The connected age: big data & data visualization.

Abstract

Welcome to the world of Big Data. care, we amass a lot of data from various sources. Francis Collins (2014), director of the National Institutes of Health, describes a mountain of data consisting of enormous, ever-expanding trove of digital data through DNA sequencing, biomedical imaging, and by replacing a patient's medical chart with a lifelong electronic medical record.In the era of Connected Health, data extracted from various care institutions, payers, research entities, and pharmaceutical industries, as well as patient-generated data (PGHD), are being used to create the lifelong electronic record (EHR) Collins describes. The Big Data revolution in care offers opportunities to discover threads of (Groves, Kayyali, Knott, & Van Kuiken, 2013).To identify these threads, it is imperative that analytic tools such as data mining be used to make sense of the trove of digital data. The analysis of these mountains of data is important to support an organi- zation as a learning system (LHS) (Olsen, Aisner, & McGinnis, 2007; Skiba, 2011). According to the National Committee on Vital Health Statistics (2011), In a learning system, people, actions, results, and knowledge are connected in continuous feedback loops that enable improvement and change - learning - over time (p. 9). The informatics infrastructure, information technology tools, and analytic techniques are making it increasingly possible for communi- ties to become dynamic learning systems that are working to improve local health (p. 9).As patients, families, caregivers, and consumers become more engaged in the Connected Age, it will be equally important to connect these various data sources (PGHD as well as data from EHRs) to help individuals better manage their health. And, for maximum benefit, especially for patients and providers, there is a need to display data in an accessible, useful, and usable manner.In a blog post on the National Center for Healthcare Leadership website, Garmen (2013) spoke to the emerging competencies needed in the era of Big Data and the LHS. Along with statistics and contextual knowledge of the healthcare organizations the data represent, there is also a need for advanced competencies in 'storytelling' - translating statistics into practical wisdom and action, through compelling narra- tive and visualization.Garmen's views resonate with me as an educator and lead to questions for nursing education: 1) Will nurses need to demonstrate data visualization literacy competency to provide care now and in the future? 2) Do we as educators need to help our students gain experience in reading and interpreting these statistical translations and using visualization techniques to provide patient data for clinical decision-making?Before tacking these questions, it is important to understand the term data visualization literacy. I have been familiar with the term visual literacy from the work of Tufte, a statistician who uses infor- mation design to display data, information, and evidence (www. edwardtufte.com/tufte/). A working definition of visualization liter- acy was offered at a EuroVis 2014 Workshop: As a scholarly subject, visualization literacy is expected to encompass both cognitive aspects (e.g., nonverbal reasoning, and spatial navigation with visual repre- sentations) and pedagogical aspects (e.g., learning visual representa- tions, metaphors and languages, educational curricula, and specialized training), and to explore cognitive abilities in visualization evaluation and competency development (www.kth.se/profile/178785/page/ eurovis-2014-workshop-towards-visualiza/).Now, as visual literacy merges with data literacy to form the new concept of data visualization literacy, we must ask: Is this a competency that nurses need? A review of the literature indicates that the answer is yes. Nurses need to understand and interpret the visual displays of data in their practice. …