Discussion: 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. Big Data Risks and Rewards Discussion Paper
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.
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.
By Day 3 of Week 5
Post 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.
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Big Data Risks and Rewards
Post a description of at least one potential benefit of using big data as part of a clinical system and explain why.
As part of a clinical system, big data offers significant benefits. First, it increases clinical efficiency while allowing for precision health care. With big data, the clinician is able to complete routine tasks, such as diagnosis and anticipate medical emergencies, without having to see the patient. This is seen when wearable devices are used in telemedicine so that the clinician is able to monitor the patient from anywhere. This means that the clinician does not have to physically see the patient, thus ensuring timely and appropriate care delivery while saving a great amount of time (Khana, Gupta & Dey, 2021). Secondly, big data allows a healthcare organization to streamline activities and improve on care delivery. Big data can indicate the activities that are working and those that are not working so that the organization is able to make changes that facilitate improvements (Sylvia & Terhaar, 2018). For instance, big data can show if more nurse rounding reduces patient fall rates.
Describe at least one potential challenge or risk of using big data as part of a clinical system and explain why.
A potential challenge of using big data is that it requires particular technology and knowledge professionals to manage the data and turn it into usable information. To run the large data tools, skilled data professionals are needed to include data engineers, data analysts and data scientists who use the tools to make sense of the big data sets (Sewell, 2018).
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.
A strategy for addressing the challenge is to acquire the right technologies and tools, as well as recruit skilled professionals. Also, there is a need to train personnel to ensure that they keep up with the tools even as they change with new ones being presented. Another strategy is to purchase tools and knowledge analytics solutions powered by machined learning and artificial intelligence. This strategy eliminates the need for skilled data professionals so that even persons who are not data science experts but have basic data knowledge can use the tools (Sewell, 2018).
Khana, A., Gupta, D., & Dey, N. (Eds.) (2021). Applications of Big Data in Healthcare: Theory and Practice. Elsevier Science.
Sewell, J. (2018). Informatics and Nursing: Opportunities and Challenges (6th ed.). Wolters Kluwer Health.
Sylvia, M. L., & Terhaar, M. F. (2018). Clinical Analytics and Data Management for the DNP (2nd ed.). Springer Publishing Company.
Big Data Risks and Rewards Discussion Paper