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Producing Applications in Practice With Data
· McGonigle, D., & Mastrian, K. (2022).  Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett.  Available in the courseroom via the VitalSource Bookshelf link.
· Chapter 23, “Translational Research: Generating Evidence for Practice.”
· Kurniati, A. P., Rojas, E., Hogg, D., Hall, G., & Johnson, O. A. (2018, November 29).  The assessment of data quality issues for process mining in healthcare using Medical Information Mart for Intensive Care III, a freely available e-health record database .  Health Informatics Journal, 1–16.
· Shameer, K., Perez-Rodriguez, M. M., Bachar, R., Li, L., Johnson, A., Johnson, K. W., Glicksberg, B. S., Smith, M. R., Readhead, B., Scarpa, J., Jebakaran, J., Kovatch, P., Lim, S., Goodman, W., Reich, D., Kasarskis, A., Tatonetti, N. P., & Dudley, J. T. (2018). (2018).  Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining .  BMC Medical Informatics and Decision Making,  18(Suppl. 3), 1–19.
· Vial, G. (2019).  Understanding digital transformation: A review and a research agenda .  The Journal of Strategic Information Systems,  28(2), 118–144.
Evidence-Based Development
· Ansaripour, A., Zendehdel, K., Tadayon, N., Sadeghi, F., Uyl-de Groot, C. A., & Redekop, W. K. (2018).  Use of data-mining to support real-world cost analyses: An example using HER2-positive breast cancer in Iran .  PloS One,  13(10), 1-16.
· Bjarnadottir, R. I., Bockting, W., Yoon, S., & Dowding, D. W. (2019).  Nurse documentation of sexual orientation and gender identity in home healthcare: A text mining study .  CIN: Computers, Informatics, Nursing,  37(4), 213-221.
· Ghorbani, R., & Ghousi, R. (2019).  Predictive data mining approaches in medical diagnosis: A review of some diseases prediction .  International Journal of Data and Network Science,  3(2), 47-70.
· Shi, J., Zheng, M., Yao, L., & Ge, Y. (2018).  Developing a healthcare Dataset Information Resource (DIR) based on semantic web .  BMC Medical Genomics,  11(Suppl. 5), 1-14.
Producing Applications in Practice With Evidence-Based Information
· Ahmed, S., Seddawy, A. I. E., & Nasr, M. (2019).  A proposed framework for detecting and predicting diseases through business intelligence applications .  International Journal of Advanced Networking and Applications,  10(4), 3951-3957.
· Ismail, W. N., Hassan, M. M., Alsalamah, H. A., & Fortino, G. (2018, August 1).  Mining productive-periodic frequent patterns in tele-health systems .  Journal of Network and Computer Applications,  115, 33-47.
· Jones, M. (2019).  What we talk about when we talk about (big) data .  Journal of Strategic Information Systems,  28(1), 3-16.
· Soleimani-Roozbahani, F., Ghatari, A. R., & Radfar, R. (2019).  Knowledge discovery from a more than a decade studies on healthcare big data systems: A scientometrics study .  Journal of Big Data,  6(1), 1-15.
· Yoo, S., Kim, S., Kim, E., Jung, E., Lee, K., & Hwang, H. (2018).  Real-time location system-based asset tracking in the healthcare field: Lessons learned from a feasibility study .  BMC Medical Informatics and Decision Making,  18(80), 1-10.
Scope and Standards of Practice
· American Nurses Association. (2015).  Nursing informatics:   Scope and standards of practice  (2nd ed.) . Author.

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