Summary
Objectives: To summarise current research that takes advantage of “Big Data” in health and biomedical
informatics applications.
Methods:Survey of trends in this work, and exploration of literature describing how large-scale
structured and unstructured data sources are being used to support applications from
clinical decision making and health policy, to drug design and pharmacovigilance,
and further to systems biology and genetics.
Results: The survey highlights ongoing development of powerful new methods for turning that
large-scale, and often complex, data into information that provides new insights into
human health, in a range of different areas. Consideration of this body of work identifies
several important paradigm shifts that are facilitated by Big Data resources and methods:
in clinical and translational research, from hypothesis-driven research to data-driven
research, and in medicine, from evidence-based practice to practice-based evidence.
Conclusions: The increasing scale and availability of large quantities of health data require
strategies for data management, data linkage, and data integration beyond the limits
of many existing information systems, and substantial effort is underway to meet those
needs. As our ability to make sense of that data improves, the value of the data will
continue to increase. Health systems, genetics and genomics, population and public
health; all areas of biomedicine stand to benefit from Big Data and the associated
technologies.
Keywords
Medical informatics - data mining - text mining - information systems - information
storage and retrieval
