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Objectives Managing participants and their data are fundamental for the success of a clinical trial. Our review identifies and describes processes that deal with management of trial participants and highlights information technology (IT) assistance for clinical research in the context of participant management. Methods A scoping literature review design, based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement, was used to identify literature on trial participant-related proceedings, work procedures, or workflows, and assisting electronic systems. Results The literature search identified 1329 articles of which 111 were included for analysis. Participant-related procedures were categorized into 4 major trial processes: recruitment, obtaining informed consent, managing identities, and managing administrative data. Our results demonstrated that management of trial participants is considered in nearly every step of clinical trials, and that IT was successfully introduced to all participant-related areas of a clinical trial to facilitate processes. Discussion There is no precise definition of participant management, so a broad search strategy was necessary, resulting in a high number of articles that had to be excluded. Nevertheless, this review provides a comprehensive overview of participant management-related components, which was lacking so far. The review contributes to a better understanding of how computer-assisted management of participants in clinical trials is possible. Open-Access-Publikationsfonds 2020 peerReviewed

Background: The protection of sensitive data against unauthorized access is especially important in healthcare and medical research. Not only medical data but also identifying administrative data in medical research projects must be managed and protected. While Clinical Data Management Systems (CDMS)[for full text, please go to the a.m. URL], 65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS)

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., Das zunehmend digitalisierte Gesundheitswesen erfordert neue Kompetenzen von allen Beteiligten. Um diese Kompetenzen vermitteln zu können, müssen an den Bildungsinstitutionen entsprechende Lehrveranstaltungen entwickelt werden. Dies ist angesichts der rasanten Entwicklung neuer Digitalisierungsaspekte eine Herausforderung; passende Lehrformate müssen sukzessive aufgebaut werden. Die Etablierung standortübergreifender Lehrverbünde ist eine Möglichkeit, den Ausbildungsbedarf besser zu decken und die notwendige Bandbreite an Bildungsinhalten verfügbar zu machen. Im Rahmen der Medizininformatik-Initiative wird im HiGHmed-Konsortium ein solcher Lehrverbund im Fachgebiet der Medizinischen Informatik aufgebaut, in welches viele Themen der Digitalisierung des Gesundheitswesens fallen. Dabei wurden verschiedene Problemfelder im deutschen Bildungswesen identifiziert, welche den Aufbau des Lehrverbundes hemmen. Diese Problemfelder wurden unter Beachtung der Dringlichkeit der Lösung aus Sicht des HiGHmeducation Konsortiums und andererseits nach vorhandenen Kompetenzen in den teilnehmenden Fachgesellschaften priorisiert. Zu den vier relevantesten Themen wurde ein Workshop mit Fachleuten der deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), der Gesellschaft für Medizinische Ausbildung (GMA) und des HiGHmed Konsortiums ausgerichtet. Diese sind: Anerkennung von Prüfungsleistungen aus Lehrmodulen, welche digital und standortübergreifend angeboten werden, und Integration in bestehende Curricula; Anerkennung digitaler, standortübergreifender Lehre im Deputat der Lehrenden; bundesweit einheitliche Kompetenzen für Lehrende, um digitale Lehre effektiv und mit vergleichbarer Qualität betreiben zu können; technische Infrastrukturen, um die Anerkennung zwischen Bildungseinrichtungen effizient und sicher kommunizieren und verwalten zu können. Für alle Themengebiete wurden anhand von Arbeitsfragen existierende Vorarbeiten identifiziert sowie kurz- und langfristige Handlungsbedarfe formuliert. Abschließend wurde themenübergreifend ein Bedarf für die Neugestaltung einer technologisch unterstützten syntaktischen und semantischen Interoperabilität der Erfassung von Lernleistungen festgestellt.

Introduction: Routine medical data from general practitioners are an eminently important source of information for health services research. Although almost all data of routine health care are nowadays recorded as electronic patient records, access to these data for research purposes in Germany is limited.[for full text, please go to the a.m. URL], 63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Supplemental material, MSJ799580_supplemental_table_1 for Symptomatology and symptomatic treatment in multiple sclerosis: Results from a nationwide MS registry by Paulus Stefan Rommer, Kerstin Eichstädt, David Ellenberger, Peter Flachenecker, Tim Friede, Judith Haas, Christoph Kleinschnitz, Dieter Pöhlau, Otto Rienhoff, Alexander Stahmann and Uwe Klaus Zettl in Multiple Sclerosis Journal

Background The progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers. Since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. We investigated which combination of the Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR)-sum-of-boxes, the word list delayed free recall from the Consortium to Establish a Registry of Dementia (CERAD) test battery, hippocampal volume (HCV), amyloid-beta1–42 (Aβ42), amyloid-beta1–40 (Aβ40) levels, the ratio of Aβ42/Aβ40, phosphorylated tau, and total tau (t-Tau) levels in the CSF best predicted a short-term conversion from MCI to AD dementia. Methods We used 115 complete datasets from MCI patients of the “Dementia Competence Network”, a German multicenter cohort study with annual follow-up up to 3 years. MCI was broadly defined to include amnestic and nonamnestic syndromes. Variables known to predict progression in MCI patients were selected a priori. Nine individual predictors were compared by receiver operating characteristic (ROC) curve analysis. ROC curves of the five best two-, three-, and four-parameter combinations were analyzed for significant superiority by a bootstrapping wrapper around a support vector machine with linear kernel. The incremental value of combinations was tested for statistical significance by comparing the specificities of the different classifiers at a given sensitivity of 85%. Results Out of 115 subjects, 28 (24.3%) with MCI progressed to AD dementia within a mean follow-up period of 25.5 months. At baseline, MCI-AD patients were no different from stable MCI in age and gender distribution, but had lower educational attainment. All single biomarkers were significantly different between the two groups at baseline. ROC curves of the individual predictors gave areas under the curve (AUC) between 0.66 and 0.77, and all single predictors were statistically superior to Aβ40. The AUC of the two-parameter combinations ranged from 0.77 to 0.81. The three-parameter combinations ranged from AUC 0.80–0.83, and the four-parameter combination from AUC 0.81–0.82. None of the predictor combinations was significantly superior to the two best single predictors (HCV and t-Tau). When maximizing the AUC differences by fixing sensitivity at 85%, the two- to four-parameter combinations were superior to HCV alone. Conclusion A combination of two biomarkers of neurodegeneration (e.g., HCV and t-Tau) is not superior over the single parameters in identifying patients with MCI who are most likely to progress to AD dementia, although there is a gradual increase in the statistical measures across increasing biomarker combinations. This may have implications for clinical diagnosis and for selecting subjects for participation in clinical trials.

Structural MRI markers may serve as surrogate endpoints in clinical trials on disease modification in Alzheimer's disease (AD). Here, we used a longitudinal MRI data set of total brain and cortical grey matter volumes from 66 patients with AD recruited across seven centres of the German Dementia Competence Network. We compared effect size estimates for the detection of a 25% reduction of atrophy progression between a priori segmentation of brain tissue, implementing an anatomical model of brain tissue distribution, and a posteriori segmentation that was not informed by an anatomical model. Additionally, we compared effect size estimates between fixed effects analysis and a mixed effects model, implementing a random effects term to account for variable spacing of observation times. A priori segmentation reduced the required sample size by 50%. Introducing a random effects term for time led to an additional 50% reduction of required samples sizes compared to fixed effects analysis. In summary, using a priori segmentation with mixed effects analysis reduced the sample size to detect clinically relevant treatment effects more than fourfold. The implementation of mixed effects models will enhance the power to detect treatment effects also with other classes of biological endpoints including molecular biomarkers of disease.

Einleitung: Der demographische Wandel und die damit einhergehende Zunahme von Multimorbidität, chronischen Erkrankungen und Pflegebedürftigkeit bedingen einen immer häufigeren Wechsel von Pflegebedürftigen zwischen den Gesundheitsinstitutionen und -sektoren. Eine Kontinuität[zum vollständigen Text gelangen Sie über die oben angegebene URL], GMDS 2015; 60. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Einleitung: Im November 2012 wurden der Bachelor- und Masterstudienschwerpunkt Medizinische Informatik (MI) der Institute für Medizinische Informatik und Informatik der Universität Göttingen durch die International Medical Informatics Association (IMIA) akkreditiert [ref:1] [for full text, please go to the a.m. URL], GMDS 2013; 58. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Einleitung: Die Verwertung wertvoller, seltener oder historischer Biomaterialien im Rahmen von Verbundforschungsprojekten erfordert eine besondere Handhabung. Vor der Herausforderung, die Nutzung dieser Materialien effizient zu gestalten, steht auch das KKNMS [ref:1]. Um Hirnbiopsien für[for full text, please go to the a.m. URL], GMDS 2012; 57. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Einleitung: Die Rolle der telematischen Anwendungen in unserem Gesundheitswesen ist mit dem neuen Versorgungsstrukturgesetzt noch bekräftig worden. Die Kassenärztliche Vereinigungen (KVen) und die Kassenärztliche Bundesvereinigung (KBV) haben die Bedeutung der Zusammenarbeit in der Gesundheitstelematik[for full text, please go to the a.m. URL], GMDS 2012; 57. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Einleitung und Fragestellung: Der dokumentenbasierte Informationsaustausch in der multiprofessionellen und intersektoralen Versorgung wird in naher Zukunft immer stärker durch die im Aufbau befindliche Telematikinfrastruktur abgelöst werden. Als ein erstes Anwendungsparadigma innerhalb der[for full text, please go to the a.m. URL], GMDS 2012; 57. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Einleitung: In den: „Empfehlungen zur Weiterentwicklung der Zahnmedizin an den Universitäten in Deutschland“ weist der Wissenschaftsrat auf die vorhandenen Defizite in der zahnmedizinischen Forschung im Vergleich zur Humanmedizin hin [ref:1]. Als ein Mittel zur Förderung[for full text, please go to the a.m. URL], Mainz//2011; 56. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds), 6. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi)