Publications

85 Publications visible to you, out of a total of 85

Abstract (Expand)

Phenotyping means the determination of clinical relevant phenotypes, e.g. by classification or calculation based on EHR data. Within the German Medical Informatics Initiative, the SMITH consortium is working on the implementation of a phenotyping pipeline. to extract, structure and normalize information from the EHR data of the hospital information systems of the participating sites; to automatically apply complex algorithms and models and to enrich the data within the research data warehouses of the distributed data integration centers with the computed results. Here we present the overall picture and essential building blocks and workflows of this concept.

Authors: Frank A Meineke, Sebastian Stäubert, Matthias Löbe, Alexandr Uciteli, Markus Löffler

Date Published: 1st Sep 2019

Publication Type: Journal article

Abstract (Expand)

Secondary use of electronic health record (EHR) data requires a detailed description of metadata, especially when data collection and data re-use are organizationally and technically far apart. This paper describes the concept of the SMITH consortium that includes conventions, processes, and tools for describing and managing metadata using common standards for semantic interoperability. It deals in particular with the chain of processing steps of data from existing information systems and provides an overview of the planned use of metadata, medical terminologies, and semantic services in the consortium.

Authors: M. Lobe, O. Beyan, S. Staubert, F. Meineke, D. Ammon, A. Winter, S. Decker, M. Loffler, T. Kirsten

Date Published: 21st Aug 2019

Publication Type: Journal article

Abstract (Expand)

The digitization of health records and cross-institutional data sharing is a necessary precondition to improve clinical research and patient care. The SMITH project unites several university hospitals and medical faculties in order to provide medical informatics solutions for health data integration and cross-institutional communication. In this paper, we focus on requirements elicitation and management for extracting clinical data from heterogeneous subsystems and data integration based on eHealth standards such as HL7 FHIR and IHE profiles.

Authors: K. Tahar, C. Muller, A. Durschmid, S. Haferkamp, K. Saleh, P. Jurs, S. Staubert, J. E. Gewehr, S. Zenker, D. Ammon, T. Wendt

Date Published: 21st Aug 2019

Publication Type: Journal article

Abstract (Expand)

We devised annotation guidelines for the de-identification of German clinical documents and assembled a corpus of 1,106 discharge summaries and transfer letters with 44K annotated protected health information (PHI) items. After three iteration rounds, our annotation team finally reached an inter-annotator agreement of 0.96 on the instance level and 0.97 on the token level of annotation (averaged pair-wise F1 score). To establish a baseline for automatic de-identification on our corpus, we trained a recurrent neural network (RNN) and achieved F1 scores greater than 0.9 on most major PHI categories.

Authors: T. Kolditz, C. Lohr, J. Hellrich, L. Modersohn, B. Betz, M. Kiehntopf, U. Hahn

Date Published: 21st Aug 2019

Publication Type: InProceedings

Abstract (Expand)

The Demonstrator study aims to analyse comorbidities and rare diseases among patients from German university hospitals within the German Medical Informatics Initiative. This work aimed to design and determine the feasibility of a model to assess the quality of the claims data used in the study. Several data quality issues were identified affecting small amounts of cases in one of the participating sites. As a next step an extension to all participating sites is planned.

Authors: G. Kamdje-Wabo, T. Gradinger, M. Lobe, R. Lodahl, S. A. Seuchter, U. Sax, T. Ganslandt

Date Published: 21st Aug 2019

Publication Type: Journal article

Abstract (Expand)

The digitization of health records and cross-institutional data sharing is a necessary precondition to improve clinical research and patient care. The SMITH project unites several university hospitals and medical faculties in order to provide medical informatics solutions for health data integration and cross-institutional communication. In this paper, we focus on requirements elicitation and management for extracting clinical data from heterogeneous subsystems and data integration based on eHealth standards such as HL7 FHIR and IHE profiles.

Authors: Kais Tahar, Christoph Müller, Andreas Dürschmid, Silke Haferkamp, Kutaiba Saleh, Patrick Jürs, Sebastian Stäubert, Jan Erik Gewehr, Sven Zenker, Danny Ammon, Thomas Wendt

Date Published: 1st Aug 2019

Publication Type: Journal article

Abstract

Not specified

Authors: Alexander Martin Heberle, Patricia Razquin Navas, Miriam Langelaar-Makkinje, Katharina Kasack, Ahmed Sadik, Erik Faessler, Udo Hahn, Philip Marx-Stoelting, Christiane A Opitz, Christine Sers, Ines Heiland, Sascha Schäuble, Kathrin Thedieck

Date Published: 28th Mar 2019

Publication Type: Journal article

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