Big data is a huge amount of structured and unstructured data of various kinds that are processed by software tools. This is a socio-economic phenomenon associated with the emergence of technological opportunities for analyzing huge amounts of data, including world data, and the resulting transformational consequences. Currently, the term includes not only the data itself but also technologies for their processing and use, methods for finding the necessary information in large arrays for healthcare. I agree with the first post that big data can allow nursing and healthcare to prevent, diagnose, treat, and evaluate diseases and outcomes. In addition, it can be applied to the healthcare community level, and it is stated that different regions can exhibit a wide range of patterns (Chen et al., 2017). However, in order to utilize the given instrument appropriately, it is essential to develop new computational methods to optimize the data management process in regards to patients, where their privacy is not violated (Baro et al., 2015).
In the case of the second post, it is true that big data can significantly improve the flow of care. I would like to add that it can also be used in clinical decision support and reduction of the overall cost (Mehta & Pandit, 2018). In addition, the technology’s capabilities are manifested in five main areas, which are traceability, decision support capability, predictive capability, analytical capability for patterns of care, and unstructured data analytical capability (Wang et al., 2018). Thus, the general benefits of big data in healthcare can come in many forms and shapes. In sum, big data technology is a newly emerging tool that can prove its high degree of use in clinical practice. It can be adjusted to enhance community-based nursing by being specific to a particular region. It can also reduce costs and support the decision processes with the help of factors, such as traceability and analytical and predictive capabilities. However, big data needs to be integrated with caution due to privacy issues, which can be overcome by designing new computational methods suited for healthcare and nursing.
Baro, E., Degoul, S., Beuscart, R., & Chazard, E. (2015). Toward a literature-driven definition of big data in healthcare. BioMed Research International, 2015, 1-9. Web.
Chen, M., Hao, Y., Hwang, K., Wang, L., & Wang, L. (2017). Disease prediction by machine learning over big data from healthcare communities. IEEE Access, 5, 8869-8879. Web.
Mehta, N., & Pandit, A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International Journal of Medical Informatics, 114, 57-65. Web.
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13. Web.