Big Data Challenges from a Human Factors Perspective

Abstract

Big data, in the form of ever increasing amounts of healthcare data, promises to revolutionize and transform healthcare. Large amounts of personal health data, fitness data, genomic data and epidemiological data are being generated at an unprecedented rate and this trend will only continue. While advances are being made in the automated collection and analysis of such data, using machine learning, data mining and artificial intelligence techniques, the issue of the human factor in all these developments still remains central to the question of whether such large and complex collections of data are useful and effective in actually improving healthcare decision making and processes. The impact of big data as well as personalized medicine, will ultimately depends on human factors related to effective access, use and application of large data repositories. This chapter will explore some of the issues related to the human factors of big data. Human cognitive limitations and their implications for design of user interfaces and systems that involve big data are described, along with illustrative examples from a number of areas in health informatics. Finally challenges and future directions for the human factors of big data will be discussed.