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Building a well-founded understanding of the concepts, tasks and limitations of IT in all areas of society is an essential prerequisite for future developments in business and research. This applies in particular to the healthcare sector and medical research, which are affected by the noticeable advances in digitization. In the transfer project “Zukunftslabor Gesundheit” (ZLG), a teaching framework was developed to support the development of further education online courses in order to teach heterogeneous groups of learners independent of location and prior knowledge. The study at hand describes the development and components of the framework.
After kidney transplantation graft rejection must be prevented. Therefore, a multitude of parameters of the patient is observed pre- and postoperatively. To support this process, the Screen Reject research project is developing a data warehouse optimized for kidney rejection diagnostics. In the course of this project it was discovered that important information are only available in form of free texts instead of structured data and can therefore not be processed by standard ETL tools, which is necessary to establish a digital expert system for rejection diagnostics. Due to this reason, data integration has been improved by a combination of methods from natural language processing and methods from image processing. Based on state-of-the-art data warehousing technologies (Microsoft SSIS), a generic data integration tool has been developed. The tool was evaluated by extracting Banff-classification from 218 pathology reports and extracting HLA mismatches from about 1700 PDF files, both written in german language.
Appropriate data models are essential for the systematic collection, aggregation, and integration of health data and for subsequent analysis. However, recommendations for modeling health data are often not publicly available within specific projects. Therefore, the project Zukunftslabor Gesundheit investigates recommendations for modeling. Expert interviews with five experts were conducted and analyzed using qualitative content analysis. Based on the condensed categories “governance”, “modeling” and “standards”, the project team generated eight hypotheses for recommendations on health data modeling. In addition, relevant framework conditions such as different roles, international cooperation, education/training and political influence were identified. Although emerging from interviewing a small convenience sample of experts, the results help to plan more extensive data collections and to create recommendations for health data modeling.
Catalogs of competency-based learning objectives (CLO) were introduced and promoted as a prerequisite for high-quality, systematic curriculum development. While this is common in medicine, the consistent use of CLO is not yet well established in epidemiology, biometry, medical informatics, biomedical informatics, and nursing informatics especially in Germany. This paper aims to identify underlying obstacles and give recommendations in order to promote the dissemination of CLO for curricular development in health data and information sciences. To determine these obstacles and recommendations a public online expert workshop was organized. This paper summarizes the findings.
Acute stroke care is a time-critical process. Improving communication
and documentation process may support a positive effect on medical outcome. To achieve this goal, a new system using a mobile application has been integrated into existing infrastructure at Hannover Medical School (MHH). Within a pilot project, this system has been brought into clinical daily routine in February 2022. Insights generated may support further applications in clinical use-cases.
In the context of the ongoing digitization of interdisciplinary subjects, the need for digital literacy is increasing in all areas of everyday life. Furthermore, communication between science and society is facing new challenges, not least since the COVID-19 pandemic. In order to deal with these challenges and to provide target-oriented online teaching, new educational concepts for the transfer of knowledge to society are necessary. In the transfer project “Zukunftslabor Gesundheit” (ZLG), a didactic concept for the creation of E-Learning classes was developed. A key factor for the didactic concept is addressing heterogeneous target groups to reach the broadest possible spectrum of participants. The concept has already been used for the creation of the first ZLG E-Learning courses. This article outlines the central elements of the developed didactic concept and addresses the creation of the ZLG courses. The courses created so far appeal to different target groups and convey diverse types of knowledge at different levels of difficulty.
During the intraoperative radiograph generation process with mobile image intensifier systems (C-arm) most of the radiation exposure for patient, surgeon and operation room personal is caused by scattered radiation. The intensity and propagation of scattered radiation depend on different parameters, e.g. the intensity of the primary radiation, and the positioning of the mobile image intensifier. Exposure through scattered radiation can be minimized when all these parameters are adjusted correctly. Because radiation is potentially dangerous and could not be perceived by any human sense the current education on correct adjustment of a C-arm is designed very theoretical. This paper presents an approach of scattered radiation calculation and visualization embedded in a computer based training system for mobile image intensifier systems called virtX. With the help of this extension the virtX training system should enrich the current radiation protection training with visual and practical training aspects.
Due to demographic change the number of serious kidney diseases and thus required transplantations will increase. The increased demand for donor organs and a decreasing supply of these organs underline the necessity for effective early rejection diagnostic measures to improve the lifetime of transplants. Expert systems might improve rejection diagnostics but for the development of such systems data models are needed that encompass the relevant information to enable optimal data aggregation and evaluation. Results of a literature review concerning published data models and information systems concerned with kidney transplant rejection diagnostic lead to a set of data elements even if no papers could be identified that publish data models explicitly.
Using openEHR Archetypes for Automated Extraction of Numerical Information from Clinical Narratives
(2019)
Up to 80% of medical information is documented by unstructured data such as clinical reports written in natural language. Such data is called unstructured because the information it contains cannot be retrieved automatically as straightforward as from structured data. However, we assume that the use of this flexible kind of documentation will remain a substantial part of a patient’s medical record, so that clinical information systems have to deal appropriately with this type of information description. On the other hand, there are efforts to achieve semantic interoperability between clinical application systems through information modelling concepts like HL7 FHIR or openEHR. Considering this, we propose an approach to transform unstructured documented information into openEHR archetypes. Furthermore, we aim to support the field of clinical text mining by recognizing and publishing the connections between openEHR archetypes and heterogeneous phrasings. We have evaluated our method by extracting the values to three openEHR archetypes from unstructured documents in English and German language.
Background: Health information systems (HIS) are one of the most important areas for biomedical and health informatics. In order to professionally deal with HIS well-educated informaticians are needed. Because of these reasons, in 2001 an international course has been established: The Frank – van Swieten Lectures on Strategic Information Management of Health Information Systems.
Objectives: Reporting about the Frank – van Swieten Lectures and about our students‘ feedback on this course during the last 16 years. Summarizing our lessons learned and making recommendations for such international courses on HIS.
Methods: The basic concept of the Frank – van Swieten lectures is to teach the theoretical background in local lectures, to organize practical exercises on modelling sub-information systems of the respective local HIS and finally to conduct Joint Three Days as an international meeting were the resulting models are introduced and compared.
Results: During the last 16 years, the Universities of Amsterdam, Braunschweig, Heidelberg/Heilbronn, Leipzig as well as UMIT were involved in running this course. Overall, 517 students from these universities participated. Our students‘ feedback was clearly positive.
The Joint Three Days of the Frank – van Swieten Lectures, where at the end of the course all students can meet, turned out to be an important component of this course. Based on the last 16 years, we recommend common teaching materials, agreement on equivalent clinical areas for the exercises, support of group building of international student groups, motivation of using a collaboration platform, ensuring quality management of the course, addressing different levels of knowledge of the students, and ensuring sufficient funding for joint activities.
Conclusions: Although associated with considerable additional efforts, we can clearly recommend establishing such international courses on HIS, such as the Frank – van Swieten Lectures.