Abstract
The Web has caused an exponential increase of available data. This has lead to a new world of applications that take on the challenge of analyzing and exploiting all this data. Data science is a new term to describe the applied blend of mathematics, statistics, computation, and hacking necessary to build data-driven solutions. More and more often, this involves working on Big Data. Breakthroughs are being made in fields in which large amounts of data are handled, leading to increased efficiency and quality of results and, above all, to an array of previously unconceived applications. In this chapter, we will give some insights into the ways in which health care is being transformed by data analysis. First, we will talk about improving data acquisition, crucial to unlocking the potential of new applications. Then, we will move on to clinical decision support systems applied to adverse drug reactions. Last but not least, we will discuss how to leverage Big Data to improve health care. The bigger picture is of data analysis fundamentally changing how we approach many healthcare problems. A data-driven future of health care is ahead.
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Notes
- 1.
Also called automatic coding, autocoding and computer aided coding.
- 2.
All healthcare providers in USA will be required to upgrade from ICD-9 to ICD-10 by October 1 st 2014.
- 3.
Integrated Primary Care Information Database in the Netherlands.
- 4.
Note that, despite using the term Big Data, current data-driven solutions for health are usually implemented at a small scale, for example, in a single hospital or region. While most experts would not label this as Big Data, we chose to stick to this term because everything we explain here is applicable on a massive and global scale.
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Esposti, M.D., Mola-Velasco, S.M., García-Blasco, S. (2014). The Data-Driven Revolution of Health Care. In: Gaddi, A., Capello, F., Manca, M. (eds) eHealth, Care and Quality of Life. Springer, Milano. https://doi.org/10.1007/978-88-470-5253-6_10
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