Transmission of respiratory illnesses in health care settings poses significant risks to patients and staff. Without clear, standardized masking thresholds, policies may vary, resulting in confusion. We developed statewide consensus thresholds to guide masking in Minnesota health care systems over three respiratory seasons.

A multidisciplinary workgroup consisting of infection preventionists, infectious disease providers, occupational health specialists, and representatives from the state health department reviewed available data, including hospitalization rates, influenza-like illness levels, test positivity, and wastewater data. Thresholds used for masking were evaluated and updated each year after analyzing performance and feedback from health care facilities.

Analysis of the first season thresholds revealed issues with data sources selected and resulted in the group changing threshold recommendations from illness levels to hospitalization rates. Analysis of the second season thresholds revealed issues with masking timing and threshold recommendations for COVID-19 hospitalization leading to changes in COVID-19 masking thresholds and the addition of a masking implementation date for season three. Nine of out ten health systems reporting implementing universal masking during the respiratory season. Those that implemented masking reporting strong staff and leadership support due to the aligned metrics.

Development of standardized thresholds improved staff support for masking and reduced staff and patient confusion. Use of basic epidemiology tools in threshold development allowed for replication across healthcare systems and easy communication of thresholds to staff and patients. Data reporting lags can delay masking during periods of rapidly increasing illness.

Community-acquired pneumonia (CAP) is a leading cause of hospitalization and mortality in the US. Studies report racial disparities in various infectious syndromes. Our objective was to assess the relationship between patient race and antibiotic prescribing in inpatient CAP management.

Retrospective cohort study.

11 Cleveland Clinic community hospitals.

Patients aged ≥18 years hospitalized with CAP between November 1, 2022, and January 31, 2025.

Parametric and non-parametric methods were used to describe demographic and clinical differences by race. The association between race and extended spectrum antibiotic (ESA) guideline concordance was assessed using multivariable logistic regression models adjusting for age, gender, admission source, area deprivation index (ADI), hospital, diabetes, cardiovascular disease, chronic respiratory disease, renal failure, liver disease, immunocompromising condition, alcohol and substance use disorder, dialysis, and clinical instability and severity on day 1.

In bivariate analyses, Non-Hispanic Black (NHB) patients were less likely than NHW patients to receive ESA guideline-concordant CAP therapy (63.2% vs 64.4%; OR = 0.91, P = .2). After adjusting for patient characteristics, there were no differences between NHB and NHW patients in receipt of ESA therapy (adjusted OR = 0.93; 95% CI = 0.83, 1.00). After adjusting for hospital, NHB patients were more likely to receive ESA guideline-concordant CAP therapy (adjusted OR = 1.17; 95% CI = 1.06, 1.30).

NHB patients were more likely to receive ESA-guideline concordant therapy, but this was influenced by where they sought care. Further studies are needed to understand why prescribing varies across hospitals.

Prospective audit and feedback (PAF) is a core antimicrobial stewardship strategy. Discontinuing PAF in favor of alternative interventions has not been previously evaluated.

This descriptive study assessed changes in antimicrobial days of therapy per 1,000 patient days (DOTs/1,000 PD) following PAF removal at two urban hospitals. Preintervention PAF included daily review of broad-spectrum antibiotics and oral therapy transitions. Postintervention efforts emphasized system standardization, education, guideline optimization, and electronic medical record enhancements. Secondary outcomes included trends in antibiotics previously reviewed under PAF: antibiotics targeting methicillin-resistant Staphylococcus aureus (MRSA) or Pseudomonas aeruginosa, carbapenems, and oral antibiotics.

Hospital A demonstrated a change in the trend of DOTs/1,000 PD with a significant downward slope after PAF removal (−5.994; 95% CI −8.072 to −3.929; P < .001). Hospital B continued to down-trend postintervention. At hospital A, carbapenem use decreased significantly postintervention (slope change −0.117; 95% CI −0.198 to −0.036; P = .007), with no changes in anti-MRSA or anti-pseudomonal agents. Hospital B demonstrated increasing use of anti-MRSA (slope change + 0.394; 95% CI 0.198 to 0.589; P < .001), anti-pseudomonal (slope change + 0.378; 95% CI 0.075 to 0.681; P = .016), and carbapenem agents (slope change + 0.124; 95% CI 0.020 to 0.228; P = .021). No changes were observed in oral antibiotic use or C. difficile rates.

Shifting stewardship resources away from PAF did not increase total antibiotic use trends. Broad-spectrum antibiotics increased modestly with unclear clinical significance (≤1.3 DOT/1,000 PD). Antimicrobial stewardship strategies, beyond PAF, should continue to be assessed to maximize effectiveness relative to effort.

To assess the association between hand hygiene adherence, as measured by an automated hand hygiene monitoring system (AHHMS), and multidrug-resistant organisms and other pathogens of epidemiologic significance (MDRO+).

Retrospective cohort study.

Acute care hospitals within an academic healthcare system.

Hand hygiene data was collected from all badged staff January 2021 through September 2022. Adult inpatients on non-maternity units during this period were eligible for inclusion.

After implementing an AHHMS, we analyzed correlations between monthly unit-level hand hygiene adherence (proportion of room entry–exit opportunities during which hand hygiene solution was dispensed) and hospital-onset MDRO+ rates from all clinical cultures and Clostridioides difficile stool tests. Mixed-effect negative binomial regression models evaluated associations between monthly unit-level hand hygiene adherence and MDRO+ rates while adjusting for the number of clinical tests ordered, unit type, and average number of inpatient COVID-19 cases.

During the study period, there were 22,767,036 hand hygiene opportunities. Mean hand hygiene adherence improved from 41% (January 2021) to 57% (September 2022). 1,847 MDRO+ detections were observed in 752,341 patient days with a median composite MDRO+ rate of 1.7 per 1,000 patient days (IQR: 0–3.6). The mixed-effect negative binomial regression model found a null association between hand hygiene adherence and MDRO+ rates (rate ratio 1.01; 95% confidence interval: 1.00–1.01).

Despite an improvement in hand hygiene adherence, we did not find a resultant impact on MDRO+ detection, likely owing to the complex interaction between the two variables and unmeasured confounders.

Antimicrobial Stewardship in the intensive care unit setting is a difficult task due to diagnostic uncertainty and perceived high-risk of poor outcomes in case of delayed or inappropriate treatment. Although novel diagnostics and other strategies have been proposed to improve antimicrobial use, their clinical effectiveness in real-world settings has been suboptimal.

We designed a critical interpretative synthesis of the literature, which allows the combination of quantitative and qualitative studies to revise and critique concepts used in Antimicrobial Stewardship efforts in the ICU setting. We searched the literature in duplicate with a sensitive strategy to identify main concepts, and we developed a main theme and conceptual framework after identifying the main concepts and strategies.

After screening 41,192 titles and abstracts and reviewing 1,335 full-text manuscripts, we selected 29 main manuscripts for this synthesis. We identified that classical concepts, such as the use of broad-spectrum antibiotics followed by de-escalation and the use of biomarkers of infection and novel diagnostics, although with face validity and supported by efficacy studies, carry a high risk of being ineffective in real-world settings. We argue that this discrepancy is due to cognitive biases in antimicrobial decision-making in the ICU setting, including risk-aversion behavior, diagnostic momentum, premature closure, therapeutic momentum, hyperbolic discounting, commission bias, and anchoring bias, among others, which drive intensivists towards overdiagnosis and overtreatment of infection.

Incorporation of the cognitive theory of decision-making in future stewardship efforts is necessary in the ICU setting along with traditional stewardship interventions.

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.

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.

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.

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.

Evaluate the prevalence and risk factors for inappropriately ordered urine cultures in primary care.

Cross-sectional study using chart reviews.

Two primary care, safety-net clinics in Houston, Texas.

Non-pregnant adults without a urinary catheter who had a urine culture and a primary care visit between 11/2018 and 3/2020.

We classified patients lacking physician documentation of the following symptoms as having an inappropriately ordered urine culture: dysuria, frequency, urgency, hematuria, fever, chills, costovertebral angle tenderness, nephrolithiasis, and pain (suprapubic, pelvic, or flank). We extracted patient demographics, visit-related diagnostic codes, past medical history, and urine culture results. Diagnostic codes were grouped based on body system, visit type (e.g. routine visit), or sign or symptom clusters. We evaluated the relationship between these factors and inappropriately ordered cultures using generalized estimating equations logistic regression.

We included 807 patients who had 870 visits. Most patients were Hispanic (66.3%) or African American/Black (24.8%) females (76.1%) with a median age of 50 years. Among 870 cultures, 210 (24%) were ordered inappropriately. We found having an abnormal urinalysis or urine characteristic (adjusted odds ratio (aOR): 13.66), acute low back pain (aOR: 4.88), a cardiovascular-related (aOR: 1.68) or gynecological/family planning visit (aOR: 10.84), being evaluated at the non-teaching clinic (aOR: 6.03), or having a routine health visit (aOR: 1.81) within the non-teaching clinic (interaction aOR: 4.27) were significantly associated with inappropriate urine cultures.

Our study revealed factors associated with inappropriately ordered urine cultures that may be unique to ambulatory settings and can help design outpatient diagnostic stewardship interventions.

Evaluate the influence of a procalcitonin (PCT) protocol and the incremental impact of a focused antimicrobial stewardship pharmacist intervention on antimicrobial exposure and hospital length of stay in acute exacerbations of chronic obstructive pulmonary disease (AECOPD).

Prospective, observational, interrupted time series.

Safety-net teaching hospital in Oakland, California.

We compared the care and outcomes of inpatients with non-severe AECOPD during three periods: Baseline Phase (before PCT testing), Intervention Phase I (after introduction of PCT testing and education) and Intervention Phase II (PCT testing and education plus an antimicrobial stewardship intervention to promote adherence). The primary study outcome was antibiotic exposure measured as mean antibiotic days per AECOPD episode.

341 total admissions were included, 134 in the Baseline Phase, 121 in Intervention Phase I and 86 in Intervention Phase II. Patient comorbidities were well balanced. Mean (SD) total antibiotic days decreased across the study from 4.7(3.8) to 3.5 (3.2) to 2.1(2.7) days in the Baseline Phase, Intervention Phase I and Intervention Phase II, respectively (P < .001). Median (IQR) hospital lengths of stay decreased from 3.7(2.6–5.2) to 2.8 (1.5–5.2) to 1.5(0.3–4.1) days (P = .003). Inclusion in Intervention Phase II was the strongest predictor of total antibiotic days (IRR = 0.45,95% CI [0.64–0.83]) and hospital length of stay (IRR = 0.68, 95% CI [0.53–0.88]). All cause 30-day readmission rates were similar across the study (16%, 21%, and 21%; p-trend 0.16).

Reductions in antimicrobial exposure and hospital length of stay achieved with PCT testing alone improved further with addition of a focused antibiotic stewardship pharmacist intervention.

To develop an approach for creating facility-specific urinary antibiograms accounting for the low number of isolates recovered in nursing homes (NHs).

Retrospective analysis of urine culture data collected in NHs in five states.

Data on 5097 urine culture isolates collected across 59 study NHs from January 1, 2020 to December 31, 2021. Four consulting microbiology laboratories served the study homes.

We compared a Clinical and Laboratory Standards Institute (CLSI) standard antibiogram model to four weighted-incidence syndromic antibiogram (WISCA) models utilizing alternate formatting rules. Ability to produce a facility-specific antibiogram with at least 30 isolates and the impact on susceptibility predictions were compared.

Only one facility could generate a CLSI standard antibiogram for the three most commonly recovered Gram-negative isolates over a one-year period. Ability to generate an antibiogram increased with each of the four WISCA models trialed (36%, 54%, 85%, 85%) with the most successful models combining all Gram-negative isolates over a two-year period. Shortening the definition of duplicate isolates from 12 to 3 months did not improve performance. Using all Gram-negative isolates, rather than the three most recovered pathogens, resulted in meaningful changes in the predicted activity of ampicillin-sulbactam, cefazolin, ceftriaxone, and trimethoprim-sulfamethoxazole in several study NHs.

These results suggest that WISCAs using 2-years of urinary culture data including all gram-negative isolates and excluding duplicate isolates within twelve months maximizes the number of NHs able to create a valid antibiogram.

A diagnosis code-based algorithm classifies outpatient antibiotic prescribing as almost always (Tier 1), sometimes (Tier 2), and almost never (Tier 3) appropriate. This algorithm has been leveraged to quantify antibiotic appropriateness and direct stewardship initiatives for adults and children, primarily based on Tier 3 encounters receiving antibiotics, but has not been validated.

To assess the performance of the algorithm for assessing antibiotic appropriateness in pediatric outpatients.

Using a pediatric care network of primary care, urgent care, and emergency departments from January 1–December 31, 2024, encounters were classified into tiers using the ICD10 algorithm. Manual chart review was performed on a stratified random sample of 300 (100 per setting) Tier 3 encounters with antibiotics using a structured protocol derived from local and national guidelines to determine antibiotic appropriateness overall and by location. Survey weights were applied to obtain estimates for all Tier 3 encounters with antibiotic prescriptions. The positive predictive value (PPV) for Tier 3 in identifying inappropriate antibiotic prescribing was calculated.

Of 272,698 encounters, 115,508 (42%) had an antibiotic prescription. The algorithm classified 10,370 (9%) as Tier 3. In the stratified manual validation sample, 170/300 were classified as appropriate, corresponding to a survey-weighted estimate of 58% appropriate (95% CI, 52%–64%) and a PPV of 42% for Tier 3 as a marker of inappropriate antibiotic use.

The established algorithm did not reliably predict antibiotic appropriateness in this pediatric outpatient population, demonstrating a need for pediatric-focused algorithms for measuring outpatient antibiotic stewardship.