Teo, JTH;
Dinu, V;
Bernal, W;
Davidson, P;
Oliynyk, V;
Breen, C;
Barker, RD;
(2021)
Real-time clinician text feeds from electronic health records.
npj Digital Medicine
, 4
(1)
, Article 35. 10.1038/s41746-021-00406-7.
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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.
| Type: | Article |
|---|---|
| Title: | Real-time clinician text feeds from electronic health records |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s41746-021-00406-7 |
| Publisher version: | https://doi.org/10.1038/s41746-021-00406-7 |
| Language: | English |
| Additional information: | © 2021 Springer Nature Limited. This article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Health care, Public health |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10124581 |
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