[Solved] WK 5 RESP

Assignment Prompt & Instructions

– ## WK5DIS.docx

**## WK5DIS.docx**

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**](https://waldenu.instructure.com/courses/175732/modules/items/6883357)

earning Resources

[Required Readings](https://waldenu.instructure.com/courses/175732/pages/week-5-learning-resources?module_item_id=6883357)

· 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._](https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1021761&site=eds-live&scope=site&authtype=shib&custid=s6527200) _: 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.](https://search.proquest.com/scholarly-journals/nursing-needs-big-data/docview/1754567620/se-2?accountid=14872).
_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.](https://search.ebscohost.com/login.aspx?direct=true&AuthType=shib&db=edselc&AN=edselc.2-52.0-85165359701&site=eds-live&scope=site&custid=s6527200).
_Online Journal of Issues in Nursing_,
_26_(3). https://doi.org/10.3912/OJIN.Vol26No03Man02

· 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.](https://search.ebscohost.com/login.aspx?direct=true&db=edsdoj&AN=edsdoj.41223e5652334f4790d24c0a1f639098&site=eds-live&scope=site&authtype=shib&custid=s6527200).
_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.](https://www.sciencedirect.com/science/article/pii/S2352013218305507).
_International Journal of Nursing Sciences, 6_ (2), 229–234. doi:10.1016/j.ijnss.2019.03.001

[Required Media](https://waldenu.instructure.com/courses/175732/pages/week-5-learning-resources?module_item_id=6883357)

· IDG TECHTalk. (2020, March 27).
[_What is predictive analyticsLinks to an external site._](https://www.youtube.com/watch?v=cVibCHRSxB0) _? Transforming data into future insights_[Video]. YouTube. https://www.youtube.com/watch?v=cVibCHRSxB0

· Simplilearn. (2019, December 10).
[_Big data in 5 minutes_ Links to an external site.](https://www.youtube.com/watch?v=bAyrObl7TYE) | What is big data?| introduction to big data | big data explained | simplilearn [Video]. YouTube. https://www.youtube.com/watch?v=bAyrObl7TYE

[Optional Resources](https://waldenu.instructure.com/courses/175732/pages/week-5-learning-resources?module_item_id=6883357)

· 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._](https://doi.org/10.1200/EDBK_238891) _, 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.](https://go.openathens.net/redirector/waldenu.edu?url=https://doi.org/10.1177%2F1460458219901232).
_Health Informatics Journal, 26_ (3), 2265–2279. doi:10.1177/1460458219901232

[Previous](https://waldenu.instructure.com/courses/175732/modules/items/6883348)

[Next](https://waldenu.instructure.com/courses/175732/modules/items/6883360)

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.).
[https://doi.org/Nursing Informatics Scope and Standards of PracticeLinks to an external site.](https://doi.org/Nursing%20Informatics%20Scope%20and%20Standards%20of%20Practice)

Brennan, P. F., & Bakken, S. (2015). Nursing needs big data, and big data needs nursing.
_Journal of Nursing Scholarship_,
_47_(5), 477–484.
[https://doi.org/10.1111/jnu.12159Links to an external site.](https://doi.org/10.1111/jnu.12159)

Olasvrud, T. (2023, October 18).
_Predictive analytics helps Fresenius Medical Care anticipate dialysis complications_. CIO.
[https://www.cio.com/article/656024/predictive-analytics-helps-fresenius-anticipate-dialysis-complications.htmlLinks to an external site.](https://www.cio.com/article/656024/predictive-analytics-helps-fresenius-anticipate-dialysis-complications.html)

U.S. Centers for Medicare and Medicaid Services. (2024, September 10).
_Manuals_. CMS.gov.
[https://www.cms.gov/medicare/regulations-guidance/manualsLinks to an external site.](https://www.cms.gov/medicare/regulations-guidance/manuals)

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.
[https://doi.org/10.1016/j.ijnss.2019.03.001Links to an external site.](https://doi.org/10.1016/j.ijnss.2019.03.001)

## image1.jpeg

**## WK5DIS.docx**

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**](https://waldenu.instructure.com/courses/175732/modules/items/6883357)

earning Resources

[Required Readings](https://waldenu.instructure.com/courses/175732/pages/week-5-learning-resources?module_item_id=6883357)

· 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._](https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1021761&site=eds-live&scope=site&authtype=shib&custid=s6527200) _: 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.](https://search.proquest.com/scholarly-journals/nursing-needs-big-data/docview/1754567620/se-2?accountid=14872).
_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.](https://search.ebscohost.com/login.aspx?direct=true&AuthType=shib&db=edselc&AN=edselc.2-52.0-85165359701&site=eds-live&scope=site&custid=s6527200).
_Online Journal of Issues in Nursing_,
_26_(3). https://doi.org/10.3912/OJIN.Vol26No03Man02

· 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.](https://search.ebscohost.com/login.aspx?direct=true&db=edsdoj&AN=edsdoj.41223e5652334f4790d24c0a1f639098&site=eds-live&scope=site&authtype=shib&custid=s6527200).
_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.](https://www.sciencedirect.com/science/article/pii/S2352013218305507).
_International Journal of Nursing Sciences, 6_ (2), 229–234. doi:10.1016/j.ijnss.2019.03.001

[Required Media](https://waldenu.instructure.com/courses/175732/pages/week-5-learning-resources?module_item_id=6883357)

· IDG TECHTalk. (2020, March 27).
[_What is predictive analyticsLinks to an external site._](https://www.youtube.com/watch?v=cVibCHRSxB0) _? Transforming data into future insights_[Video]. YouTube. https://www.youtube.com/watch?v=cVibCHRSxB0

· Simplilearn. (2019, December 10).
[_Big data in 5 minutes_ Links to an external site.](https://www.youtube.com/watch?v=bAyrObl7TYE) | What is big data?| introduction to big data | big data explained | simplilearn [Video]. YouTube. https://www.youtube.com/watch?v=bAyrObl7TYE

[Optional Resources](https://waldenu.instructure.com/courses/175732/pages/week-5-learning-resources?module_item_id=6883357)

· 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._](https://doi.org/10.1200/EDBK_238891) _, 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.](https://go.openathens.net/redirector/waldenu.edu?url=https://doi.org/10.1177%2F1460458219901232).
_Health Informatics Journal, 26_ (3), 2265–2279. doi:10.1177/1460458219901232

[Previous](https://waldenu.instructure.com/courses/175732/modules/items/6883348)

[Next](https://waldenu.instructure.com/courses/175732/modules/items/6883360)

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.).
[https://doi.org/Nursing Informatics Scope and Standards of PracticeLinks to an external site.](https://doi.org/Nursing%20Informatics%20Scope%20and%20Standards%20of%20Practice)

Brennan, P. F., & Bakken, S. (2015). Nursing needs big data, and big data needs nursing.
_Journal of Nursing Scholarship_,
_47_(5), 477–484.
[https://doi.org/10.1111/jnu.12159Links to an external site.](https://doi.org/10.1111/jnu.12159)

Olasvrud, T. (2023, October 18).
_Predictive analytics helps Fresenius Medical Care anticipate dialysis complications_. CIO.
[https://www.cio.com/article/656024/predictive-analytics-helps-fresenius-anticipate-dialysis-complications.htmlLinks to an external site.](https://www.cio.com/article/656024/predictive-analytics-helps-fresenius-anticipate-dialysis-complications.html)

U.S. Centers for Medicare and Medicaid Services. (2024, September 10).
_Manuals_. CMS.gov.
[https://www.cms.gov/medicare/regulations-guidance/manualsLinks to an external site.](https://www.cms.gov/medicare/regulations-guidance/manuals)

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.
[https://doi.org/10.1016/j.ijnss.2019.03.001Links to an external site.](https://doi.org/10.1016/j.ijnss.2019.03.001)

## image1.jpeg