Semantic transformation model for clinical documents in big data to support healthcare analytics

The standardized healthcare documents are being adopted at an exponential rate all around the world which poses several challenges about its large scale analysis and comprehension. The healthcare standards are complex and difficult to understand for a health analytics expert due to its comprehensive nature. This paper proposes a semantic transformation model of the healthcare documents in a distributed environment to tackle the voluminous data and its variety. In this paper Hadoop is used for the semantic transformation model and clinical document architecture (CDA) standard for the case study. The case study shows that the health analytics can be well supported by the transformation model as it is simple and tailor made for the situation.