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A quasi-experimental analysis comparing antimicrobial usage on COVID-19 and non-COVID-19 wards
To describe antimicrobial usage (AMU) trends before and during the coronavirus disease 2019 (COVID-19) pandemic, between COVID-19 and non-COVID-19 wards, and if there was any association with a COVID-19 order set. Quasi-experimental retrospective interrupted time series analysis of AMU rates with a...
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Published in: | Antimicrobial stewardship & healthcare epidemiology : ASHE 2024, Vol.4 (1), p.e192, Article e192 |
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creator | Doyle, Daniel Dalton, Bruce Zhang, Zuying Sabuda, Deana Rajakumar, Irina Rennert-May, Elissa Leal, Jenine Conly, John M |
description | To describe antimicrobial usage (AMU) trends before and during the coronavirus disease 2019 (COVID-19) pandemic, between COVID-19 and non-COVID-19 wards, and if there was any association with a COVID-19 order set.
Quasi-experimental retrospective interrupted time series analysis of AMU rates with a contemporaneous comparison of COVID-19 versus non-COVID-19 control wards. Analysis using incidence rate ratios (IRR) was conducted using a Poisson regression generalized linear model.
Five COVID-19 and 4 comparable non-COVID-19 wards and 6 intensive care units (ICUs) at 4 hospitals during pandemic waves 1-4.
All inpatients receiving systemic antimicrobials.
The COVID-19 checkbox antimicrobial order set was implemented in March 2020, to be used only if considered clinically indicated with modification in August 2021.
The primary outcome was a change in AMU rates (defined daily dose per 100 patient days per month) comparing pre- versus peri-pandemic periods and COVID-19 versus control non-COVID-19 wards. Secondary outcomes included antifungal usage rate in ICUs and assessing AMUs following implementation and modification of a COVID-19 order set.
Significantly greater rates of AMU (IRR[95%CI]) were observed on COVID-19 wards versus non-COVID-19 wards during waves 1-4 for all systemic antimicrobials (1.76[1.71-1.81], 1.10[1.07-1.13], 1.48[1.43-1.53], and 1.06[1.03-1.09]); for azithromycin (11.76[9.80-14.23], 10.96[9.49-12.74], 12.41[10.73-14.45], and 4.88[4.31-5.55]); and for ceftriaxone (2.39[2.16-2.65], 3.64[3.29-4.03], 2.94[2.67-3.23], and 1.62[1.49-1.76]).
We observed significantly increased AMU rates of all systemic agents during the first 4 waves of the pandemic and on COVID-19 wards compared with control wards for azithromycin and ceftriaxone. These agents saw a twofold reduction following order-set removal, suggesting that the clinical decision-support tool order set, as utilized, had influenced prescribing behavior. |
doi_str_mv | 10.1017/ash.2024.417 |
format | article |
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Quasi-experimental retrospective interrupted time series analysis of AMU rates with a contemporaneous comparison of COVID-19 versus non-COVID-19 control wards. Analysis using incidence rate ratios (IRR) was conducted using a Poisson regression generalized linear model.
Five COVID-19 and 4 comparable non-COVID-19 wards and 6 intensive care units (ICUs) at 4 hospitals during pandemic waves 1-4.
All inpatients receiving systemic antimicrobials.
The COVID-19 checkbox antimicrobial order set was implemented in March 2020, to be used only if considered clinically indicated with modification in August 2021.
The primary outcome was a change in AMU rates (defined daily dose per 100 patient days per month) comparing pre- versus peri-pandemic periods and COVID-19 versus control non-COVID-19 wards. Secondary outcomes included antifungal usage rate in ICUs and assessing AMUs following implementation and modification of a COVID-19 order set.
Significantly greater rates of AMU (IRR[95%CI]) were observed on COVID-19 wards versus non-COVID-19 wards during waves 1-4 for all systemic antimicrobials (1.76[1.71-1.81], 1.10[1.07-1.13], 1.48[1.43-1.53], and 1.06[1.03-1.09]); for azithromycin (11.76[9.80-14.23], 10.96[9.49-12.74], 12.41[10.73-14.45], and 4.88[4.31-5.55]); and for ceftriaxone (2.39[2.16-2.65], 3.64[3.29-4.03], 2.94[2.67-3.23], and 1.62[1.49-1.76]).
We observed significantly increased AMU rates of all systemic agents during the first 4 waves of the pandemic and on COVID-19 wards compared with control wards for azithromycin and ceftriaxone. These agents saw a twofold reduction following order-set removal, suggesting that the clinical decision-support tool order set, as utilized, had influenced prescribing behavior.</description><identifier>ISSN: 2732-494X</identifier><identifier>EISSN: 2732-494X</identifier><identifier>DOI: 10.1017/ash.2024.417</identifier><identifier>PMID: 39483329</identifier><language>eng</language><publisher>England: Cambridge University Press</publisher><subject>Antimicrobial agents ; COVID-19 ; Ethics ; Generalized linear models ; Hospitalists ; Hospitals ; Intensive care ; Original ; Pandemics ; Patients ; Severe acute respiratory syndrome coronavirus 2 ; Systematic review ; Time series ; Viral infections</subject><ispartof>Antimicrobial stewardship & healthcare epidemiology : ASHE, 2024, Vol.4 (1), p.e192, Article e192</ispartof><rights>Cambridge University Press 2024.</rights><rights>The Author(s), 2024. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America. This work is licensed under the Creative Commons Attribution License 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, provided the original article is properly cited. (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Cambridge University Press 2024 2024 Cambridge University Press</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c366t-70cc32b58a092f4749681751a0296faa8526ad618f078384caf74db69f92d4583</cites><orcidid>0000-0003-4666-8391 ; 0000-0002-3348-0157 ; 0000-0001-9884-6423 ; 0000-0002-0308-4890</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3122465924/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3122465924?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,4024,25753,27923,27924,27925,37012,37013,38516,43895,44590,53791,53793,74412,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39483329$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Doyle, Daniel</creatorcontrib><creatorcontrib>Dalton, Bruce</creatorcontrib><creatorcontrib>Zhang, Zuying</creatorcontrib><creatorcontrib>Sabuda, Deana</creatorcontrib><creatorcontrib>Rajakumar, Irina</creatorcontrib><creatorcontrib>Rennert-May, Elissa</creatorcontrib><creatorcontrib>Leal, Jenine</creatorcontrib><creatorcontrib>Conly, John M</creatorcontrib><title>A quasi-experimental analysis comparing antimicrobial usage on COVID-19 and non-COVID-19 wards</title><title>Antimicrobial stewardship & healthcare epidemiology : ASHE</title><addtitle>Antimicrob Steward Healthc Epidemiol</addtitle><description>To describe antimicrobial usage (AMU) trends before and during the coronavirus disease 2019 (COVID-19) pandemic, between COVID-19 and non-COVID-19 wards, and if there was any association with a COVID-19 order set.
Quasi-experimental retrospective interrupted time series analysis of AMU rates with a contemporaneous comparison of COVID-19 versus non-COVID-19 control wards. Analysis using incidence rate ratios (IRR) was conducted using a Poisson regression generalized linear model.
Five COVID-19 and 4 comparable non-COVID-19 wards and 6 intensive care units (ICUs) at 4 hospitals during pandemic waves 1-4.
All inpatients receiving systemic antimicrobials.
The COVID-19 checkbox antimicrobial order set was implemented in March 2020, to be used only if considered clinically indicated with modification in August 2021.
The primary outcome was a change in AMU rates (defined daily dose per 100 patient days per month) comparing pre- versus peri-pandemic periods and COVID-19 versus control non-COVID-19 wards. Secondary outcomes included antifungal usage rate in ICUs and assessing AMUs following implementation and modification of a COVID-19 order set.
Significantly greater rates of AMU (IRR[95%CI]) were observed on COVID-19 wards versus non-COVID-19 wards during waves 1-4 for all systemic antimicrobials (1.76[1.71-1.81], 1.10[1.07-1.13], 1.48[1.43-1.53], and 1.06[1.03-1.09]); for azithromycin (11.76[9.80-14.23], 10.96[9.49-12.74], 12.41[10.73-14.45], and 4.88[4.31-5.55]); and for ceftriaxone (2.39[2.16-2.65], 3.64[3.29-4.03], 2.94[2.67-3.23], and 1.62[1.49-1.76]).
We observed significantly increased AMU rates of all systemic agents during the first 4 waves of the pandemic and on COVID-19 wards compared with control wards for azithromycin and ceftriaxone. These agents saw a twofold reduction following order-set removal, suggesting that the clinical decision-support tool order set, as utilized, had influenced prescribing behavior.</description><subject>Antimicrobial agents</subject><subject>COVID-19</subject><subject>Ethics</subject><subject>Generalized linear models</subject><subject>Hospitalists</subject><subject>Hospitals</subject><subject>Intensive care</subject><subject>Original</subject><subject>Pandemics</subject><subject>Patients</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>Systematic review</subject><subject>Time series</subject><subject>Viral infections</subject><issn>2732-494X</issn><issn>2732-494X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>COVID</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdks1v1DAQxS0EotXSG2cUiQsHsvj744SqhcJKlXoBxAlr4jhbr5J4aydA__t6u2XVchpr5qeneeOH0GuClwQT9QHy9ZJiypecqGfolCpGa274z-eP3ifoLOctxphqgpVRL9EJM1wzRs0p-nVe3cyQQ-3_7nwKgx8n6CsYob_NIVcuDjtIYdyU1hSG4FJsQgHmDBtfxbFaXf1Yf6qJKfO2GuNYHxt_ILX5FXrRQZ_92UNdoO8Xn7-tvtaXV1_Wq_PL2jEpp1ph5xhthAZsaMcVN1ITJQhgamQHoAWV0EqiO6w009xBp3jbSNMZ2nKh2QKtD7pthK3dFSOQbm2EYO8bMW0spCm43lvuhTZMYUE85bxoNKIjDZUO01aAwUXr40FrNzeDb105SYL-iejTyRiu7Sb-toSUNYneK7x7UEjxZvZ5skPIzvc9jD7O2TJCGS4mS1mgt_-h2zincv57inIpDOWFen-gyv1zTr47bkOw3QfBliDYfRBsCULB3zx2cIT_fTu7A1nxq4E</recordid><startdate>2024</startdate><enddate>2024</enddate><creator>Doyle, Daniel</creator><creator>Dalton, Bruce</creator><creator>Zhang, Zuying</creator><creator>Sabuda, Deana</creator><creator>Rajakumar, Irina</creator><creator>Rennert-May, Elissa</creator><creator>Leal, Jenine</creator><creator>Conly, John M</creator><general>Cambridge University Press</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M0T</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-4666-8391</orcidid><orcidid>https://orcid.org/0000-0002-3348-0157</orcidid><orcidid>https://orcid.org/0000-0001-9884-6423</orcidid><orcidid>https://orcid.org/0000-0002-0308-4890</orcidid></search><sort><creationdate>2024</creationdate><title>A quasi-experimental analysis comparing antimicrobial usage on COVID-19 and non-COVID-19 wards</title><author>Doyle, Daniel ; 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Quasi-experimental retrospective interrupted time series analysis of AMU rates with a contemporaneous comparison of COVID-19 versus non-COVID-19 control wards. Analysis using incidence rate ratios (IRR) was conducted using a Poisson regression generalized linear model.
Five COVID-19 and 4 comparable non-COVID-19 wards and 6 intensive care units (ICUs) at 4 hospitals during pandemic waves 1-4.
All inpatients receiving systemic antimicrobials.
The COVID-19 checkbox antimicrobial order set was implemented in March 2020, to be used only if considered clinically indicated with modification in August 2021.
The primary outcome was a change in AMU rates (defined daily dose per 100 patient days per month) comparing pre- versus peri-pandemic periods and COVID-19 versus control non-COVID-19 wards. Secondary outcomes included antifungal usage rate in ICUs and assessing AMUs following implementation and modification of a COVID-19 order set.
Significantly greater rates of AMU (IRR[95%CI]) were observed on COVID-19 wards versus non-COVID-19 wards during waves 1-4 for all systemic antimicrobials (1.76[1.71-1.81], 1.10[1.07-1.13], 1.48[1.43-1.53], and 1.06[1.03-1.09]); for azithromycin (11.76[9.80-14.23], 10.96[9.49-12.74], 12.41[10.73-14.45], and 4.88[4.31-5.55]); and for ceftriaxone (2.39[2.16-2.65], 3.64[3.29-4.03], 2.94[2.67-3.23], and 1.62[1.49-1.76]).
We observed significantly increased AMU rates of all systemic agents during the first 4 waves of the pandemic and on COVID-19 wards compared with control wards for azithromycin and ceftriaxone. These agents saw a twofold reduction following order-set removal, suggesting that the clinical decision-support tool order set, as utilized, had influenced prescribing behavior.</abstract><cop>England</cop><pub>Cambridge University Press</pub><pmid>39483329</pmid><doi>10.1017/ash.2024.417</doi><orcidid>https://orcid.org/0000-0003-4666-8391</orcidid><orcidid>https://orcid.org/0000-0002-3348-0157</orcidid><orcidid>https://orcid.org/0000-0001-9884-6423</orcidid><orcidid>https://orcid.org/0000-0002-0308-4890</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Antimicrobial agents COVID-19 Ethics Generalized linear models Hospitalists Hospitals Intensive care Original Pandemics Patients Severe acute respiratory syndrome coronavirus 2 Systematic review Time series Viral infections |
title | A quasi-experimental analysis comparing antimicrobial usage on COVID-19 and non-COVID-19 wards |
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