Trends in and Predictors of Carbapenem Consumption across North American Hospitals : Results from a Multicenter Survey by the MAD-ID Research Network
Copyright © 2019 American Society for Microbiology..
We sought to define trends in and predictors of carbapenem consumption across community, teaching, and university-affiliated hospitals in the United States and Canada. We conducted a retrospective multicenter survey of carbapenem and broad-spectrum noncarbapenem beta-lactam consumption between January 2011 and December 2013. Consumption was tabulated as defined daily doses (DDD) or as days of therapy (DOT) per 1,000 patient days (PD). Multivariate mixed-effects models were explored, and final model goodness of fit was assessed by regressions of observed versus predicted values and residual distributions. A total of 20 acute-care hospitals responded. The centers treated adult patients (n = 19/20) and pediatric/neonatal patients (n = 17/20). The majority of the centers were nonprofit (n = 17/20) and not affiliated with medical/teaching institutions (n = 11/20). The median (interquartile range [IQR]) carbapenem consumption rates were 38.8 (17.4 to 95.7) DDD/1,000 PD and 29.7 (19.2 to 40.1) DOT/1,000 PD overall. Carbapenem consumption was well described by a multivariate linear mixed-effects model (fixed effects, R2 = 0.792; fixed plus random effects, R2 = 0.974). Carbapenem consumption increased by 1.91-fold/quarter from 48.6 DDD/1,000 PD (P = 0.004) and by 0.056-fold/quarter from 45.7 DOT/1,000 PD (P = 0.93) over the study period. Noncarbapenem consumption was independently related to increasing carbapenem consumption (beta = 0.31 for increasing noncarbapenem beta-lactam consumption; P < 0.001). Regular antibiogram publication and promotion of conversion from intravenous (i.v.) to oral (p.o.) administration independently affected carbapenem consumption rates. In the final model, 58.5% of the observed variance in consumption was attributable to between-hospital differences. Rates of carbapenem consumption across 20 North American hospitals differed greatly, and the observed differences were correlated with hospital-specific demographics. Additional studies focusing on the drivers of hospital-specific carbapenem consumption are needed to determine whether these rates are justifiable.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2019 |
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| Erschienen: |
2019 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:63 |
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| Enthalten in: |
Antimicrobial agents and chemotherapy - 63(2019), 7 vom: 15. Juli |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Rhodes, Nathaniel J [VerfasserIn] |
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| Links: |
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| Themen: |
Anti-Bacterial Agents |
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| Anmerkungen: |
Date Completed 07.05.2020 Date Revised 07.05.2020 published: Electronic-Print Citation Status MEDLINE |
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| doi: |
10.1128/AAC.00327-19 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 100 | 1 | |a Rhodes, Nathaniel J |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Trends in and Predictors of Carbapenem Consumption across North American Hospitals |b Results from a Multicenter Survey by the MAD-ID Research Network |
| 264 | 1 | |c 2019 | |
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| 500 | |a Date Completed 07.05.2020 | ||
| 500 | |a Date Revised 07.05.2020 | ||
| 500 | |a published: Electronic-Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2019 American Society for Microbiology. | ||
| 520 | |a We sought to define trends in and predictors of carbapenem consumption across community, teaching, and university-affiliated hospitals in the United States and Canada. We conducted a retrospective multicenter survey of carbapenem and broad-spectrum noncarbapenem beta-lactam consumption between January 2011 and December 2013. Consumption was tabulated as defined daily doses (DDD) or as days of therapy (DOT) per 1,000 patient days (PD). Multivariate mixed-effects models were explored, and final model goodness of fit was assessed by regressions of observed versus predicted values and residual distributions. A total of 20 acute-care hospitals responded. The centers treated adult patients (n = 19/20) and pediatric/neonatal patients (n = 17/20). The majority of the centers were nonprofit (n = 17/20) and not affiliated with medical/teaching institutions (n = 11/20). The median (interquartile range [IQR]) carbapenem consumption rates were 38.8 (17.4 to 95.7) DDD/1,000 PD and 29.7 (19.2 to 40.1) DOT/1,000 PD overall. Carbapenem consumption was well described by a multivariate linear mixed-effects model (fixed effects, R2 = 0.792; fixed plus random effects, R2 = 0.974). Carbapenem consumption increased by 1.91-fold/quarter from 48.6 DDD/1,000 PD (P = 0.004) and by 0.056-fold/quarter from 45.7 DOT/1,000 PD (P = 0.93) over the study period. Noncarbapenem consumption was independently related to increasing carbapenem consumption (beta = 0.31 for increasing noncarbapenem beta-lactam consumption; P < 0.001). Regular antibiogram publication and promotion of conversion from intravenous (i.v.) to oral (p.o.) administration independently affected carbapenem consumption rates. In the final model, 58.5% of the observed variance in consumption was attributable to between-hospital differences. Rates of carbapenem consumption across 20 North American hospitals differed greatly, and the observed differences were correlated with hospital-specific demographics. Additional studies focusing on the drivers of hospital-specific carbapenem consumption are needed to determine whether these rates are justifiable | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Multicenter Study | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a antimicrobial stewardship | |
| 650 | 4 | |a beta-lactams | |
| 650 | 4 | |a consumption | |
| 650 | 4 | |a epidemiology | |
| 650 | 4 | |a pharmacoeconometrics | |
| 650 | 7 | |a Anti-Bacterial Agents |2 NLM | |
| 650 | 7 | |a Carbapenems |2 NLM | |
| 700 | 1 | |a Wagner, Jamie L |e verfasserin |4 aut | |
| 700 | 1 | |a Davis, Susan L |e verfasserin |4 aut | |
| 700 | 1 | |a Bosso, John A |e verfasserin |4 aut | |
| 700 | 1 | |a Goff, Debra A |e verfasserin |4 aut | |
| 700 | 1 | |a Rybak, Michael J |e verfasserin |4 aut | |
| 700 | 1 | |a Scheetz, Marc H |e verfasserin |4 aut | |
| 700 | 0 | |a MAD-ID Research Network |e verfasserin |4 aut | |
| 700 | 1 | |a Zimmer, Drew |e investigator |4 oth | |
| 700 | 1 | |a Edwards, Jonathan |e investigator |4 oth | |
| 700 | 1 | |a Barnes, Vicki |e investigator |4 oth | |
| 700 | 1 | |a Rooks, Christy |e investigator |4 oth | |
| 700 | 1 | |a Womack, Tanea |e investigator |4 oth | |
| 700 | 1 | |a Chastain, Daniel |e investigator |4 oth | |
| 700 | 1 | |a Jacob, Jesse |e investigator |4 oth | |
| 700 | 1 | |a Wong, Jordan |e investigator |4 oth | |
| 700 | 1 | |a Kandiah, Sheetal |e investigator |4 oth | |
| 700 | 1 | |a Kenney, Rachel |e investigator |4 oth | |
| 700 | 1 | |a Wardlow, Lynn |e investigator |4 oth | |
| 700 | 1 | |a Patel, Sonal |e investigator |4 oth | |
| 700 | 1 | |a Sorenson, Carrie |e investigator |4 oth | |
| 700 | 1 | |a Galbraith, Joan |e investigator |4 oth | |
| 700 | 1 | |a Monteforte, Melinda |e investigator |4 oth | |
| 700 | 1 | |a Annette, Brady |e investigator |4 oth | |
| 700 | 1 | |a Debra, Boswell |e investigator |4 oth | |
| 700 | 1 | |a Chapple, Kevin |e investigator |4 oth | |
| 700 | 1 | |a Cubick, Edward |e investigator |4 oth | |
| 700 | 1 | |a Morita, Kazumi |e investigator |4 oth | |
| 700 | 1 | |a Mohamed, Yasser |e investigator |4 oth | |
| 700 | 1 | |a Kisgen, Jamie |e investigator |4 oth | |
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