The need to manage large volumes of data while making it readily accessible and easy to use has accelerated the demand for big data systems. While sectors like retail and banking were quick to adopt big data systems, the healthcare industry was initially reluctant to adopt these systems partly due to concerns with patient confidentiality. However, with research demonstrating the extent to which big data could positively impact healthcare systems, the industry is gradually adopting it. The result has been an increased capacity by healthcare providers to access and manage large volumes of data, gain access to a wide variety of resources, and to interact with data in real time. Big data has also made it possible to have ready access to accurate and trustworthy data. Hence, big data has improved healthcare delivery by easing the processes of promoting informed lifestyle choices; guaranteeing that treatment choices are based on evidence-based care; and ameliorating quality while lessening the cost of healthcare. While big data is still relatively new in the healthcare industry, early signs indicate that the industry could greatly benefit from systems for managing large volumes of data.
In the healthcare industry, big data presents a shift from the traditional system in which healthcare providers had limited access to large volumes of data. Instead, physicians would rely on their judgment to make treatment decisions. Thus, while the concept of evidence-based practice was not new, physicians had limited opportunities to access the right information on-demand. Data were processed using conventional tools like a desktop computer installed on a standalone desk ( Groves et al., 2016 ). Whenever large volumes of data required to be processed, healthcare providers would rely on third-party operators of big data systems. However, with the advent of big data in healthcare, big data is processed by clustering and scanning multiple clusters in a unified network ( Groves et al., 2016 ). The implication is that systems facilitate the processing of large volumes of data and uphold the security, scalability, and manageability of data ( Groves et al., 2016 ). The process of handling and generating big data sets is made possible by programs like MapReduce paradigm and Online Analytical Processing, depending on the needs of the industry.
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The primary role of big data in the health sector is to manage data sets that are too complex and difficult to manage using conventional hardware, software, and management tools. Such data management is increasingly necessary as the volume of healthcare data grows over time and as the variety of payment options increases. The impact of big data systems on the industry, however, goes beyond increased convenience. As Kumar and Singh (2018) explain, the four key attributes of big data that have proved beneficial to the healthcare sector are volume, veracity, variety, and velocity. Volume is relevant as there is no limit to the quantity of data managed with big data systems. Velocity is equally significant as it guarantees that data is accessed on-demand in its various forms. Variety, on the other hand, is the attribute that makes it possible to store data in diverse attributes, such as structured and unstructured data, medical imagery, text, and sensor data. Finally, veracity guarantees that the data is accurate and is, as such, credible and reliable. Veracity is particularly relevant in healthcare because an evidence-based practice has to be based on valid and verifiable information (Kumar & Singh, 2018). Therefore, these four attributes of big data are relevant in impacting the healthcare industry positively.
Owing to the existing capabilities realized by utilizing big data systems and the potential that could be realized with increased use, it is evident that big data is beneficial to the healthcare industry. Kumar and Singh (2018) demonstrate that the impact of big data goes beyond day-to-day applications in healthcare practice. Big data is attributable to better living standards owing to increased active engagement of clients and guaranteeing that the right healthcare provider delivers services to clients. Big data is also linked with the assurance that the right innovations are put in place to advance care standards (Groves et al., 2016). Furthermore, big data facilitates assessment and comparisons, thus guiding stakeholders to understand the frontiers that deserve research and development investments. Big data in healthcare also makes it possible to guarantee that value is enhanced by improving quality and reducing healthcare costs.
Conclusion
The move to adopt big data systems in healthcare has been necessitated by the need to manage data sets that are too complex and difficult to manage using conventional hardware, software, and management tools. While big data is still relatively new in the healthcare industry, early signs indicate that the industry could greatly benefit from systems for managing large volumes of data. T he four key attributes of big data, namely, volume, veracity, variety, and velocity, have particularly proved beneficial to the healthcare sector by enhancing day-to-day healthcare operations. In addition, big data has been shown to improve healthcare outcomes by enhancing clients' lifestyle choices, the choice of the healthcare provider available for a particular client, the value of care, and innovations in healthcare. Based on these observations, it is justifiable to argue that big data has impacted the healthcare industry positively.
References
Groves, P., Kayyali, B., Knott, D., & Kuiken, S. V. (2016). The'big data'revolution in healthcare: Accelerating value and innovation. McKinsey and Company. https://www.mckinsey.com/industries/healthcare-systems-and-services/our-insights/the-big-data-revolution-in-us-health-care#
Kumar, S., & Singh, M. (2018). Big data analytics for healthcare industry: impact, applications, and tools. Big Data Mining and Analytics , 2 (1), 48-57.
