Clinical Research Informatics
The use of informatics in the discovery and management of new knowledge relating to health and disease. It includes management of information related to clinical trials and also involves informatics related to secondary research use of clinical data. Clinical research informatics and translational bioinformatics are the primary domains related to informatics activities to support translational research.
The science and art of generating data-driven solutions through comprehension of complex real-world health problems, employing critical thinking and analytics to derive knowledge from (big) data. Health Data Science is an emergent discipline, arising at the intersection of (bio)statistics, computer science, and health. Solutions require integrative approaches, analytics, decision support using technologies like machine learning and artificial intelligence.
Development, deployment and evaluation of success of innovative tools in health and clinical decision support, cognitive aspects of implementation, team dynamics, educational and cultural aspects, software dissemination approaches, are all essential requirements for improving usability, accuracy and efficiency of solutions that are making real-world impact and democratizing critical access to data and knowledge resources.
The development of storage, analytic, and interpretive methods to optimize the transformation of increasingly voluminous biomedical data, and genomic data, into proactive, predictive, preventive, and participatory health. Translational bioinformatics includes research on the development of novel techniques for the integration of biological and clinical data and the evolution of clinical informatics methodology to encompass biological observations. The end product of translational bioinformatics is newly found knowledge from these integrative efforts that can be disseminated to a variety of stakeholders, including biomedical scientists, clinicians, and patients.