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Topic: Use of artificial Intelligence in nursing practice. NEEDS TO HAVE PRIMARY SOURCES! Provided below are 3 primary sources that can be utilized for the paper Primary sources: Kim, Ryu, J. M., Nursing Assignment Help

August 25, 2023

Topic: Use of artificial Intelligence in nursing practice.

NEEDS TO HAVE PRIMARY SOURCES!

Provided below are 3 primary sources that can be utilized for the paper

Primary sources:

Kim, Ryu, J. M., & Choi, B. K. (2022). Development and Effectiveness of a Clinical Decision Support System for Pressure Ulcer Prevention Care Using Machine Learning: A Quasi-experimental Study. Computers, Informatics, Nursing, 41(4), 236–245. https://doi.org/10.1097/CIN

Ignatovski, M. (2022). Healthcare breaches during COVID-19: the effect of the healthcare entity type on the number of impacted individuals. Perspectives in Health Information Management, 19(4), p.63.

Seh, A. H., Zarour, M., Alenezi, M., Sarkar, A. K., Agrawal, A., Kumar, R., & Ahmad Khan, R. (2020). Healthcare data breaches: insights and implications. In Healthcare, Vol 8(2), p.133.

Attached is the rubric for the assignment, the evidence matrix table, and 3 papers that can be used as a reference for this paper.

Expert Solution Preview

Introduction:
The use of artificial intelligence (AI) in nursing practice has gained significant attention in recent years. AI technology has the potential to revolutionize healthcare delivery, improving patient outcomes, enhancing decision-making processes, and streamlining clinical workflows. As a medical professor responsible for creating college assignments and evaluating student performance, it is vital to explore and understand the role of AI in nursing practice. In this regard, three primary sources have been provided, which can serve as valuable references for students’ research.

Answer:

Title: Development and Effectiveness of a Clinical Decision Support System for Pressure Ulcer Prevention Care Using Machine Learning: A Quasi-experimental Study

Reference: Kim, Ryu, J. M., & Choi, B. K. (2022). Computers, Informatics, Nursing, 41(4), 236–245. https://doi.org/10.1097/CIN

Summary: The study conducted by Kim, Ryu, and Choi (2022) focuses on the development and effectiveness of a clinical decision support system (CDSS) for pressure ulcer prevention care using machine learning. They employed a quasi-experimental design to evaluate the impact of the CDSS on preventing pressure ulcers in a healthcare setting. This primary source provides valuable insights into the implementation of AI-driven CDSS in nursing practice and its effectiveness in improving patient outcomes.

Title: Healthcare breaches during COVID-19: the effect of the healthcare entity type on the number of impacted individuals

Reference: Ignatovski, M. (2022). Perspectives in Health Information Management, 19(4), p.63.

Summary: Ignatovski’s (2022) study investigates healthcare breaches during the COVID-19 pandemic and specifically examines the impact of the healthcare entity type on the number of individuals affected. The author explores the vulnerabilities and challenges faced by healthcare organizations in safeguarding patient data during the pandemic. This source provides valuable information concerning the potential risks and ethical considerations associated with the use of AI in nursing practice.

Title: Healthcare data breaches: insights and implications

Reference: Seh, A. H., Zarour, M., Alenezi, M., Sarkar, A. K., Agrawal, A., Kumar, R., & Ahmad Khan, R. (2020). Healthcare, 8(2), p.133.

Summary: Seh et al. (2020) present a comprehensive overview of healthcare data breaches, providing insights into their causes, consequences, and implications for healthcare organizations. The authors discuss the potential role of AI in mitigating and preventing data breaches and highlight the importance of data security in the healthcare sector. This source offers students a broader understanding of the challenges and opportunities associated with AI adoption in nursing practice.

Conclusion:
The utilization of AI in nursing practice has the potential to revolutionize healthcare delivery, improve patient outcomes, and streamline clinical workflows. The provided primary sources offer valuable insights into the implementation of AI-driven clinical decision support systems, the impact of healthcare breaches on patient data, and the implications of AI adoption in healthcare settings. These sources can serve as reliable references for students’ research on the use of artificial intelligence in nursing practice.

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