Big data in healthcare: Prospects, challenges and resolutions

Abstract

The healthcare system consists of large volumes of data which are usually generated from diverse sources such as physicians' case notes, hospital admission notes, discharge summaries, pharmacies, insurance companies, medical imaging, laboratories, sensor based devices, genomics, social media as well as articles in medical journals. Healthcare data are however very complex and difficult to manage. This is as a result of the astronomical growth of healthcare data, the high speed at which these data are generated as well as the diversity of data types in healthcare. The capturing, storage, analysis and retrieval of health related data are rapidly shifting from paper based system towards digitization. However, the vast volume as well as the complexity of these data makes it difficult for the data to be processed and analyzed by traditional approaches and techniques. Consequently, technologies such as cloud computing and virtualization are now gradually used for processing massive data effectively and securely in healthcare. Hence, the healthcare system is swiftly becoming a big data industry. Thus, this paper examines the concept of big data in healthcare, its benefits and attendant challenges. This paper revealed that the fragmentation of healthcare data, ethical issues, usability issues as well as security and privacy issues are some of the factors impeding the successful implementation of big data in healthcare. This paper therefore suggests that ensuring security and privacy of healthcare data, the adoption of a standardized healthcare terminology, education strategy and the design of usable systems for processing large volumes of data are some of the ways of successfully implementing big data in healthcare.