Identifying Importation and Asymptomatic Spreaders of Multi-drug Resistant Organisms in Hospital Settings.

Healthcare-associated infections (HAIs) due to multi-drug resistant organisms (MDROs) are a significant burden to the healthcare system. Patients are sometimes already infected at the time of admission to the hospital (referred to as "importation"), and additional patients might get infected in the hospital through transmission ("nosocomial infection"). Since many of these importation and nosocomial infection cases may present no symptoms (i.

Improving Risk Prediction of Methicillin-Resistant Staphylococcus aureus Using Machine Learning Methods With Network Features: Retrospective Development Study.

Background: Health care-associated infections due to multidrug-resistant organisms (MDROs), such as methicillin-resistant Staphylococcus aureus (MRSA) and Clostridioides difficile (CDI), place a significant burden on our health care infrastructure.

Objective: Screening for MDROs is an important mechanism for preventing spread but is resource intensive. The objective of this study was to develop automated tools that can predict colonization or infection risk using electronic health record (EHR) data, provide useful information to aid infection control, and guide empiric antibiotic coverage.

Modeling relaxed policies for discontinuation of methicillin-resistant contact precautions.

Objective: To evaluate the economic costs of reducing the University of Virginia Hospital's present "3-negative" policy, which continues methicillin-resistant (MRSA) contact precautions until patients receive 3 consecutive negative test results, to either 2 or 1 negative.

Design: Cost-effective analysis.

Settings: The University of Virginia Hospital.