COVID-19 clusters in a teaching hospital during the second wave of the SARS-CoV-2 pandemic in France: A descriptive study and lessons learned for waves to come.

A total of 92 coronavirus disease 2019 clusters involving 1,156 individuals (729 patients and 427 healthcare workers) occurred in Lyon University Hospital between September 1, 2020 and March 31, 2021, mostly on medical and geriatric wards. The number of clusters was closely correlated to the trend in coronavirus disease 2019 community incidence over time; in-hospital clusters did not persist when community incidence decreased. Recommended preventive measures were not fully applicable due to specific ward-associated determinants and patient characteristics.

Evaluation of natural language processing from emergency department computerized medical records for intra-hospital syndromic surveillance.

Background: The identification of patients who pose an epidemic hazard when they are admitted to a health facility plays a role in preventing the risk of hospital acquired infection. An automated clinical decision support system to detect suspected cases, based on the principle of syndromic surveillance, is being developed at the University of Lyon's Hôpital de la Croix-Rousse. This tool will analyse structured data and narrative reports from computerized emergency department (ED) medical records.

Automated detection of nosocomial infections: evaluation of different strategies in an intensive care unit 2000-2006.

The aim of this study was to evaluate seven different strategies for the automated detection of nosocomial infections (NIs) in an intensive care unit (ICU) by using different hospital information systems: microbiology database, antibiotic prescriptions, medico-administrative database, and textual hospital discharge summaries. The study involved 1,499 patients admitted to an ICU of the University Hospital of Lyon (France) between 2000 and 2006. The data were extracted from the microbiology laboratory information system, the clinical information system on the ward and the medico-administrative database.

[Use of the French medico-administrative database (PMSI) to detect nosocomial infections in the University hospital of Lyon].

Background: Surveillance is an effective element in the fight against nosocomial infections, but the monitoring methods are often cumbersome and time consuming. The detection of infection in computerized databases is a means to alleviate the workload of health care teams. The objective of this study was to evaluate the performance of using discharge summaries in medico-administrative databases (PMSI) for the identification of nosocomial infections in surgery, intensive care and obstetrics.