Antimicrobial resistance is increased by antibiotic overuse, so it’s crucial for stewardship programs to monitor and control their use. Pneumonia, particularly prevalent among older adults in Japan, is requiring higher rates of medical treatment. This study aimed to develop an improved method for benchmarking broad-spectrum antibiotic use in the empiric treatment of pneumonia in older adult inpatients by applying the “smoothed” observed-to-expected (O/E) ratio which adjusts for hospital-level variations and minimizes the effect of extreme values.

Using nationwide data from the Diagnosis Procedure Combination research group, pneumonia patients between April 1st 2018 and March 31st 2020 were analyzed. The primary outcome was the smoothed O/E ratio of the broad-spectrum antibiotic use for hospitals. It was calculated from the predicted values of broad-spectrum antibiotic use that were obtained through multilevel logistic regression using patient characteristics as predictors from data clustered by hospitals. The analysis investigated the risk-adjusted use of broad-spectrum antibiotics among hospitals.

A total of 244,747 patients from 958 hospitals were included, with a mean age of 81 (±8.30) years. The proportion of broad-spectrum antibiotic use was 35.3% (n = 86,316). The prediction model showed a C-statistic of 0.722. There was a noticeable variation in the O/E ratio among hospitals with values ranging from 0.13 (95% CI: 0.09–0.20) to 2.81 (95% CI: 2.64–2.97).

Using a risk-adjusted smoothed O/E ratio, we assessed the use of broad-spectrum antibiotics across hospitals, identifying those with high O/E ratios that may indicate a need for improvement.

Clinical trials for assessing the effects of infection prevention and control (IPC) interventions are expensive and have shown mixed results. Mathematical models can be relatively inexpensive tools for evaluating the potential of interventions. However, capturing nuances between institutions and in patient populations have adversely affected the power of computational models of nosocomial transmission.

In this study, we present an agent-based model of ICUs in a tertiary care hospital, which directly uses data from the electronic medical records (EMR) to simulate pathogen transmission between patients, HCWs, and the environment. We demonstrate the application of our model to estimate the effects of IPC interventions at the local hospital level. Furthermore, we identify the most important sources of uncertainty, suggesting areas for prioritization in data collection.

Our model suggests that the stochasticity in ICU infections was mainly due to the uncertainties in admission prevalence, hand hygiene compliance/efficacy, and environmental disinfection efficacy. Analysis of interventions found that improving mean HCW compliance to hand hygiene protocols to 95% from 70%, mean terminal room disinfection efficacy to 95% from 50%, and reducing post-handwashing residual contamination down to 1% from 50%, could reduce infections by an average of 36%, 31%, and 26%, respectively.

In-silico models of transmission coupled to EMR data can improve the assessment of IPC interventions. However, reducing the uncertainty of the estimated effectiveness requires collecting data on unknown or lesser known epidemiological and operational parameters of transmission, particularly admission prevalence, hand hygiene compliance/efficacy, and environmental disinfection efficacy.

To identify and present the pathogens and sources of contamination linked to outbreaks within hematopoietic stem cell transplant (HSCT) units.

Systematic review.

Inpatient HSCT units.

The PubMed/Medline databases were systematically searched as per the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, employing the search terms “stem cell”, “bone marrow”, “transplant”, “transplantation”, “outbreak” and “pseudo-outbreak” from inception until July 31, 2024. Data on the type of event, pathogen involved, and source of contamination were extracted from eligible publications.

In total, 39 studies including 387 patients were included in this review. The overall mortality rate was 23%. Pathogens identified included adenovirus, RSV, Pseudomonas aeruginosa, Aspergillus spp., and non-tuberculous mycobacteria (NTM). P. aeruginosa outbreaks were associated with contaminated sanitary fixtures (P = .007) and water (P = .039), outbreaks caused by NTM were associated with water (P = .009), while Aspergillus spp. outbreaks were associated with construction (P < .001). An index case was identified in 36.8% of viral outbreaks (P = .016). Other sources included inadequate disinfection and transmission from visitors.

Our study highlights several associations between pathogens involved in HSCT unit outbreaks and their respective sources. Establishing standardized guidelines for unit construction – particularly for ventilation and water safety – could further reduce the risk of pathogen transmission and enhance infection prevention in these high-risk settings.

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.