Urinary tract infections (UTIs) are among the top 3 infections encountered in the emergency department (ED), accounting for nearly 2 million visits for females of all ages and 160,000 visits for males aged 65 years and older in the United States (1). Selection of antibiotic therapy for UTIs in the ED is challenging due to the absence of microbiologic data at the time of clinical decision and patient discharge or transfer. Furthermore, the increasing emergence of antimicrobial resistance among uropathogens in both the community and inpatient settings (2, 3) presents a significant challenge for ED clinicians to balance prompt initiation of effective empirical antibiotics without overprescribing broad-spectrum antibiotics. Incorporating local antibiograms into clinical decision-making can assist in the selection of appropriate empirical therapy (4, 5). Institution-wide antibiograms, however, may not accurately reflect susceptibility patterns of uropathogens from patients treated in the ED. Patients presenting to the ED represent a heterogeneous population comprised of all ages, from both the community and skilled nursing facilities (SNFs), and at various risks for resistant pathogens. Thus, even ED-specific antibiograms may obscure important differences among patient populations. Antibiograms stratified by patient characteristics may better facilitate empirical antibiotic selection for UTIs in the ED. The aim of this study was to compare patient group-specific urinary antibiograms for the predominant pathogen Escherichia coli isolated from patients treated in the ED to ultimately guide the development of an algorithm-based clinical order set with patient group-specific treatment options.
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