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Susceptibility reporting and antibiotic prescribing for UTIs in the inpatient setting: a nudge toward improved stewardship

Published online by Cambridge University Press:  08 October 2025

Madison G. Ponder
Affiliation:
Gillings School of Global Public Health, Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Kevin Alby
Affiliation:
Department of Pharmacy, University of North Carolina Medical Center, Chapel Hill, NC, USA
Lindsay M. Daniels
Affiliation:
Department of Pathology and Laboratory Medicine, University of North Carolina Medical Center, Chapel Hill, NC, USA
Ashlyn M. Norris
Affiliation:
Department of Pathology and Laboratory Medicine, University of North Carolina Medical Center, Chapel Hill, NC, USA
Alan C. Kinlaw*
Affiliation:
School of Pharmacy, Division of Pharmaceutical Outcomes and Policy, University of North Carolina at Chapel Hill , Chapel Hill, NC, USA
*
Corresponding author: Alan C. Kinlaw; Email: akinlaw@unc.edu

Abstract

Information

Type
Research Brief
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 (https://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), 2025. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

Introduction

Urinary tract infections (UTIs) are common infections, particularly among women and older adults. Reference McLellan and Hunstad1 Antimicrobial resistance among UTI pathogens is increasing, making them key targets for antimicrobial stewardship programs. Reference Simmering, Tang, Cavanaugh, Polgreen and Polgreen2,Reference Wagenlehner, Bjerklund Johansen and Cai3 Electronic health records (EHRs) can provide decision support to guide stewardship efforts and antibiotic prescribing. Reference Parzen-Johnson, Kronforst and Shah4

We evaluated the impact of a low-resource EHR-based intervention where cephalexin was added to the susceptibility profile for urine culture results from inpatient, observation, and emergency settings based on inferred susceptibility of cefazolin for uncomplicated UTIs. Reference Nguyen and Jones57

Methods

Study population

We included patients age ≥18 years admitted to inpatient, observation, or emergency settings at University of North Carolina Medical Center with urine cultures positive for Escherichia coli, Klebsiella pneumonia, and/or Proteus mirabilis who received ≥1 antibiotic indicated for UTI. All settings could order a urinalysis or urine culture separately, while only the emergency department could also order a urinalysis to reflex urine culture. The pre and postintervention periods were September 1, 2018–September 9, 2019 and September 10, 2019–March 11, 2020, respectively. We excluded patients with: (1) specimen collection >15 days after admission and (2) susceptibility results returned ≥5 days after specimen collection (Supplemental Figure 1).

To assess the effect of the intervention on prescribing in response to timely availability of culture results, we examined medication orders occurring until discharge (not exceeding 7 d after culture susceptibility results). Patients were classified as “result not used” if ≥5 days passed between susceptibility result availability and any antibiotic prescription, or if discharged before results became available.

Intervention

On September 10, 2019, cephalexin was added to EHR susceptibility profiles for all urine cultures positive for Escherichia coli, Klebsiella pneumonia, and/or Proteus mirabilis with susceptibility testing for cefazolin. A comment on the susceptibility profile noted that cephalexin is recommended for uncomplicated cases only (Supplemental Figure 2). No announcement or training accompanied the intervention, but prospective audit-and-feedback was conducted by the antimicrobial stewardship team routinely. Monthly prescription prevalence was calculated as the number of patients prescribed each antibiotic after susceptibility results became available out of all eligible patients that month.

Interrupted time series statistical analysis

To evaluate the impact of the intervention on prescribing (shown by trend deflections), we used segmented linear regression to model interrupted time series data for monthly prescription prevalence. Our models accounted for seasonality using a sinusoidal function Reference Brookhart and Rothman8 and autocorrelated errors using lagged model parameters based on Durbin-Watson alpha of 0.3. Reference Durbin and Watson9

This study was approved by the University of North Carolina institutional review board. Analyses were performed using SAS 9.4 (SAS Institute, Cary, NC); Figures were created using R version 4.4.3 (R Core Team, Vienna, Austria) and RStudio version 2024.12.1.563 (Posit Team, Boston, MA).

Results

In total, 1981 UTIs were treated among 1788 unique patients (preintervention: n = 1 342; postintervention: n = 639). The median length of stay for both intervention periods was 2 days (interquartile range (IQR): 0–5 d). Among patients who were inpatient or observation stays, the median was 4 days (IQR: 2–7 d). Half (49.1%) of patients were discharged before culture results were returned; 70.0% of these were emergency department patients. Most patients were treated empirically with ceftriaxone (preintervention: 49.0%; postintervention: 53.4%).

At the beginning of the study period, fluoroquinolones had the highest prescription prevalence (29.0%) compared to 14.7% for cephalexin, which was the targeted antibiotic for this intervention (Figure 1; Supplemental Table 1).

Figure 1. Interrupted time series analysis of antibiotic prescribing by medication for urinary tract infection after results from urine culture with susceptibilities. The interrupted time series includes one inflection point at the intervention timepoint of September 2019. Patients could have multiple prescriptions of antibiotics, meaning prevalence measures for each antibiotic combined could be greater than 100%.

Before the intervention, cephalexin prevalence decreased by 0.4% (95%CI: –0.6%, –0.3%) per month. Afterward, this trend deflected upward (P = .01), increasing by 0.5% (95%CI: 0.1%, 0.9%) per month. Preintervention fluoroquinolone prevalence decreased by 1.0% per month (95%CI: –1.2%, –0.9%) but stabilized postintervention (P = .01). Ceftriaxone prevalence increased 0.6% (95%CI: 0.0%, 1.1%) per month before the intervention but negligibly decreased by –0.9% (95%CI: –2.5%, 0.8%) afterward. Nitrofurantoin increased modestly in prevalence by 0.6% (95%CI: 0.2%, 1.0%) per month postintervention (P = .03). Cefdinir negligibly increased by 1.1% (95%CI: –0.1%, 2.2%) per month postintervention (P = .18).

Discussion

This analysis demonstrates a modest increase in cephalexin use following a subtle, low-resource EHR-based intervention on antibiotic prescribing patterns for UTIs. While small, this change highlights potential for a greater impact with additional provider engagement or resource-intensive strategies.

Almost half of patients either received no medication within 5 days following culture result availability or were discharged before. This was most common among emergency department patients, whose stays were often shorter than the typical turnaround time. This may have led to susceptibility results going unused in decision-making for many patients and may relate to urinalysis to reflex cultures being available for order in the emergency department.

The prevalence of fluoroquinolones declined prior to the intervention, potentially related to an increased awareness of resistance and adverse reactions to fluoroquinolones in the medical community. Aside from prospective audit-and-feedback, no other interventions were in effect during the study periods.

UTI indications did not distinguish between complicated or uncomplicated cases. Cephalexin is recommended for uncomplicated UTIs, with unclear efficacy in complicated cases. Reference Geyer, VanLangen, Jameson and Dumkow10 Cephalexin may have been avoided for uncomplicated cases, likely leading to a weaker observed impact. We also could not determine if UTIs was recurrent; about 10% of patients had multiple UTIs during the study period. Notably, resistance to the oral cephalosporins, based on the cefazolin urine surrogate breakpoint, remained stable and consistently low (≤10%) for 2019 and 2020.

EHR-based interventions like this one can have meaningful impact on practice and given their low-resource use, they may warrant broader implementation. Similar efforts in outpatient settings or with other antibiotics, such as inferring doxycycline susceptibility from tetracycline, could expand stewardship impact. 7

Supplementary material

Supplementary material for this article can be found at https://doi.org/10.1017/ash.2025.10159.

Acknowledgments

None.

Financial support

No financial support was provided for this work.

Competing interests

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

Research transparency and reproducibility

Data sources are not publicly available. Analytic code is available upon request.

References

McLellan, LK, Hunstad, DA Urinary tract infection: pathogenesis and outlook. Trends Mol Med 2016;22:946957.CrossRefGoogle ScholarPubMed
Simmering, JE, Tang, F, Cavanaugh, JE, Polgreen, LA, Polgreen, PM. The Increase in Hospitalizations for Urinary Tract Infections and the Associated Costs in the United States, 1998–2011. Open Forum Infect Dis 2017;4:ofw281.10.1093/ofid/ofw281CrossRefGoogle ScholarPubMed
Wagenlehner, FME, Bjerklund Johansen, TE, Cai, T, et al. Epidemiology, definition and treatment of complicated urinary tract infections. Nat Rev Urol 2020;17:586600.10.1038/s41585-020-0362-4CrossRefGoogle ScholarPubMed
Parzen-Johnson, S, Kronforst, KD, Shah, RM, et al. Use of the electronic health record to optimize antimicrobial prescribing. Clin Ther 2021;43:16811688.10.1016/j.clinthera.2021.09.009CrossRefGoogle ScholarPubMed
Nguyen, HM, Jones, RN. Reanalysis of cefazolin surrogate susceptibility breakpoints utilized as guidances for oral cephalosporin treatments of uncomplicated urinary tract infections: caution concerning application to cefadroxil. Diagn Microbiol Infect Dis 2020;97:115053.10.1016/j.diagmicrobio.2020.115053CrossRefGoogle ScholarPubMed
Nguyen, HM, Graber, CJ. A critical review of cephalexin and cefadroxil for the treatment of acute uncomplicated lower urinary tract infection in the era of “bad bugs, few drugs”. Int J Antimicrob Agents 2020;56:106085.10.1016/j.ijantimicag.2020.106085CrossRefGoogle Scholar
Clinical and Laboratory Standards Institute. Performance Standards For Antimicrobial Susceptibility Testing, 35th ed., vol. 45. Clinical and Laboratory Standards Insitute (CLSI); 2025.Google Scholar
Brookhart, MA, Rothman, KJ. Simple estimators of the intensity of seasonal occurrence. BMC Med Res Methodol 2008;8:67.CrossRefGoogle ScholarPubMed
Durbin, J, Watson, GS. Testing for serial correlation in least squares regression: I. Biometrika 1950;37:409428.Google Scholar
Geyer, AC, VanLangen, KM, Jameson, AP, Dumkow, LE. Outcomes of high-dose oral beta-lactam definitive therapy compared to fluoroquinolone or trimethoprim-sulfamethoxazole oral therapy for bacteremia secondary to a urinary tract infection. Antimicrob Steward Healthc Epidemiol 2023;3:e148.CrossRefGoogle ScholarPubMed
Figure 0

Figure 1. Interrupted time series analysis of antibiotic prescribing by medication for urinary tract infection after results from urine culture with susceptibilities. The interrupted time series includes one inflection point at the intervention timepoint of September 2019. Patients could have multiple prescriptions of antibiotics, meaning prevalence measures for each antibiotic combined could be greater than 100%.

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