Big Data Risks and Rewards When you wake in the morning, you may reach for your cell phone to reply to a few text or email messages that you missed overnight. On your drive to work, you may stop to refuel your car. Upon your arrival, you might swipe a key card at the door to gain entrance to the facility. And before finally reaching your workstation, you may stop by the cafeteria to purchase a coffee. From the moment you wake, you are in fact a data-generation machine. Each use of your phone, every transaction you make using a debit or credit card, even your entrance to your place of work, creates data. It begs the question: How much data do you generate each day? Many studies have been conducted on this, and the numbers are staggering: Estimates suggest that nearly 1 million bytes of data are generated every second for every person on earth. As the volume of data increases, information professionals have looked for ways to use

Big Data refers to high volume and highly diverse biological, clinical, lifestyle, and environmental data on health and wellness status. Data collection ranges from one person to large cohorts. Big data in clinical systems obtain information from numerous sources such as patient summaries, EHRs, clinical trials, genomic data, telehealth, pharmaceutical data, and mobile apps (Pastorino et al., 2019). Employing big data in a clinical system comes with several benefits since it helps discover disease risk factors in an individual patient or a specific population (Glassman, 2017). Using big data increases disease prevention opportunities and informs health promotion activities for patients and the community.

Health professionals can analyze big data from a patient’s clinical data gathered from EHR and summaries in predicting the possible risk of a patient developing a lifestyle disease or a disease complication (Wang et al., 2019). From the risk prediction, the health can then plan appropriate health promotion interventions to lower the risk of having the disease or slow the progression of an existing condition.

However, using big data in a clinical system has its limitation, like the risk of a data breach.  Big data compromises the security of patient data from data breaches, system hacks, and ransomware (Pastorino et al., 2019). A data breach occurs due to ineffective administrative system safeguards to secure patient data. In addition, public cloud services increase the risk of system hacks causing a data breach.

The risk of a data breach in big data can be alleviated through staff training to enhance the organization’s data security measures. McGonigle and Mastrian (2017) assert that organizations can train staff on data security protocols and updates in the protocols. Furthermore, organizations can frequently evaluate the staff with access to sensitive patient data to avoid data breach or damage by hackers and malicious parties.

References

Glassman, K. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45-47.

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th Ed.). Burlington, MA: Jones & Bartlett Learning.

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