Publications

33 Publications visible to you, out of a total of 33

Abstract

Not specified

Authors: Matthias Löbe, O. Beyan, Sebastian Stäubert, Frank A. Meineke, D. Ammon, Alfred Winter, S. Deckert, Markus Löffler, Toralf Kirsten

Date Published: 2019

Publication Type: InProceedings

Abstract

Not specified

Authors: S. Zabka, D. Ammon, T. Ganslandt, J. E. Gewehr, C. Haverkamp, S. Kiefer, H. Lautenbacher, Matthias Löbe, S. Thun, M. Boeker

Date Published: 2019

Publication Type: InProceedings

Abstract (Expand)

INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. "Smart Medical Information Technology for Healthcare (SMITH)" is one of four consortia funded by the German Medical Informatics Initiative (MI-I) to create an alliance of universities, university hospitals, research institutions and IT companies. SMITH's goals are to establish Data Integration Centers (DICs) at each SMITH partner hospital and to implement use cases which demonstrate the usefulness of the approach. OBJECTIVES: To give insight into architectural design issues underlying SMITH data integration and to introduce the use cases to be implemented. GOVERNANCE AND POLICIES: SMITH implements a federated approach as well for its governance structure as for its information system architecture. SMITH has designed a generic concept for its data integration centers. They share identical services and functionalities to take best advantage of the interoperability architectures and of the data use and access process planned. The DICs provide access to the local hospitals' Electronic Medical Records (EMR). This is based on data trustee and privacy management services. DIC staff will curate and amend EMR data in the Health Data Storage. METHODOLOGY AND ARCHITECTURAL FRAMEWORK: To share medical and research data, SMITH's information system is based on communication and storage standards. We use the Reference Model of the Open Archival Information System and will consistently implement profiles of Integrating the Health Care Enterprise (IHE) and Health Level Seven (HL7) standards. Standard terminologies will be applied. The SMITH Market Place will be used for devising agreements on data access and distribution. 3LGM(2) for enterprise architecture modeling supports a consistent development process.The DIC reference architecture determines the services, applications and the standardsbased communication links needed for efficiently supporting the ingesting, data nourishing, trustee, privacy management and data transfer tasks of the SMITH DICs. The reference architecture is adopted at the local sites. Data sharing services and the market place enable interoperability. USE CASES: The methodological use case "Phenotype Pipeline" (PheP) constructs algorithms for annotations and analyses of patient-related phenotypes according to classification rules or statistical models based on structured data. Unstructured textual data will be subject to natural language processing to permit integration into the phenotyping algorithms. The clinical use case "Algorithmic Surveillance of ICU Patients" (ASIC) focusses on patients in Intensive Care Units (ICU) with the acute respiratory distress syndrome (ARDS). A model-based decision-support system will give advice for mechanical ventilation. The clinical use case HELP develops a "hospital-wide electronic medical record-based computerized decision support system to improve outcomes of patients with blood-stream infections" (HELP). ASIC and HELP use the PheP. The clinical benefit of the use cases ASIC and HELP will be demonstrated in a change of care clinical trial based on a step wedge design. DISCUSSION: SMITH's strength is the modular, reusable IT architecture based on interoperability standards, the integration of the hospitals' information management departments and the public-private partnership. The project aims at sustainability beyond the first 4-year funding period.

Authors: A. Winter, S. Staubert, D. Ammon, S. Aiche, O. Beyan, V. Bischoff, P. Daumke, S. Decker, G. Funkat, J. E. Gewehr, A. de Greiff, S. Haferkamp, U. Hahn, A. Henkel, T. Kirsten, T. Kloss, J. Lippert, M. Lobe, V. Lowitsch, O. Maassen, J. Maschmann, S. Meister, R. Mikolajczyk, M. Nuchter, M. W. Pletz, E. Rahm, M. Riedel, K. Saleh, A. Schuppert, S. Smers, A. Stollenwerk, S. Uhlig, T. Wendt, S. Zenker, W. Fleig, G. Marx, A. Scherag, M. Loffler

Date Published: 18th Jul 2018

Publication Type: Journal article

Abstract (Expand)

Metadata Repositories (MDR) are databases for data elements that can be utilized in research as well as in medical care. These data elements are not the actual patient data (facts), but a complete definition of the variables or characteristics used, including coding, unit of measurement, data type and other aspects. The aim of the project described here was to evaluate possible application scenarios for MDRs by a larger group of experts. The focus was not on specific software, but on the community's basic expectation of such a database of data elements. To achieve this goal, a questionnaire was designed that contained questions on general aspects of setting up a registry for data elements in biomedical research as well as more specific points with regard to necessary functionalities, desired contents, tools for community work and the quality of data elements. One of the main results was that the users attach more importance to the quality of the content than to the efficiency in implementing their documentation concepts. At the same time, they consider the effort involved in using existing software systems to be too much compared with the benefits and have concerns about the use of their designs by third parties.

Author: Matthias Löbe

Date Published: 9th May 2018

Publication Type: Misc

Abstract (Expand)

BACKGROUND: Medical plaintext documents contain important facts about patients, but they are rarely available for structured queries. The provision of structured information from natural language texts in addition to the existing structured data can significantly speed up the search for fulfilled inclusion criteria and thus improve the recruitment rate. OBJECTIVES: This work is aimed at supporting clinical trial recruitment with text mining techniques to identify suitable subjects in hospitals. METHOD: Based on the inclusion/exclusion criteria of 5 sample studies and a text corpus consisting of 212 doctor's letters and medical follow-up documentation from a university cancer center, a prototype was developed and technically evaluated using NLP procedures (UIMA) for the extraction of facts from medical free texts. RESULTS: It was found that although the extracted entities are not always correct (precision between 23% and 96%), they provide a decisive indication as to which patient file should be read preferentially. CONCLUSION: The prototype presented here demonstrates the technical feasibility. In order to find available, lucrative phenotypes, an in-depth evaluation is required.

Authors: M. Lobe, S. Staubert, C. Goldberg, I. Haffner, A. Winter

Date Published: 5th May 2018

Publication Type: Journal article

Human Diseases: breast cancer

Abstract

Not specified

Authors: Christian R. Bauer, T. Ganslandt, B. Baum, J. Christoph, I. Engel, Matthias Löbe, S. Mate, Sebastian Stäubert, J. Drepper, Hans-Ulrich Prokosch, Alfred Winter, U. Sax

Date Published: 8th Jan 2018

Publication Type: Journal article

Abstract

Not specified

Authors: T. Ganslandt, M. Boeker, Matthias Löbe, F. Prasser, J. Schepers, S. C. Semler, S. Thun, U. Sax

Date Published: 2018

Publication Type: InBook

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