Data Science: making sense of data

#artificialintelligence 

Written by PHASTAR on 01 November 2019. The volume of digital data in healthcare is projected to increase more rapidly in the coming years than any other sector. On a day-to-day basis it is vital that clinical teams ensure they are maximising the value, not only of their own trial data but also of the wealth of external data for example electronic healthcare records, real-world data and peer-reviewed research published in journals. The ability to utilise this data requires not only an understanding of what is available but how to access the data, work with the structure of the data, understand the quality and inherent biases and importantly apply the right methodology to extract value. In addition to the large volume of standard data generated on a clinical trial there can be a raft of other, more specialised data, such as genomics, proteomics, wearables and comprehensive measurements all of which rely on the skills of an experienced data management, programming and statistics team to utilise.