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Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data.

Jeffrey G KlannHossein EstiriGriffin M WeberBertrand MoalPaul AvillachChuan HongAmelia Li Min TanBrett K Beaulieu-JonesVictor CastroThomas MaulhardtAlon GevaAlberto MaloviniAndrew Michael SouthShyam VisweswaranMichele M MorrisMalarkodi J SamayamuthuGilbert S OmennKee-Yuan NgiamKenneth D MandlMartin BoekerKaren L OlsonDanielle L MoweryRobert W FollettDavid A HanauerRiccardo BellazziJason H MooreNe Hooi Will LohDouglas S BellKavishwar B WagholikarLuca ChiovatoValentina TibolloSiegbert RiegAnthony L L J LiVianney JouhetEmily SchriverZongqi XiaMeghan HutchYuan LuoIsaac S Kohanenull nullGabriel A BratShawn N Murphy
Published in: Journal of the American Medical Informatics Association : JAMIA (2021)
We developed an EHR-based severity phenotype for COVID-19 in hospitalized patients and validated it at 12 international sites.
Keyphrases
  • electronic health record
  • coronavirus disease
  • sars cov
  • clinical decision support
  • adverse drug
  • big data
  • case report
  • respiratory syndrome coronavirus
  • deep learning