[Qualification and classification of medical apps : What should be noted and what is BfArM's contribution?] / Abgrenzung und Klassifizierung von Medical Apps : Was ist zu beachten und welche Unterstützung bietet das BfArM?

Smartphones and tablets with their nearly unlimited number of different applications have become an integral part of everyday life. Thus, mobile devices and applications have also found their way into the healthcare sector.For developers, manufacturers, or users as well, it is often difficult to decide whether a mobile health application is a medical device.In this context, it is extremely important for manufacturers to decide at an early stage of the development whether the product is to be introduced into the market as a medical device and is therefore subject to the legislation on medical devices.This article first presents the regulatory framework and subsequently introduces the reader to the Federal Institute for Drugs and Medical Devices' (BfArM) view of the criteria for differentiating between apps as non-medical products and apps as medical apps as well as the classification thereof. Various examples are presented to demonstrate how these criteria are applied practically and options that support developers and manufacturers in their decision making are shown. The article concludes with a reference to current developments and offers a perspective on the new European medical device regulations MDR/IVDR (Medical Device Regulation/In-Vitro Diagnostic Regulation) as well as on future challenges regarding medical apps.

EUROCOURSE lessons learned from and for population-based cancer registries in Europe and their programme owners: Improving performance by research programming for public health and clinical evaluation.

UNLABELLED: Population-based cancer registries (CRs) in Europe have played a supportive, sometimes guiding, role in describing geographic variation of cancer epidemics and comparisons of oncological practice and preventive interventions since the 1950s for all types of cancer, separate and simultaneously. This paper deals with historical and longitudinal developments of the roughly 160 CRs and their programme owners (POs) that emerged since 1927 and accelerating since the late 70s especially in southern and continental Europe. About 40 million newly diagnosed patients were recorded since the 1950s out of a total of 100 million of whom almost 20 million are still alive and about 10% annually dying from cancer. The perception of unity in diversity and suboptimal comparability in performance and governance of CRs was confirmed in the EUROCOURSE (EUROpe against cancer: Optimisation of the Use of Registries for Scientific Excellence in research) European Research Area (ERA)-net coordination FP7 project of the European Commission (EU) which explored best practices, bottlenecks and future challenges of CRs. Regional oncologic and public health changes but also academic embedding of CRs varied considerably, although Anno 2012 optimal cancer surveillance indeed demanded intensive collaboration with professional and institutional stakeholders in two major areas (public health and clinical research) and five minor overlapping cancer research domains: aetiologic research, mass screening evaluation, quality of care, translational prognostics and survivorship. Each of these domains address specific study questions, mixes of disciplines, methodologies, additional data-sources and funding mechanisms. POs tended to become more and more public health institutes, Health ministries, but also comprehensive cancer centres and cancer societies through more and more funding at project or programme basis. POs were not easy to pin down because of their multiple, sometimes competitive (funding) obligations and increasing complexity of cancer surveillance. But they also rather seemed to need guiding principles for Governance of 'their' CR(s) as well as to appreciate value of collaborative research in Europe and shield CRs against unreasonable data protection in case of linkages. Despite access to specialised care related shortcomings, especially of survival cohort studies, European databases for studies of incidence and survival (such as ACCIS and EUREG on the one hand and EUROCARE and RARECARE on the other hand) have proved to be powerful means for comparative national or regional cancer surveillance. Pooling of comparable data will exhibit much instructive variation in time and place. If POs of CRs would consider multinational European studies of risk and prognosis of cancer more to serve their own regional or national interest, then progress in this field will accelerate and lead to more consistent funding from the EU. The current 20 million cancer survivors and their care providers are likely to appreciate more feedback. CONCLUSION: Most CRs remain uniquely able to report on progress against cancer by studies of variation in incidence (in time and place), detection and survival, referral and treatment patterns and their (side) effects in unselected patients, the latter especially in the (very) elderly. Programming and profiling its multiple and diverse clinical and prevention research is likely to promote involvement of public health and clinical stakeholders with a population-based research interest, increasingly patient groups and licensed 'buyers' of oncologic services.

OpenMEEG: opensource software for quasistatic bioelectromagnetics.

BACKGROUND: Interpreting and controlling bioelectromagnetic phenomena require realistic physiological models and accurate numerical solvers. A semi-realistic model often used in practise is the piecewise constant conductivity model, for which only the interfaces have to be meshed. This simplified model makes it possible to use Boundary Element Methods. Unfortunately, most Boundary Element solutions are confronted with accuracy issues when the conductivity ratio between neighboring tissues is high, as for instance the scalp/skull conductivity ratio in electro-encephalography. To overcome this difficulty, we proposed a new method called the symmetric BEM, which is implemented in the OpenMEEG software. The aim of this paper is to present OpenMEEG, both from the theoretical and the practical point of view, and to compare its performances with other competing software packages. METHODS: We have run a benchmark study in the field of electro- and magneto-encephalography, in order to compare the accuracy of OpenMEEG with other freely distributed forward solvers. We considered spherical models, for which analytical solutions exist, and we designed randomized meshes to assess the variability of the accuracy. Two measures were used to characterize the accuracy. the Relative Difference Measure and the Magnitude ratio. The comparisons were run, either with a constant number of mesh nodes, or a constant number of unknowns across methods. Computing times were also compared. RESULTS: We observed more pronounced differences in accuracy in electroencephalography than in magnetoencephalography. The methods could be classified in three categories: the linear collocation methods, that run very fast but with low accuracy, the linear collocation methods with isolated skull approach for which the accuracy is improved, and OpenMEEG that clearly outperforms the others. As far as speed is concerned, OpenMEEG is on par with the other methods for a constant number of unknowns, and is hence faster for a prescribed accuracy level. CONCLUSIONS: This study clearly shows that OpenMEEG represents the state of the art for forward computations. Moreover, our software development strategies have made it handy to use and to integrate with other packages. The bioelectromagnetic research community should therefore be able to benefit from OpenMEEG with a limited development effort.