 May 23;60(6):3265-9. doi: 10.1128/AAC.00572-16. Print 2016 Jun.
- The World Health Organization. Health Topics: Disease Outbreaks, 2015.
- MWU3004_STU00205629