Stroke Care and the Role of Big Data in Healthcare and Stroke
Rehabilitation Science
Volume 1, Issue 1, November 2016, Pages: 16-24
Received: Sep. 11, 2016; Accepted: Sep. 30, 2016; Published: Nov. 25, 2016
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Lidong Wang, Department of Engineering Technology, Mississippi Valley State University, Itta Bena, USA
Cheryl Ann Alexander, Technology and Healthcare Solutions, Incorporated, Itta Bena, USA
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Theoretically current electronic health data can now be securely linked on an unprecedented scale, potentially illuminating how diseases manifest and which treatments are best applied in the real world. Increasing volumes of information on real-time, actual patient experiences are now contained on social media and patient portal websites. Innovations and insight into the health care for individuals and entire populations can be gained when information from health monitors, genomic data, and clinical trial data is merged. In other words, we now have the theoretical technology to accumulate, store, convert, access, and evaluate massive amounts of data at a modest cost. Performance and clinical data from health care facilities, including clinics and hospitals, clinical research data by industry, and academic data from patient populations and the general public which may be generated through social media and/or other sources is included in big data. Just as access to sizable datasets evolves and becomes easier, analytical mistakes may occur more often and be easier to make lest rigorous standards and governance controls are employed. Indeed, it is more likely that improved analytics will also introduce us to at least a few more uncomfortable insights into the negligible value of some medicines. It is also noteworthy to mention that one common error is the assumption that the value of big data is within the data itself—its volume, accuracy, accessibility, “linkability,” etc. Unfortunately, despite the importance of the information, or the “bigger” the data, the greater the likelihood that this does not hold true. This review paper examines the relationship of big data to stroke care in a variety of stroke-related issues including: big data in stroke care, big data and visual analytics, big data in telecardiology, and some challenges and indications for future research.
Stroke, Big Data, Hypertension, Telecardiology, Electronic Medical Record (EMR), Electronic Health Record (EHR), Big Data Analytics, Machine Learning, Data Mining
To cite this article
Lidong Wang, Cheryl Ann Alexander, Stroke Care and the Role of Big Data in Healthcare and Stroke, Rehabilitation Science. Vol. 1, No. 1, 2016, pp. 16-24. doi: 10.11648/
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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