Patients with Opioid Use Disorder (OUD) are prone to Multidrug-Resistant Organism (MDRO) colonization and infections, thus at risk for worse outcomes during critical illness. Understanding the prevalence and predictors of MDRO infections is essential to optimize interventions and treatments.

Retrospective cohort study.

The study evaluated the prevalence of MDRO isolation among adults with OUD admitted to an intensive care unit (ICU) between January 1, 2018, and July 31, 2023. It included adults admitted to an ICU with bacterial infections and positive cultures obtained within 48 hours of admission. Demographics, clinical traits, and MDRO isolation rates were analyzed using descriptive statistics, univariate methods, and Least Absolute Shrinkage and Selection Operator (LASSO) regression.

MDRO isolation occurred in 178 of 790 patients (22.5%), with methicillin-resistant Staphylococcus aureus as the most frequently isolated organism. LASSO regression identified housing insecurity (OR: 1.79, 95% CI 1.09–2.93, P = .022), no receipt of medications for OUD treatment (OR: 1.56, 95% CI 1.06–2.29, P = .023), positive hepatitis C virus (HCV) status (OR: 2.19, 95% CI 1.19–4.03, P = .012), and intravenous antibiotic use in the prior 90 days (OR: 1.04 per 24 h, 95% CI 1.01–1.07, P = .007) as significant predictors of MDRO isolation.

The study highlights a high prevalence of MDRO isolation in critically ill OUD patients admitted for infection-related issues with positive cultures obtained within 48 hours of admission, influenced by factors like housing insecurity, no receipt of medications for OUD treatment, HCV status, and prior antibiotic use.

Medicare claims are frequently used to study Clostridioides difficile infection (CDI) epidemiology. However, they lack specimen collection and diagnosis dates to assign location of onset. Algorithms to classify CDI onset location using claims data have been published, but the degree of misclassification is unknown.

We linked patients with laboratory-confirmed CDI reported to four Emerging Infections Program (EIP) sites from 2016–2021 to Medicare beneficiaries with fee-for-service Part A/B coverage. We calculated sensitivity of ICD-10-CM codes in claims within ±28 days of EIP specimen collection. CDI was categorized as hospital, long-term care facility, or community-onset using three different Medicare claims-based algorithms based on claim type, ICD-10-CM code position, duration of hospitalization, and ICD-10-CM diagnosis code presence-on-admission indicators. We assessed concordance of EIP case classifications, based on chart review and specimen collection date, with claims case classifications using Cohen’s kappa statistic.

Of 12,671 CDI cases eligible for linkage, 9,032 (71%) were linked to a single, unique Medicare beneficiary. Compared to EIP, sensitivity of CDI ICD-10-CM codes was 81%; codes were more likely to be present for hospitalized patients (93.0%) than those who were not (56.2%). Concordance between EIP and Medicare claims algorithms ranged from 68% to 75%, depending on the algorithm used (κ = 0.56–0.66).

ICD-10-CM codes in Medicare claims data had high sensitivity compared to laboratory-confirmed CDI reported to EIP. Claims-based epidemiologic classification algorithms had moderate concordance with EIP classification of onset location. Misclassification of CDI onset location using Medicare algorithms may bias findings of claims-based CDI studies.

Many post-acute and long-term care settings (PALTCs) struggle to measure antibiotic use via the standard metric, days of therapy (DOT) per 1000 days of care (DOC). Our objective was to develop antibiotic use metrics more tailored to PALTCs.

Retrospective cohort study with a validation cohort.

PALTC settings within the same network.

We obtained census data and pharmacy dispensing data for 13 community PALTCs (January 2020–December 2023). We calculated antibiotic DOT/1000 DOC, DOT per unique residents, and antibiotic starts per unique residents, at monthly intervals for community PALTCs. The validation cohort was 135 Veterans Affairs Community Living Centers (VA CLCs). For community PALTCs only, we determined the DOT and antibiotics starts per unique residents cared for by individual prescribers.

For community PALTCs, the correlation between facility-level antibiotic DOT/1000 DOC and antibiotic DOT/unique residents and antibiotic courses/unique residents was 0.97 (P < 0.0001) and 0.84 (P < 0.0001), respectively. For VA CLCs, those values were 0.96 (P < 0.0001) and 0.85 (P < 0.0001), respectively. At community PALTCs, both novel metrics permitted assessment and comparison of antibiotic prescribing among practitioners.

At the facility level, the novel metric antibiotic DOT/unique residents demonstrated strong correlation with the standard metric. In addition to supporting tracking and reporting of antibiotic use among PALTCs, antibiotic DOT/unique residents permits visualization of the antibiotic prescribing rates among individual practitioners, and thus peer comparison, which in turn can lead to actionable feedback that helps improve antibiotic use in the care of PALTC residents.

To assess the association between social vulnerability index (SVI) and surgical site infections (SSIs) using National Healthcare Safety Network (NHSN) criteria.

Retrospective cohort study between August 1, 2022, and August 31, 2023.

In total, 20 acute care hospitals in the Southeast United States.

Totally, 23,768 total hip arthroplasty, total knee arthroplasty, abdominal hysterectomy, colon, and spinal fusion surgeries in 22,239 patients were included. Procedures with infection present at the time of surgery or incomplete geographic tracking data were excluded.

Patient addresses as noted in the electronic health record were geocoded to determine census tract of residence and determine SVI. Demographic and clinical data were linked with SVI scores. SSIs were identified according to NHSN criteria. SVI was categorized into quartiles, and logistic regression was used to evaluate the association between SVI quartile (overall and for each SVI theme) and SSI risk. Subgroup analyses by procedure type and race were performed. Multivariable models of the association between overall SVI and SSI were adjusted for demographic and clinical factors.

Patients in the top SVI quartiles had significantly higher odds of developing SSIs after adjusting for other clinical and demographic factors. Increased risk was found for socioeconomic status and household characteristics themes, but not for the racial/ethnic minority theme. Association between SVI and SSI risk varied by type of surgery.

Living in an area with a higher SVI is associated with increased SSI risk. Targeted interventions are needed to mitigate these disparities and improve outcomes.

An association between weekend/off-hour care and unfavorable clinical outcomes has been observed, commonly called the “weekend effect.” In the present study, we examined whether there was a weekend effect associated with blood culture (BC) contamination, which can lead to inappropriate medical resource consumption.

We conducted a single-center retrospective observational study using data from BC tests performed on adult patients. The primary outcome was the incidence of BC contamination, which was compared between weekend and weekday sampling groups. In a multivariable logistic analysis, we evaluated the association between weekend sampling and the incidence of BC contamination.

The analysis included 7,597 weekend and 50,655 weekday BC sets from 1 January 2013 to 31 December 2019. The proportion of BC contamination during the study period was 1.15% (87/7,597) and 0.80% (405/50,655) in the weekend and weekday groups, respectively. In the logistic regression analysis adjusted for blood sampling settings, weekend sampling was significantly associated with increased BC contamination (odds ratio, 1.36; 95% confidence interval, 1.06–1.71).

This study highlighted a significant association between weekend blood sampling for BC and an increased incidence of contamination. To provide better-quality care, further studies evaluating the differences in staffing and blood collection processes on weekends and weekdays are warranted.

To identify global research priorities for improving hand hygiene in healthcare settings and develop a 2023–2030 research agenda to guide funding, coordinate research, promote investment, and inform policy for enhanced healthcare quality and safety.

Expert consensus study using a modified Delphi process.

A 105-member panel of international hand hygiene experts including the World Health Organization (WHO) Technical Advisory Group of Experts on Hand Hygiene in Healthcare representing all WHO regions and World Bank income levels.

The research priorities were identified through a multiphase approach including a meta-review to establish knowledge gaps and inform initial priorities, followed by expert consultations using a modified Delphi process. 192 preliminary priorities were included in a two-round Delphi survey. Experts rated each priority in the first round, and then reviewed and adjusted responses based on the panel’s aggregated, anonymous responses in the second round. Ratings were collected on a five-point Likert scale. Consensus was defined as a combined “strongly agree” and “agree” frequency of at least 70%.

Consensus was achieved for 178 of 192 priorities (92.7%), categorized into six domains: system change; training and education; evaluation and feedback; reminders and communications; institutional safety climate; and hand hygiene improvement impact on healthcare-associated infections and antimicrobial resistance. Of these, 121 priorities reached >80% consensus. The Delphi process, maintained a 92% response rate over two rounds.

A structured consensus process yielded a research agenda to address gaps in hand hygiene improvement, supporting enhanced healthcare quality and safety globally.

Concerns about penicillin-cephalosporin cross-reactivity have historically led to conservative prescribing and avoidance of cephalosporins in patients with penicillin allergy labels, potentially causing suboptimal outcomes. Recent evidence suggests a lower risk of cross-reactivity, prompting a reassessment of alert systems.

To assess the impact of limited penicillin cross-reactivity alerts on outpatient cephalosporin use and the incidence of adverse reactions in a healthcare setting.

This retrospective cohort study compared cephalosporin prescribing and adverse reactions in patients labeled as penicillin-allergic before and after limiting penicillin cross-reactivity alerts in the electronic medical record at a large academic medical center.

Among 17,174 patients (8,131 pre- and 9,043 post-implementation), there was a statistically significant increase in outpatient cephalosporin prescribing by 8% (P < .001). The use of alternative antibiotic classes decreased. There was no statistically significant increase in adverse events pre- and post-implementation (0.036%–0.058%, P = .547), and no severe events were attributable to cross-reactivity. The alert modification reduced alerts by 92% (P < .001).

The reduction of penicillin-cephalosporin cross-reactivity alerts was associated with increased cephalosporin use, without a significant increase in adverse reactions. This demonstrates that the practice is safe and decreases alert burden.

Evaluate Department of Defense (DoD) antimicrobial stewardship programs (ASPs) by assessing the relationship between key clinical outcome metrics (antibiotic use, incidence of resistant pathogens, and incidence of Clostridioides difficile infections) and CDC Core Element (CE) adherence.

Retrospective, cross-sectional study of DoD hospitals in 2018 and 2021

National Healthcare Safety Network Standardized Antimicrobial Administration Ratios (SAARs) were used to measure antibiotic use and microbiology results to evaluate four types of pathogen incidence. A novel CE scoring approach used scores to quantitatively assess relationships with CE adherence and outcome metrics using correlation and regression models. Assessments were repeated with 2021 data for Priority CE adherence and to conduct adjusted regressions for CEs and Priority CEs controlling for categorical bed size.

Compared to 2022 national data, DoD hospitals in 2021 had a similar proportion of facilities with a SAAR statistically significantly > 1.0. Leadership, Action, and Tracking CEs followed a more normal score distribution, while Reporting and Education were somewhat left-skewed. Unadjusted models often showed a positive relationship with higher CE scores associated with worse outcomes for the SAAR and pathogen incidence. Adjusted models indicated that procedural CEs, particularly Priority Reporting, were associated with better ASP-related outcomes.

CEs should be more quantitatively assessed. Results provide initial evidence to prioritize procedural CE implementation within the DoD; however, additional investigation for structural CEs is needed. Patient outcome data should be collected as an important indicator of ASP performance.

To better understand clinicians’ rationale for ordering testing for C. difficile infection (CDI) for patients receiving laxatives and the impact of the implementation of a clinical decision support (CDS) intervention.

A mixed-methods, case series was performed from March 2, 2017 to December 31, 2018.

Yale New Haven Hospital, a 1,541 bed tertiary academic medical center.

Hospitalized patients ≥ 18 years old, and clinicians who were alerted by the CDS.

CDS was triggered in real-time when a clinician sought to order testing for CDI for a patient who received one or more doses of laxatives within the preceding 24 hours.

A total of 3,376 CDS alerts were triggered during the 21-month study period from 2,567 unique clinician interactions. Clinicians bypassed the CDS alert 74.5% of the time, more frequent among residents (48.3% bypass vs. 39.9% accept) and advanced practice providers (APPs) (34.9% bypass vs. 30.6% accept) than attendings (11.3% bypass vs. 22.5% accept). Ordering clinicians noted increased stool frequency/output (48%), current antibiotic exposure (34%), and instructions by an attending physician to test (28%) were among the most common reasons for overriding the alert and proceeding with testing for CDI.

Testing for CDI despite patient laxative use was associated with an increased clinician concern for CDI, patient risk for CDI, and attending physician instruction for testing. Attendings frequently accepted CDS guidance while residents and APPs often reinstated CDI test orders, suggesting a need for greater empowerment and discretion when ordering tests.

Central line-associated bloodstream infections (CLABSIs) result in morbidity and mortality among hospitalized patients. Hospital interventions to reduce the incidence of CLABSI are often broadly applied to all patients with central venous access. Identifying central lines at high risk for CLABSI at time of insertion will allow for a more focused delivery of preventative interventions.

This was an observational cohort study conducted at three hospitals including all patients who received central venous access. CLABSIs were identified using an institutional CLABSI database maintained by the hospital epidemiology team. Logistic regression (LASSO) and machine learning (random forest, XGboost) techniques were applied for the prediction of CLABSI occurrence, adjusting for selected patent and insertion-level characteristics.

A total of 40,008 central venous catheters were included, of which 409 (1.02%) were associated with CLABSI. The random forest and the XGBoost models had the highest discrimination (Area Under the Received Operating Curve [AUC] 0.79) followed by LASSO (0.73). High illness severity, receipt of total parenteral nutrition, receipt of hemodialysis, pre-insertion hospital length-of-stay, and low albumin levels were all predictive of CLABSI occurrence. Precision for all models was poor owing to a high false-positive rate.

CLABSI can be predicted based upon patient and insertion level factors in the electronic health record. In this study, random forest and gradient-boosted models had the highest AUC. Prediction cut-offs for the identification of CLABSI can be adjusted based upon the acceptable rate of false-positives for a given CLABSI preventative intervention.