SRI Security Research Institute, Edith Cowan University
Place of Publication
Perth, Western Australia
Big data analytics is a growth area with the potential to provide useful insight in healthcare. Whilst many dimensions of big data still present issues in its use and adoption, such as managing the volume, variety, velocity, veracity, and value, the accuracy, integrity, and semantic interpretation are of greater concern in clinical application. However, such challenges have not deterred the use and exploration of big data as an evidence source in healthcare. This drives the need to investigate healthcare information to control and reduce the burgeoning cost of healthcare, as well as to seek evidence to improve patient outcomes. Whilst there are a number of well-publicised examples of the use of big data in health, such as Google Flu and HealthMap, there is no general classification of its uses to date. This study used a systemic review methodology to create a categorisation of big data use in healthcare. The results indicate that the natural classification is not clinical application based, rather it falls into four broad categories: administration and delivery, clinical decision support (with a sub category of clinical information), consumer behaviour, and support services. Further, the results demonstrate that the use of big data in all examples in the literature is not singular in its approach and each study covers multiple use and application areas. This study provides a baseline to assess the proliferation of the use of big data in healthcare and can assist in the understanding the breadth of big data applications.