Big data in healthcare describes the massive amounts of health information that is collected through the use of digital technologies. Big data not only offers promise in several sectors but has also changed how data is analyzed, managed, and leveraged across sectors, and healthcare is looking at big data to transform public health, clinical care, and personal care. However, as much as various benefits have been associated with the use of big data in healthcare, there are also certain risks that come with the application of big data in healthcare.
One potential benefit of using big data is a clinical system is the identification of patterns of care. According to Wang, Kung & Byrd, big data analytics can be used to identify care patterns and discover associations from massive patient records to offer a wider view for evidence-based practice (EBP) in clinical area. For instance, in a hospital clinical system, big data can be used to discover patterns related to the rates of re-hospitalization. Consequently, there would be efforts to find appropriate measures to address the issues leading to re-hospitalization, which would benefit patients, improve patient outcomes, and impact reimbursement from insurance. Besides, big data can be used in the clinical system to provide insights into the causes and outcomes of illnesses.
One potential challenge of using big data is a clinical system relates to the security and confidentiality of patient information. Pastorino et al. note that the use of big data in healthcare carries new legal and ethical changes due to the personal or private nature of the information it contains. With the use of big data in clinical systems, chances are that personal autonomy and privacy can be compromised. There is also the risk to compromise the effects on public demand for fairness, trust, and transparency with the use of big data.