Multihospital Outbreak of Clostridium difficile Ribotype 027 Infection: Epidemiology and Analysis of Control Measures

Objective. To report a large outbreak of Clostridium difficile infection (CDI; ribotype 027) between June 2007 and August 2008, describe infection control measures, and evaluate the impact of restricting the use of fluoroquinolones in controlling the outbreak. Design. Outbreak investigation in 3 acute care hospitals of the Northern Health and Social Care Trust in Northern Ireland. Interventions. Implementation of a series of CDI control measures that targeted high-risk antibiotic agents (ie, restriction of fluoroquinolones), infection control practices, and environmental hygiene. Results. A total of 318 cases of CDI were identified during the outbreak, which was the result of the interaction between C. difficile ribotype 027 being introduced into the affected hospitals for the first time and other predisposing risk factors (ranging from host factors to suboptimal compliance with antibiotic guidelines and infection control policies). The 30-day all-cause mortality rate was 24.5%; however, CDI was the attributable cause of death for only 2.5% of the infected patients. Time series analysis showed that restricting the use of fluoroquinolones was associated with a significant reduction in the incidence of CDI (coefficient, —0.054; lag time, 4 months; P = .003). Conclusion. These findings provide additional evidence to support the value of antimicrobial stewardship as an essential element of multifaceted interventions to control CDI outbreaks. The present CDI outbreak was ended following the implementation of an action plan improving communication, antibiotic stewardship, infection control practices, environmental hygiene, and surveillanc

Antibiotic Review Kit for Hospitals (ARK-Hospital): a stepped wedge cluster randomised controlled trial

Background: Strategies to reduce antibiotic overuse in hospitals depend on clinicians reviewing antibiotics which have been started empirically. There is a lack of evidence on how to do this effectively. We evaluated a multifaceted behaviour change intervention (ARK) aimed at reducing antibiotic consumption in hospitals by increasing prescriber decisions to stop antibiotics at clinical review. Methods: We performed a stepped-wedge, hospital-level, cluster -randomised controlled trial using computer-generated sequence randomisation of 39 acute hospitals to 7 calendar-time blocks (12/February/2018–01/July/2019). Co-primary outcomes were monthly antibiotic defined-dailydoses (DDD) per acute/medical admission (organisation-level, superiority) and all-cause 30-day mortality (patient-level, non-inferiority, margin 5%). Clusters were eligible if they admitted nonelective medical patients, could identify an intervention “champion” and provide pre-intervention data from February/2016. Sites were followed up for a minimum of 14 months. Intervention effects were assessed using interrupted time series analyses in each cluster. Overall effects were derived through random-effects meta-analysis, using meta-regression to assess heterogeneity in effects across prespecified factors. Trial registration was ISRCTN12674243. Findings: Adjusted estimates showed a year-on-year reduction in antibiotic consumption (-4.8%, 95%CI: -9.1%,-0.2%, p=0.042) following the ARK intervention. Among 7,160,421 acute/medicaladmissions, we observed a -2.7% (95%CI: -5.7%,+0.3%, p=0.079) immediate and +3.0% (95%CI: - 0.1%,+6.2%, p=0.060) sustained change in adjusted 30-day mortality. This mortality trend was not related to the magnitude of antibiotic reduction achieved (Spearman’s ρ=0.011, p=0.949). Whilst 90- day mortality odds appeared to increase over time (+3.9%, 95%CI:+0.5%,+7.4%, p=0.023), this was not observed among admissions before COVID-19 onset (+3.2%, 95%CI:-1.5%,+8.2%, p=0.182). Length of hospital stay was unaffected. Interpretation: The weak, inconsistent effects of the intervention on mortality are likely to be explained by the COVID-19 pandemic onset during the post-implementation phase. We conclude that the ARK-intervention resulted in sustained, safe reductions in hospital antibiotic use

Challenges When Using Grounded Theory

The grounded theory (GT) method is widely applied, yet frequently misunderstood. We outline the main variants of GT and dispel the most common myths associated with GT. We argue that the different variants of GT incorporate a core set of shared procedures that can be put to work by any researcher or team from their chosen ontological and epistemological perspective. This “shared core” of the GT method is articulated as the principles of (1) taking the word “grounded” seriously, (2) capturing and explaining context-related social processes, (3) pursuing theory through engagement with data, and (4) pursuing theory through theoretical sampling. In this article, we have put forward, in a nutshell, a distillation of core principles underpinning existing GT approaches that can aid further engagement with the different variants of GT. We are motivated by the wish to make GT more comprehensible and accessible, especially for researchers who are new to the method

Confused about theoretical sampling? Engaging theoretical sampling in diverse grounded theory studies

Theoretical sampling is a key procedure for theory building in the grounded theory method. Confusion about how to employ theoretical sampling in grounded theory can exist among researchers who use or who want to use the grounded theory method. We illustrate how we employed theoretical sampling in diverse grounded theory studies and answer key questions about theoretical sampling in grounded theory. We show how theoretical sampling functions in grounded theory and how it differs from sampling for data generation alone. We demonstrate how induction, retroduction and abduction operate in grounded theory and how memoing drives theoretical sampling in the pursuit of theory. We explicate how theoretical sampling can contextualize data in order to build concepts and theory. Finally, we show how theoretical sampling in grounded theory operates in secondary analysis to derive theory that goes beyond the original purpose of data collection

Effects of Antibiotic Cycling Policy on Incidence of Healthcare-Associated MRSA and <em>Clostridioides difficile</em> Infection in Secondary Healthcare Settings

This quasi-experimental study investigated the effect of an antibiotic cycling policy based on time-series analysis of epidemiologic data, which identified antimicrobial drugs and time periods for restriction. Cyclical restrictions of amoxicillin/clavulanic acid, piperacillin/tazobactam, and clarithromycin were undertaken over a 2-year period in the intervention hospital. We used segmented regression analysis to compare the effect on the incidence of healthcare-associated Clostridioides difficile infection (HA-CDI), healthcare-associated methicillin-resistant Staphylococcus aureus (HA-MRSA), and new extended-spectrum β-lactamase (ESBL) isolates and on changes in resistance patterns of the HA-MRSA and ESBL organisms between the intervention and control hospitals. HA-CDI incidence did not change. HA-MRSA incidence increased significantly in the intervention hospital. The resistance of new ESBL isolates to amoxicillin/clavulanic acid and piperacillin/tazobactam decreased significantly in the intervention hospital; however, resistance to piperacillin/tazobactam increased after a return to the standard policy. The results question the value of antibiotic cycling to antibiotic stewardship