Real-time clinician text feeds from electronic health records

• Main Authors: James T. H. Teo, Vlad Dinu, William Bernal, Phil Davidson, Vitaliy Oliynyk, Cormac Breen, Richard D. Barker, Richard J. B. Dobson
• Format: Article
• Language: English
• Published: Nature Publishing Group 2021-02-01
• Series: npj Digital Medicine
• Online Access: https://doi.org/10.1038/s41746-021-00406-7

Abstract Analyses of search engine and social media feeds have been attempted for infectious disease outbreaks, but have been found to be susceptible to artefactual distortions from health scares or keyword spamming in social media or the public internet. We describe an approach using real-time aggregation of keywords and phrases of freetext from real-time clinician-generated documentation in electronic health records to produce a customisable real-time viral pneumonia signal providing up to 4 days warning for secondary care capacity planning. This low-cost approach is open-source, is locally customisable, is not dependent on any specific electronic health record system and can provide an ensemble of signals if deployed at multiple organisational scales.