NURS 6051 Big Data Risks and Rewards

NURS 6051 Big Data Risks and Rewards

Big Data Risks and Rewards

Technology has allowed healthcare professionals to enhance health outcomes by implementing data-driven practices. Guided by the principles of health informatics, the evolving practice has witnessed the rise of big data influencing critical nursing processes. One potential benefit of using big data in clinical systems is personalizing patient care by helping clinicians identify patent-specific treatments (Batko & Ślęzak, 2022). Personalizing care is a foundation of high patient outcomes since it ensures interventions match patient needs. Pastorino et al. (2019) explained that the potential of big data to enhance outcomes is centered on its ability to detect illness patterns and other metrics and turn them into actionable knowledge. Data analytics helps healthcare professionals to analyze and interpret trends.

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Despite the great potential of big data in personalizing care, it encounters numerous challenges that hamper its overall effectiveness. To benefit from data, healthcare professionals collect massive amounts of health information from patients. As Pastorino et al. (2019) observed, this data is highly susceptible to security threats, particularly in organizations without a robust technical infrastructure to avert risks. Security threats compromise privacy since patients’ private information can be accessed by unauthorized users. Pastorino et al. (2019) further highlighted that the healthcare industry is the most susceptible to data security threats, and attackers use data mining techniques to phish sensitive data. Protecting this data requires organizations to intensify security to avoid breaches.

Healthcare facilities use various approaches to mitigate big data security threats. Abouelmehdi et al. (2018) posited that a multifaceted approach is the most effective due to the variance in the type and magnitude of security threats. Authentication and data encryption are among the recommended safety measures. Authentication protects users’ identities and secures access to the organization’s vital network and databases (Ristevski & Chen, 2018). Encryption also secures clinical systems from unauthorized access to sensitive data. Consequently, it protects sensitive data and its ownership throughout its lifecycle.

References

Abouelmehdi, K., Beni-Hessane, A., & Khaloufi, H. (2018). Big healthcare data: Preserving security and privacy. Journal of Big Data5(1), 1-18. https://doi.org/10.1186/s40537-017-0110-7

Batko, K., & Ślęzak, A. (2022). The use of big data analytics in healthcare. Journal of Big Data9(1), 3. https://doi.org/10.1186/s40537-021-00553-4

Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European journal of public health29(Supplement_3), 23-27. https://doi.org/10.1093/eurpub/ckz168

Ristevski, B., & Chen, M. (2018). Big data analytics in medicine and healthcare. Journal of Integrative Bioinformatics15(3), 20170030. https://doi.org/10.1515/jib-2017-0030

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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—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.

Resources

 

Be sure to review the Learning Resources before completing this activity.
Click the weekly resources link to access the resources.

WEEKLY RESOURCES

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.

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

NURS_5051_Module03_Week05_Discussion_Rubric

NURS_5051_Module03_Week05_Discussion_Rubric

Criteria Ratings Pts
This criterion is linked to a Learning Outcome Main Posting
50 to >44.0 ptsExcellent

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.

44 to >39.0 ptsGood

Responds to the discussion question(s) and is reflective with critical analysis and synthesis of knowledge gained from the course readings for the module. … At least 75% of post has exceptional depth and breadth. … Supported by at least three credible sources. … Written clearly and concisely with one or no grammatical or spelling errors and fully adheres to current APA manual writing rules and style.

39 to >34.0 ptsFair

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.

34 to >0 ptsPoor

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.

50 pts
This criterion is linked to a Learning Outcome Main Post: Timeliness
10 to >0.0 ptsExcellent

Posts main post by day 3.

0 ptsPoor

Does not post by day 3.

10 pts
This criterion is linked to a Learning Outcome First Response
18 to >16.0 ptsExcellent

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.

16 to >14.0 ptsGood

Response exhibits critical thinking and application to practice settings. … Communication is professional and respectful to colleagues. … Responses to faculty questions are answered, if posed. … Provides clear, concise opinions and ideas that are supported by two or more credible sources. … Response is effectively written in standard, edited English.

14 to >12.0 ptsFair

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.

12 to >0 ptsPoor

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.

18 pts
This criterion is linked to a Learning Outcome Second Response
17 to >15.0 ptsExcellent

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.

15 to >13.0 ptsGood

Response exhibits critical thinking and application to practice settings. … Communication is professional and respectful to colleagues. … Responses to faculty questions are answered, if posed. … Provides clear, concise opinions and ideas that are supported by two or more credible sources. … Response is effectively written in standard, edited English.

13 to >11.0 ptsFair

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.

11 to >0 ptsPoor

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.

17 pts
This criterion is linked to a Learning Outcome Participation
5 to >0.0 ptsExcellent

Meets requirements for participation by posting on three different days.

0 ptsPoor

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

5 pts
Total Points: 100

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