Big Data and Healthcare: Big Opportunity or Big

Problem?

Abstract The concept of big data in industry first appeared on the academic and professional scene around the turn of the millennium, however despite several investigations the exact etymology of the phrase remains unclear, whilst the term may have been used in scientific papers or reports in the late 1980s and early 90s it is not clear when it first assumed the connotations associated with it today. An exact definition of what the term ‘big data’ means has yet to be defined however the majority of common literature refers to data that exceeds the processing capacity of conventional information management systems. It is too large for normal storage, accumulates too quickly and is difficult to share, visualise and analyse due to its complexity. The 4 Vs of volume, variety, velocity and veracity currently define big data. This thesis provides a qualitative literature review of big data, a collection of possible areas of application to the healthcare sector supported with case studies of current projects, barriers that may limit its application and a summary of big data’s future prospects in healthcare. Much is expected of the potential for big data analysis, particularly in the healthcare sector, where it is anticipated to provide new insights into clinical trials and pharmaceutical development, improved healthcare efficiency and efficacy and better overall health outcomes. Regardless of the expectations it is still early days for big data and analytics in the healthcare sector. It appears inevitable that big data applications such as public health surveillance, biometric monitoring and clinical decision support systems will play a role in healthcare in the near future. However practical integration of these and other initiatives will be a gradual process and not the instantaneous revolution that some big data proponents envisage. Despite being in its infancy, big data could act as a major catalyst for healthcare reform and innovation.