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2016-01-12Zeitschriftenartikel DOI: 10.1016/j.ebiom.2016.01.008
Enabling Precision Medicine With Digital Case Classification at the Point-of-Care
dc.contributor.authorObermeier, Patrick
dc.contributor.authorMuehlhans, Susann
dc.contributor.authorHoppe, Christian
dc.contributor.authorKarsch, Katharina
dc.contributor.authorTief, Franziska
dc.contributor.authorChen, Xi
dc.contributor.authorConrad, Tim
dc.contributor.authorBöttcher, Sindy
dc.contributor.authorDiedrich, Sabine
dc.contributor.authorRath, Barbara
dc.date.accessioned2018-05-07T19:15:25Z
dc.date.available2018-05-07T19:15:25Z
dc.date.created2016-08-10
dc.date.issued2016-01-12none
dc.identifier.otherhttp://edoc.rki.de/oa/articles/revvy3V3IznAo/PDF/2910H2Eobc5s.pdf
dc.identifier.urihttp://edoc.rki.de/176904/2392
dc.description.abstractInfectious and inflammatory diseases of the central nervous system are difficult to identify early. Case definitions for aseptic meningitis, encephalitis, myelitis, and acute disseminated encephalomyelitis (ADEM) are available, but rarely put to use. The VACC-Tool (Vienna Vaccine Safety Initiative Automated Case Classification-Tool) is a mobile application enabling immediate case ascertainment based on consensus criteria at the point-of-care. The VACC-Tool was validated in a quality management program in collaboration with the Robert-Koch-Institute. Results were compared to ICD-10 coding and retrospective analysis of electronic health records using the same case criteria. Of 68,921 patients attending the emergency room in 10/2010–06/2013, 11,575 were hospitalized, with 521 eligible patients (mean age: 7.6 years) entering the quality management program. Using the VACC-Tool at the point-of-care, 180/521 cases were classified successfully and 194/521 ruled out with certainty. Of the 180 confirmed cases, 116 had been missed by ICD-10 coding, 38 misclassified. By retrospective application of the same case criteria, 33 cases were missed. Encephalitis and ADEM cases were most likely missed or misclassified. The VACC-Tool enables physicians to ask the right questions at the right time, thereby classifying cases consistently and accurately, facilitating translational research. Future applications will alert physicians when additional diagnostic procedures are required.eng
dc.language.isoeng
dc.publisherRobert Koch-Institut, Infektionskrankheiten / Erreger
dc.subjectMeningitiseng
dc.subjectSurveillanceeng
dc.subjectEncephalitiseng
dc.subjectADEMeng
dc.subjectMobile healtheng
dc.subjectData standardseng
dc.subject.ddc610 Medizin
dc.titleEnabling Precision Medicine With Digital Case Classification at the Point-of-Care
dc.typeperiodicalPart
dc.identifier.urnurn:nbn:de:0257-10046420
dc.identifier.doi10.1016/j.ebiom.2016.01.008
dc.identifier.doihttp://dx.doi.org/10.25646/2317
local.edoc.container-titleEBioMedicine
local.edoc.fp-subtypeArtikel
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttp://www.sciencedirect.com/science/article/pii/S2352396416300068
local.edoc.container-publisher-nameElsevier
local.edoc.container-volume4
local.edoc.container-year2016

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