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Real-time clinician text feeds from electronic health records
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 o...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904856/ https://www.ncbi.nlm.nih.gov/pubmed/33627748 http://dx.doi.org/10.1038/s41746-021-00406-7 |
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author | Teo, James T. H. Dinu, Vlad Bernal, William Davidson, Phil Oliynyk, Vitaliy Breen, Cormac Barker, Richard D. Dobson, Richard J. B. |
author_facet | Teo, James T. H. Dinu, Vlad Bernal, William Davidson, Phil Oliynyk, Vitaliy Breen, Cormac Barker, Richard D. Dobson, Richard J. B. |
author_sort | Teo, James T. H. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7904856 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79048562021-03-11 Real-time clinician text feeds from electronic health records Teo, James T. H. Dinu, Vlad Bernal, William Davidson, Phil Oliynyk, Vitaliy Breen, Cormac Barker, Richard D. Dobson, Richard J. B. NPJ Digit Med Brief Communication 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. Nature Publishing Group UK 2021-02-24 /pmc/articles/PMC7904856/ /pubmed/33627748 http://dx.doi.org/10.1038/s41746-021-00406-7 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Brief Communication Teo, James T. H. Dinu, Vlad Bernal, William Davidson, Phil Oliynyk, Vitaliy Breen, Cormac Barker, Richard D. Dobson, Richard J. B. Real-time clinician text feeds from electronic health records |
title | Real-time clinician text feeds from electronic health records |
title_full | Real-time clinician text feeds from electronic health records |
title_fullStr | Real-time clinician text feeds from electronic health records |
title_full_unstemmed | Real-time clinician text feeds from electronic health records |
title_short | Real-time clinician text feeds from electronic health records |
title_sort | real-time clinician text feeds from electronic health records |
topic | Brief Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904856/ https://www.ncbi.nlm.nih.gov/pubmed/33627748 http://dx.doi.org/10.1038/s41746-021-00406-7 |
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