Required Media (click to expand/reduce)
Begin your review of required Learning Resources with these quick media resources to define some of the many terms you will hear in Nursing Informatics and Project Management today. If you are more interested in a particular one, there are many longer videos available.
GovLoop. (2016, June 15). Defining data analytics [Video]. YouTube. https://www.youtube.com/watch?v=RAw55JEcnEs
IDG TECHTalk. (2020, March 27). What is predictive analytics? Transforming data into future insights [Video]. YouTube. https://www.youtube.com/watch?v=cVibCHRSxB0
ProjectManager. (2016, March 11). Gantt charts, simplified â€“ project management training [Video]. YouTube. https://www.youtube.com/watch?v=cGkHjby1xKM
Simplilearn. (2017, August 3). Data science vs big data vs data analytics [Video]. YouTube. https://www.youtube.com/watch?v=yR2wWQYiVKM
Simplilearn. (2019, December 10). Big data in 5 minutes | What is big data?| introduction to big data | big data explained | simplilearn
[Video]. YouTube. https://www.youtube.com/watch?v=bAyrObl7TYE
Required Readings (click to expand/reduce)
Sipes, C. (2020). Project management for the advanced practice nurse (2nd ed.). Springer Publishing.
â€¢ Chapter 4, â€œPlanning: Project Managementâ€”Phase 2â€ (pp. 75â€“120)
American Nurses Association. (2015). Nursing informatics: Scope and standards of practice (2nd ed.).
â€¢ â€œStandard 3: Outcomes Identificationâ€ (p. 71)
â€¢ â€œStandard 4: Planningâ€ (p. 72)
Brennan, P. F., & Bakken, S. (2015). Nursing needs big data and big data needs nursing. Journal of Nursing Scholarship, 47(5), 477â€“484. doi:10.1111/jnu.12159 National Institutes of Health, Office of Data Science Strategy. (2021). Data science.
National Institutes of Health, Office of Data Science Strategy. (2021). Data science. https://datascience.nih.gov/
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), 229â€“234. doi:10.1016/j.ijnss.2019.03.001
Data Analytics (click to expand/reduce)
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 services. Sensors, 20(4), 953. doi:10.3390/s20040953
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 Book, 39, e53â€“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 abuse. Health Informatics Journal, 26(3), 2265â€“2279. doi:10.1177/1460458219901232
Optional Resources (click to expand/reduce)
Mehta N., & Pandit, A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International Journal of Medical Informatics, 114, 57â€“65. doi:10.1016/j.ijmedinf.2018.03.013
Ristevski, B., & Chen, M. (2018). Big data analytics in medicine and healthcare. Journal of Integrative Bioinformatics, 15(3), 1â€“5. https://doi.org/10.1515/jib-2017-0030
Shea, K. D., Brewer, B. B., Carrington, J. M., Davis, M., Gephart, S., & Rosenfeld, A. (2018). A model to evaluate data science in nursing doctoral curricula. Nursing Outlook, 67(1), 39â€“48. https://www.nursingoutlook.org/article/S0029-6554(18)30324-5/fulltext
Sheehan, J., Hirschfeld, S., Foster, E., Ghitza, U., Goetz, K., Karpinski, J., Lang, L., Moser. R. P., Odenkirchen, J., Reeves, D., Runinstein, Y., Werner, E., & Huerta, M. (2016). Improving the value of clinical research through the use of common data elements. Clinical Trials, 13(6), 671â€“676, doi:10.1177/ 1740774516653238
Topaz, M., & Pruinelli, L. (2017). Big data and nursing: Implications for the future. Studies in Health Technology and Informatics, 232, 165â€“171.
Westra, B. L., Sylvia, M., Weinfurter, E. F., Pruinelli, L., Park, J. I., Dodd, D., Keenan, G. M., Senk, P., Richesson, R. L., Baukner, V., Cruz, C., Gao, G., Whittenburg, L., & Delaney, C. W. (2017). Big data science: A literature review of nursing research exemplars. Nursing Outlook, 65(5), 549â€“561.
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, A., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. O., Bourne, P., Bouwman, J., Brookes, A. J., Clark. T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C., Finkers, R., â€¦ GonzÃ¡lez-BeltrÃ¡n, A. (2016). The FAIR guiding principles for scientific data management and stewardship. Scientific Data, 3, Article 160018, 1â€“9. doi:10.1038/sdata.2016.18
â€¢ Review the Learning Resources for this week related to the topics: Big Data, Data Science, Data Mining, Data Analytics, and Machine Learning.
â€¢ Consider the process and application of each topic.
â€¢ Reflect on how each topic relates to nursing practice.
Post a succinct summary on how each topic might apply to nursing practice. Be specific. 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:
â€¢ Explain how you see the data concepts presented aligning with your current practice. What do you need to know to apply these concepts?
â€¢ Do you currently use one of these processes in your healthcare organization or nursing practice? If so, how and in what context?
â€¢ If you do not currently use one of these processes in your healthcare organization or nursing practice, what would it take to implement it? What do you see as a benefit for use?
â€¢ How is predictive analytics applied to clinical practice? Be specific and provide examples.
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