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Background: Data regarding outpatient antibiotic prescribing for urinary tract infections (UTIs) are limited, and they have never been formally summarized in Virginia. Objective: We describe outpatient antibiotic prescribing trends for UTIs based on gender, age, geographic region, insurance payer and International Classification of Disease, Tenth Revision (ICD-10) codes in Virginia. Methods: We used the Virginia All-Payer Claims Database (APCD), administered by Virginia Health Information (VHI), which holds data for Medicare, Medicaid, and private insurance. The study cohort included Virginia residents who had a primary diagnosis of UTI, had an antibiotic claim 0–3 days after the date of the diagnosis and who were seen in an outpatient facility in Virginia between January 1, 2016, and December 31, 2016. A diagnosis of UTI was categorized as cystitis, urethritis or pyelonephritis and was defined using the following ICD-10 codes: N30.0, N30.00, N30.01, N30.9, N30.90, N30.91, N39.0, N34.1, N34.2, and N10. The following antibiotics were prescribed: aminoglycosides, sulfamethoxazole/trimethoprim (TMP-SMX), cephalosporins, fluoroquinolones, macrolides, penicillins, tetracyclines, or nitrofurantoin. Patients were categorized based on gender, age, location, insurance payer and UTI type. We used χ2 and Cochran-Mantel-Haenszel testing. Analyses were performed in SAS version 9.4 software (SAS Institute, Cary, NC). Results: In total, 15,580 patients were included in this study. Prescriptions for antibiotics by drug class differed significantly by gender (P < .0001), age (P < .0001), geographic region (P < .0001), insurance payer (P < .0001), and UTI type (P < .0001). Cephalosporins were prescribed more often to women (32.48%, 4,173 of 12,846) than to men (26.26%, 718 of 2,734), and fluoroquinolones were prescribed more often to men (53.88%, 1,473 of 2,734) than to women (47.91%, 6,155 of 12,846). Although cephalosporins were prescribed most frequently (42.58%, 557 of 1,308) in northern Virginia, fluoroquinolones were prescribed the most in eastern Virginia (50.76%, 1677 of 3,304). Patients with commercial health insurance, Medicaid, and Medicare were prescribed fluoroquinolones (39.31%, 1,149 of 2,923), cephalosporins (56.33%, 1,326 of 2,354), and fluoroquinolones (57.36%, 5,910 of 10,303) most frequently, respectively. Conclusions: Antibiotic prescribing trends for UTIs varied by gender, age, geographic region, payer status and UTI type in the state of Virginia. These data will inform future statewide antimicrobial stewardship efforts.Funding: NoneDisclosures: Michelle Doll reports a research grant from Molnlycke Healthcare.

Background: In this study, we assessed whether meropenem restriction led to delays in administration for patients in a medical intensive care unit (MICU) at a large tertiary-care urban teaching hospital. Methods: The antimicrobial stewardship program (ASP) at Virginia Commonwealth University Health System (VCUHS) requires approval for restricted antimicrobial orders placed between 8 a.m. and 9 p.m. Between 8 a.m. and 5 p.m. (daytime), authorized approvers include ASP and infectious diseases (ID) physicians. From 5 p.m. to 9 p.m. (evening) orders are approved by ID fellows. Orders were entered as Stat, Now, and Routine. Between 9 p.m. and 8 a.m. (night), patients receive doses without approval. Meropenem restriction began in mid-January 2018. Pre- and postmeropenem restriction periods were defined as February–December 2017 and February–December 2018. Meropenem use data were compared for adult patients in the MICU. A multivariable Cox regression model was implemented to compare (1) time from order entry to approval; (2) time from order approval to patient administration; (3) total time from order entry to patient administration, adjusting for order priority, approver (ASP, ID consult, ID fellow, pharmacy); and (4) time of day of order placement (day, eve, night). The analyses were performed using SAS version 9.4 software (SAS Institute, Cary, NC). Result: Time from order approval to patient administration was significantly decreased in the postrestriction period (HR, 1.840; P < .001) (Table 1). Stat orders were faster compared to routine orders for order entry to approval (HR, 1.735; P < .001), approval to administration (HR, 2.610; P < .001), and total time from order entry to administration (HR, 2.812; P < .001). No significant differences were found in time to approval by approving service. Time from order entry to approval was faster for nighttime orders than for daytime orders (HR, 1.399; P = .037). Conclusions: Our data indicate that the time from order entry to administration decreased following meropenem restriction in our MICU. More research is needed to identify the reason for this finding, but we postulate that this is due to an effect on drug administration prioritization within nursing workflow. These data will inform our local meropenem restriction efforts.Funding: NoneDisclosures: Michelle Doll reports a research grant from Molnlycke Healthcare.