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51. Development and Assessment of a Process to Describe the Timing of Antibiotic Changes in Adult Inpatients

BACKGROUND: Hospital antimicrobial stewardship programs (ASP) perform prospective audit and feedback to optimize use of antimicrobials; however, workflow inefficiency continues to be a distinct challenge. We developed a method to describe the volume and timing of antimicrobial changes to inform deci...

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Autores principales: Livengood, Spencer J, Drew, Richard H, Moehring, Rebekah W, Wilson, Dustin, Spivey, Justin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7777645/
http://dx.doi.org/10.1093/ofid/ofaa439.096
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author Livengood, Spencer J
Drew, Richard H
Moehring, Rebekah W
Wilson, Dustin
Spivey, Justin
author_facet Livengood, Spencer J
Drew, Richard H
Moehring, Rebekah W
Wilson, Dustin
Spivey, Justin
author_sort Livengood, Spencer J
collection PubMed
description BACKGROUND: Hospital antimicrobial stewardship programs (ASP) perform prospective audit and feedback to optimize use of antimicrobials; however, workflow inefficiency continues to be a distinct challenge. We developed a method to describe the volume and timing of antimicrobial changes to inform decisions on optimal timing of ASP review and intervention. METHODS: This retrospective study was performed at Duke University Hospital using anonymized antibiotic administration records from the DASON central database. Eligible antibiotic courses were administered to inpatients ≥ 18 years of age and had received ≥ 2 antibiotics administrations for ≥ 24 hours of treatment. A 2-month exploratory cohort (September to October 2017) was used to develop an antibiotic spectrum ranking (Table 1) and decision algorithm which was applied to a 1-year cohort (November 2017 to October 2018) for analysis of total change in antibiotic orders by day of the week. For each interval, the sum of antibiotic ranks was calculated and applied using specified definitions (Table 2) to determine the type of change occurring. The primary outcome was the number of total antibiotic changes that occurred on each day of the week. Secondary outcomes included the number and type (initiations, discontinuations, de-escalations, and escalations) of change. Descriptive statistics were used to describe the outcomes by day of the week. Table 1: Antibiotic Spectrum Ranking [Image: see text] Table 2: Key Definitions [Image: see text] RESULTS: The ranking and decision algorithm were applied to 16,993 unique antibiotic courses. Total changes occurred most on Wednesday (14,971, 16.2% [95% CI 15.7–17.1%]) and Friday (14,349, 15.6% [95% CI 15.0–16.2%]). Compared to intervals on weekdays (0.407 mean changes per patients on antibiotics [95% CI 0.401–0.413]), weekends had a lower number of changes (0.363 mean changes per patients on antibiotics [95% CI 0.349–0.377]). Initiations occurred most frequently on Tuesday (3,078, 18.1% [95% CI 16.3–19.9%]), and discontinuations on Wednesday (3,179, 18.7% [95% CI 17.4–20.5%]) (Figure 1). Figure 1: Types of Changes per Day [Image: see text] CONCLUSION: We developed and applied a method to characterize antimicrobial changes. In our institution, the reductions in the number of changes observed on weekends provide an opportunity for ASP involvement to be incorporated and help facilitate appropriate antimicrobial changes. DISCLOSURES: Rebekah W. Moehring, MD, MPH, Agency for Healthcare Quality and Research (Grant/Research Support)Centers for Disease Control and Prevention (Grant/Research Support)
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spelling pubmed-77776452021-01-07 51. Development and Assessment of a Process to Describe the Timing of Antibiotic Changes in Adult Inpatients Livengood, Spencer J Drew, Richard H Moehring, Rebekah W Wilson, Dustin Spivey, Justin Open Forum Infect Dis Poster Abstracts BACKGROUND: Hospital antimicrobial stewardship programs (ASP) perform prospective audit and feedback to optimize use of antimicrobials; however, workflow inefficiency continues to be a distinct challenge. We developed a method to describe the volume and timing of antimicrobial changes to inform decisions on optimal timing of ASP review and intervention. METHODS: This retrospective study was performed at Duke University Hospital using anonymized antibiotic administration records from the DASON central database. Eligible antibiotic courses were administered to inpatients ≥ 18 years of age and had received ≥ 2 antibiotics administrations for ≥ 24 hours of treatment. A 2-month exploratory cohort (September to October 2017) was used to develop an antibiotic spectrum ranking (Table 1) and decision algorithm which was applied to a 1-year cohort (November 2017 to October 2018) for analysis of total change in antibiotic orders by day of the week. For each interval, the sum of antibiotic ranks was calculated and applied using specified definitions (Table 2) to determine the type of change occurring. The primary outcome was the number of total antibiotic changes that occurred on each day of the week. Secondary outcomes included the number and type (initiations, discontinuations, de-escalations, and escalations) of change. Descriptive statistics were used to describe the outcomes by day of the week. Table 1: Antibiotic Spectrum Ranking [Image: see text] Table 2: Key Definitions [Image: see text] RESULTS: The ranking and decision algorithm were applied to 16,993 unique antibiotic courses. Total changes occurred most on Wednesday (14,971, 16.2% [95% CI 15.7–17.1%]) and Friday (14,349, 15.6% [95% CI 15.0–16.2%]). Compared to intervals on weekdays (0.407 mean changes per patients on antibiotics [95% CI 0.401–0.413]), weekends had a lower number of changes (0.363 mean changes per patients on antibiotics [95% CI 0.349–0.377]). Initiations occurred most frequently on Tuesday (3,078, 18.1% [95% CI 16.3–19.9%]), and discontinuations on Wednesday (3,179, 18.7% [95% CI 17.4–20.5%]) (Figure 1). Figure 1: Types of Changes per Day [Image: see text] CONCLUSION: We developed and applied a method to characterize antimicrobial changes. In our institution, the reductions in the number of changes observed on weekends provide an opportunity for ASP involvement to be incorporated and help facilitate appropriate antimicrobial changes. DISCLOSURES: Rebekah W. Moehring, MD, MPH, Agency for Healthcare Quality and Research (Grant/Research Support)Centers for Disease Control and Prevention (Grant/Research Support) Oxford University Press 2020-12-31 /pmc/articles/PMC7777645/ http://dx.doi.org/10.1093/ofid/ofaa439.096 Text en © The Author 2020. 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 Poster Abstracts
Livengood, Spencer J
Drew, Richard H
Moehring, Rebekah W
Wilson, Dustin
Spivey, Justin
51. Development and Assessment of a Process to Describe the Timing of Antibiotic Changes in Adult Inpatients
title 51. Development and Assessment of a Process to Describe the Timing of Antibiotic Changes in Adult Inpatients
title_full 51. Development and Assessment of a Process to Describe the Timing of Antibiotic Changes in Adult Inpatients
title_fullStr 51. Development and Assessment of a Process to Describe the Timing of Antibiotic Changes in Adult Inpatients
title_full_unstemmed 51. Development and Assessment of a Process to Describe the Timing of Antibiotic Changes in Adult Inpatients
title_short 51. Development and Assessment of a Process to Describe the Timing of Antibiotic Changes in Adult Inpatients
title_sort 51. development and assessment of a process to describe the timing of antibiotic changes in adult inpatients
topic Poster Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7777645/
http://dx.doi.org/10.1093/ofid/ofaa439.096
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