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2000. Utilization of a ‘Never Event’ Framework to Classify Antimicrobial Appropriateness
BACKGROUND: Contemporary strategies can be leveraged to predict antimicrobial overuse, yet little information is gained on the appropriateness of antibiotics prescribed. Classifying appropriateness is complicated by the lack of a standard definition for appropriateness. Thus, we created and implemen...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6809449/ http://dx.doi.org/10.1093/ofid/ofz360.1680 |
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author | Liu, Jiajun Mercuro, Nicholas Davis, Susan L Yarnold, Paul Patel, Twisha S Petty, Lindsay A Pais, Gwendolyn M Kaye, Keith S Scheetz, Marc H |
author_facet | Liu, Jiajun Mercuro, Nicholas Davis, Susan L Yarnold, Paul Patel, Twisha S Petty, Lindsay A Pais, Gwendolyn M Kaye, Keith S Scheetz, Marc H |
author_sort | Liu, Jiajun |
collection | PubMed |
description | BACKGROUND: Contemporary strategies can be leveraged to predict antimicrobial overuse, yet little information is gained on the appropriateness of antibiotics prescribed. Classifying appropriateness is complicated by the lack of a standard definition for appropriateness. Thus, we created and implemented a novel ‘antibiotic never event’ (NE) framework to systematically classify the most inappropriate usages of vancomycin and correlated these NE to abnormal consumption trends (i.e., antibiotic outbreaks). METHODS: Vancomycin use was categorized by an algorithm using data query from the electronic medical records. Extracted data included vancomycin use, relevant patient demographics, and microbiological data. Electronic classifications placed each vancomycin therapy into type 1 (use for non-susceptible organism after susceptibility finalization) or type 2 (use exceeding 48h after susceptibility report when a safe de-escalation is possible) NE. Patients were categorized as cases or controls (no NE) at Northwestern Memorial Hospital (NM) and Henry Ford Hospital (HF) between January 2014 and October 2017. A manual chart review was performed. Sensitivity (SEN), specificity (SPEC), PPV, and NPV were calculated for NE prediction. Vancomycin use was quantified during the same period. Linear models with prediction intervals (PI) were generated to identify potential outbreaks, which were linked to monthly NE counts defined as a binary factor. RESULTS: A total of 220 NE cases were electronically identified for vancomycin at NM (n = 197) and HF (n = 23). Random cases were matched 1:1 (NM = 200) and 1:5 (HF = 115) to controls for manual review. At NM and HF, 35 and 24 true positives were identified, respectively. Thus, overall SEN and SPEC were 93.7% and 75.1% and PPV and NPV were 45.7% and 98.1%, respectively. Linear models revealed 11 potential outbreak periods at HF and 5 at NM. A PI of 80% showed a combined SEN below 10% and SPEC above 90%, respectively. CONCLUSION: The methodology was generalizable across two centers. In the pilot review, our method was highly sensitive and an effective screening tool for NE identification. Antibiotic consumption trends did not correlate with NE. In summary, the NE classification was sensitive in assessment of antibiotic appropriateness, whereas consumption alone does not predict NE. DISCLOSURES: All authors: No reported disclosures. |
format | Online Article Text |
id | pubmed-6809449 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-68094492019-10-28 2000. Utilization of a ‘Never Event’ Framework to Classify Antimicrobial Appropriateness Liu, Jiajun Mercuro, Nicholas Davis, Susan L Yarnold, Paul Patel, Twisha S Petty, Lindsay A Pais, Gwendolyn M Kaye, Keith S Scheetz, Marc H Open Forum Infect Dis Abstracts BACKGROUND: Contemporary strategies can be leveraged to predict antimicrobial overuse, yet little information is gained on the appropriateness of antibiotics prescribed. Classifying appropriateness is complicated by the lack of a standard definition for appropriateness. Thus, we created and implemented a novel ‘antibiotic never event’ (NE) framework to systematically classify the most inappropriate usages of vancomycin and correlated these NE to abnormal consumption trends (i.e., antibiotic outbreaks). METHODS: Vancomycin use was categorized by an algorithm using data query from the electronic medical records. Extracted data included vancomycin use, relevant patient demographics, and microbiological data. Electronic classifications placed each vancomycin therapy into type 1 (use for non-susceptible organism after susceptibility finalization) or type 2 (use exceeding 48h after susceptibility report when a safe de-escalation is possible) NE. Patients were categorized as cases or controls (no NE) at Northwestern Memorial Hospital (NM) and Henry Ford Hospital (HF) between January 2014 and October 2017. A manual chart review was performed. Sensitivity (SEN), specificity (SPEC), PPV, and NPV were calculated for NE prediction. Vancomycin use was quantified during the same period. Linear models with prediction intervals (PI) were generated to identify potential outbreaks, which were linked to monthly NE counts defined as a binary factor. RESULTS: A total of 220 NE cases were electronically identified for vancomycin at NM (n = 197) and HF (n = 23). Random cases were matched 1:1 (NM = 200) and 1:5 (HF = 115) to controls for manual review. At NM and HF, 35 and 24 true positives were identified, respectively. Thus, overall SEN and SPEC were 93.7% and 75.1% and PPV and NPV were 45.7% and 98.1%, respectively. Linear models revealed 11 potential outbreak periods at HF and 5 at NM. A PI of 80% showed a combined SEN below 10% and SPEC above 90%, respectively. CONCLUSION: The methodology was generalizable across two centers. In the pilot review, our method was highly sensitive and an effective screening tool for NE identification. Antibiotic consumption trends did not correlate with NE. In summary, the NE classification was sensitive in assessment of antibiotic appropriateness, whereas consumption alone does not predict NE. DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2019-10-23 /pmc/articles/PMC6809449/ http://dx.doi.org/10.1093/ofid/ofz360.1680 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Abstracts Liu, Jiajun Mercuro, Nicholas Davis, Susan L Yarnold, Paul Patel, Twisha S Petty, Lindsay A Pais, Gwendolyn M Kaye, Keith S Scheetz, Marc H 2000. Utilization of a ‘Never Event’ Framework to Classify Antimicrobial Appropriateness |
title | 2000. Utilization of a ‘Never Event’ Framework to Classify Antimicrobial Appropriateness |
title_full | 2000. Utilization of a ‘Never Event’ Framework to Classify Antimicrobial Appropriateness |
title_fullStr | 2000. Utilization of a ‘Never Event’ Framework to Classify Antimicrobial Appropriateness |
title_full_unstemmed | 2000. Utilization of a ‘Never Event’ Framework to Classify Antimicrobial Appropriateness |
title_short | 2000. Utilization of a ‘Never Event’ Framework to Classify Antimicrobial Appropriateness |
title_sort | 2000. utilization of a ‘never event’ framework to classify antimicrobial appropriateness |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6809449/ http://dx.doi.org/10.1093/ofid/ofz360.1680 |
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