Big Data Challenges from a Human Factors Perspective

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.

[1]  Philip Kortum,et al.  HCI Beyond the GUI: Design for Haptic, Speech, Olfactory, and Other Nontraditional Interfaces , 2008 .

[2]  Wyeth W. Wasserman,et al.  Dynamic software design for clinical exome and genome analyses: insights from bioinformaticians, clinical geneticists, and genetic counselors , 2015, J. Am. Medical Informatics Assoc..

[3]  Elizabeth M. Borycki,et al.  Usability problems do not heal by themselves: National survey on physicians' experiences with EHRs in Finland , 2017, Int. J. Medical Informatics.

[4]  T. Murdoch,et al.  The inevitable application of big data to health care. , 2013, JAMA.

[5]  Wyeth W. Wasserman,et al.  Usability study of clinical exome analysis software: Top lessons learned and recommendations , 2014, J. Biomed. Informatics.

[6]  André Kushniruk,et al.  Analysis of Complex Decision-Making Processes in Health Care: Cognitive Approaches to Health Informatics , 2001, J. Biomed. Informatics.

[7]  A Kushniruk,et al.  Human Factors in the Large: Experiences from Denmark, Finland and Canada in Moving Towards Regional and National Evaluations of Health Information System Usability , 2014, Yearbook of Medical Informatics.

[8]  André Kushniruk,et al.  A Framework for User Involvement and Context in the Design and Development of Safe e-Health Systems , 2012, MIE.

[9]  Vimla L. Patel,et al.  Cognitive and usability engineering methods for the evaluation of clinical information systems , 2004, J. Biomed. Informatics.

[10]  Vimla L. Patel,et al.  Review: A Primer on Aspects of Cognition for Medical Informatics , 2001, J. Am. Medical Informatics Assoc..

[11]  Elizabeth M. Borycki,et al.  Development of a Video Coding Scheme for Analyzing the Usability and Usefulness of Health Information Systems , 2015, CSHI.

[12]  Andrew Sears and Julie A. Jacko The human-computer interaction handbook , 2013 .

[13]  Harold Lehmann,et al.  Big Data and Health Analytics , 2014 .