Leveraging Clinical Data Warehouses to Detect Potential False-Negatives EBV Patients Automatically

Epstein-Barr virus infects over 90% of the adults and timely detection of severe infection or reinfection is essential to avoid complications. Since January 2024, the new serology kit to detect EBV was used at Rennes University Hospital, and virologists observed discrepancies between serologies and PCR results. We developed an algorithm using the clinical data warehouse to identify patients with negative EBV serology, but who could be positive at PCR. The algorithm is based on searching keywords associated with the symptoms/characteristics of the EBV infections in clinical notes of patients with a negative EBV serology. By crossing the criteria, we detected potential FN patients. The virologists are alerted by an email sent automatically and could provide better care.