Authors
Anna Emilie Henius, Lone Jannok Porsbo, Anette M Hammerum, Matt Denwood, Kåre Mølbak, Henrik Hasman
Published in
International journal of medical informatics. Volume 223. Pages 106779. Oct 24, 2026. Epub Oct 24, 2026.
Abstract
Healthcare-associated infections remain a major public health challenge worldwide. Effective surveillance requires timely identification of epidemiological links. Although electronic health records are widely used, their complexity often hinder rapid analysis in practice. We developed EpiLinx, a user-friendly tool that uses administrative patient data to support systematic investigation of suspected outbreaks in healthcare settings. The aim of this paper is to present EpiLinx and assess its usability against two real-life healthcare associated outbreaks.
EpiLinx is an R shiny application that identifies spatio-temporal overlaps between patients' hospital contacts in extensive datasets. It provides interactive tables and visualizations, including timelines and network diagrams, to support rapid data exploration. The software is designed to be generic with minimal data requirements to ensure accessibility for non-technical users.
EpiLinx was applied to a Danish Enterobacter hormaechei outbreak and a British norovirus outbreak. In both cases, EpiLinx rapidly generated visualizations and network structures consistent with the conclusions of the original investigations. Analyses that previously required hours of manual data handling were completed within seconds.
EpiLinx enables rapid and intuitive exploration of epidemiological links in large healthcare datasets, supporting more timely outbreak investigations. Its simplicity and minimal data requirements make it readily applicable in clinical practice, including for non-technical users. The approach is broadly applicable across settings where routinely collected administrative data are available. By improving transparency and accessibility in link assessment, EpiLinx has the potential to strengthen infection control in both clinical and public health contexts.
PMID:
42933268
Bibliographic data and abstract were imported from PubMed on 27 Oct 2026.
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