The Application Of Data To Problem-Solving
In the modern era, there are few professions that do not to some extent rely on data. Stockbrokers rely on market data to advise clients on financial matters. Meteorologists rely on weather data to forecast weather conditions, while realtors rely on data to advise on the purchase and sale of property. In these and other cases, data not only helps solve problems, but adds to the practitioner’s and the discipline’s body of knowledge.
Of course, the nursing profession also relies heavily on data. The field of nursing informatics aims to make sure nurses have access to the appropriate date to solve healthcare problems, make decisions in the interest of patients, and add to knowledge.
In this Discussion, you will consider a scenario that would benefit from access to data and how such access could facilitate both problem-solving and knowledge formation.
- Reflect on the concepts of informatics and knowledge work as presented in the Resources.
- Consider a hypothetical scenario based on your own healthcare practice or organization that would require or benefit from the access/collection and application of data. Your scenario may involve a patient, staff, or management problem or gap.
Post a description of the focus of your scenario. ( 5-6 paragraphs)
Describe the data that could be used and how the data might be collected and accessed.
What knowledge might be derived from that data?
How would a nurse leader use clinical reasoning and judgment in the formation of knowledge from this experience?
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.
· Chapter 1, “Nursing Science and the Foundation of Knowledge” (pp. 7–19)
· Chapter 2, “Introduction to Information, Information Science, and Information Systems” (pp. 21–33)
· Chapter 3, “Computer Science and the Foundation of Knowledge Model” (pp. 35–62)
Nagle, L., Sermeus, W., & Junger, A. (2017). Evolving Role of the Nursing Infomatics Specialist. In J. Murphy, W. Goosen, & P. Weber (Eds.), Forecasting Competencies for Nurses in the Future of Connected Health (212-221). Clifton, VA: IMIA and IOS Press. Retrieved from https://serval.unil.ch/resource/serval:BIB_4A0FEA56B8CB.P001/REF
Public Health Informatics Institute. (2017). Public Health Informatics: “translating” knowledge for health [Video file]. Retrieved from https://www.youtube.com/watch?v=fLUygA8Hpfo