Various metrics have been proposed to measure antibiotic consumption in inpatient settings, but little is known about how these metrics correlate with appropriateness of antibiotic usage (i.e. construct validity). We developed two metrics (risk-standardized ratio: RSR), one based on Days of Therapy (RSR-DOT) and another based on Days of Antimicrobial Spectrum Coverage (RSR-DASC). We aimed to evaluate whether hospital performance on these metrics is associated with appropriateness of antibiotic selection and duration.Table 1:Assessments of Diagnosis, Antibiotic Selection on Day 3, and Antibiotic Duration for LRTI and UTIFigure 1:Application of Inclusion and Exclusion Criteria Using data from October 2020 to September 2021, we constructed RSR-DOT and RSR-DASC for 118 acute-care hospitals in the Veterans Health Administration and selected 24 with lower or higher RSRs for DOT and DASC. For each hospital, an Infectious Disease physician, blinded to the hospital’s performance, reviewed 10 cases each of lower respiratory tract infections (LRI) and urinary tract infections (UTIs) to assess the appropriateness of antibiotic selection on day 3 (6-level ordinal outcomes) and appropriateness of antibiotic duration. Associations with RSR metrics were assessed using ordinal logistic regression (antibiotic selection) and logistic regression (antibiotic duration).Figure 2:Pie Charts representing Frequency of LRTI and UTI Diagnosis, Antibiotic Selection on Day 3, and Duration AssessmentTable 2.Association between Hospital Performance on the risk-standardized metrics and antibiotic appropriateness for LRTI and UTI The final cohort included 240 cases for both LRI and UTI diagnoses after applying exclusion criteria (Figure 1 and Table 1). Lower RSR-DASC was significantly associated with better antibiotic selection at day 3 and appropriate duration for LRI, while RSR-DOT did not show significant associations (Table 2). For UTIs, we did not observe significant associations between antibiotic selection at day 3 or appropriate duration with either metric. When cases of LRI and UTI were combined, lower RSR-DASC was significantly associated with better antibiotic selection at day 3. Hospital evaluations by RSR-DASC were associated with appropriateness of antibiotic selection at day 3 and the antibiotic duration in LRI, while RSR-DOT did not show any significant associations, suggesting higher construct validity with RSR-DASC. The lack of associations with both metrics in UTI might be due to fewer intra-hospital differences in antibiotic selection when microbiologic data (e.g. urine cultures) are available and high frequency of asymptomatic bacteriuria treatment. All Authors: No reported disclosures

Importance:The Centers for Disease Control and Prevention offers a standardized antimicrobial administration ratio (SAAR) as an evaluation metric for inpatient antibiotic use through rankings and peer comparisons (ie, benchmarking). However, the SAAR model only accounts for facility- and unit-level factors without considering the hierarchical nature of the health care data, and it does not directly reflect patient-level factors or stewardship efforts to avoid overly broad-spectrum therapy. Objective:To examine the use of antimicrobial use risk adjustment methods and choice of basic metrics (eg, days of therapy [DOT] and days of antimicrobial spectrum coverage [DASC], which do not and do consider antimicrobial spectrum, respectively) in hospital benchmarking. Design, Setting, and Participants:This retrospective cohort study was conducted using data from 117 acute care hospitals within the Veterans Health Administration (VHA) system. All patients admitted between January 1, 2021, and December 31, 2023, were included. Main Outcomes and Measures:Monthly antibiotic use was measured with 2 basic metrics and risk adjustment models created using baseline data for 2021 to 2022. Hospitals were benchmarked for 2023 use via 3 methods: (1) unadjusted comparison, (2) risk adjustment with hospital- and unit-level factors with single-level negative binomial regression models (method 1, similar in approach to the SAAR), and (3) risk adjustment with hospital-, unit-, and patient-level factors with hierarchical zero-inflated negative binomial regression models (method 2). Results:This study included 736 810 patients (median age, 70 [IQR, 61-76] years; 94.7% male). There was wide variability in unadjusted antibiotic use among hospitals (median, 477 [IQR, 420-523] DOT per 1000 days present [DP]; and median, 3115 [IQR, 2739-3602] DASC per 1000 DP). Risk adjustments with methods 1 and 2 resulted in moderate ranking changes, but there were only weak correlations between benchmarking results by the 2 methods (τB = 0.43 for DOT and 0.44 for DASC). The choice of basic metrics with or without consideration of antimicrobial spectrums (DOT vs DASC) had a modest correlation after risk adjustment (τB = 0.84). Conclusions and Relevance:In this cohort study of the nationwide VHA system, there were substantial differences in risk-adjusted benchmarking results between models with only hospital- and unit-level factors and models with hospital-, unit-, and patient-level factors. Future studies should evaluate whether these models with higher content validity also have better construct validity and can inform hospitals and stewardship programs about their objective performance compared with other programs.

Abstract Background PJI occurs in 0.5-2% of Joint Arthroplasty. Patients with acute non-Staphylococcal PJI who undergo DAIR are treated with 6 weeks of antimicrobials after which CAS may be considered. We aimed to compare the incidence of treatment failure between people who received CAS and those who did not. Methods This is a retrospective cohort study of patients admitted to Veterans Affairs (VA) hospitals from 2003-2017 with a non-Staphylococcal PJI, underwent DAIR and received 6 weeks of antimicrobial treatment (Table 1). CAS was defined as at least 30 days of oral antibiotics after 6 weeks of antimicrobial treatment. Duration of CAS was categorized as short (1-3 months), moderate (3-6 months) and long ( >6 months) (Fig 1). Patients were followed for 5 years. Treatment failure was defined as microbiologically confirmed recurrent PJI, additional debridement or re-operation at the same site. Cause-specific Kaplan-Meier curves were used to compare treatment failure rates between those who did and did not receive CAS, censoring on death. Results Among 468 patients with non-staphylococcal PJI who underwent DAIR, 208 (44.4%) received CAS. Patients with Enterococcus PJI were statistically more likely to receive CAS. K-M curves showed patients on CAS had a higher estimated failure free survival probability at 5 years when compared to those who did not get CAS (66% vs. 55%, p< 0.01) (Fig 2). When antibiotic use was considered as a time-dependent covariate, CAS was associated with a decreased hazard of treatment failure (hazard ratio (HR): .47 (95% confidence interval [CI]: 0.29, 0.76). After statistically adjusting for surgical site, severity of illness, and alcohol abuse, a short duration of CAS was significantly associated with decreased treatment failure (HR=0.24; 95% CI: 0.11, 0.52). There was no significant association between moderate or long duration of CAS and treatment failure (Table 2) Table 2 Conclusion A short duration of CAS may be beneficial among patients with non-Staphylococcal PJI who underwent DAIR. However, there was not a statistically significant association between longer duration of CAS use and treatment failure. Thus, the risks and benefits of long-term antibiotics should be weighed when aiming to prevent recurrence of PJI. Disclosures Mireia Puig-Asensio, MD, GILEAD: Honoraria Andrew Pugely, MD, MBA, Globus Medical: Advisor/Consultant|Globus Medical: Grant/Research Support|Globus Medical: IP royalties|Medtronic: Advisor/Consultant|Medtronic: Grant/Research Support|RDB Bioinformatics: Grant/Research Support|United Healthcare: Advisor/Consultant

Group Name: VHA Center for Antimicrobial Stewardship and Prevention of Antimicrobial Resistance (CASPAR) Background: Antimicrobial stewardship programs (ASPs) are advised to measure antimicrobial consumption as a metric for audit and feedback. However, most ASPs lack the tools necessary for appropriate risk adjustment and standardized data collection, which are critical for peer-program benchmarking. We created a system that automatically extracts antimicrobial use data and patient-level factors for risk-adjustment and a dashboard to present risk-adjusted benchmarking metrics for ASP within the Veterans’ Health Administration (VHA). Methods: We built a system to extract patient-level data for antimicrobial use, procedures, demographics, and comorbidities for acute inpatient and long-term care units at all VHA hospitals utilizing the VHA’s Corporate Data Warehouse (CDW). We built baseline negative binomial regression models to perform risk-adjustments based on patient- and unit-level factors using records dated between October 2016 and September 2018. These models were then leveraged both retrospectively and prospectively to calculate observed-to-expected ratios of antimicrobial use for each hospital and for specific units within each hospital. Data transformation and applications of risk-adjustment models were automatically performed within the CDW database server, followed by monthly scheduled data transfer from the CDW to the Microsoft Power BI server for interactive data visualization. Frontline antimicrobial stewards at 10 VHA hospitals participated in the project as pilot users. Results: Separate baseline risk-adjustment models to predict days of therapy (DOT) for all antibacterial agents were created for acute-care and long-term care units based on 15,941,972 patient days and 3,011,788 DOT between October 2016 and September 2018 at 134 VHA hospitals. Risk adjustment models include month, unit types (eg, intensive care unit [ICU] vs non-ICU for acute care), specialty, age, gender, comorbidities (50 and 30 factors for acute care and long-term care, respectively), and preceding procedures (45 and 24 procedures for acute care and long-term care, respectively). We created additional models for each antimicrobial category based on National Healthcare Safety Network definitions. For each hospital, risk-adjusted benchmarking metrics and a monthly ranking within the VHA system were visualized and presented to end users through the dashboard (an example screenshot in Figure 1). Conclusions: Developing an automated surveillance system for antimicrobial consumption and risk-adjustment benchmarking using an electronic medical record data warehouse is feasible and can potentially provide valuable tools for ASPs, especially at hospitals with no or limited local informatics expertise. Future efforts will evaluate the effectiveness of dashboards in these settings. Funding: No Disclosures: None Figure 1. Figure 2. Figure 3.

Abstract Background 2-stage exchange (2SE) surgery is often used to treat chronic prosthetic joint infections (PJI). IDSA guidelines do not recommend oral antibiotic suppression after 2SE. However, a recent randomized trial suggested that oral antibiotics for 3 months after arthroplasty reimplantation may prevent recurrent PJI. Objective: To compare rates of treatment failure (i.e., recurrent PJI) and adverse reactions (ARs) among patients who received < 1 month of antibiotics directly after reimplantation to those who received 1-3 months of antibiotics following reimplantation (extended antibiotics). Methods This retrospective cohort study included patients with hip, knee, or shoulder PJI who underwent 2SE at 83 VA hospitals between the years 2003-2017. PJI was defined using administrative codes and microbiology data. Patients were followed for 5 years to assess treatment failure (TF) and ARs. TF was defined as recurrent PJI, debridement, or reoperation. ARs included Clostridioides difficile infections (CDI), or antibiotic associated diarrhea (AAD) during or 72 hours after antibiotics. Chi-square tests were used to compare outcomes. Cumulative incidence function curves were created to compare TF rates between those who did and did not receive extended antibiotic treatment, incorporating the competing risks of TF and death. Results Of the 433 patients, most (97%) received < 1 month of oral antibiotics and 3% received extended antibiotics. The 15 patients who received extended antibiotics had similar rates of TF and ARs compared with patients who received < 1 month of oral antibiotics (Table). However, there was a trend toward higher rates of CDI (6.7% vs. 3.8%) and AAD (13.3% vs. 9.6%) among those who received extended antibiotics. There was no difference in TF comparing extended antibiotics with < 1 month of antibiotics, accounting for death (Figure). Table: Treatment Failure and Adverse Reactions Among Those Who Did and Did Not Receive Extended Antibiotics Conclusion Few patients received extended oral antibiotics in the study period. There were no statistically significant differences in TF or ARs between the 2 groups. Yet, there was a trend toward higher rates of ARs among the extended antibiotic group. Future prospective studies should assess both the potential benefits and ARs associated with extended antibiotics among patients undergoing 2SE surgery. Disclosures Marin L. Schweizer, PhD, 3M (Grant/Research Support)PDI (Grant/Research Support) Bruce Alexander, PharmD, Bruce Alexander Consulting (Independent Contractor) Daniel Suh, MS MPH, General Electric (Shareholder)Merck (Shareholder)Moderna (Shareholder)Smile Direct Club (Shareholder) Aaron J. Tande, MD, UpToDate.com (Other Financial or Material Support, Honoraria for medical writing) Andrew Pugely, MD, MBA, Globus Medical (Research Grant or Support)Medtronic (Consultant)United Healthcare (Consultant)

Abstract Background The necessary data elements and optimal statistical methods for benchmarking hospital-level antimicrobial use are still being debated. We aimed to describe the relative influence of case-mix adjustment and different statistical methods when ranking hospitals on antimicrobial use (AU) within inpatient settings. Methods Using administrative data from the Veterans Health Administration (VHA) system in October 2016, we calculated total antimicrobial days of therapy (DOT) and days present according to the National Healthcare Safety Network (NHSN) protocol. Patient-level demographics, comorbidities, and recent procedures were used for case-mix adjustments. We compared hospital rankings across 4 different methods: (A) crude antimicrobial DOT per 1,000 days present, aggregated at the hospital-level; (B) observed/expected (O/E) AU ratio with risk adjustment for ward-level variables (analogous to NHSN’s Standardized Antimicrobial Administration Ratio); (C) O/E AU ratio with risk adjustment for ward-/patient-level variables; (D) predicted/expected (P/E) AU ratio with risk adjustment for ward-/patient-level variables, based on a multilevel model accounting for clustering effects at hospital- and ward-levels. Results The cohort included 165,949 DOTs and 318,321 days present at 122 acute care hospitals within VHA. Crude DOTs per 1,000 days present ranged from 153.6 to 900.8 (Figure A), and ward-level risk adjustment only modestly changed rankings (Figure B). When adjusted for ward- and patient-level variables (including demographics, 14 comorbidities and 22 procedures), rankings changed substantially (Figure C). Risk-adjustment by a multilevel model changed rankings even further, while shrinking variabilities (Figure D). Ten hospitals in the lowest and 11 hospitals in the highest quartiles by O/E risk adjustment for only ward-level variables were classified to different quartiles on P/E risk adjustment. Conclusion We observed that the selection of variables and statistical methods for case-mix adjustment had a substantial impact on hospital rankings for antimicrobial use within inpatient settings. Careful consideration of methodologies is warranted when providing benchmarking metrics for hospitals. Disclosures All Authors: No reported Disclosures.