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293. Influence of a Pharmacist Led Treatment Algorithm for the Management of Staphylococcus Bacteremia
BACKGROUND: Staphylococcus bacteremia is a major healthcare burden and currently there is no widely recommended treatment algorithm. Our institution adopts all elements of antimicrobial stewardship including rapid diagnostic testing. Despite these efforts, management of staphylococcus bacteremia con...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7777304/ http://dx.doi.org/10.1093/ofid/ofaa439.336 |
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author | Lomanno, Jessica Elarabi, Salwa Fleisher, Jorge |
author_facet | Lomanno, Jessica Elarabi, Salwa Fleisher, Jorge |
author_sort | Lomanno, Jessica |
collection | PubMed |
description | BACKGROUND: Staphylococcus bacteremia is a major healthcare burden and currently there is no widely recommended treatment algorithm. Our institution adopts all elements of antimicrobial stewardship including rapid diagnostic testing. Despite these efforts, management of staphylococcus bacteremia continues to be problematic. The objective of this project is to evaluate implementation of a pharmacist-driven algorithm to guide treatment selection for staphylococcus bacteremia. METHODS: This is a single center, IRB-approved cohort study with a retrospective and prospective phase. The algorithm was designed in collaboration with the infectious disease (ID) service. Retrospective data was collected from June 2019 through September 2019. The algorithm was implemented on October 1, 2019 and prospective data was collected through January 2020. Prospectively a pharmacy resident identified positive blood cultures and recommended treatment based on the algorithm. Patients 18 years of age or older with a positive blood culture for staphylococcus were included. Patients were excluded if treatment was initiated at an outside hospital. The primary outcome is algorithm adherence. Secondary outcomes include days to negative blood culture, days to de-escalation, length of hospital stay and whether ID was consulted. Treatment Algorithm [Image: see text] RESULTS: A total of 64 patients were identified in the retrospective cohort and 46 in the intervention group. There were no significant differences in baseline characteristics. Algorithm adherence increased from 45% to 72% upon implementation (p=0.006). The algorithm resulted in a shorter time to de-escalation from 2.1 to 1.3 days (p=0.04). There were no statistically significant differences in days to negative blood culture, 2.3 vs. 2.2 days, or in average length of stay, 12.1 vs. 10.6 days in the retrospective and intervention groups, respectively. ID was consulted on 50% of patients in the retrospective cohort and 48% in the intervention group. CONCLUSION: Implementation of a staphylococcus bacteremia treatment algorithm optimizes management. Additional layers of pharmacy involvement also result in a shorter time to de-escalation. These results highlight the importance of continuity of antimicrobial stewardship efforts. DISCLOSURES: All Authors: No reported disclosures |
format | Online Article Text |
id | pubmed-7777304 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77773042021-01-07 293. Influence of a Pharmacist Led Treatment Algorithm for the Management of Staphylococcus Bacteremia Lomanno, Jessica Elarabi, Salwa Fleisher, Jorge Open Forum Infect Dis Poster Abstracts BACKGROUND: Staphylococcus bacteremia is a major healthcare burden and currently there is no widely recommended treatment algorithm. Our institution adopts all elements of antimicrobial stewardship including rapid diagnostic testing. Despite these efforts, management of staphylococcus bacteremia continues to be problematic. The objective of this project is to evaluate implementation of a pharmacist-driven algorithm to guide treatment selection for staphylococcus bacteremia. METHODS: This is a single center, IRB-approved cohort study with a retrospective and prospective phase. The algorithm was designed in collaboration with the infectious disease (ID) service. Retrospective data was collected from June 2019 through September 2019. The algorithm was implemented on October 1, 2019 and prospective data was collected through January 2020. Prospectively a pharmacy resident identified positive blood cultures and recommended treatment based on the algorithm. Patients 18 years of age or older with a positive blood culture for staphylococcus were included. Patients were excluded if treatment was initiated at an outside hospital. The primary outcome is algorithm adherence. Secondary outcomes include days to negative blood culture, days to de-escalation, length of hospital stay and whether ID was consulted. Treatment Algorithm [Image: see text] RESULTS: A total of 64 patients were identified in the retrospective cohort and 46 in the intervention group. There were no significant differences in baseline characteristics. Algorithm adherence increased from 45% to 72% upon implementation (p=0.006). The algorithm resulted in a shorter time to de-escalation from 2.1 to 1.3 days (p=0.04). There were no statistically significant differences in days to negative blood culture, 2.3 vs. 2.2 days, or in average length of stay, 12.1 vs. 10.6 days in the retrospective and intervention groups, respectively. ID was consulted on 50% of patients in the retrospective cohort and 48% in the intervention group. CONCLUSION: Implementation of a staphylococcus bacteremia treatment algorithm optimizes management. Additional layers of pharmacy involvement also result in a shorter time to de-escalation. These results highlight the importance of continuity of antimicrobial stewardship efforts. DISCLOSURES: All Authors: No reported disclosures Oxford University Press 2020-12-31 /pmc/articles/PMC7777304/ http://dx.doi.org/10.1093/ofid/ofaa439.336 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 Lomanno, Jessica Elarabi, Salwa Fleisher, Jorge 293. Influence of a Pharmacist Led Treatment Algorithm for the Management of Staphylococcus Bacteremia |
title | 293. Influence of a Pharmacist Led Treatment Algorithm for the Management of Staphylococcus Bacteremia |
title_full | 293. Influence of a Pharmacist Led Treatment Algorithm for the Management of Staphylococcus Bacteremia |
title_fullStr | 293. Influence of a Pharmacist Led Treatment Algorithm for the Management of Staphylococcus Bacteremia |
title_full_unstemmed | 293. Influence of a Pharmacist Led Treatment Algorithm for the Management of Staphylococcus Bacteremia |
title_short | 293. Influence of a Pharmacist Led Treatment Algorithm for the Management of Staphylococcus Bacteremia |
title_sort | 293. influence of a pharmacist led treatment algorithm for the management of staphylococcus bacteremia |
topic | Poster Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7777304/ http://dx.doi.org/10.1093/ofid/ofaa439.336 |
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