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—large, complex sets of data that require specialized approaches to use effectively. Big data has the potential for significant rewards—and significant risks—to healthcare. In this Discussion, you will consider these risks and rewards.
To Prepare this Discussion: Big Data Risks and Rewards NURS 6051:
Review the Resources and reflect on the web article Big Data Means Big Potential, Challenges for Nurse Execs.
Reflect on your own experience with complex health information access and management and consider potential challenges and risks you may have experienced or observed.
Discussion: Big Data Risks and Rewards NURS 6051
By Day 3 of Week 5Post a description of at least one potential benefit of using big data as part of a clinical system and explain why. Then, describe at least one potential challenge or risk of using big data as part of a clinical system and explain why. Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using big data you described. Be specific and provide examples.
By Day 6 of Week 5Respond to at least two of your colleagues* on two different days, by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks Discussion: Big Data Risks and Rewards NURS 6051.
*Note: Throughout this program, your fellow students are referred to as colleagues.
Big Data: Potential Benefits and Risks Example
Big Data in nursing practice has no unified definition. However, the baseline meaning of Big Data corresponds to the enormous size of data regarding volume, velocity, variety, and veracity (Wong et al., 2016).
The advancement of technology and clinical research studies has increased the amount of data handled in every facet of nursing practice. The use of big data in the clinical system has potential benefits and risks. This paper will discuss the potential benefits and risks associated with the utilization of big data in nursing clinical systems and propose one strategy to prevent the risks.
Potential Benefit of Using Big Data
In the nursing practice, big data sources include the nursing clinical research findings, patient medical records, and results of clinical examination and laboratory investigations, including imaging. The application of big data concepts in the healthcare industry aims at improving the quality of healthcare outcomes by revolutionizing and modernizing healthcare practice (Agrawal & Prabakaran, 2020).
Including technology in handling big data in nursing and clinical research has potential benefits for future healthcare. Analysis and utilization of big data will positively impact healthcare quality by increasing its effectiveness while reducing costs.
Secondly, insight descriptive analysis of big data yields diagnostic data that result in predictive outcomes. The predictive outcomes yield prescriptive results that lead to smarter and cost-effective health outcomes (Dash et al., 2019).
This can happen in four different ways: early risk factor determination; early determination of markers or signals of adverse situations of disease or intervention; timely decision making based on analyzed past data; and ability to predict future outcomes of diseases (Pastorino et al., 2019). Through these four ways, big data ensures timely diagnosis and effectiveness of interventions, improved patient safety and pharmaco-vigilance, and disease prevention.
Scrutinizing big data differs from a secondary healthcare data analysis in the health setting. The intention of big data analysis and utilization of this data with undiscovered scope or size is to answer certain research questions and uncover certain disease conditions that are yet to be fully epidemiologically described. Therefore, big data has the potential of changing the course and practice of medicine and nursing by making them more preventive, diagnostic, and therapeutic (Ienca et al., 2018).
