Real-time clinician text feeds from electronic health records

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 aggr...

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Autores principales:	James T. H. Teo, Vlad Dinu, William Bernal, Phil Davidson, Vitaliy Oliynyk, Cormac Breen, Richard D. Barker, Richard J. B. Dobson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/d131c890e49a44d29a3e707c80b44572
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spelling	oai:doaj.org-article:d131c890e49a44d29a3e707c80b445722021-12-02T13:20:05ZReal-time clinician text feeds from electronic health records10.1038/s41746-021-00406-72398-6352https://doaj.org/article/d131c890e49a44d29a3e707c80b445722021-02-01T00:00:00Zhttps://doi.org/10.1038/s41746-021-00406-7https://doaj.org/toc/2398-6352Abstract 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.James T. H. TeoVlad DinuWilliam BernalPhil DavidsonVitaliy OliynykCormac BreenRichard D. BarkerRichard J. B. DobsonNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 4, Iss 1, Pp 1-3 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 James T. H. Teo Vlad Dinu William Bernal Phil Davidson Vitaliy Oliynyk Cormac Breen Richard D. Barker Richard J. B. Dobson Real-time clinician text feeds from electronic health records
description	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.
format	article
author	James T. H. Teo Vlad Dinu William Bernal Phil Davidson Vitaliy Oliynyk Cormac Breen Richard D. Barker Richard J. B. Dobson
author_facet	James T. H. Teo Vlad Dinu William Bernal Phil Davidson Vitaliy Oliynyk Cormac Breen Richard D. Barker Richard J. B. Dobson
author_sort	James T. H. Teo
title	Real-time clinician text feeds from electronic health records
title_short	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_sort	real-time clinician text feeds from electronic health records
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/d131c890e49a44d29a3e707c80b44572
work_keys_str_mv	AT jamesthteo realtimecliniciantextfeedsfromelectronichealthrecords AT vladdinu realtimecliniciantextfeedsfromelectronichealthrecords AT williambernal realtimecliniciantextfeedsfromelectronichealthrecords AT phildavidson realtimecliniciantextfeedsfromelectronichealthrecords AT vitaliyoliynyk realtimecliniciantextfeedsfromelectronichealthrecords AT cormacbreen realtimecliniciantextfeedsfromelectronichealthrecords AT richarddbarker realtimecliniciantextfeedsfromelectronichealthrecords AT richardjbdobson realtimecliniciantextfeedsfromelectronichealthrecords
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Real-time clinician text feeds from electronic health records

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