Review
Version 1
Preserved in Portico This version is not peer-reviewed
Impact of Big Data Analysis on Health
Version 1
: Received: 30 March 2022 / Approved: 31 March 2022 / Online: 31 March 2022 (12:24:19 CEST)
How to cite: Rosário, A.T.; Dias, J.C. Impact of Big Data Analysis on Health. Preprints 2022, 2022030407. https://doi.org/10.20944/preprints202203.0407.v1 Rosário, A.T.; Dias, J.C. Impact of Big Data Analysis on Health. Preprints 2022, 2022030407. https://doi.org/10.20944/preprints202203.0407.v1
Abstract
Big data analytics tools are the use of advanced analytic techniques targeting large and diverse volumes of data that include structured, semi-structured, and unstructured data from different sources and in different sizes from terabytes to zetabytes. The health sector is faced with the need to generate and manage large data sets from various health systems, such as electronic health records and clinical decision support systems. This data can be used by providers, clinicians, and policymakers to plan and implement interventions, detect disease more quickly, predict outcomes, and personalize care delivery. However, little attention is paid to the connection between big data analytics tools and the health sector. Thus, a systematic review of the bibliometric literature (LRSB) was developed to study how the adoption of big data analytics tools and infrastructures will revolutionize the healthcare industry. The review integrated 77 scientific and/or academic documents indexed in SCOPUS presenting up‐to‐date knowledge on current insights on how big data analytics technologies influence the healthcare sector and the different big data analytical tools used. The LRSB provides findings related to the impact of Big Data analytics on the health sector by introducing opportunities and technologies that provide practical solutions to various challenges.
Keywords
big data analytics; healthcare; data technologies; decision making; information management; EHR
Subject
Computer Science and Mathematics, Information Systems
Copyright: This 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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