Innovative Informatics Tools and Applications to Clinical Practice
New technology and tools will undoubtedly shape nursing practice. “Research suggests that between 8% and 16% of nursing time is spent on non-nursing activities and tasks that should be delegated to others” (Robert, 2019). As a result, new innovations may minimize the time spent on these non-nursing activities and tasks to further support and strengthen patient care.
One such technology is the use of robots. While nursing robots are not yet readily available, researchers have earned millions in grants over the last decade researching and developing AI and robotic innovations to improve healthcare and nursing practice. From clinical practice to patient support, the future seems endless with possibilities.
For this Discussion, you will explore various topics associated with innovative technology and your healthcare organization or nursing practice. You will consider how you might utilize these advancements, as well as consider how these advancements might influence nursing informatics.
Robert, N. (2019). How artificial intelligence is changing nursing. Nursing Management, 50(9), 30–39. doi:10.1097/01.NUMA.0000578988.56622.21.
- Review any Resources within the last five years associated with the topics: AI, Machine Learning, Genomics, Precision Health, and Robotics.
- Consider the role of these technologies in your healthcare organization or nursing practice.
- Analyze the differences of these technologies as they may impact healthcare delivery and nursing practice.
- Reflect on the potential use of each of these topics and your personal experiences with their implementation into practice.
Post a two-page response addressing each of the following:
- From the five topics: AI, Machine Learning, Genomics, Precision Health, and Robotics, assess the applications of the technology, noting the potential benefits and potential challenges of the innovations. Be specific.
- Appraise the potential of the innovations to improve healthcare practice and related outcomes.
- Explain whether these applications integrate Big Data? Why or why not?
- Explain the difference between AI, Machine Learning, Data Mining and
- Deep Learning as presented in the Bini (2018) article.
- Why do these differences matter and how relevant are they for Big Data?
- Thoroughly responds to the Discussion question(s).
Is reflective with critical analysis and synthesis representative of knowledge gained from the course readings for the module and current credible sources.
No less than 75% of post has exceptional depth and breadth.
Supported by at least three current credible sources.
- Written clearly and concisely.
Contains no grammatical or spelling errors.
Adheres to current APA manual writing rules and style.
- Meets requirements for timely, full, and active participation.
Posts main Discussion by due date.
- Response exhibits critical thinking and application to practice settings.
Responds to questions posed by faculty.
The use of scholarly sources to support ideas demonstrates synthesis and understanding of learning objectives.
- Communication is professional and respectful to colleagues.
Response to faculty questions are fully answered, if posed.
Provides clear, concise opinions and ideas that are supported by two or more credible sources.
Response is effectively written in standard, edited English