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.
Reference:
Robert, N. (2019). How artificial intelligence is changing nursing.
Nursing Management, 50(9), 30–39. doi:10.1097/01.NUMA.0000578988.56622.21
Resources
Be sure to review the Learning Resources before completing this activity.
Click the weekly resources link to access the resources.
· American Nurses Association. (2015).
Nursing informaticsLinks to an external site.
: Scope and standards of practice (2nd ed.).
· “Standard 5: Implementation” (pp. 73–74)
· “Standard 5a: Coordination of Activities” (p. 75)
· “Standard 6: Evaluation” (p. 78)
· “Standard 11: Communication” (p. 86)
· “Standard 12: Leadership” (pp. 87–88)
· “Standard 15: Resource Utilization” (p. 92)
· Billingsley, L., Calderon, A., & Agosta, L. (2024).
Transforming health care: Exploring artificial intelligence integration, data governance, and ethical considerations in nursingLinks to an external site..
Journal of Radiology Nursing,
43(2), 107–111.
· Calik, A., Ozkul, D., & Kapucu, S. (2024).
Smart glasses use experience of nursing graduate students: Qualitative studyLinks to an external site..
BMC Nursing,
23(1), 1–10.
· Dordunoo, D., Limoges, J., Chiu, P., Puddester, R., Carlsson, L., & Pike, A. (2023).
Genomics-informed nursing strategies and health equity: A scoping review protocolLinks to an external site..
PLoS ONE,
18(12), e0295914.
· Krupp, A., & Lopez, K. D. (2023).
Leveraging implementation science with using decision support technology to drive meaningful change for nurses and nursing leadershipLinks to an external site..
Nurse Leader,
21(6), 636–640.
· Madi, M., Nielsen, S., Schweitzer, M., Meyer, G., Langensiepen, S., Stephan, A., Siebert, M., & Körner, D. (2024).
Acceptance of a robotic system for nursing care: A cross-sectional survey with professional nurses, care recipients and relativesLinks to an external site..
BMC Nursing,
23(1).
· AHRQ Digital Healthcare Research. (2021, July 12).
AHRQ CDS connect: A primerLinks to an external site.
[Video].
· U.S. Food and Drug Administration. (2019, December 20).
What is precision medicine? Links to an external site.
[Video]. YouTube.
· Chen, M., & Decary, M. (2020).
Artificial intelligence in healthcare: An essential guide for health leadersLinks to an external site..
Healthcare Management Forum, 33 (1),10–18. doi:10.1177/0840470419873123
· Lee, M. S., Grabowski, M. M., Habboub, G., & Mroz, T. E. (2020).
The Impact of artificial intelligence on quality and safetyLinks to an external site..
Global Spine Journal, 10 (1 Suppl), 99S–103S.
· Scudellari, M. (2020).
AI recognizes COVID-19 in the sound of a cough Links to an external site.
. IEEE Spectrum.
To Prepare
· Review the Learning Resources 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.
By Day 3 of Week 7
Post a response to your blog for the following:
· Choose one of the five topics: AI, Machine Learning, Genomics, Precision Health, or Robotics, how has this technology been applied in your practice or in the lives of your patients
· How do you think this innovation will impact the future of your practice?
By Day 6 of Week 7
Read a selection of your colleagues’ blog posts and
respond to
at least two of your colleagues on
two different days by expanding upon their responses or sharing additional or alternative perspectives.
RESPOND TO THIS DISCUSSION POST
Amanda Newton
MAIN POST
Artificial intelligence (AI) technology has become increasingly integrated into nursing practice, improving clinical decision-making, efficiency, and patient care outcomes. At my facility, we use tools like the Rothman Index to detect early signs of patient deterioration by analyzing real-time electronic health record (EHR) data, allowing for timely interventions. AI also supports documentation efficiency through predictive text, automated charting, and voice recognition software, significantly reducing the time nurses spend on manual data entry. In addition, automated medication dispensing systems and AI-driven triage tools help streamline routine tasks and prioritize patient needs, enabling nurses to spend more time on direct patient care and emotional support. These tools directly align with the American Nurses Association’s (2015) standards on implementation, coordination, communication, and resource utilization, which emphasize the nurse’s role in effectively integrating technologies to enhance patient care and outcomes.
I also care for oncology patients receiving precision therapies targeted to specific genetic mutations. These personalized treatments rely on genomic sequencing, and AI-driven platforms help identify actionable mutations and match patients to appropriate therapies, such as targeted immunotherapies or kinase inhibitors. As Dordunoo et al. (2023) highlight, genomics-informed nursing care requires a shift toward incorporating genetic literacy and health equity considerations. Nurses are central to this shift, serving as advocates and educators who help patients understand and manage complex treatment regimens based on their genetic profiles.
Looking to the future, AI will continue shaping nursing care by promoting individualized treatment, reducing disparities, and enabling data-driven decision-making. For example, Krupp and Lopez (2023) discuss how implementation science and decision support technologies can drive sustainable change in nursing leadership and improve outcomes across systems. Emerging technologies like smart glasses, as explored by Calik et al. (2024), are also expanding nursing education and practice by providing real-time access to patient information and clinical guidance at the bedside. Additionally, robotic systems are gaining acceptance in nursing care delivery, with Madi et al. (2024) noting positive perceptions among nurses and patients regarding the role of robotics in reducing workload and enhancing patient support.
The American Nurses Association (2015) also reinforces the importance of nurse leadership, evaluation, and effective communication in guiding the use of innovative technologies. As AI and gene technologies continue to evolve, nurses must be at the forefront equipped with the tools, education, and leadership strategies needed to navigate this new frontier in healthcare, while adhering to professional standards of practice.
References
American Nurses Association. (2015). *Nursing informatics: Scope and standards of practice* (2nd ed.).
Calik, A., Ozkul, D., & Kapucu, S. (2024). Smart glasses use experience of nursing graduate students: Qualitative study. *BMC Nursing, 23*(1), 1–10.
Dordunoo, D., Limoges, J., Chiu, P., Puddester, R., Carlsson, L., & Pike, A. (2023). Genomics-informed nursing strategies and health equity: A scoping review protocol. *PLoS ONE, 18*(12), e0295914.
Krupp, A., & Lopez, K. D. (2023). Leveraging implementation science with using decision support technology to drive meaningful change for nurses and nursing leadership. *Nurse Leader, 21*(6), 636–640.
Madi, M., Nielsen, S., Schweitzer, M., Meyer, G., Langensiepen, S., Stephan, A., Siebert, M., & Körner, D. (2024). Acceptance of a robotic system for nursing care: A cross-sectional survey with professional nurses, care recipients and relatives. *BMC Nursing, 23*(1).
