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Information Technology for Clinical, Translational and Comparative Effectiveness ResearchFindings from the Yearbook 2015 Section on Clinical Research Informatics
13 August 2015
10 March 2018 (online)
Objectives: To select and summarize key constributions to current research and to select best papers published in 2014 in the field of Clinical Research Informatics (CRI).
Method: A bibliographic search using a combination of MeSH and free terms search over PubMed on Clinical Research Informatics (CRI) was performed followed by a double-blind literature review.
Results: The review process yielded four papers, illustrating various aspects of current research efforts done in the area of CRI. The first paper exemplifies the process of developping a domain ontology for integrating structured, unstructured, and signal data into a coherent structure for patient care as well as clinical research. In the second paper, the authors analysed in five sites’ hospital information system environments in Germany the possibility of implementing a patient recruitment process and provided recommendations for the development of dedicated patient recruitment modules. The third paper describes the IMI EHR4CR project which developed an instance of a platform, providing communication, security and semantic interoperability services to the eleven participating hospitals and ten pharmaceutical companies located in seven European countries. The last paper describes the relation between health status severity and the availability of data in EHR systems. They demonstrate that it introduces a biasis in patient selection for clinical research.
Conclusions: Distributed research networks are growing in importance for clinical research and population health surveillance and current research demonstartes that different projects and initiatives could be well placed to deliver international scale solutions to enable the reuse of hospital EHR data to support clinical research studies. Selected articles demonstrate the potential of formal representation of multimodal and multi-level data in supporting data interoperability across clinical research and care domains. With the development of pragmatic research, designed with input from health systems and producing evidence that can be readily used to improve care, a key issue for “learning health care organizations” is to systematically assess the quality of their data.
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