scholarly journals Has the COVID-19 pandemic wiped out the seasonality of outpatient antibiotic use and influenza activity? A time-series analysis from 2014 to 2021

2022 ◽  
Author(s):  
Ana Belén Guisado-Gil ◽  
Regina Sandra Benavente ◽  
Román Villegas-Portero ◽  
María Victoria Gil-Navarro ◽  
Raquel Valencia ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Antibiotic Use ◽  
Series Analysis ◽  
Influenza Activity

scholarly journals Impact of Removal of Automatic 7-Day Stop Orders for Inpatient Antimicrobials

2020 ◽  
Vol 41 (S1) ◽  
pp. s264-s265
Author(s):  
Afia Adu-Gyamfi ◽  
Keith Hamilton ◽  
Leigh Cressman ◽  
Ebbing Lautenbach ◽  
Lauren Dutcher
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Antibiotic Use ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Treatment Interruptions ◽  
Days Of Therapy ◽  
Quasi Experimental ◽  
The Impact

Background: Automatic discontinuation of antimicrobial orders after a prespecified duration of therapy has been adopted as a strategy for reducing excess days of therapy (DOT) as part of antimicrobial stewardship efforts. Automatic stop orders have been shown to decrease antimicrobial DOT. However, inadvertent treatment interruptions may occur as a result, potentially contributing to adverse patient outcomes. To evaluate the effects of this practice, we examined the impact of the removal of an electronic 7-day ASO program on hospitalized patients. Methods: We performed a quasi-experimental study on inpatients in 3 acute-care academic hospitals. In the preintervention period (automatic stop orders present; January 1, 2016, to February 28, 2017), we had an electronic dashboard to identify and intervene on unintentionally missed doses. In the postintervention period (April 1, 2017, to March 31, 2018), the automatic stop orders were removed. We compared the primary outcome, DOT per 1,000 patient days (PD) per month, for patients in the automatic stop orders present and absent periods. The Wilcoxon rank-sum test was used to compare median monthly DOT/1,000 PD. Interrupted time series analysis (Prais-Winsten model) was used to compared trends in antibiotic DOT/1,000 PD and the immediate impact of the automatic stop order removal. Manual chart review on a subset of 300 patients, equally divided between the 2 periods, was performed to assess for unintentionally missed doses. Results: In the automatic stop order period, a monthly median of 644.5 antibiotic DOT/1,000 PD were administered, compared to 686.2 DOT/1,000 PD in the period without automatic stop orders (P < .001) (Fig. 1). Using interrupted time series analysis, there was a nonsignificant increase by 46.7 DOT/1,000 PD (95% CI, 40.8 to 134.3) in the month immediately following removal of automatic stop orders (P = .28) (Fig. 2). Even though the slope representing monthly change in DOT/1,000 PD increased in the period without automatic stop orders compared to the period with automatic stop orders, it was not statistically significant (P = .41). Manual chart abstraction revealed that in the period with automatic stop orders, 9 of 150 patients had 17 unintentionally missed days of therapy, whereas none (of 150 patients) in the period without automatic stop orders did. Conclusions: Following removal of the automatic stop orders, there was an overall increase in antibiotic use, although the change in monthly trend of antibiotic use was not significantly different. Even with a dashboard to identify missed doses, there was still a risk of unintentionally missed doses in the period with automatic stop orders. Therefore, this risk should be weighed against the modest difference in antibiotic utilization garnered from automatic stop orders.Funding: NoneDisclosures: None

scholarly journals 1089. Implementation of a Febrile Neutropenia Management Algorithm on Antibiotic Use and Outcomes: An Interrupted Time Series Analysis

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S386-S387
Author(s):  
Trang D Trinh ◽  
Luke Strnad ◽  
Lloyd E Damon ◽  
John H Dzundza ◽  
Larissa R Graff ◽  
...  
Keyword(s):  
Time Series ◽  
Febrile Neutropenia ◽  
Time Series Analysis ◽  
Clinical Outcomes ◽  
Interrupted Time Series ◽  
Antibiotic Use ◽  
Evidence Based ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Management Algorithm

Abstract Background Febrile neutropenia (FN) is a common complication of cancer therapy and often necessitates prolonged antibiotic treatment. Antibiotic de-escalation can be challenging given tenuous clinical status. Furthermore, a microbiological or clinical etiology is identified in a minority of FN patients. In 2016 we implemented several evidence-based strategies to guide antibiotic use in high-risk FN patients including specifying vancomycin use indications, minimizing carbapenem escalation in stable patients with ongoing fevers, and defining antibiotic durations regardless of neutrophil count. The study objective was to characterize and evaluate our experience implementing these strategies on antibiotic use and clinical outcomes. Methods Interrupted time series analysis of all admissions to the Malignant Hematology service at the University of California, San Francisco between June 2014 and December 2018. The primary outcome was monthly days of therapy (DOT) per 1,000 patient-days of broad-spectrum IV antibiotics (aztreonam, cefepime, piperacillin–tazobactam, meropenem, and vancomycin). Secondary outcomes included DOT/1,000 patient-days for each IV antibiotic, incidence rates of bloodstream infections (BSI) and C. difficile infections (CDI), and in-hospital all-cause mortality. A segmented regression analysis was conducted to evaluate the impact of the FN management algorithm implementation on antibiotic use and clinical outcomes. Summary statistics and time series scatter plots were used to visualize the trends and outliers. Results 2319 unique patients with 6,788 encounters were included. The median (IQR) age was 59 (46–68) years and 60% were male. Regression results and time series plots are shown in Table 1 and Figures 1–3. Conclusion Implementation of an evidence-based FN management algorithm led to decreased vancomycin and meropenem use without a statistically significant impact on overall antibiotic use, CDI rates, or mortality.While BSI rates fluctuated in the 2 months post-implementation, rates returned to baseline thereafter. A multidisciplinary effort facilitated successful implementation of this stewardship project. This collaboration remains essential to addressing future antimicrobial management strategies in this population. Disclosures All authors: No reported disclosures.

Impact of administrative restrictions on antibiotic use and expenditure in Ontario: time series analysis

2006 ◽  
Vol 11 (1) ◽  
pp. 13-20 ◽  
Author(s):  
Deborah Marshall ◽  
Jacqueline Gough ◽  
Paul Grootendorst ◽  
Melanie Buitendyk ◽  
Barbara Jaszewski ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Antibiotic Use ◽  
Series Analysis

scholarly journals Outpatient antibiotic use in Dutch infants after 10-valent pneumococcal vaccine introduction: a time-series analysis

BMJ Open ◽  
2018 ◽  
Vol 8 (6) ◽  
pp. e020619 ◽  
Author(s):  
Alexandre C Fortanier ◽  
Roderick P Venekamp ◽  
Rebecca K Stellato ◽  
Elisabeth A M Sanders ◽  
Roger A M J Damoiseaux ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Pneumococcal Vaccine ◽  
Antibiotic Use ◽  
Vaccine Introduction ◽  
Series Analysis

scholarly journals Author Correction: A nonlinear time-series analysis approach to identify thresholds in associations between population antibiotic use and rates of resistance

2020 ◽  
Vol 5 (11) ◽  
pp. 1449-1449
Author(s):  
José-María López-Lozano ◽  
◽  
Timothy Lawes ◽  
César Nebot ◽  
Arielle Beyaert ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Antibiotic Use ◽  
Nonlinear Time Series ◽  
Analysis Approach ◽  
Nonlinear Time Series Analysis ◽  
Series Analysis

Pneumococcal susceptibility to antibiotics in carriage: a 17 year time series analysis of the adaptive evolution of non-vaccine emerging serotypes to a new selective pressure environment

2019 ◽  
Vol 74 (10) ◽  
pp. 3077-3086 ◽  
Author(s):  
Naim Ouldali ◽  
Robert Cohen ◽  
Corinne Levy ◽  
Nathalie Gelbert-Baudino ◽  
Elisa Seror ◽  
...  
Keyword(s):  
Time Series ◽  
Antibiotic Resistance ◽  
Time Series Analysis ◽  
Selective Pressure ◽  
Acute Otitis Media ◽  
Antibiotic Use ◽  
Antibiotic Consumption ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Dynamic Patterns

Abstract Background Pneumococcal conjugate vaccine (PCV) implementations led to major changes in serotype distribution and antibiotic resistance in carriage, accompanied by changes in antibiotic consumption. Objectives To assess the dynamic patterns of antimicrobial non-susceptibility across non-PCV13 serotypes following PCV implementations. Methods We conducted a quasi-experimental interrupted time series analysis based on a 17 year French nationwide prospective cohort. From 2001 to 2018, 121 paediatricians obtained nasopharyngeal swabs from children with acute otitis media who were aged 6 months to 2 years. The main outcome was the rate of penicillin-non-susceptible pneumococci (PNSP), analysed by segmented regression. Results We enrolled 10 204 children. After PCV13 implementation, the PNSP rate decreased (−0.5% per month; 95% CI −0.9 to −0.1), then, after 2014, the rate slightly increased (+0.7% per month; 95% CI +0.2 to +1.2). Global antibiotic use within the previous 3 months decreased over the study period (−22.2%; 95% CI −33.0 to −11.3), but aminopenicillin use remained high. Among the main non-PCV13 serotypes, four dynamic patterns of penicillin susceptibility evolution were observed, including unexpected patterns of serotypes emerging while remaining or even becoming penicillin susceptible. In contrast to PNSP strains, for these latter patterns, the rate of co-colonization with Haemophilus influenzae increased concomitant with their emergence. Conclusions In a context of continuing high antibiotic selective pressure, a progressive increase in PNSP rate was observed after 2014. However, we highlighted an unexpected variability in dynamic patterns of penicillin susceptibility among emerging non-PCV13 serotypes. Antibiotic resistance may not be the only adaptive mechanism to antimicrobial selective pressure, and co-colonization with H. influenzae may be involved.

scholarly journals A nonlinear time-series analysis approach to identify thresholds in associations between population antibiotic use and rates of resistance

2019 ◽  
Vol 4 (7) ◽  
pp. 1160-1172 ◽  
Author(s):  
José-María López-Lozano ◽  
◽  
Timothy Lawes ◽  
César Nebot ◽  
Arielle Beyaert ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Antibiotic Use ◽  
Nonlinear Time Series ◽  
Analysis Approach ◽  
Nonlinear Time Series Analysis ◽  
Series Analysis

scholarly journals Impact of restricting procalcitonin measurements in a Swiss tertiary-care hospital on antibiotic use, clinical outcomes, and costs: An interrupted time-series analysis

2020 ◽  
pp. 1-3
Author(s):  
Mohamed Abbas ◽  
Nathalie Vernaz ◽  
Elodie von Dach ◽  
Nicolas Vuilleumier ◽  
Stephan J. Harbarth ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Interrupted Time Series ◽  
Antibiotic Use ◽  
Care Hospital ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
The Impact

Abstract We evaluated the impact of a restriction of procalcitonin measurements on antibiotic use, length of stay, mortality, and cost in a Swiss tertiary-care hospital using interrupted time-series analysis. There was no significant change in level or slope for rates of antibiotic consumption, and costs decreased considerably, by ~54,488 CHF (US$55,714) per month.

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