Candida auris inpatient screening in collaboration with the public health department.

Candida auris is a multidrug-resistant fungal pathogen that is associated with nosocomial outbreaks in patients with extensive health care exposure and treatment outside the United States. The Ohio Department of Health recommends C auris screening in high-risk patients. However, this can be operationally difficult for many health care facilities. This report describes a C auris and carbapenem-resistant Enterobacterales inpatient screening program done in collaboration with state public health.

Outbreak of postpartum group a Streptococcus infections on a labor and delivery unit.

A healthcare-associated group A Streptococcus outbreak involving six patients, four healthcare workers, and one household contact occurred in the labor and delivery unit of an academic medical center. Isolates were highly related by whole genome sequencing. Infection prevention measures, healthcare worker screening, and chemoprophylaxis of those colonized halted further transmission.

Describing the monthly variability of hospital-onset Clostridioides difficile during early coronavirus disease 2019 (COVID-19) using electronic health record data.

OBJECTIVE: To assess the relative risk of hospital-onset Clostridioides difficile (HO-CDI) during each month of the early coronavirus disease 2019 (COVID-19) pandemic and to compare it with historical expectation based on patient characteristics. DESIGN: This study used a retrospective cohort design. We collected secondary data from the institution's electronic health record (EHR). SETTING: The Ohio State University Wexner Medical Center, Ohio, a large tertiary healthcare system in the Midwest. PATIENTS OR PARTICIPANTS: All adult patients admitted to the inpatient setting between January 2018 and May 2021 were eligible for the study. Prisoners, children, individuals presenting with Clostridioides difficile on admission, and patients with <4 days of inpatient stay were excluded from the study. RESULTS: After controlling for patient characteristics, the observed numbers of HO-CDI cases were not significantly different than expected. However, during 3 months of the pandemic period, the observed numbers of cases were significantly different from what would be expected based on patient characteristics. Of these 3 months, 2 months had more cases than expected and 1 month had fewer. CONCLUSIONS: Variations in HO-CDI incidence seemed to trend with COVID-19 incidence but were not fully explained by our case mix. Other factors contributing to the variability in HO-CDI incidence beyond listed patient characteristics need to be explored.

Novel Visualization of Clostridium difficile Infections in Intensive Care Units.

BACKGROUND: Accurate and timely surveillance and diagnosis of healthcare-facility onset Clostridium difficile infection (HO-CDI) is vital to controlling infections within the hospital, but there are limited tools to assist with timely outbreak investigations. OBJECTIVES: To integrate spatiotemporal factors with HO-CDI cases and develop a map-based dashboard to support infection preventionists (IPs) in performing surveillance and outbreak investigations for HO-CDI. METHODS: Clinical laboratory results and Admit-Transfer-Discharge data for admitted patients over two years were extracted from the Information Warehouse of a large academic medical center and processed according to Center for Disease Control (CDC) National Healthcare Safety Network (NHSN) definitions to classify Clostridium difficile infection (CDI) cases by onset date. Results were validated against the internal infection surveillance database maintained by IPs in Clinical Epidemiology of this Academic Medical Center (AMC). Hospital floor plans were combined with HO-CDI case data, to create a dashboard of intensive care units. Usability testing was performed with a think-aloud session and a survey. RESULTS: The simple classification algorithm identified all 265 HO-CDI cases from 1/1/15-11/30/15 with a positive predictive value (PPV) of 96.3%. When applied to data from 2014, the PPV was 94.6% All users "strongly agreed" that the dashboard would be a positive addition to Clinical Epidemiology and would enable them to present Hospital Acquired Infection (HAI) information to others more efficiently. CONCLUSIONS: The CDI dashboard demonstrates the feasibility of mapping clinical data to hospital patient care units for more efficient surveillance and potential outbreak investigations.

Development and validation of an automated ventilator-associated event electronic surveillance system: A report of a successful implementation.

BACKGROUND: Surveillance is an important tool for infection control; however, this task can often be time-consuming and take away from infection prevention activities. With the increasing availability of comprehensive electronic health records, there is an opportunity to automate these surveillance activities. The objective of this article is to describe the implementation of an electronic algorithm for ventilator-associated events (VAEs) at a large academic medical center METHODS: This article reports on a 6-month manual validation of a dashboard for VAEs. We developed a computerized algorithm for automatically detecting VAEs and compared the output of this algorithm to the traditional, manual method of VAE surveillance. RESULTS: Manual surveillance by the infection preventionists identified 13 possible and 11 probable ventilator-associated pneumonias (VAPs), and the VAE dashboard identified 16 possible and 13 probable VAPs. The dashboard had 100% sensitivity and 100% accuracy when compared with manual surveillance for possible and probable VAP. We report on the successfully implemented VAE dashboard. Workflow of the infection preventionists was simplified after implementation of the dashboard with subjective time-savings reported. CONCLUSIONS: Implementing a computerized dashboard for VAE surveillance at a medical center with a comprehensive electronic health record is feasible; however, this required significant initial and ongoing work on the part of data analysts and infection preventionists.

Infection control link nurse program: an interdisciplinary approach in targeting health care-acquired infection.

BACKGROUND: We describe a successful interdisciplinary liaison program that effectively reduced health care-acquired (HCA), methicillin-resistant Staphylococcus aureus (MRSA) in a university hospital setting. METHODS: Baseline was from January 2006 to March 2008, and intervention period was April 2008 to September 2009. Staff nurses were trained to be liaisons (link nurses) to infection prevention (IP) personnel with clearly defined goals assigned and with ongoing monthly education. HCA-MRSA incidence per 1,000 patient-days (PD) was compared between baseline and intervention period along with total and non-HCA-MRSA, HCA and non-HCA-MRSA bacteremia, and hand soap/sanitizer usage. Hand hygiene compliance was assessed. RESULTS: A reduction in MRSA rates was as follows in intervention period compared with baseline: HCA-MRSA decreased by 28% from 0.92 to 0.67 cases per 1,000 PD (incidence rate ratio, 0.72; 95% confidence interval: 0.62-0.83, P < .001), and HCA-MRSA bacteremia rate was reduced by 41% from 0.18 to 0.10 per 1,000 PD (incidence rate ratio, 0.59; 95% confidence interval: 0.42-0.84, P = .003). Total MRSA rate and MRSA bacteremia rate also showed significant reduction with nonsignificant reductions in overall non-HCA-MRSA and non-HCA-MRSA bacteremia. Hand soap/sanitizer usage and compliance with hand hygiene also increased significantly during IP. CONCLUSION: Link nurse program effectively reduced HCA-MRSA. Goal-defined metrics with ongoing re-education for the nurses by IP personnel helped drive these results.