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The increasingly digitized healthcare system requires new skills from all those involved. In order to impart these competencies, appropriate courses must be developed at educational institutions. In view of the rapid development of new aspects of digitization, this presents a challenge; suitable teaching formats must be developed successively. The establishment of cross-location teaching networks is one way to better meet training needs and to make the necessary spectrum of educational content available. As part of the Medical Informatics Initiative, the HiGHmed consortium is establishing such a teaching network, in the field of medical informatics, which covers many topics related to the digitization of the health care system. Various problem areas in the German education system were identified that hinder the development of the teaching network. These problem areas were prioritized firstly according to the urgency of the solution from the point of view of the HiGHmed consortium and secondly according to existing competencies in the participating societies. A workshop on the four most relevant topics was organized with experts from the German Society for Medical Informatics, Biometry and Epidemiology (GMDS), the Society for Medical Education (GMA) and the HiGHmed consortium. These are: recognition of exam results from teaching modules that are offered digitally and across locations, and their integration into existing curricula; recognition of digital, cross-location teaching in the teachers' teaching load; nationwide uniform competencies for teachers, in order to be able to conduct digital teaching effectively and with comparable quality; technical infrastructure to efficiently and securely communicate and manage the recognition of exam results between educational institutions. For all subject areas, existing preliminary work was identified on the basis of working questions, and short- and long-term needs for action were formulated. Finally, a need for the redesign of a technologically supported syntactic and semantic interoperability of learning performance recording was identified., Competing Interests: The authors declare that they have no competing interests., (Copyright © 2020 Benning et al.)

In University Medical Centers, heterogeneous data are generated that cannot always be clearly attributed to patient care or biomedical research. Each data set has to adhere to distinct intrinsic and operational quality standards. However, only if high-quality data, tools to work with the data, and most importantly guidelines and rules of how to work with the data are addressed adequately, an infrastructure can be sustainable. Here, we present the IT Research Architecture of the University Medical Center Göttingen and describe our ten years' experience and lessons learned with infrastructures in networked medical research.

The observation of growing "difficulties" in IT-infrastructures in neuroscience research during the last years led to a search for reasons and an analysis on how this phenomenon is reflected in the scientific literature. With a retrospective analysis of nine examples of multicenter research projects in the neurosciences and a literature review the observation was systematically analyzed. Results show that the rise in complexity mainly stems from two reasons: (1) more and more need for information on quality and context of research data (metadata) and (2) long-term requirements to handle the consent and identity/pseudonyms of study participants and biomaterials in relation to legal requirements. The combination of these two aspects together with very long study times and data evaluation periods are components of the subjectively perceived "difficulties". A direct consequence of this result is that big multicenter trials are becoming part of integrated research data environments and are not standing alone for themselves anymore. This drives up the resource needs regarding the IT-infrastructure in neuroscience research. In contrast to these findings, literature on this development is scarce and the problem probably underestimated., (Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.)

The historical roots of IT-based monitoring in health care are described. Since the 1970ies monitoring has been spreading to more and more domains of health care and public health. Today one can observe monitoring of persons in many environments and regarding widely different questions. While these monitoring applications have been introduced ethical questions have been raised to balance the possible positive and negative outcomes of the approaches. Today IT-technology is entering many parts of our life - IT eventually became what had been coined already in the last century by IBM as "electronic dust" which one can find in every part of our environment. As most of these "dust-particles" are able to observe something one can also understand this development as a development into ubiquitous monitoring of nearly everything at any time. The foreseen ambient intelligence worlds are also spaces of ambient monitoring. This article describes this historical development. It emphasizes why ethical and data protection questions are an absolute must in most IT activities today.

In order to provide a systematic basis for communication in trans-disciplinary research projects, there is a need for taxonomies and ontologies. Our developed taxonomy of personal health monitoring (PHM) is based on a systematic literature review and an iterative adaption process with trans-disciplinary partners. The construction method of the taxonomy is an ongoing process and need regularly updates.

Natural scientists such as physicists pioneered the sharing of computing resources, which resulted in the Grid. The inter domain transfer process of this technology has been an intuitive process. Some difficulties facing the life science community can be understood using the Bozeman's "Effectiveness Model of Technology Transfer". Bozeman's and classical technology transfer approaches deal with technologies that have achieved certain stability. Grid and Cloud solutions are technologies that are still in flux. We illustrate how Grid computing creates new difficulties for the technology transfer process that are not considered in Bozeman's model. We show why the success of health Grids should be measured by the qualified scientific human capital and opportunities created, and not primarily by the market impact. With two examples we show how the Grid technology transfer theory corresponds to the reality. We conclude with recommendations that can help improve the adoption of Grid solutions into the biomedical community. These results give a more concise explanation of the difficulties most life science IT projects are facing in the late funding periods, and show some leveraging steps which can help to overcome the "vale of tears".

Although grid computing middlewares are in research use since many years, they lack of particular security features for biomedical applications. The analysis of the common Globus middleware reveals several security-related shortcomings. As a result, extended security measures for HealthGrids have been identified. They include tools for auditing, tracking, fine grained access control for structured documents, trust and trust delegation. The German MediGRID project is facing this with an "Enhanced Security" package intending to bridge the gap between current legal, data protection as well as data security requirements and the available grid technology.

Coming from a short international review reasons for networking of scientific research in Germany are given. Success and challenges of medical competence networks are listed, and it is argued how important it is to bridge networks in health care and medical research networks. Some examples from internal medicine are given. The prominent central role of patients is emphasized. Finally it is stated that Germany so far has not established the prerequisites to implement sustainable collaborative infrastructures. Specifically financial, legal, and political support is missing. In addition, it becomes clear that -- in contrast to the USA -- Germany lacks sufficient medical informatics specialists as well as health managers trained to manage IT or networked research. The planned introduction of a telematics infrastructure for health in Germany is perceived as a big chance for improvement.

In the Approbationsordnung für Ärzte (German regulation for the Curriculum in Medicine) of 27th June, 2002 the disciplines Epidemiology, Medical Biometry and Medical Informatics are combined in one obligatory cross-sectional subject of the second part of the medical exam. In addition, it is possible to study topics from these disciplines in more detail on a voluntary basis. The aim of teaching this cross-sectional subject is to qualify the students to assess their own actions critically, to apply recommendations with care, and to learn to use tools like systematic documentation and modern information technology.For the mentioned disciplines a catalogue has been developed which is subdivided in three parts. In the first part methods are described which are needed to support medical decisions. The second part refers to support of medical supply and quality management, whereas the third part deals with the basic elements of Public Health and Health Economics, with respect to causation of diseases and prevention.

Medical informatics is still in its early stages of evolution and definition. If informatics is to obtain the status of a specialized field of study within the health science curriculum, its ambiguity must be eliminated. This article discusses the term "medical informatics" and the impact of the new field of study on curriculum, education, and training of health care professionals, and health care information systems research and development. [ABSTRACT FROM AUTHOR]

Highlights from the article: To allow data from these consortia to flow together, three common cross-sectional platforms for biomaterials, clinical data and imaging data were established. B Results: b A data protection concept and a broad informed consent based on the national data protection guidelines was developed which was positively assessed by the Munich ethics commission (LMU) and serves as an example for further ethics commissions. Pseudonyms used in each research consortium within the research network are converted again into another pseudonym.