Medical research is currently facing the Big Data wave. High resolution digital images, genomics data, and the vast amount of medical data resources on-line (medical reports, clinical tests, biology samples, large amounts of structured and unstructured text data...) lead to an unprecedented demand for large-scale data management and analysis. This new situation demands appropriate IT-infrastructures, where medical data can be processed within an acceptable timespan – reaching from minutes in health-care applications to days in large-scale research projects. Large-scale distributed IT-systems such as Grids, Clouds and Big-Data-Environments are promising to address clinical and medical research community requirements. They allow for significant reduction of computational time for running large experiments, for speeding-up the development time for new algorithms, for increasing the availability of new methods for the research community, and for supporting large-scale multi-centric collaborations. However, specific challenges in the employment of such systems for medical applications such as security, reliability and user-friendliness, often impede straightforward adoption of existing solutions from other application domains. This workshop aims at bringing together developers of medical applications and researchers in the field of distributed IT systems. On the one hand, it addresses researchers who are already employing distributed infrastructure techniques in medical applications, in particular scientists developing data- and compute-intensive medical applications that include multi-data studies, large-scale parameter scans or complex analysis pipelines. On the other hand, it addresses computer scientists working in the field of distributed systems interested in bringing new developments into medical applications. The goals are to exchange and discuss existing solutions and latest developments in both fields, and to gather an overview of challenges (technologies, achievements, gaps, roadblocks). The workshop further intends to identify common requirements to lead future developments in collaboration between Health and Computing Sciences, and to collaboratively explore new ideas and approaches to successfully apply distributed IT-systems in translational research, clinical intervention, and decision-making.