Big Data in Medicine Is Driving Big Changes

F. Martin-Sanchez; K. Verspoor

doi:10.15265/IY-2014-0020

Yearbook of Medical Informatics, Table of Contents

Yearb Med Inform 2014; 23(01): 14-20
DOI: 10.15265/IY-2014-0020

Original Article

Georg Thieme Verlag KG Stuttgart

Big Data in Medicine Is Driving Big Changes

Authors

F. Martin-Sanchez

¹Health and Biomedical Informatics Centre, The University of Melbourne, Parkville VIC 3010 Australia

²Department of Computing and Information Systems, The University of Melbourne, Parkville VIC 3010 Australia
K. Verspoor

²Department of Computing and Information Systems, The University of Melbourne, Parkville VIC 3010 Australia

¹Health and Biomedical Informatics Centre, The University of Melbourne, Parkville VIC 3010 Australia

Abstract

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

Full Text

References

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