Investigating the dimensions, components, and key indicators of the use of big data in the health industry

Hamed Nozari () and Javid Ghahremani-Nahr ()

Journal of Data Analytics, 2022, vol. 1, issue 1, 1-7

Abstract: Using big data analytics in healthcare has positive as well as life-saving results. Big data refers to the vast amounts of information generated by the digitization of everything that is synthesized and analyzed by specific technologies. Here Big Data uses health services to use specific health data of a population (or a specific individual) and potentially help prevent disease pandemics, treat diseases, reduce costs, and more. In the field of health, big data covers a wide range of information, including physiological, behavioral, molecular, clinical, medical imaging, disease management, medication history, nutrition, or exercise parameters. Big Data Analysis In the field of health, it is a complex process of examining big data to discover information. This information includes hidden patterns, market trends, unknown correlations, and customer preferences. Information analysis can help organizations make informed business and clinical decisions. The medical data-driven industry is the most complex among industries. Not only is this data available from a variety of sources, but it must also comply with government regulations. This process is difficult and delicate and requires some level of security and communication. Due to the importance of this issue, in this article, after introducing the types of data available in the health industry, the characteristics and sources of big data in health are defined and an analytical model for the use of large data in the health industry is presented. This model helps to understand the dimensions, components, and key elements of using big data in the health industry.

Keywords: Big Data Analysis; Health Industry; Data Production; Intelligent Technologies in the Medical Industry (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:bao:jdaisn:v:1:y:2022:i:1:p:1-7:id:1

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