Big Data management offers considerable opportunities in healthcare – for example, in refining the treatment procedures. The main appeal of Big Data is the fact that it allows for establishing previously unnoticed patterns within large amounts of information. In particular, data mining would allow accounting for more factors in treatment, as the treatment efficiency for any given condition could be analyzed by other diseases or conditions, gender, or age (McGonigle & Mastrian, 2017). This is what Wang et al. (2016) refer to when they mention that Big Data can “improve the quality and accuracy of clinical decisions” (p. 9). Thus, Big Data would allow utilizing much larger amounts of information when developing, implementing, evaluating, and improving treatments for any given condition.
The most notable challenge to implementing Big Data in healthcare settings is the lack of sufficient training among the key personnel. McGonigle and Mastrian (2017) point out that, without sufficient training, a medical professionals cannot be sure that they will pick and develop the tools best suited for their data among the numerous techniques available. For example, clinicians may not be aware that regression trees are most suitable too for classifying patients suffering from a particular condition (Ionita, I. & Ionita, L., 2016). Such a lack of relevant competencies is an obstacle to implementing data mining in healthcare.
A strategy to overcome this challenge is training the key personnel in Big Data usage. As noted by Wang et al. (2016), healthcare organizations should implement comprehensive strategies involving personnel training in statistics and data mining. Such approaches as “mentoring, cross-functional team-based training, and self-study” seem to be the most promising in this regard (Wang et al., 2016, p. 10). Improving the personnel’s competency in handling and analyzing Big Data will lead to increased efficiency in its use and implementation.
Ionita, I., & Ionita, L. (2016). Applying data mining techniques in healthcare. Studies in Informatics and Control, 25(3), 385-394. Web.
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
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(1), 3–13. Web.