Objective:We evaluated how antibiotic use changed after implementation of a multifaceted intervention that sent providers individualized peer-comparison feedback on their antibiotic use for respiratory conditions that do not warrant antibiotics (never-events). Design:An interrupted time-series analysis was performed with a baseline (January 2018-January 2020) and intervention period (November 2021-December 2023), while controlling for COVID-19 era (February 2020-February 2022). Setting:Walk-in ambulatory clinics. Participants:Providers caring for patients in walk-in clinics. Methods:We conducted a mixed-methods study across 7 walk-in clinics in one health system. We included data from visits from 2018-2023 and conducted 17 semi-structured interviews with 10 providers. Results:After intervention implementation, antibiotic use for all visits decreased 8% (RR 0.92, 95% CI 0.86-0.97), then began to increase by 1% per month (RR 1.01, 95% CI 1.00-1.01). Once the intervention started, the use of never-event diagnostic codes decreased by 24% (RR 0.69-0.83) and continued to decrease by 1% per month (RR 0.99, 95% CI 0.98-0.99). Antibiotic use for never-event visits showed no immediate change after the intervention started (RR 0.80, 95% CI 0.61-1.04), then decreased by 3% per month (RR 0.97, 95% CI 0.96-0.98). Some providers valued receiving feedback on the metric; others admitted to shifting their codes. Conclusions:Delivering feedback to walk-in clinic providers was associated with temporary reductions in antibiotic-prescribing across all visits but also changes in diagnostic coding (ie, "gaming"). Antibiotic stewardship programs should monitor for changes in both when implementing new outpatient metrics.

Importance:Antibiotics prescribed at hospital discharge are frequently unnecessary or suboptimal. Strategies to improve prescribing are not well defined. Objective:To evaluate whether a discharge-focused prospective audit and feedback process decreases antibiotic overuse at hospital discharge. Design, Setting, and Participants:This stepped-wedge cluster-randomized clinical trial was conducted across participating units at 10 hospitals with antibiotic stewardship (AS) teams and supporting staff from December 5, 2022, to November 17, 2023. After a 24-week baseline period, 1 hospital crossed into the intervention arm every 2 weeks. Intervention:The intervention consisted of disseminating institutional guidelines for oral antibiotic step-down to frontline prescribers and conducting a prospective audit and feedback process for inpatients receiving antibiotics with an anticipated discharge date in the next 48 hours. Main Outcomes and Measures:The primary outcome was postdischarge antibiotic use. Secondary outcomes included inpatient antibiotic use, length of hospital stay, and readmission. Manual electronic health record reviews were performed in 434 cases to assess optimal antibiotic prescribing at discharge for patients who met specific criteria. Analysis was performed on a per-protocol basis. Results:There were 21 842 patient admissions (baseline, 14 288; intervention, 7554) across 10 hospitals. The median (IQR) age was 66 (53-75) years, with 13 380 (61.3%) males. At the hospital level, the mean (SD) number of patients audited by the AS team per week was 19.9 (5.8); approximately one-quarter of these audits (mean [SD], 5.0 [2.6]) resulted in feedback to the frontline prescribers. There were 3133 patients (21.9%) prescribed postdischarge antibiotics at baseline compared with 1645 patients (21.8%) during the intervention (odds ratio, 0.94 [95% CI, 0.84-1.05]). The mean (SD) postdischarge antibiotic duration was 7.1 (5.2) days at baseline compared with 7.6 (5.6) days during the intervention (mean difference, 0.02 [95% CI, -0.50 to 0.53] days). There were no statistical differences during the intervention compared with baseline for inpatient antibiotic duration (mean [SD], 4.4 (3.6) vs 4.2 [3.5] days; mean difference, 0.04 [95% CI, -0.20 to 0.27] days), length of hospital stay (mean [SD], 5.4 [4.8] vs 5.4 [5.0] days; mean difference 0.11 [95% CI, -0.12 to 0.33] days), or hospital readmission within 30 days (odds ratio, 1.02 [95% CI, 0.88-1.18]). Optimal antibiotic prescribing was more common during the intervention (122 of 264 cases [46.2%] vs 100 of 170 cases [58.8%]; odds ratio, 1.61 [95% CI, 1.08-2.40]). A total of 112 inpatient frontline prescribers were sent a postintervention survey; 40 (35.7%) responded, and 34 of 36 (94.4%) believed that the initiative improved antibiotic prescribing at hospital discharge. Conclusions and Relevance:In this stepped-wedged cluster-randomized clinical trial conducted across 10 hospitals, discharge-focused prospective audit and feedback did not decrease antibiotic use at hospital discharge but did improve optimal antibiotic prescribing for common and uncomplicated diagnoses. Other AS strategies are needed to decrease unnecessary antibiotic prescribing at this transition of care. Trial Registration:ClincialTrials.gov Identifier: NCT05471726.

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

This stepped-wedge cluster-randomized clinical trial investigates whether implementation of a discharge-focused prospective audit and feedback process decreases antibiotic overuse at hospital discharge. QuestionDoes a discharge-focused prospective audit and feedback process decrease antibiotic overuse at hospital discharge?FindingsIn this stepped-wedge cluster-randomized clinical trial across participating units at 10 hospitals with 21 842 admissions, the frequency and duration of antibiotic prescribing at hospital discharge did not decrease after implementing a prospective audit and feedback process. However, in selected patients with uncomplicated infections, optimal antibiotic-prescribing increased once the intervention went into effect.MeaningDischarge-focused prospective audit and feedback was not effective in reducing general antibiotic overuse at hospital discharge, but it did improve antibiotic prescribing in a subset of patients, suggesting that other strategies are needed to prevent unnecessary antibiotic use at this transition of care. ImportanceAntibiotics prescribed at hospital discharge are frequently unnecessary or suboptimal. Strategies to improve prescribing are not well defined.ObjectiveTo evaluate whether a discharge-focused prospective audit and feedback process decreases antibiotic overuse at hospital discharge.Design, Setting, and ParticipantsThis stepped-wedge cluster-randomized clinical trial was conducted across participating units at 10 hospitals with antibiotic stewardship (AS) teams and supporting staff from December 5, 2022, to November 17, 2023. After a 24-week baseline period, 1 hospital crossed into the intervention arm every 2 weeks.InterventionThe intervention consisted of disseminating institutional guidelines for oral antibiotic step-down to frontline prescribers and conducting a prospective audit and feedback process for inpatients receiving antibiotics with an anticipated discharge date in the next 48 hours.Main Outcomes and MeasuresThe primary outcome was postdischarge antibiotic use. Secondary outcomes included inpatient antibiotic use, length of hospital stay, and readmission. Manual electronic health record reviews were performed in 434 cases to assess optimal antibiotic prescribing at discharge for patients who met specific criteria. Analysis was performed on a per-protocol basis.ResultsThere were 21 842 patient admissions (baseline, 14 288; intervention, 7554) across 10 hospitals. The median (IQR) age was 66 (53-75) years, with 13 380 (61.3%) males. At the hospital level, the mean (SD) number of patients audited by the AS team per week was 19.9 (5.8); approximately one-quarter of these audits (mean [SD], 5.0 [2.6]) resulted in feedback to the frontline prescribers. There were 3133 patients (21.9%) prescribed postdischarge antibiotics at baseline compared with 1645 patients (21.8%) during the intervention (odds ratio, 0.94 [95% CI, 0.84-1.05]). The mean (SD) postdischarge antibiotic duration was 7.1 (5.2) days at baseline compared with 7.6 (5.6) days during the intervention (mean difference, 0.02 [95% CI, -0.50 to 0.53] days). There were no statistical differences during the intervention compared with baseline for inpatient antibiotic duration (mean [SD], 4.4 (3.6) vs 4.2 [3.5] days; mean difference, 0.04 [95% CI, -0.20 to 0.27] days), length of hospital stay (mean [SD], 5.4 [4.8] vs 5.4 [5.0] days; mean difference 0.11 [95% CI, -0.12 to 0.33] days), or hospital readmission within 30 days (odds ratio, 1.02 [95% CI, 0.88-1.18]). Optimal antibiotic prescribing was more common during the intervention (122 of 264 cases [46.2%] vs 100 of 170 cases [58.8%]; odds ratio, 1.61 [95% CI, 1.08-2.40]). A total of 112 inpatient frontline prescribers were sent a postintervention survey; 40 (35.7%) responded, and 34 of 36 (94.4%) believed that the initiative improved antibiotic prescribing at hospital discharge.Conclusions and RelevanceIn this stepped-wedged cluster-randomized clinical trial conducted across 10 hospitals, discharge-focused prospective audit and feedback did not decrease antibiotic use at hospital discharge but did improve optimal antibiotic prescribing for common and uncomplicated diagnoses. Other AS strategies are needed to decrease unnecessary antibiotic prescribing at this transition of care.Trial RegistrationClincialTrials.gov Identifier: NCT05471726

OBJECTIVE:Describe the workload associated with using telehealth to support Antimicrobial Stewardship efforts at Veterans Affairs Medical Centers (VAMCs) without local infectious diseases (ID) expertise. DESIGN:A mixed-methods process assessment to evaluate workload and workflow associated with Videoconference Antimicrobial Stewardship Teams (VASTs). SETTING AND PARTICIPANTS:Rural VAMC champions paired with ID consultants at geographically distant VAMCs to form VASTs. METHODS:Total workload estimates were based on time that champions and ID consultants allocated to VAST activities. Clinical Procedural Terminology (CPT) codes were used to estimate the workloads for clinical encounters. Role-based process maps were developed to understand variation in implementation by VAMC. RESULTS:The average workload that champions and ID consultants allocated to VAST activities was 6.7% (range 1.0%-20.0%) and 8.4% (range 2.0%-12.5%) full-time equivalents (FTEs), respectively. Clinical encounters completed by ID consultants contributed an average of 1.4% (range < 0.01%-2.5%) FTEs to the workload. The average proportion of FTEs required to sustain VASTs was 13.0% (range 3.0%-31.6%). Process maps showed four phases common to each VAST's workflow: case identification, meeting preparation, team meeting, and documentation. The tasks associated with each phase varied between VASTs. Champions carried out most tasks related to case finding and meeting preparation; the ID consultants completed most documentation tasks. CONCLUSIONS:The distribution of tasks within and among the VASTs indicated opportunities to improve workflow efficiency. Investing <12.5% of the FTE allocated to VA Antimicrobial Stewardship programs to support the time of an ID consultant from another VAMC can help rural VAMCs achieve staffing sustainability.

BACKGROUND:To support Antimicrobial Stewardship programs (ASPs) as well as the clinical care of patients with infections, we disseminated and implemented a Videoconference Antimicrobial Stewardship Team (VAST) to connect multidisciplinary teams from rural Veterans Affairs (VA) medical centers with geographically distant ID experts. Here, we describe the clinical syndromes discussed and the response to recommendations made during VAST sessions. METHODS:Between September 2021 to February 2024, eight ID consultants established VASTs with ten rural VAMCs, holding regularly scheduled videoconference sessions to discuss clinical cases and provide recommendations. Data were collected on patient demographics, clinical syndromes, and recommendations. Acceptance of recommendations within one week of each session was assessed via chart review. Six months after the intervention began, we conducted semi-structured interviews to assess participants' perceptions of VASTs. RESULTS:VASTs reviewed 626 cases involving 527 unique patients. Among 763 clinical syndromes discussed, the most common were infections of the respiratory (29%) or urinary tract (21%). Overall, VASTs made 973 recommendations, of which 71% were accepted. Of 570 recommendations related to antibiotics, 459 (80%) were accepted. Among 403 other recommendations, 235 (58%) were accepted. Interviews with participants indicated the importance of building trust and strong interpersonal relationships. CONCLUSIONS:VASTs effectively supported Antimicrobial Stewardship in rural VA medical centers (VAMCs) without local ID expertise. High acceptance rates, particularly for antibiotic-related recommendations, suggest that telehealth-enabled provider-to-provider models enhance stewardship efforts.

Background: The pneumococcal urinary antigen test can help rapidly identify Streptococcus pneumoniae as the cause of community-acquired pneumonia (CAP). In this study, we assessed the utility of this test across an integrated healthcare system. Methods: This retrospective cohort study included all acute-care admissions with CAP who were hospitalized during 2018-2023 and underwent pneumococcal urinary antigen testing at 85 Veterans Health Administration facilities. The primary outcome was days of antibiotic-spectrum coverage (DASC) score per length of antibiotic therapy (LOT). We used 1:5 propensity score matching to estimate the difference in the outcomes between patients who tested positive versus negative for the pneumococcal urinary antigen. Results: The pneumococcal urinary antigen test was performed in 10,923 patient-admissions with CAP; 473 (4.3%) tested positive. There were 77 patient-admissions who grew S. pneumoniae in their blood, and 35 (45.5%) of these had a positive antigen test. After propensity-score matching with 454 patients across 66 medical centers who tested positive and 2,153 who tested negative, the median DASC per LOT was significantly smaller in patients with a positive versus negative test [positive: 8.0, negative 9.2; Wilcoxon Z=6.68; p<0.0001]. The median LOT was 8 days in both patients with a positive and negative test. Conclusions: In this retrospective propensity-matched cohort study of patients with CAP, patients with a positive pneumococcal urinary antigen received more narrow-spectrum antibiotics than patients with negative results. However, the test had poor sensitivity. Because few patients tested positive, opportunities to practice antibiotic stewardship by leveraging the test’s results were limited.

Antibiotic overuse at hospital discharge is common and often overlooked. We conducted interviews with 91 clinicians across 9 Veterans Health Administration hospitals to assess perceptions of a metric comparing discharge antibiotic-prescribing. Clinicians found the metric valid and meaningful, but successful implementation will require more granular contextual data and quality-improvement framing.

We conducted a survey assessing antibiotic stewardship activities and resources in Veterans Health Administration Community Living Centers, which provide skilled nursing and residential care. We found high rates of implementation of cornerstone stewardship practices and opportunities for increased stewardship intervention with greater informatics support.

INTRODUCTION:Benchmarking hospitals on their antibiotic use may be facilitated by metrics that adjust for inter-hospital differences in patient case-mix, such as types of infections, procedures, and comorbidities. Metrics that capture antibiotic spectrum [e.g., days of antibiotic spectrum coverage (DASC)] can be more sensitive to stewardship activities than metrics based on days of therapy (DOT). In this study, we developed risk-standardized metrics for both DOT and DASC. METHODS:We performed a mixed-methods study to build risk-standardized metrics for inpatient antibiotic use, using a modified Delphi process integrating expert- and data-driven strategies to identify nonmodifiable risk factors associated with appropriate inpatient antibiotics. These factors were used to create risk-standardized ratios (RSR) for DOT and DASC. A standardized antimicrobial administration ratio (SAAR)-like metric was also constructed. RESULTS:In 2021, there were 497,061 patient-admissions across 121 Veterans Health Administration (VHA) hospitals. The median hospital RSR was 1.00 (interquartile range (IQR) 0.95-1.05) for DOT and 1.00 (IQR 0.96-1.04) for DASC; the median ratio for the SAAR-like metric was 0.85 (IQR 0.68-1.03). The Kendall's tau for RSR-DOT and the SAAR-like metric was 0.48; RSR-DASC and the SAAR-like metric was 0.33; and RSR-DOT and RSR-DASC were 0.48. Compared to the SAAR-like metric, 60 (49.6%) and 80 (66.1%) hospitals ranked in a different quartile for RSR-DOT and RSR-DASC, respectively. CONCLUSIONS:Hospital performance on the SAAR-like metric was weakly correlated with the RSR-DASC and moderately correlated with the RSR-DOT. Hospitals' performance on the SAAR-like metric differed from that of the RSR metrics, suggesting the RSR metrics may have added value over the SAAR.

The Veterans Affairs (VA) Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act expanded eligibility for community-based care particularly for Veterans facing geographic or capacity-related barriers. Patients with diabetic foot ulcers (DFU) require timely specialty management and are vulnerable to fragmented care, yet little is known about how the MISSION Act reshaped patterns of DFU-related specialty care within and outside the VA. We conducted a retrospective cohort study of Veterans aged 65 or older with a new DFU diagnosis in VA between 2016 and 2022. We identified DFU-related specialty encounters (podiatry, vascular surgery, infectious diseases and endocrinology) and categorised community encounters as VA-paid or Medicare-paid. We assessed annual trends in community specialty care and changes in the proportion and payer type of care before and after the MISSION Act. Among 76 398 patients, VA-paid community specialty care increased substantially following the MISSION Act, with larger relative growth among rural Veterans (rural: +119%; urban: +96%). In contrast, Medicare-paid DFU specialty care declined during the same period (rural: -12%; urban: -13%). Following the MISSION Act, reliance on VA-paid community specialty care increased markedly for Veterans with DFU, particularly in rural areas, while reliance on Medicare-paid care decreased.

BACKGROUND:Inpatient antimicrobial stewardship programs (ASPs) promote avoiding unnecessary initiation, excessively long duration, and overly broad-spectrum selection of antimicrobials, but currently available metrics do not adequately reflect or distinguish these three components. We aimed to develop a novel framework that captures them while providing information specific to each, based on Days of Antimicrobial Spectrum Coverage (DASC) and length of therapy (LOT). METHODS:We developed a three-level conditional modeling framework to extract hospital-level variability, risk-adjusted for three components (initiation, duration, and spectrum). This was applied to data from 118 Veterans Health Administration (VHA) hospitals, with models built on 2022-2023 data and validated with 2024 data. Patient demographics, intensive care status, admitting specialty, 86 comorbidities, and 224 procedure categories were considered candidate variables for risk adjustment. Overall hospital performance was evaluated using a composite metric that integrated three components ("S3 [start, stop, select] Metric") and was visualized in a radar chart for each hospital. RESULTS:The cohort included 727,958 unique patients with 9,363,922 days present. Hospital-level usage ranged widely (DASC per 1,000 DP: 1,311-5,275 [interquartile range (IQR): 2,738-3,563]; LOT per 1,000 DP: 132.2-517.6 [IQR: 301.0-367.5]). Risk-adjustment models included 116 variables for initiation, 77 for duration, and 91 for spectrum components. S3 metrics ranged from 0.703 to 1.572 (IQR: 0.906-1.086). A three-component evaluation could provide specific information on each hospital's usage patterns. CONCLUSIONS:We propose a DASC-LOT framework and S3 metric to assess ASP practices in initiation, duration, and spectrum separately while providing overall composite benchmarking.

Early conversions from intravenous (IV) to oral antibiotics have been proposed as a target for antibiotic stewardship programs, but it is unclear how often these conversions are actually performed We performed a retrospective cohort study to measure the frequency that patients with community-acquired pneumonia (CAP) had an early IV to oral antibiotic conversion, i.e. within 72 hours of admission. All acute-care admissions during 2018-2023 to Veterans Health Administration (VHA) hospitals were included. Patients were ineligible for switching if they were in the intensive care unit, not taking other oral medications, or were diagnosed with another infection. The secondary outcome was death and/or hospital readmission within 30 days of discharge. To account for the possibility that hospitals with lower switch rates had a different patient case-mix, we calculated an expected switch rate at each facility by using patient-level variables in a log-binomial model. Hospitals were grouped into quartiles based on their observed-to-expected (O:E) ratios and the secondary outcome was compared across quartiles using a Kruskal Wallis test. There were 31,183 admissions that met criteria across 124 VHA hospitals (Table 1). Median age was 73 years (IQR 67-80); 29,805 (96%) were male. There were 17,282 (55%) patients who were switched to oral antibiotics by day 3. Among 16,070 patients still in the hospital on day 3, only 2169 (13.5%) were switched. The hospital-level median switch rate was 57% (IQR 50-62%), and the frequency of switching did not change over time (Figures 1 and 2). The O:E ratio for switches ranged from 0.79 among hospitals in the lowest quartile to 1.23 in the highest quartile. Overall, 5,629 (18.1%) patients died and/or were re-admitted within 30 days. There was no difference in this composite outcome across quartiles (Kruskal-Wallis χ2 =5.4; p=0.14) (Table 2). Early conversions from IV-to-oral antibiotics for patients hospitalized with CAP occurred in approximately half of eligible cases. Outcomes among patients at hospitals with high conversion rates were comparable to outcomes at hospitals with low rates, thereby supporting the safety of early conversions. More concerted efforts to promote these conversions, when appropriate, are needed. All Authors: No reported disclosures

Antibiotic overuse for viral respiratory conditions that never require antibiotics is common in the outpatient setting, especially walk-in clinics. We evaluated the effect of a multifaceted stewardship intervention, which included sending providers individualized peer comparison feedback reports on their antibiotic use for conditions that do not benefit from antibiotics (“never-events”). We used mixed-methods to evaluate the intervention (Figure 1) in 8 walk-in clinics during a baseline period (Jan 2018-Oct 2021) and an intervention period (Nov 2021-Dec 2023). To analyze whether the intervention was associated with changes in antibiotic-prescribing across all visits (regardless of the diagnosis), we fit a generalized linear mixed model using a Poisson distribution and a log link, including random intercepts for physicians and adjustment for practice changes that occurred during the COVID-19 pandemic. Secondary outcomes included changes in the use of never-event diagnostic codes. In 2023, we conducted 17 semi-structured interviews with 10 providers about the acceptability of the metric in comparison to a new metric for all respiratory diagnoses. There were 445,349 visits; median age was 27 (IQR 18-44), and 61% were female (Table 1). After implementation of the intervention, the frequency of antibiotic-prescribing for all visits changed from 23.1% to 23.7% (p< 0.001), and the use of never-event codes changed from 12.0% to 8.5% (p< 0.001). In the adjusted analysis, the frequency of antibiotic-prescribing across all visits was 11% lower compared to before the intervention (RR 0.89, 95% CI 0.85-0.94), and the use of never-event diagnostic codes decreased by 24% relative to baseline (RR 0.76, 95% CI 0.70-0.82) (Table 2). Some providers valued receiving feedback on the metric while others admitted to shifting their codes to avoid metric detection (Table 3). Delivering feedback to walk-in clinics providers on their antibiotic use was associated with reductions in antibiotic-prescribing across all visits but also changes in diagnostic coding (i.e., “gaming”). Antibiotic stewardship programs should monitor for changes in both when implementing new outpatient metrics. All Authors: No reported disclosures

Abstract Background Antibiotic overuse at hospital discharge is common, and it is unclear which antibiotic stewardship (AS) strategies are effective at improving post-discharge antibiotic-prescribing. In this study, we compared how hospitals’ AS processes differed based on their performance on a risk-adjusted metric for post-discharge antibiotic use.Figure 1.Risk-adjusted comparison of post-discharge antibiotic-prescribing frequency and duration across 124 VA hospitalsGroup 1 hospitals (n=40) had less frequent post-discharge antibiotic-prescribing and used shorter post-discharge antibiotic duration. Group 2 hospitals (n=26) had more frequent post-discharge antibiotic-prescribing and used shorter post-discharge antibiotic durations. Group 3 hospitals (n=34) had less frequent post-discharge antibiotic-prescribing and used longer post-discharge antibiotic durations. Group 4 hospitals (n=24) had more frequent post-discharge antibiotic-prescribing and used longer post-discharge antibiotic durations. Methods We performed a retrospective study of discharges to home from 124 acute-care VA hospitals. Discharges occurred 6 months before/after a mandatory hospital-level AS survey (11/10/20); patients who received ≥ 30 days of post-discharge antibiotics were excluded. We built a zero-inflated negative binomial mixed-model with two random intercepts for each hospital to predict post-discharge oral antibiotic exposure and duration. Key model covariates included patient comorbidities, discharge diagnoses of infection, and inpatient antibiotic duration. Using the predicted random intercepts, hospitals were categorized into 4 groups. Next, we used a multinomial logistic regression model to compare how often AS processes, as reported in the survey, were used at hospitals across these groups.Table 1.Characteristics of 124 VA hospitals, stratified by a hospital’s performance on a risk-adjusted metric for post-discharge antibiotic useAbbreviations: AS = antibiotic stewardship; FTEE = full time employee equivalents; IQR = interquartile range; LOT = length of therapy; PA = prior authorization; PAF = prospective audit-and-feedback; SD = standard deviation. (1) Facility complexity scores are created by the VA Healthcare Analysis and Information Group. Hospitals are scored according to their patient population, clinical services (e.g., intensive care unit and surgery services), education and research. A score of 1a and 1b is categorized as the highest complexity. Lower complexity facilitates are scored as 1c, 2, or 3. (2) This survey question was dichotomized to compare stewardship physicians and stewardship pharmacists who interact daily or several times a week versus teams that interact weekly, monthly or less frequently than monthly. (3) This variable ranges from 1-10 and captures whether certain antibiotics were managed by prior authorization (PA) or prospective audit-and-feedback (PAF). Each additional antibiotic managed with one of these strategies increased the PA or PAF score by 1, except as noted: vancomycin (intravenous), daptomycin, oral/IV linezolid (each formulation = 0.5 points), piperacillin-tazobactam, cefepime, ceftazidime, anti-pseudomonal carbapenems, ertapenem, ciprofloxacin + levofloxacin oral/IV (each 0.5), and moxifloxacin oral/IV (each 0.5). Results There were 399,234 discharges; 17.2% received post-discharge antibiotics (median duration 6). Hospital performance on the metric is shown in Figure 1, and Table 1 shows hospital characteristics, based on the group. Forty (32.3%) hospitals were in group 1, i.e., they prescribed antibiotics less frequently than expected at discharge and used shorter post-discharge duration. Twenty-four (19.4%) hospitals were in group 4, i.e., they prescribed antibiotics more often than expected at discharge and used longer post-discharge duration. Compared to group 1 hospitals, hospitals in group 4 were less likely to report interactions between their AS physician and AS pharmacist(s) every day or several times per week (0.17, 95% CI 0.05-0.64). No other AS processes significantly differed between the groups (Table 2).Table 2.Odds ratios for a hospital within each group reporting the use of specific antibiotic stewardship processes, based on a multinomial logistic regression modelAbbreviations: AS = antibiotic stewardship; FTEE = full time employee equivalents; LOT = length of therapy; OR = odds ratio; PA = prior authorization; PAF = prospective audit-and-feedback; Ref = reference group. (1) This survey question was dichotomized to compare stewardship physicians and stewardship pharmacists who interact daily or several times a week versus teams that interact weekly, monthly or less frequently than monthly. (2) The odds ratio reflects the effect on the odds of increasing the number of antibiotics managed with this strategy by a single unit (i.e., managing 10 antibiotics by PA versus managing only 9 by PA). Conclusion The findings of this mixed-methods study suggest that routine AS physician-pharmacist collaboration may be important to reducing antibiotic overuse at discharge. Future studies should more precisely measure AS processes to better understand how these are associated with differences in hospital performance at this transition of care. Disclosures Daniel J. Livorsi, MD, Merck: Grant/Research Support Michihiko Goto, MD MSCI, Merck: Grant/Research Support

Abstract Background Studies have shown that both patient- and hospital-level factors can influence the evaluation of antimicrobial consumption, and appropriate risk adjustments are necessary for reliable benchmarking. The curation of candidate variables through experts can be helpful in gaining the trust of users. We conducted a modified two-stage Delphi method to build consensus on candidate variables that should be considered in developing a risk-adjustment model for benchmarking metrics of hospital antimicrobial consumption. Summary of Expert Consensus for Candidate Variables for Risk-Adjusted Benchmarking Metrics Methods In preparation, we listed potential variables for consideration from past literature (8 facility characteristics, 6 patient demographics, 4 care processes, 56 comorbidities, 42 procedure categories). We distributed a survey to a 9-member expert panel to rate variables independently to “can be considered” or “should not be included” with comments. Consensus was defined as agreement by 7 or more out of 9 members, and the results with comments were presented to the panel at a conference call for further discussions. The second survey was distributed, focusing on items that did not reach consensus or the panel suggested reconsideration. Results At the first survey, 8 facility characteristics, 3 patient demographics, 4 care processes, 27 comorbidities, and 19 procedure categories reached a consensus. The panel discussed the remaining 29 comorbidities and 23 procedure categories and whether any item that reached consensus required reconsideration on a follow-up conference call. In the second survey, 3 facility characteristics, 2 patient demographics, 27 comorbidity categories, and 4 procedure categories were included in the second survey based on the discussion. At the end of the process, 7 facility characteristics, 6 patient demographics, 4 care processes, 49 comorbidities, and 41 procedure categories reached a consensus (Figure). Conclusion In this modified two-stage Delphi process, we successfully classified the majority of variables as either to be considered or not to be included in statistical model development. These variables, curated by subject matter experts, can serve as a foundation for further model development for objective evaluation and benchmarking of hospital antimicrobial consumption. Disclosures Michihiko Goto, MD MSCI, Merck: Grant/Research Support Daniel J. Livorsi, MD, Merck: Grant/Research Support

Abstract Background Diabetic foot ulcers (DFU) are associated with high morbidity and mortality, including major lower limb amputation (LLA). Little is known about racial/ethnic disparities and facility level variation in major LLA in large healthcare systems, such as Veterans Health Administration (VHA). VHA cares for over 9 million Veterans in 140 facilities with no insurance-related barriers to care.Figure:Caterpillar plot of relative odds of major LLA in each medical center Methods This is a retrospective cohort study of all Veterans with a new diagnosis of DFU during 2016-2021. The outcome was major LLA within 12 months from DFU diagnosis. We conducted multivariable logistic regression with random facility intercepts to assess variation in major LLA across VHA facilities while adjusting for patient demographics, comorbidities, and the severity of DFU at initial diagnosis. We calculated odds ratios (ORs) and confidence intervals (CIs) for associations between patient-level variables and major LLA. We calculated the median OR (MOR) as a measure of facility-level variation in major LLA. The MOR can be interpreted as the median change in odds of major LLA associated with care in all pairs of facilities. Results There were 105,644 patients from 140 hospitals in the cohort. The median age was 67. Most patients were White (75.6%), followed by Black (18.5%) and Hispanic (6.0%). At presentation, 91.6% had an early-stage ulcer while the rest had complicated DFU. Major LLA occurred in 4055 patients (3.8%). In the logistic regression model, variables associated with higher odds of major LLA were Black (OR 1.77, 95%CI 1.62-1.92), Native American (OR 2.08, 95%CI 1.57-2.75), Hispanic (OR 1.38, 95%CI 1.19-1.60), complicated DFU (OR 3.36, 95%CI 3.11-3.64), chronic kidney disease (OR 1.11, 95%CI 1.01-1.21), peripheral vascular disease (OR 3.49, 95%CI 3.24-3.76) and myocardial infarction (OR 1.32, 95%CI 1.21-1.49). The facility-level variation in major LLA (MOR: 1.87, p< 0.001) was larger than most of patient-level risk factors, suggesting that facility-level factors play an important role in the outcome of DFU. Conclusion Our study showed racial/ethnic disparities and facility-level variation in major LLA within the VHA. Future studies should investigate the reasons for this variation and develop strategies for reducing disparities in LLA. Disclosures Daniel J. Livorsi, MD, Merck: Grant/Research Support

Abstract Background Post-procedural antimicrobial prophylaxis is not recommended by professional guidelines but is still commonly prescribed and can lead to patient harm. The goal of this multicenter pilot intervention trial was to encourage less frequent use of post-procedural antimicrobials after common endoscopic urologic procedures.Table 1.Characteristics of patients across the 3 participating hospitals during both the baseline and intervention periods Methods We evaluated a bundled intervention using a pre-post, quasi-experimental design at three Veterans Affairs medical centers that performed common endoscopic urologic procedures: ureteroscopy and transurethral resection of a bladder tumor or prostate. There was a 2-year baseline, 1-month implementation, and 12-month intervention period. The intervention consisted of education, local champion(s), and audit-and-feedback of data, aggregated to the hospital-level, on the frequency of post-procedural antimicrobial use with comparisons to other facilities. The primary outcome was antimicrobial use on post-procedural day 1 and was evaluated using a logistic regression model for each site. Secondary outcomes were a) unplanned visits (i.e., Emergency Department visits and/or hospital readmissions within 30 days of the procedure) as well as b) late antimicrobial prescriptions (i.e., antimicrobials prescribed within 7-30 days after the procedure).Figure 1.Probability of post-procedural antimicrobial use after common urologic procedures across the 3 participating hospitals during the baseline and intervention periods Results There were 1,272 procedures performed across all sites at baseline compared to 525 during the intervention period (Table 1). During the baseline period, 644 (50.6%) patients received post-procedural antimicrobials compared to 216 (41.1%) during the intervention period. There was no change in the use of post-procedural antimicrobials at sites 1 and 2 between the two periods (Figure 1). At site 3, the odds of prescribing a post-procedural antimicrobial significantly decreased during the intervention period relative to the baseline time trend (0.089; 95% CI 0.016-0.445). There was no significant increase in unplanned visits or late antimicrobial prescriptions at any of the sites. Conclusion Implementation of a bundled intervention was associated with reduced post-procedural antimicrobial use after urologic procedures at 1 of the 3 participating sites. These mixed findings support the safety and also the difficulty of implementing guidelines on surgical antimicrobial prophylaxis. Disclosures Daniel J. Livorsi, MD, Merck: Grant/Research Support

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.

Importance The prevalence of diabetes is increasing over time, fueling an epidemic of diabetic foot ulcers (DFUs) and subsequent risk of leg amputation. However, little is known about the variation in outcomes for patients with DFUs according to the health care facilities treating them. Objective To examine facility-level variation in major leg amputation among veterans with incident DFUs using the Veterans Health Administration (VHA) cohort. Design, Setting, and Participants A retrospective cohort study was conducted from January 1, 2016, to December 31, 2021, of all veterans with a new diagnosis of DFU at 140 VHA facilities across the US. Patients were followed up to 1 year from DFU diagnosis. Analyses were conducted between March 22, 2024, and January 13, 2025. Exposure A facility was assigned to each patient corresponding to the health care site where the initial DFU diagnosis was made. Main Outcomes and Measures The primary outcome was major leg amputation during the follow-up period. A multivariable mixed-effects regression model with random facility intercepts was applied to assess variation in major leg amputation rates across facilities, adjusting for social drivers of health, comorbidities, and complicated DFU at initial diagnosis. The median odds ratio (MOR) was calculated to quantify facility-level variation in outcomes. Results A total of 86 094 veterans (98.3% male; mean [SD] age, 73.0 [8.1] years; age range, 55-102 years) were included. Major leg amputation was performed for 3279 veterans (3.8%) within a year of DFU diagnosis. The MOR for facility-level variation in major leg amputation was 1.85, indicating that the odds of major leg amputation were 1.85 times higher between 2 randomly selected facilities for an average patient ( P < .001). In contrast, the MOR for facility-level variation in 1-year mortality was 1.16 ( P < .001). Conclusions and Relevance This cohort study of veterans with newly diagnosed DFU found significant facility-level variation in major leg amputation rates within 1 year of DFU diagnosis. Facility-level variation in 1-year mortality rates was much smaller, suggesting variation in leg amputation was likely to stem from variation in DFU-specific care. The VHA should strive to minimize the odds of major leg amputation and interfacility variation.