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Trends in antibiotic use before and during the coronavirus disease 2019 (COVID-19) pandemic across an integrated health system with different antimicrobial stewardship program models trends in antibiotic use by ASP model

Published online by Cambridge University Press:  08 April 2022

Jennifer M. Peterson
Affiliation:
Des Moines University, Des Moines, Iowa
Kristina White
Affiliation:
Department of Pharmacy, UnityPoint Health–Peoria, Peoria, Illinois
Emily Muehling
Affiliation:
Department of Pharmacy, System Clinical Services, UnityPoint Health–Des Moines, Des Moines, Iowa
Steven C. Ebert
Affiliation:
Department of Pharmacy, UnityPoint Health–Meriter, Madison, Wisconsin
Lisa Lambi
Affiliation:
Department of Pharmacy, UnityPoint Health–Cedar Rapids, Cedar Rapids, Iowa
Corey Thieman
Affiliation:
Department of Pharmacy, UnityPoint Health–Sioux City, Sioux City, Iowa
Nathan Peterson
Affiliation:
Department of Pharmacy, UnityPoint Health–Quad Cities, Bettendorf, Iowa
Kia Deuel
Affiliation:
Department of Infection Prevention, UnityPoint Health–Fort Dodge, Fort Dodge, Iowa
Amanda M. Bushman
Affiliation:
Department of Pharmacy, UnityPoint Health–Des Moines, Des Moines, Iowa
Sudhir Kumar
Affiliation:
Infectious Diseases Service, UnityPoint Health–Des Moines, Des Moines, Iowa Department of Internal Medicine, University of Iowa–Des Moines Campus, Des Moines, Iowa
Leyla A. Best
Affiliation:
Infectious Diseases Service, UnityPoint Health–Des Moines, Des Moines, Iowa Department of Internal Medicine, University of Iowa–Des Moines Campus, Des Moines, Iowa
Rossana Rosa*
Affiliation:
Infectious Diseases Service, UnityPoint Health–Des Moines, Des Moines, Iowa Department of Internal Medicine, University of Iowa–Des Moines Campus, Des Moines, Iowa
*
Author for correspondence: Rossana Rosa MD, MSc, Associate Medical Director for Infection Prevention and Antimicrobial Stewardship, Jackson Health System, 1611 NW 12th Avenue, Central 767, Miami, FL33136. E-mail: [email protected]

Abstract

Changes in antimicrobial use during the pandemic in relation to long-term trends in utilization among different antimicrobial stewardship program models have not been fully characterized. We analyzed data from an integrated health system using joinpoint regression and found temporal fluctuations in prescribing as well as continuation of existing trends.

Type
Concise Communication
Creative Commons
Creative Common License - CCCreative Common License - BY
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.
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

It has been postulated that the coronavirus disease 2019 (COVID-19) pandemic has disrupted the functions of antimicrobial stewardship programs (ASPs), which are considered one of the key tools for mitigating the evolution of multidrug-resistant organisms (MDROs). Reference Stevens, Patel and Nori1,Reference Stevens, Doll, Pryor, Godbout, Cooper and Bearman2 This concern has arisen since members of the ASPs have been diverted in large part to develop institutional guidance and policies for the management of COVID-19. Reference Furukawa and Graber3 Moreover, increases in empiric antibiotic prescribing during the COVID-19 pandemic have been described. Reference Langford, So and Raybardhan4 However, the extent to which long-term trends in antimicrobial use across different antimicrobial stewardship program (ASP) models have changed throughout the COVID-19 pandemic is less well understood. We have described temporal fluctuations and longitudinal trends in antimicrobial prescribing of key agents across an integrated healthcare system with different ASP models.

Methods

This study was conducted at 12 hospitals that are part of an integrated health system in Iowa. Data for antibiotic days of therapy (DOT) and days present were extracted from a centralized database. Only medical–surgical and intensive care units (ICUs) were included. The antibiotics most frequently prescribed at our facilities were selected for analysis: meropenem, piperacillin–tazobactam, cefepime, ceftriaxone, vancomycin, azithromycin, doxycycline, and levofloxacin. None of the antibiotics included are subject to preauthorization. We collected data from January 1, 2019, to February 28, 2021, which encompasses a period prior to the widespread availability of vaccines and preceding the circulation of the δ (delta) and δ (omicron) variants. The prepandemic period was defined as January 1, 2019, to February 29, 2020, and the pandemic period was defined as March 1, 2020, to February 28, 2021. During the first year of the pandemic, the state of Iowa experienced 2 significant increases in community spread with commensurate increase in hospitalizations for COVID-19. The first peak occurred in early May 2020 (peak number of patients hospitalized, 417) and the second peak occurred in mid-November 2020 (peak number of patients hospitalized, 1,510). 5

Antimicrobial stewardship program models

The daily antimicrobial stewardship activities and the composition of the staff performing them varied by site. Stewardship activities remained unchanged throughout the study period. The characteristics of the hospitals supported by each ASP model, as well as the ASP members and workflow are described in Table 1.

Table 1. Hospital and Antimicrobial Stewardship Program (ASP) Model Characteristics

Note. ICU, intensive care unit; ID, infectious disease.

Statistical analysis

We examined the trends in antibiotic DOT per 1,000 days present among the 3 different ASP models. We used joinpoint regression to determine the number of joinpoints, the monthly percentage changes (MPCs), and the average monthly percent changes (AMPCs). 6 The joinpoints are points at which the trend changes. The MPC characterizes changes in trends in antibiotic DOT rates occurring at any point during the entire observation period. The AMPC summarizes the trend over prespecified fixed intervals, which in our study were the prepandemic period (January 2019–February 2020) and the pandemic period (March 2020–February 2021). Models were fit to log-transformed antibiotic DOT rates, and permutation analysis was used to select the best-fit model. An autocorrelated error structure was selected to account for autoregression in prescribing rates over time. Analyses were conducted on the Joinpoint Regression Program version 4.7 software (National Cancer Institute, Bethesda, MD).

Results

Facilities using antimicrobial stewardship model A

In these facilities, estimates of the MPC for the entire observation showed significant changes in trend of use of piperacillin–tazobactam, ceftriaxone, azithromycin and doxycycline (Table 2, Supplementary Fig. 1B, 1D, 1F, and 1G). During the prepandemic period, AMPC estimates showed monthly increases in the use of ceftriaxone, vancomycin, azithromycin, and a decrease in levofloxacin use (Supplementary Table 1). During the pandemic period, the AMPC showed monthly increases in the use of cefepime, piperacillin–tazobactam, and vancomycin. The AMPC of vancomycin was the same for both the prepandemic and pandemic periods (+0.4%; 95% CI, 0.1–07; P = .04), reflecting a longstanding trend.

Table 2. Monthly Percent Change in Antibiotic Days of Therapy Per 1,000 Days Present According to Antimicrobial Stewardship Program (ASP) Model, January 1, 2019, to February 28, 2021

Facility using antimicrobial stewardship model B

At this site, estimates of the MPC for the entire observation period detected significant changes in the trends in cefepime and azithromycin use (Table 2 and Supplementary Fig. 2C and 2F). For the prepandemic period, AMPC estimates showed monthly increases in the use of meropenem, cefepime, ceftriaxone, vancomycin, and azithromycin, and a decrease in levofloxacin use (Supplementary Table 1). For the pandemic period, AMPCs showed monthly increases in the use of meropenem, ceftriaxone and vancomycin, and a decrease in levofloxacin use (Supplementary Table 1). The AMPCs for meropenem (+2.3; 95% CI, 0.8–3.8; P < .01), ceftriaxone (+1.0; 95% CI, 0.2–1.7; P = .02), vancomycin (+2.4; 95% CI, 1.0–3.5; P < .01), and levofloxacin (−2.4; 95% CI, −3.3 to −1.5; P < .01) remained the same for the prepandemic and pandemic periods, reflecting longstanding trends.

Facilities using antimicrobial stewardship model C

In these facilities, the MPC estimates for the entire observation period indicated multiple significant fluctuations in the use of meropenem, cefepime, azithromycin, doxycycline, and levofloxacin (Table 2 and Supplementary Figs 3A, 3C, 3F, 3G and 3H). For the prepandemic period, the AMPCs showed monthly increases in the use of meropenem, piperacillin–tazobactam, ceftriaxone, and doxycycline, and a decreases in the use of vancomycin and levofloxacin (Supplementary Table 1). For the pandemic period, the AMPC showed monthly increases in the use of piperacillin–tazobactam and ceftriaxone and a decrease in vancomycin use (Table 2). The AMPCs of piperacillin–tazobactam (+0.6; 95% CI, 0.2–1; P < .01), ceftriaxone (+0.9; 95% CI, 0.4–1.3; P < .01), and vancomycin (−0.3; 95% CI, −0.5 to −0.1; P = .05) remained the same for both the prepandemic and pandemic periods, reflecting the longstanding trend.

Discussion

Across hospitals using different ASP models, we identified multiple fluctuations in the rates of antibiotic use throughout the study period. In most cases, the average monthly percent changes reflected trends that preceded the COVID-19 pandemic.

Up to 75% of patients with COVID-19 are prescribed antibiotics, and rates of prescribing have decreased throughout the pandemic. Reference Langford, So and Raybardhan4 Our assessment of longitudinal trends in prescribing revealed fluctuations that, in most instances, did not reach a statistically significant deviation from the existing trend. There is a need for development of ASPs in settings with both limited access to the expertise of infectious diseases specialists, particularly during the COVID-19 pandemic, as well as a lack of reports of stewardship practices. Reference Pierce and Stevens7 Our study contributes to the literature on this topic by describing 3 ASP models in urban and semirural areas and by describing trends of use of key antibiotic agents under different stewardship practices.

The limitations of our study include use of registry-type data obtained from a centralized database in which accuracy depends on appropriate capture of data in the medication administration record. This aspect is mitigated by previous reviews on the accuracy of this data performed by clinical pharmacists. Also, we did not have data for the precise indication of antibiotic prescribing, which precluded us from evaluating changes in trends used specifically for respiratory infection. Furthermore, we did not assess the role of individual tools for mitigating antimicrobial use such as procalcitonin trends. Reference Martin, Philbin, Hughes, Bergin and Talento8

In conclusion, across 3 different ASP models, the core stewardship activities were maintained during the COVID-19 pandemic. Changes in antibiotic use were limited to temporal fluctuations and, for most agents, longstanding trends continued. Continued support and development of ASPs in accordance with local resources is crucial to their success.

Supplementary material

For supplementary material accompanying this paper visit https://doi.org/10.1017/ash.2022.39

Acknowledgments

Financial support

No financial support was provided relevant to this article.

Conflicts of interest

All authors report no conflicts of interest relevant to this article.

Footnotes

a

(Present affiliation: Department of Quality and Patient Safety, Jackson Health System, Miami, Florida [R.R.])

References

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COVID-19 in Iowa summary statistics. Iowa Department of Public Health website. https://coronavirus.iowa.gov. Accessed March 16, 2021.Google Scholar
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Martin, E, Philbin, M, Hughes, G, Bergin, C, Talento, AF. Antimicrobial stewardship challenges and innovative initiatives in the acute hospital setting during the COVID-19 pandemic. J Antimicrob Chemother 2021;76:272275.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Hospital and Antimicrobial Stewardship Program (ASP) Model Characteristics

Figure 1

Table 2. Monthly Percent Change in Antibiotic Days of Therapy Per 1,000 Days Present According to Antimicrobial Stewardship Program (ASP) Model, January 1, 2019, to February 28, 2021

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