Walden University NURS 6051 Week 3 4 Big Data Capabilities and Challenges Discussion

Walden University NURS 6051 Week 3 4 Big Data Capabilities and Challenges Discussion

Walden University NURS 6051 Week 3 4 Big Data Capabilities and Challenges Discussion

Module 3: Data-Information-Knowledge-Wisdom (DIKW) (Week 5)

Laureate Education (Producer). (2018). Data-Information-Knowledge-Wisdom [Video file]. Baltimore, MD: Author.

Accessible player  –Downloads– Download Video w/CC Download Audio Download Transcript

Learning Objectives

Students will:

  • Analyze benefits, challenges, and risks of using big data in clinical systems
  • Recommend strategies to mitigate challenges and risks of using big data in clinical systems

Learning Resources

Big Data Capabilities and Challenges Discussion 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. 

Big Data Capabilities and Challenges Discussion Required Media

Laureate Education (Executive Producer). (2012). Data, information, knowledge and wisdom continuum [Multimedia file]. Baltimore, MD: Author. Retrieved from http://mym.cdn.laureate-media.com/2dett4d/Walden/NURS/6051/03/mm/continuum/index.html

Laureate Education (Producer). (2018). Health Informatics and Population Health: Analyzing Data for Clinical Success [Video file]. Baltimore, MD: Author.

Accessible player  –Downloads– Download Video w/CC Download Audio Download Transcript

Vinay Shanthagiri. (2014). Big Data in Health Informatics [Video file]. Retrieved from https://www.youtube.com/watch?v=4W6zGmH_pOw

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 Capabilities and Challenges Discussion

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. Big Data Capabilities and Challenges Discussion

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 examples.

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 risks. Big Data Capabilities and Challenges Discussion

*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

Big Data Capabilities and Challenges Discussion Rubric Detail

Name: NURS_5051_Module02_Week03_Discussion_Rubric

  Excellent Good Fair Poor
Main Posting 45 (45%) – 50 (50%)

Answers all parts of the discussion question(s) expectations with reflective critical analysis and synthesis of knowledge gained from the course readings for the module and current credible sources.

 

Supported by at least three current, credible sources.

 

Written clearly and concisely with no grammatical or spelling errors and fully adheres to current APA manual writing rules and style.

35 (35%) – 39 (39%)

Responds to some of the discussion question(s).

 

One or two criteria are not addressed or are superficially addressed.

 

Is somewhat lacking reflection and critical analysis and synthesis.

 

Somewhat represents knowledge gained from the course readings for the module.

 

Post is cited with two credible sources.

 

Written somewhat concisely; may contain more than two spelling or grammatical errors.

 

Contains some APA formatting errors.

0 (0%) – 34 (34%)

Does not respond to the discussion question(s) adequately.

 

Lacks depth or superficially addresses criteria.

 

Lacks reflection and critical analysis and synthesis.

 

Does not represent knowledge gained from the course readings for the module.

 

Contains only one or no credible sources.

 

Not written clearly or concisely.

 

Contains more than two spelling or grammatical errors.

 

Does not adhere to current APA manual writing rules and style.

Main Post: Timeliness 10 (10%) – 10 (10%)

Posts main post by day 3. Big Data Capabilities and Challenges Discussion

0 (0%) – 0 (0%) 0 (0%) – 0 (0%)

Does not post by day 3.

First Response 17 (17%) – 18 (18%)

Response exhibits synthesis, critical thinking, and application to practice settings.

 

Responds fully to questions posed by faculty.

 

Provides clear, concise opinions and ideas that are supported by at least two scholarly sources.

 

Demonstrates synthesis and understanding of learning objectives.

 

Communication is professional and respectful to colleagues.

 

Responses to faculty questions are fully answered, if posed. Big Data Capabilities and Challenges Discussion

 

Response is effectively written in standard, edited English.

13 (13%) – 14 (14%)

Response is on topic and may have some depth.

 

Responses posted in the discussion may lack effective professional communication.

 

Responses to faculty questions are somewhat answered, if posed.

 

Response may lack clear, concise opinions and ideas, and a few or no credible sources are cited.

0 (0%) – 12 (12%)

Response may not be on topic and lacks depth.

 

Responses posted in the discussion lack effective professional communication.

 

Responses to faculty questions are missing.

 

No credible sources are cited.

Second Response 16 (16%) – 17 (17%)

Response exhibits synthesis, critical thinking, and application to practice settings.

 

Responds fully to questions posed by faculty.

 

Provides clear, concise opinions and ideas that are supported by at least two scholarly sources.

 

Demonstrates synthesis and understanding of learning objectives.

 

Communication is professional and respectful to colleagues.

 

Responses to faculty questions are fully answered, if posed.

 

Response is effectively written in standard, edited English.

.Big Data Capabilities and Challenges Discussion 12 (12%) – 13 (13%)

Response is on topic and may have some depth.

 

Responses posted in the discussion may lack effective professional communication.

 

Responses to faculty questions are somewhat answered, if posed.

 

Response may lack clear, concise opinions and ideas, and a few or no credible sources are cited.

0 (0%) – 11 (11%)

Response may not be on topic and lacks depth.

 

Responses posted in the discussion lack effective professional communication.

 

Responses to faculty questions are missing.

 

No credible sources are cited.

Participation 5 (5%) – 5 (5%)

Meets requirements for participation by posting on three different days.

Big Data Capabilities and Challenges Discussion 0 (0%) – 0 (0%) Big Data Capabilities and Challenges Discussion 0 (0%) – 0 (0%)

Does not meet requirements for participation by posting on 3 different days.

Total Points: 100

Big Data Capabilities and Challenges Discussion Rubric