Publications

217 Publications visible to you, out of a total of 217

Abstract

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Authors: A. Lagemann, Reinhold Haux, Alfred Winter

Date Published: No date defined

Publication Type: Misc

Abstract (Expand)

Clinical Trial Recruitment Support Systems can booster patient inclusion of clinical trials by automatically analyzing eligibility criteria based on electronic health records. However, missing interoperability has hindered introduction of those systems on a broader scale. Therefore, our aim was to develop a recruitment support system based on FHIR R4 and evaluate its usage and features in a cardiology department. Clinical conditions, anamnesis, examinations, allergies, medication, laboratory data and echocardiography results were imported as FHIR resources. Clinical trial information, eligibility criteria and recruitment status were recorded using the appropriate FHIR resources without extensions. Eligibility criteria linked by the logical operation “OR” were represented by using multiple FHIR Group resources for enrollment. The system was able to identify 52 of 55 patients included in four clinical trials. In conclusion, use of FHIR for defining eligibility criteria of clinical trials may facilitate interoperability and allow automatic screening for eligible patients at multiple sites of different healthcare providers in the future. Upcoming changes in FHIR should allow easier description of “OR”-linked eligibility criteria.

Authors: Clemens Scherer, Stephan Endres, Martin Orban, Stefan Kääb, Steffen Massberg, Alfred Winter, Matthias Löbe

Date Published: 1st May 2022

Publication Type: Journal article

Abstract (Expand)

Catalogues of learning objectives for Biomedical and Health Informatics are relevant prerequisites for systematic and effective qualification. Catalogue management needs to integrate different catalogues and support collaborative revisioning. The Health Informatics Learning Objectives Navigator (HI-LONa) offers an open, interoperable platform based on Semantic Web Technology. At present HI-LONa contains 983 learning objectives of three relevant catalogues. HI-LONa successfully supported a multiprofessional consensus process.

Authors: Cord Spreckelsen, Ulrike Schemmann, Lo An Phan-Vogtmann, André Scherag, Alfred Winter, Birgit Schneider

Date Published: 1st May 2021

Publication Type: Journal article

Abstract (Expand)

Despite their young age, the FAIR principles are recognised as important guidelines for research data management. Their generic design, however, leaves much room for interpretation in domain-specific application. Based on practical experience in the operation of a data repository, this article addresses problems in FAIR provisioning of medical data for research purposes in the use case of the Leipzig Health Atlas project and shows necessary future developments.

Authors: M. Lobe, F. Matthies, S. Staubert, F. A. Meineke, A. Winter

Date Published: 16th Jun 2020

Publication Type: Journal article

Abstract (Expand)

Despite their young age, the FAIR principles are recognised as important guidelines for research data management. Their generic design, however, leaves much room for interpretation in domain-specific application. Based on practical experience in the operation of a data repository, this article addresses problems in FAIR provisioning of medical data for research purposes in the use case of the Leipzig Health Atlas project and shows necessary future developments.

Authors: Matthias Löbe, Franz Matthies, Sebastian Stäubert, Frank A Meineke, Alfred Winter

Date Published: 1st Jun 2020

Publication Type: Journal article

Abstract (Expand)

BACKGROUND Against the background of a steadily increasing degree of digitalization in health care, a professional information management (IM) is required to successfully plan, implement, and evaluatee information technology (IT). At its core, IM has to ensure a high quality of health data and health information systems to support patient care. OBJECTIVES The goal of the present study was to define what constitutes professional IM as a construct as well as to propose a reliable and valid measurement instrument. METHODS To develop and validate the construct of professionalism of information management (PIM) and its measurement, a stepwise approach followed an established procedure from information systems and behavioral research. The procedure included an analysis of the pertaining literature and expert rounds on the construct and the instrument, two consecutive and comprehensive surveys at the national and international level, exploratory and confirmatory factor analyses as well as reliability and validity testing. RESULTS Professionalism of information management was developed as a construct consisting of the three dimensions of strategic, tactical, and operational IM as well as of the regularity and cyclical phases of IM procedures as the two elements of professionalism. The PIM instrument operationalized the construct providing items that incorporated IM procedures along the three dimensions and cyclical phases. These procedures had to be evaluated against their degree of regularity in the instrument. The instrument proved to be reliable and valid in two consecutive measurement phases and across three countries. CONCLUSION It can be concluded that professionalism of information management is a meaningful construct that can be operationalized in a scientifically rigorous manner. Both science and practice can benefit from these developments in terms of improved self-assessment, benchmarking capabilities, and eventually, obtaining a better understanding of health IT maturity.

Authors: Johannes Thye, Moritz Esdar, Jan-David Liebe, Franziska Jahn, Alfred Winter, Ursula Hübner

Date Published: 2020

Publication Type: Journal article

Abstract (Expand)

Having precise information about health IT evaluation studies is important for evidence-based decisions in medical informatics. In a former feasibility study, we used a faceted search based on ontological modeling of key elements of studies to retrieve precisely described health IT evaluation studies. However, extracting the key elements manually for the modeling of the ontology was time and resource-intensive. We now aimed at applying natural language processing to substitute manual data extraction by automatic data extraction. Four methods (Named Entity Recognition, Bag-of-Words, Term-Frequency-Inverse-Document-Frequency, and Latent Dirichlet Allocation Topic Modeling were applied to 24 health IT evaluation studies. We evaluated which of these methods was best suited for extracting key elements of each study. As gold standard, we used results from manual extraction. As a result, Named Entity Recognition is promising but needs to be adapted to the existing study context. After the adaption, key elements of studies could be collected in a more feasible, time- and resource-saving way.

Authors: Verena Dornauer, Franziska Jahn, Konrad Hoeffner, Alfred Winter, Elske Ammenwerth

Date Published: 2020

Publication Type: Journal article

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