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Impact of different COVID-19 encounter definitions on antibiotic prescribing rates in urgent care

Background: Billing data have been used in the outpatient setting to identify targets for antimicrobial stewardship. However, COVID-19 ICD-10 codes are new, and the validity of using COVID-19 ICD-10 codes to accurately identify COVID-19 encounters is unknown. We investigated COVID-19 ICD-10 utilizat...

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Autores principales: Onguti, Sharon, Ha, David, Mui, Emily, Chang, Amy, Stenehjem, Eddie, Hersh, Adam, Holubar, Marisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614951/
http://dx.doi.org/10.1017/ash.2022.63
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author Onguti, Sharon
Ha, David
Mui, Emily
Chang, Amy
Stenehjem, Eddie
Hersh, Adam
Holubar, Marisa
author_facet Onguti, Sharon
Ha, David
Mui, Emily
Chang, Amy
Stenehjem, Eddie
Hersh, Adam
Holubar, Marisa
author_sort Onguti, Sharon
collection PubMed
description Background: Billing data have been used in the outpatient setting to identify targets for antimicrobial stewardship. However, COVID-19 ICD-10 codes are new, and the validity of using COVID-19 ICD-10 codes to accurately identify COVID-19 encounters is unknown. We investigated COVID-19 ICD-10 utilization in our urgent care clinics during the pandemic and the impact of using different COVID-19 encounter definitions on antibiotic prescribing rates (APRs). Methods: We included all telemedicine and office visits at 2 academic urgent-care clinics from January 2020 to September 2021. We extracted ICD-10 encounter codes and testing data from the electronic medical record. We compared encounters for which COVID-19 ICD-10 codes were present with encounters for which SARS-CoV-2 nucleic acid amplification testing (NAAT) was performed within 5 days of and up to 2 days after the encounter (Fig. 1). We calculated the sensitivity of the use of COVID-19 ICD-10 codes against a positive NAAT. We calculated the APR as the proportion of encounters in which an antibacterial drug was prescribed. This quality improvement project was deemed non–human-subjects research by the Stanford Panel on Human Subjects in Medical Research. Funding: None Disclosures: None
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spelling pubmed-96149512022-10-29 Impact of different COVID-19 encounter definitions on antibiotic prescribing rates in urgent care Onguti, Sharon Ha, David Mui, Emily Chang, Amy Stenehjem, Eddie Hersh, Adam Holubar, Marisa Antimicrob Steward Healthc Epidemiol Antibiotic Stewardship Background: Billing data have been used in the outpatient setting to identify targets for antimicrobial stewardship. However, COVID-19 ICD-10 codes are new, and the validity of using COVID-19 ICD-10 codes to accurately identify COVID-19 encounters is unknown. We investigated COVID-19 ICD-10 utilization in our urgent care clinics during the pandemic and the impact of using different COVID-19 encounter definitions on antibiotic prescribing rates (APRs). Methods: We included all telemedicine and office visits at 2 academic urgent-care clinics from January 2020 to September 2021. We extracted ICD-10 encounter codes and testing data from the electronic medical record. We compared encounters for which COVID-19 ICD-10 codes were present with encounters for which SARS-CoV-2 nucleic acid amplification testing (NAAT) was performed within 5 days of and up to 2 days after the encounter (Fig. 1). We calculated the sensitivity of the use of COVID-19 ICD-10 codes against a positive NAAT. We calculated the APR as the proportion of encounters in which an antibacterial drug was prescribed. This quality improvement project was deemed non–human-subjects research by the Stanford Panel on Human Subjects in Medical Research. Funding: None Disclosures: None Cambridge University Press 2022-05-16 /pmc/articles/PMC9614951/ http://dx.doi.org/10.1017/ash.2022.63 Text en © The Society for Healthcare Epidemiology of America 2022 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Antibiotic Stewardship
Onguti, Sharon
Ha, David
Mui, Emily
Chang, Amy
Stenehjem, Eddie
Hersh, Adam
Holubar, Marisa
Impact of different COVID-19 encounter definitions on antibiotic prescribing rates in urgent care
title Impact of different COVID-19 encounter definitions on antibiotic prescribing rates in urgent care
title_full Impact of different COVID-19 encounter definitions on antibiotic prescribing rates in urgent care
title_fullStr Impact of different COVID-19 encounter definitions on antibiotic prescribing rates in urgent care
title_full_unstemmed Impact of different COVID-19 encounter definitions on antibiotic prescribing rates in urgent care
title_short Impact of different COVID-19 encounter definitions on antibiotic prescribing rates in urgent care
title_sort impact of different covid-19 encounter definitions on antibiotic prescribing rates in urgent care
topic Antibiotic Stewardship
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614951/
http://dx.doi.org/10.1017/ash.2022.63
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