Objectives: Even though today most university hospitals have already implemented commercial hospital information systems and started to build up comprehensive electronic medical records, reuse of such data for data warehousing and research purposes is still very rare. Given this situation, the focus of this paper is to present an overview on exemplary projects, which have already tackled this challenge, reflect on current initiatives within the United States of America and the European Union to establish IT infrastructures for clinical and translational research, and draw attention to new challenges in this area.
Methods: This paper does not intend to provide a fully comprehensive review on all the issues of clinical routine data reuse. It is based, however, on a presentation of a large variety of historical, but also most recent activities in data warehousing, data retrieval and linking medical informatics with translational research.
Results: The article presents an overview of the various international approaches to this issue and illustrates concepts and solutions which have been published, thus giving an impression of activities pursued in this field of medical informatics. Further, problems and open questions, which have also been named in the literature, are presented and three challenges (to establish comprehensive clinical data warehouses, to establish professional IT infrastructure applications supporting clinical trial data capture and to integrate medical record systems and clinical trial databases) related to this area of medical informatics are identified and presented.
Conclusions: Translational biomedical research with the aim "to integrate bedside and biology" and to bridge the gap between clinical care and medical research today and in the years to come, provides a large and interesting field for medical informatics researchers. Especially the need for integrating clinical research projects with data repositories built up during documentation of routine clinical care, today still leaves many open questions and research challenges. Consideration of regulatory requirements, data privacy issues, data standards as well as people/organizational issues are prerequisites in order to vanquish existing obstacles.