Repository: Freie Universität Berlin, Math Department

Enabling Precision Medicine With Digital Case Classification at the Point-of-Care

Obermeier, P. and Muehlhans, S. and Hoppe, Ch. and Karsch, K. and Tief, F. and Seeber, L. and Chen, X. and Conrad, T. O. F. and Boettcher, S. and Diedrich, S. and Rath , B. (2016) Enabling Precision Medicine With Digital Case Classification at the Point-of-Care. EBioMedicine, 4 . pp. 191-196.

Full text not available from this repository.

Official URL: http://dx.doi.org/10.1016/j.ebiom.2016.01.008

Abstract

Infectious 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.

Item Type:Article
Subjects:Mathematical and Computer Sciences > Mathematics > Mathematical Modelling
Mathematical and Computer Sciences > Statistics > Statistical Modelling
Medicine and Dentistry > Clinical Medicine
Divisions:Department of Mathematics and Computer Science > Institute of Mathematics
Department of Mathematics and Computer Science > Institute of Mathematics > BioComputing Group
Department of Mathematics and Computer Science > Institute of Mathematics > Comp. Proteomics Group
ID Code:1780
Deposited By: Admin Administrator
Deposited On:04 Feb 2016 12:15
Last Modified:07 Mar 2017 20:06

Repository Staff Only: item control page