Discussion: Big Data Risk and Rewards

Discussion: Big Data Risk and Rewards 

Discussion: Big Data Risk 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—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:

 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


By Day 6 of Week 5

Respond 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


*Note: Throughout this program, your fellow students are referred to as colleagues.

Submission and Grading Information

Grading Criteria

To access your rubric:

Week 5 Discussion Rubric


Post by Day 3 and Respond by Day 6 of Week 5


To participate in this Discussion:

Week 5 Discussion


Next Module


To go to the next module:

Module 4


Module 4: Technologies Supporting Applied Practice and Optimal


Patient Outcomes (Weeks 6-8)


Laureate Education (Producer). (2018). Informatics Tools and Technologies [Video file]. Baltimore, MD:


Accessible player

Learning Objectives

Students will:

 Evaluate healthcare technology


Learning Resources

Required Readings

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.).

Burlington, MA: Jones & Bartlett Learning.

 Chapter 22, “Data Mining as a Research Tool” (pp. 477-493)


 Chapter 24, “Bioinformatics, Biomedical Informatics, and Computational Biology” (pp. 537-551)


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

from https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf


Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved

from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs


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.


Required Media


Laureate Education (Executive Producer). (2012). Data, information, knowledge and wisdom

continuum [Multimedia file]. Baltimore, MD: Author. Retrieved from http://mym.cdn.laureate-



Laureate Education (Producer). (2018). Health Informatics and Population Health: Analyzing Data for

Clinical Success [Video file]. Baltimore, MD: Author.

Accessible player


Vinay Shanthagiri. (2014). Big Data in Health Informatics [Video file]. Retrieved

from https://www.youtube.com/watch?v=4W6zGmH_pOw

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