How antibiotic stewardship programs can effectively reduce antibiotic overuse at hospital discharge is unclear. In this study, we assessed barriers and facilitators to performing prospective audit-and-feedback at this transition of care.

A qualitative study using semi-structured interviews.

Ten acute-care hospitals participating in a stepped-wedge cluster-randomized trial, including three Veteran’s Health Administration hospitals, two academic medical centers and five community hospitals

Fourteen antimicrobial stewards in participating hospitals across the United States.

A semi-structured interview guide was created applying the RE-AIM framework to focus on perceptions of implementing the intervention. All interviews were audio recorded, transcribed, and coded in a three-person team. Using thematic analysis, codes were developed and collapsed into themes.

Half of the intervention sites struggled to identify patients at discharge, limiting the stewardship teams’ ability to conduct prospective audit-and-feedback at discharge. In contrast, strong provider–stewardship relationships and existing hospital initiatives, such as handshake stewardship and discharge planning meetings, facilitated implementation. Stewardship teams at four sites also reported not needing to guide antibiotic use for patients with Infectious Disease (ID) consults, as they agreed with the documented recommendations from the ID specialists.

Our findings underscore the importance of accounting for the hospital and organizational context when implementing discharge-focused audit-and-feedback interventions, paying particular attention to existing policies, procedures, and the dynamics between antibiotic stewardship teams and front-line prescribers.

Outpatient parenteral antimicrobial therapy (OPAT) programs continue to evolve with increases in multidisciplinary teams, complex oral antibiotics, long-acting injectable antimicrobials, patients with substance use disorder (SUD) and telehealth. We sought to examine how OPAT programs are currently structured and identify barriers to safe care.

Cross-sectional survey.

Physician, pharmacist, and advanced practice providers (APP) Emerging Infections Network (EIN) members.

A survey was conducted between February and March 2025 to assess OPAT structure, expansion to complex outpatient antimicrobial therapy (COpAT), and barriers to safe OPAT care.

Of 1639 EIN members, 622 (38%) responded; 75% reported an active role in OPAT. Oversight of patients on COpAT was reported by 59%, and mandatory ID consultation for OPAT by 59%. Eighty-one percent reported >75% of OPAT patients were followed by ID. Most patients received OPAT at home (78%) followed by post-acute care facilities. Outpatient and inpatient ID physicians were responsible for laboratory test monitoring (75% and 30% respectively), while 37% reported a multidisciplinary OPAT team and 32% reported non-specialists. Respondents cited inadequate support in data analysis, administration, information technology and financial support for clinical staff. Common challenges were lack of leadership awareness (51%), difficulty managing patients with SUD (50%) and timely access to laboratory test results (48%).

ID physicians were commonly involved in OPAT care, with many programs expanding to COpAT. Several barriers to the safe delivery of OPAT remain, including lack of institutional support, reimbursement and poor communication between stakeholders.

This study aimed to assess staff nurses’ perceptions of the infection control team’s (ICT) role and the infection control environment across healthcare settings in the Sultanate of Oman.

A descriptive cross-sectional design was employed.

Data were collected from 997 staff nurses working in 18 public and private tertiary hospitals across 10 governorates in Oman.

Participants completed self-reported questionnaires measuring the perceived role of the ICT (PRICT) and the perceived infection control environment (PICE).

The mean PRICT score was 64.7 (SD = 9.4), indicating basic perceived ICT competence, while the mean PICE score was 56.1 (SD = 12.1), reflecting an acceptable infection-control environment. Hospital affiliation, accreditation status, and availability of an infection control manual significantly predicted PRICT. PRICT was moderately correlated with PICE (r = 0.50, p<.001). Nurses in private and accredited hospitals reported higher PRICT and PICE scores.

The findings underscore the significance of consistent infection control team practices, effective communication, hospital accreditation, and accessible infection control manuals. Strengthening ICT roles through structured interdisciplinary collaboration and standardized programs may enhance infection control practices and patient safety in Omani hospitals and support quality improvement initiatives nationwide across healthcare sectors and inform infection control policy development.

To evaluate the incidence, risk factors, and outcomes associated with multidrug-resistant organisms (MDROs) colonization in patients undergoing elective orthopedic surgery at the Thammasat University Hospital.

We conducted a prospective MDROs surveillance screening (swabs from the nose, throat, groin, and rectum) in patients undergoing orthopedic surgery. MDROs were defined as extended-spectrum β-lactamase (ESBL)-producing Gram-negative bacteria (GNB), carbapenem-resistant Enterobacterales, methicillin-resistant Staphylococcus aureus, and vancomycin-resistant enterococci. The incidence of MDROs colonization, risk factors, and outcomes including surgical site infections (SSIs) were assessed. Postoperative SSIs were compared between patients with and without MDROs colonization.

Of 384 swabs tested from 96 patients, ESBL-producing Escherichia coli was identified in 38 isolates (31 rectal swabs and 7 groin swabs) from 31 patients (32.3%). Only one patient had a history of admission within the previous year. Majority of procedures involved prosthetic implantation (77.1%) including total knee arthroplasty (30.2%). Seven patients (7.3%) developed SSIs without microbiological confirmation. The incidence of SSIs was higher among patients with ESBL-producing E. coli colonization compared to patients without colonization (6/31, 19.4% vs. 1/65, 1.5%; P = .004; odds ratio, 15.36; 95% CI 1.7–356.3). From the multivariate logistic regression analysis, preoperative ESBL-producing E. coli colonization was associated with SSIs (P = .014, adjusted odds ratio 16.53, 95% CI 1.78–153.44).

Preoperative ESBL-producing E. coli colonization was common among patients undergoing orthopedic surgery and possibly increased risk of SSIs. Further studies for multidrug-resistant GNB screening, surgical outcomes, and antibiotic prophylaxis modification should be considered in endemic regions.

This study evaluates the impact of the COVID-19 pandemic on the profile of bacterial resistance in healthcare-associated lower respiratory tract infections (HAI/LRTI), in an intensive care unit.

City of Belém-PA.

This is a retrospective and analytical cross-sectional study, in which the resistance profile of HAI/LRTI bacterial isolates was evaluated over 2018–2022.

The review of HAI notifications revealed 330 lower respiratory tract infections during the study period. The bacteria with a significant change in the resistance profile between the period pre-COVID and the post-COVID periods were P. aeruginosa (P = .011), K. pneumoniae (P < .001) and A. baumannii (P = .001), with increased profiles multidrug-resistant, and extensively drug-resistant, and strains with pandrug-resistant profile, in 2020 and 2021. In the analysis by antibiotic class, there was a significant increase in A. baumannii resistance to carbapenems and K. pneumoniae resistance to carbapenems.

Comparing the periods, there was an emergence of K. pneumoniae resistant to aminoglycosides and carbapenems; of P. aeruginosa with tendency to resistance to aminoglycoside, carbapenem, 4th generation cephalosporin and anti-pseudomonal penicillin + beta-lactamase inhibitor; of A. baumannii resistant to aminoglycoside, carbapenem, quinolone, anti-pseudomonal penicillin + beta-lactamase inhibitor and penicillin + beta-lactamase inhibitor and 4th generation cephalosporin.

To evaluate the impact of electronic medical record (EMR) transitions of care tools on antibiotic durations for uncomplicated community-acquired pneumonia (CAP).

IRB-approved, quasi-experiment.

Five acute-care hospitals in Michigan.

Hospitalized adults with uncomplicated CAP between 07/01/2023 and 11/30/2023 (pre-intervention) and 07/01/2024 and 11/30/2024 (post-intervention) were included. Patients were excluded if antibiotics were completed prior to discharge date, admitted to intensive care unit, respiratory culture with methicillin-resistant Staphylococcus aureus or Pseudomonas aeruginosa ≤12-months before admission, suspected concomitant infection, or complicated CAP.

EMR tools implemented March–May 2024 included a total antibiotic days counter and an inpatient stop date carryover on discharge order. The primary outcome was the proportion of patients prescribed ≤6-calendar-days of therapy. Secondary outcomes included 30-day CAP-related readmission, Clostridioides difficile infection (CDI), multidrug-resistant organisms (MDRO) ≤90-days of discharge, and days of therapy prescribed at discharge.

234 patients were included: 124 pre- and 110 post-intervention. A higher proportion of post-intervention patients received ≤6-days of therapy (54% pre- vs 72.7% post-intervention, P = 0.003). No notable differences were seen in CDI or MDROs. Pre-intervention patients experienced more CAP-related readmissions (12.1% pre- vs. 4.5% post-intervention, P = 0.039) and more days of therapy at discharge [3-d (IQR 2–4) pre- vs. 2-d (IQR 1–4) post-intervention, P < 0.001]. After adjustment for confounders, the post-intervention group had 2-fold increased odds of receiving ≤ 6-days of therapy for CAP (adjOR, 2.27; 95%CI, 1.31–3.93).

Implementation of EMR transitions of care tools significantly improved antibiotic durations in hospitalized adults with CAP, without negatively impacting patient outcomes.

Early-onset sepsis (EOS) is a significant cause of neonatal morbidity and mortality. Due to fear of missing cases, many newborns are unnecessarily exposed to antibiotics. We implemented the neonatal EOS calculator to reduce over-utilization of antibiotics and decrease costs.

Quality improvement study.

Neonatal Intensive Care Unit (NICU).

Infants born at ≥34 weeks’ gestation were divided between two periods: the pre-EOS calculator time frame and the post-EOS calculator time frame.

We changed our EOS evaluation for inborn infants by implementing the EOS-calculator and decreasing “rule-out sepsis” time frame from 48 to 36 hours for infants started on antibiotics.

1,306 infants, with similar demographics, were included: 814 in pre-EOS calculator time frame and 492 in post-EOS calculator time frame. Following our interventions, the percentage of NICU admissions ≥34 weeks’ gestation started on antibiotics decreased from 62% to 51% (P < .01). In the chorioamnionitis subgroup, antibiotic starts decreased by 50% (P < .01). There was a reduction in days of therapy per 1,000 NICU (168 vs 110, P < .01) and total (93 vs 57, P < .01) patient days. Fewer patients had blood cultures drawn (84% vs 67%, P < .01) with a decrease in infants treated for culture-negative sepsis (7% vs 3%, P < .01). NICU and hospital length of stay reduced by 1 day (P < .01), equivalent to a savings of $916,000 to $1.84 million per 1,000 NICU patients in costs and savings of $5.82 million to $12.5 million per 1,000 NICU patients in charges.

Antibiotic usage significantly decreased, with substantial savings after implementation of the EOS calculator, without significant negative effects.

With emerging variants of SARS-CoV-2, there is an increasing demand for comprehensive data on vaccine effectiveness disaggregated by vaccine type and/or country to frame future pandemic readiness plans.

We investigated comparative effectiveness (VE) of CoronaVac® and Comirnaty® vaccines among health students, considering potential risk factors. An open, prospective cohort study was conducted to follow participants with valid COVID-19 vaccinations, up to 2 years. Investigations included VE against symptomatic PCR-confirmed COVID-19 infections, along with vaccine-induced humoral immunity (including durability) and potential methodologic threats to conclusive decisions.

Symptomatic COVID-19 incidence rate was 4.24 (95% CI = 3.69–4.86) per 10,000 person-days among 1133 students (46.6% males) over 478,466 person-days. Taking a primary series/booster with CoronaVac as the reference, a primary series with Comirnaty or a Comirnaty booster protected students up to twenty times early in the pandemic, adjusting for covariates; significance disappeared in the Omicron period, though. Unexpected upsurges in virus-specific antibody levels, starting 3-6 months after the last vaccination when titers decreased to almost nill, suggested that disproportionality in vaccine durability could have led to a bias towards the null in VE estimates, due to mediator role of undetected breakthrough infections.

Hybrid immunity may differentially deplete the susceptibles in either arm of the study, leading to bias in VE estimations. High infection rate in Omicron period might have augmented this bias, favoring the protective effect of the less potent vaccine. Periodic PCR testing as an integrated measure in future VE studies can avoid such bias.

To identify system-level barriers to effective environmental cleaning and disinfection in long-term care (LTC) facilities.

Transdisciplinary, mixed-methods approach using human factors engineering and environmental sampling to assess environmental cleaning practices and associated multi-drug resistant organism (MDRO) burden in LTC patient rooms and common areas.

Two high-acuity skilled nursing facilities in Maryland.

Environmental sampling of high-touch surfaces (HTSs) was performed in resident rooms, communal areas, and nursing stations. Samples were analyzed for MDROs and overall bacterial burden. System-level barriers were assessed through observations of cleaning and focus groups with environmental services (EVS) staff and supervisors, guided by the Systems Engineering Initiative for Patient Safety (SEIPS) model.

Of 123 composite samples of environmental surfaces, 76% of patient room samples were culture positive for 1+ MDRO, with MRSA the most prevalent organism. Quantitative bacterial burden was higher from Composite 1 (the area in the room closest to the resident) than any other composite in the resident room (median of 27.17 CFU/mL/cm2 vs 4.55 (near door) and 1.22 (bathroom)). Observations indicated significant deviations from cleaning protocols, with only 43% of HTSs cleaned per facility policy. Focus group discussions highlighted systemic challenges, including inconsistent training, frequent interruptions, and poor communication among staff.

The findings underscore the burden of MDRO contamination in LTC settings and critical barriers to effective environmental cleaning. Addressing these issues through standardized training with feedback mechanisms, enhanced communication, and leadership engagement is essential for improving infection prevention efforts and resident safety in LTC facilities.

Artificial intelligence (AI)-based clinical decision support tools are increasingly developed for diagnostic stewardship, yet their clinical adoption remains limited. A barrier to implementation is concern about potential patient-level harm, particularly when algorithms recommend withholding diagnostic tests that would otherwise be standard practice. Existing evaluation frameworks emphasize aggregate performance metrics but do not provide structured methods to assess clinical consequences of algorithmic errors prior to implementation.

Developing a protocol for retrospective, patient-level evaluation of potential harms associated with false-negative predictions of an AI-tool for blood culture stewardship in the emergency department.

We developed a protocol to identify and evaluate cases at potential risk of harm following retrospective application of an AI-model predicting blood culture outcomes. False-negative cases, defined as positive blood cultures with a model-predicted probability below 5%, are selected after exclusion of contaminants and clinical scenarios in which the algorithm would not be applied. Multidisciplinary experts perform case-by-case evaluation using a questionnaire covering three domains: antibiotic management, diagnostic procedures, and patient outcomes, supplemented by overall harm and cost assessments. Inter-observer agreement is quantified, and discrepancies are resolved through expert adjudication.

This protocol is designed as a preimplementation safety assessment to support go/no-go decisions for advancing AI tools into clinical research or practice. By operationalizing patient-level harm assessment using routinely collected data, the framework complements existing AI evaluation standards and addresses a critical gap in diagnostic stewardship. Although developed for blood culture stewardship, the protocol may be adaptable to other AI-based decision support tools in infectious diseases and beyond.

Identify patients at increased risk of hospital-onset Staphylococcus aureus (SA) bacteremia based on objective and routinely collected data on presentation to the emergency room (ER).

Nested case–control study.

A large, inner city, tertiary care center between January 1, 2011 and August 31, 2020.

375 cases and 2,248 matched controls.

All hospitalized persons ≥18 years, found to have SA bacteremia at least 48 hours after admission were matched to 1–12 controls on birth year, race/ethnicity, sex, and month and year of admission. Vital signs and lab results were coded as “low” or “high” based on laboratory definitions. Multivariable models identified patient characteristics associated with an increased risk of SA bacteremia.

SA bacteremia was associated with high aspartate aminotransferase (AST) (>35 u/L )(HR = 1.92, 95%CI (1.30, 2.83), P = .001), high creatinine (Cr) (>1.1 mg/dl) (HR = 1.91, 95% CI (1.28, 2.85), P = .200), high bicarbonate (CO2) (>30 mEq/L) (HR = 2.07, 95% CI (1.17, 3.64), P = .01), and high total protein (>8.3 g/dl) (HR = 2.14, 95% CI (0.99, 4.66), P = .05). Fifteen or more days of hospital stay was associated with an increased risk of SA bacteremia (HR = 6.23, 95% CI (4.84, 8.00), P < .001).

A prediction tool applied on admission of hospital stay ≥15 days OR any elevated two of the following: AST, creatinine, CO2, or total protein has sensitivity between 57%–64% and specificity to between 65%–78%.

Whole genome sequencing (WGS) of microbes is a powerful tool for pathogen detection, antimicrobial resistance (AMR) genes, and outbreak analysis. However, WGS data analysis is a challenging process and a major limitation of adopting WGS in clinical use. In this manuscript, we performed in-depth review of three cloud-based sequencing data analysis platforms that are user-friendly and require minimal or no bioinformatics expertise.

Total of 90 bacterial isolates collected from inpatient units of the Central Texas Veterans healthcare system were sequenced on Nextseq 550 system (Illumina). FASTQ files generated after the sequencing were uploaded to the sequence analysis platforms: BugSeq™, EPISEQ® CS, and Solu. Each platform’ s usability, cost, output type, turnaround time from uploading files to results, and analysis output including number of identifiable pathogen species, AMR genes, and epidemiological clusters were assessed.

All platforms were easy to use and offered analysis features including pathogen identification, AMR gene and plasmid detection, and epidemiological analysis. Analysis results were generated within hours (BugSeq™ & EPISEQ® CS, 3 ∼ 4 hrs; Solu, 1 hr) after sequence file upload. All platforms identified most pathogen species correctly (BugSeq™, 89; EPISEQ® CS, 83; Solu, 87). Among 90 isolates, wide-ranging number of AMR genes were detected (BugSeq™, 83; EPISEQ® CS, 358; Solu, 137). Epidemiological clusters (closely related isolates) detection was also varied (BugSeq™, 9; EPISEQ® CS, 11; Solu, 12) because each platform used different methodologies.

While users need to consider factors such as cost, IT infrastructure, and data security, cloud-based platforms may ease barriers for adopting WGS for clinical and infection prevention purposes.