# Characterizing the ImPact of COVID-19 on Antibiotic PreScribing in AcutE Care and IDentifying Resilient Stewardship Strategies (POISED)

> **NIH AHRQ R01** · UNIVERSITY OF WISCONSIN-MADISON · 2021 · $499,999

## Abstract

Project Summary/Abstract
The ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2), has resulted in over 26 million infections and overwhelmed healthcare systems
throughout the U.S. The novel nature of COVID-19 has generated unprecedented diagnostic and therapeutic
dilemmas. One area of emerging concern is the collateral impact of the pandemic on increased antibiotic
prescribing and an associated acceleration of bacterial resistance. For instance, early reports indicate that a
high percentage of patients hospitalized with COVID-19 receive antibiotics despite few having confirmed
bacterial co-infections. In addition to the public health implications, overuse of antibiotics is also a threat to
patient safety due to the risk of serious adverse drug events and Clostridioides difficile colitis. In January 2021,
the Society for Healthcare Epidemiology of America issued a white paper outlining research priorities related to
COVID-19 that highlighted an urgent need to “identify the impact of changes in health care utilization and
delivery on antibiotic prescribing” and “develop and implement optimal Antimicrobial Stewardship Program
(ASP) strategies to improve antimicrobial use and patient outcomes while adapting to changing healthcare
delivery during COVID-19”. This project is specifically designed to address this call to action as we aim to
comprehensively characterize the impact of the COVID-19 pandemic on antibiotic prescribing and bacterial
resistance trends in acute care hospitals and identify strategies that effectively promote resilient antibiotic
stewardship. The assembled team is uniquely qualified to conduct this project given our expertise in evaluating
antibiotic prescribing patterns, access to data from ~350 U.S. hospitals and extensive experience using
systems engineering methods to analyze stewardship interventions. For the quantitative analyses, we will first
characterize overall and condition specific antibiotic prescribing trends before and after COVID-19 using an
interrupted time series analysis. Next, we will identify patient and hospital level factors that increased the risk of
non-indicated antibiotic prescribing during the COVID-19 pandemic, with the goal of identifying potential
intervention targets. Finally, we will complete a systems engineering guided qualitative analysis, focused on
hospitals that least and most effectively mitigated the impact of COVID-19 on antibiotic prescribing, to identify
systems-level contextual factors and strategies. These results will be used in a multidisciplinary co-design
process to develop an antibiotic stewardship implementation toolkit that enhances resiliency during operational
upheaval and is transferable between organizations. Given the dynamic nature of the pandemic (e.g. variant
strains), it is imperative to classify the previous, ongoing and future adverse impacts on antibiotic prescribing to
guide development of tail...

## Key facts

- **NIH application ID:** 10346674
- **Project number:** 1R01HS028669-01
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** Michael Santino Pulia
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2021
- **Award amount:** $499,999
- **Award type:** 1
- **Project period:** 2021-09-30 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10346674

## Citation

> US National Institutes of Health, RePORTER application 10346674, Characterizing the ImPact of COVID-19 on Antibiotic PreScribing in AcutE Care and IDentifying Resilient Stewardship Strategies (POISED) (1R01HS028669-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10346674. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*