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WK 5 RESP

Data Science Applications and Processes

How might data compiled and analyzed in your healthcare organization or nursing practice help support efforts aimed at patient quality and safety? Why might it be important to consider the how’s and why’s of data collection, application, and implementation? How might these practices shape your nursing practice or even the future of nursing?

For this Discussion, you will explore various topics related to data and consider the process and application of each. Reflect on the use of these applications, but also consider the implications of how these applications might shape the future of nursing and healthcare practice.

Resources

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


WEEKLY RESOURCES

earning Resources

Required Readings

· Sipes, C. (2025). 
Project management for the advanced practice nurse (3rd ed.). Springer Publishing.

· Chapter 4, “Planning: Project Management—Phase 2” (pp. 85–130) 

· American Nurses Association. (2015). 

Nursing informaticsLinks to an external site.

: Scope and standards of practice  (2nd ed.).

· “Standard 3: Outcomes Identification” (p. 71)

· “Standard 4: Planning” (p. 72)1

· Brennan, P. F., & Bakken, S. (2015). 
Nursing needs big data and big data needs nursingLinks to an external site.. 
Journal of Nursing Scholarship, 47 (5), 477–484. doi:10.1111/jnu.12159 National Institutes of Health, Office of Data Science Strategy. (2021). 
Data science .

· Carter-Templeton, H., Nicoll, L. H., Wrigley, J., & Wyatt, T. H. (2021). 
Big data in nursing: A bibliometric analysisLinks to an external site.. 
Online Journal of Issues in Nursing, 
26(3).

· Elsaleh, T., Enshaeifar, S., Rezvani, R., Acton, S. T., Janeiko, V., & Bermudez-Edo, M. (2020). 
IoT-stream: A lightweight ontology for internet of things data streams and its use with data analytics and event detection servicesLinks to an external site.. 
Sensors, 20 (4), 953. doi:10.3390/s20040953

· Zhu, R., Han, S., Su, Y., Zhang, C., Yu, Q., & Duan, Z. (2019). 
The application of big data and the development of nursing science: A discussion paperLinks to an external site.. 
International Journal of Nursing Sciences, 6 (2), 229–234. doi:10.1016/j.ijnss.2019.03.001

Required Media

· IDG TECHTalk. (2020, March 27). 

What is predictive analyticsLinks to an external site.

? Transforming data into future insights [Video]. YouTube.

· Simplilearn. (2019, December 10). 

Big data in 5 minutes Links to an external site.
 | What is big data?| introduction to big data | big data explained | simplilearn [Video]. YouTube.

Optional Resources

· Parikh, R. B., Gdowski, A., Patt, D. A., Hertler, A., Mermel, C., & Bekelman, J. E. (2019). Using big data and predictive analytics to determine patient risk in oncology. 

American Society of Clinical Oncology Educational BookLinks to an external site.

, 39 , e53–e58. doi:10.1200/EDBK_238891

· Spachos, D., Siafis, S., Bamidis, P., Kouvelas, D., & Papazisis, G. (2020). 
Combining big data search analytics and the FDA adverse event reporting system database to detect a potential safety signal of mirtazapine abuseLinks to an external site.. 
Health Informatics Journal, 26 (3), 2265–2279. doi:10.1177/1460458219901232

Previous

Next

To Prepare

· Review the Learning Resources for this week related to the topics: Big Data, Data Science, Data Mining, Data Analytics, and Machine Learning. 

· Consider the process and application of each topic.

· Reflect on how each topic relates to nursing practice. 

By Day 3 of Week 5

Post a summary on how predictive analytics might be used to support healthcare. 
Note: These topics may overlap as you will find in the readings (e.g., some processes require both Data Mining and Analytics).

In your post include the following:

· Describe a practical application for predictive analytics in your nursing practice. What challenges and opportunities do you envision for the future of predictive analytics in healthcare?

By Day 6 of Week 5

Read a selection of your colleagues’ responses and 
respond to 
at least two of your colleagues on 
two different days. Expand upon your colleague’s posting or offer an alternative perspective.

RESPOND TO THIS DISCUSSION POST

Markesia

Week 5 Main Response

            Predictive analytics and artificial intelligence have emerged as valuable tools to improve nursing science and patient outcomes. Big data systems can collectively gather data through machine learning and predictive analysis that tailors personalized care and better informs clinical decisions (Zhu et al., 2019). Nursing informatics applies technology to support disseminating evidence-based practices through education, support systems, and predictive analysis (American Nurses Association, 2015).  The American Nurses Association Standards of Professional Performance Standard 10 suggest using data to analyze outcomes, while monitoring the effectiveness of each action (American Nurses Association, 2015). This discussion will review the practical application of predictive analysis in the outpatient hemodialysis center.  

Data science and analytics require a collaborative approach from many disciplines, using theory, research, and a methodical approach to information discovery (Brennan & Bakken, 2015). Fresenius Medical Care’s outpatient dialysis centers developed a machine learning program incorporating cloud computing to send signals to the dialysis machine based on trends proactively. (Olasvrud, 2023). The process of ultrafiltration, or fluid removal, can result in severe intradialytic hypotension requiring emergency treatment. Prolonged hypotension is associated with decreased quality of life, excessive clotting of vascular access, and lower clinical effectiveness of treatments (Olasvrud, 2023).  As a Quality nurse in facilities, Quality Assessment and improvement programs demonstrate reduced hospitalizations and treatment complications, and improved outcomes throughout clinics nationwide through early interventions.  

The importance of big data and predictive analytics cannot be overstated in our healthcare system. Despite the improvement in outcomes, data privacy remains a concern. Outpatient dialysis clinics must use VPN and firewalls to maintain the integrity of information. As part of government standards, firewall and VPN protection are now required for many services. The Center for Medicare and Medicaid Services now provides the CMS online manual system, which provides direction for billing services (U.S. Centers for Medicare and Medicaid Services, 2024). Data analytics and mining could further inform nursing practice, decreasing mortality and improving overall outcomes.

References

 

American Nurses Association. (2015). 
Nursing Informatics Scope and Standards of Practice (2nd ed.). 
Informatics Scope and Standards of PracticeLinks to an external site.

Brennan, P. F., & Bakken, S. (2015). Nursing needs big data, and big data needs nursing. 
Journal of Nursing Scholarship, 
47(5), 477–484. 
to an external site.

Olasvrud, T. (2023, October 18). 
Predictive analytics helps Fresenius Medical Care anticipate dialysis complications. CIO. 
to an external site.

U.S. Centers for Medicare and Medicaid Services. (2024, September 10). 
Manuals. CMS.gov. 
to an external site.

Zhu, R., Han, S., Su, Y., Zhang, C., Yu, Q., & Duan, Z. (2019). The application of big data and the development of nursing science: A discussion paper. 
International Journal of Nursing Sciences, 
6(2), 229–234. 
to an external site.

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