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Assessment 03 – Evidence-Based Proposal and Annotated
Bibliography on Technology in Nursing For this assessment, you will write a 4–6 page annotated bibliography where you identify peer- reviewed publications that promote the use of one of the technologies presented below that enhance quality and safety standards in nursing. Before you complete the detailed instructions in the courseroom, first review the technologies below and select the one you’re most interested in researching. After selecting one of the following technologies to be the focus of your assessment, return to the courseroom to review the detailed instructions there.
Artificial Intelligence: AI in healthcare can analyze complex data sets, assist in diagnosis, predict patient deterioration, and even suggest treatment options. It’s a rapidly evolving field with vast potential to revolutionize healthcare.
Data Management Resources: These tools help in the collection, storage, and analysis of vast amounts of patient data. Proper data management can lead to better patient outcomes, more efficient operations, and significant research advancements.
Workflow Management Systems: These systems streamline and automate routine tasks and operations in healthcare settings. They can improve efficiency, reduce errors, and enhance the overall quality of care.
### Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing
#### Topic: Artificial Intelligence in Healthcare
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### Introduction
Artificial Intelligence (AI) in healthcare is revolutionizing the field by enabling more accurate diagnoses, predicting patient outcomes, and personalizing treatment plans. This paper will explore the impact of AI on quality and safety standards in nursing, providing an annotated bibliography of peer-reviewed publications that highlight the benefits and applications of AI in nursing practice.
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### Annotated Bibliography
**1. Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44-56.**
**Summary:**
Topol’s article discusses the integration of AI into various aspects of healthcare, emphasizing its potential to enhance diagnostic accuracy, predict patient deterioration, and tailor personalized treatment plans. The article outlines how AI can process complex data sets far beyond human capabilities, thus improving clinical decision-making and patient outcomes.
**Relevance:**
This publication is crucial for understanding the broad applications of AI in healthcare, particularly its role in improving diagnostic processes and patient care. It underscores the transformative potential of AI, making it a foundational reference for discussions on AI in nursing.
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**2. Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., … & Dean, J. (2019). A guide to deep learning in healthcare. Nature Medicine, 25(1), 24-29.**
**Summary:**
Esteva et al. provide a comprehensive overview of deep learning, a subset of AI, and its applications in healthcare. The article explains how deep learning algorithms can analyze medical images, predict disease progression, and assist in developing personalized treatment plans.
**Relevance:**
This article is relevant for its detailed exploration of deep learning techniques in healthcare, offering insights into specific AI applications that can enhance nursing practices. It highlights how AI can assist nurses in early diagnosis and intervention, thereby improving patient safety and outcomes.
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**3. Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., … & Wang, Y. (2017). Artificial intelligence in healthcare: past, present, and future. Stroke and Vascular Neurology, 2(4), 230-243.**
**Summary:**
Jiang et al. review the historical development of AI in healthcare, current applications, and future prospects. The article emphasizes AI’s role in diagnostic imaging, predictive analytics, and patient monitoring, demonstrating how these applications can lead to better patient care and safety.
**Relevance:**
This review is significant for its historical perspective and future outlook on AI in healthcare. It provides a comprehensive understanding of how AI has evolved and its potential to continue improving nursing care through enhanced diagnostic and monitoring capabilities.
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**4. McCoy, M. J., & Darlington, T. (2019). Artificial intelligence in nursing: Automating the predictable, personalizing the human. Nursing Management, 50(2), 28-33.**
**Summary:**
McCoy and Darlington explore the specific implications of AI for the nursing profession. They discuss how AI can automate routine tasks, such as medication administration and patient monitoring, allowing nurses to focus on personalized patient care. The article also addresses ethical considerations and the importance of maintaining the human element in nursing.
**Relevance:**
This article directly addresses the intersection of AI and nursing, making it highly relevant for understanding how AI can support nursing practice. It highlights practical applications and ethical concerns, providing a balanced view of AI’s impact on nursing.
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**5. Morley, J., Machado, C. C., Burr, C., Cowls, J., Joshi, I., Taddeo, M., & Floridi, L. (2020). The ethics of AI in health care: A mapping review. Social Science & Medicine, 260, 113172.**
**Summary:**
Morley et al. conduct a review of the ethical considerations surrounding AI in healthcare. The article maps out key ethical issues, including privacy, bias, and the need for transparency in AI algorithms. It emphasizes the importance of ethical guidelines to ensure AI benefits all patients equally.
**Relevance:**
Understanding the ethical implications of AI is crucial for its responsible implementation in nursing. This article provides a thorough analysis of ethical challenges, helping nurses navigate the complexities of AI use while maintaining patient trust and safety.
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### Conclusion
The integration of AI into nursing has the potential to significantly enhance quality and safety standards in patient care. The selected articles provide a comprehensive overview of the current state and future prospects of AI in healthcare, highlighting its benefits, practical applications, and ethical considerations. By understanding and leveraging AI technologies, nurses can improve diagnostic accuracy, patient outcomes, and overall efficiency in healthcare settings.
### References
1. Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. *Nature Medicine, 25*(1), 44-56.
2. Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., … & Dean, J. (2019). A guide to deep learning in healthcare. *Nature Medicine, 25*(1), 24-29.
3. Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., … & Wang, Y. (2017). Artificial intelligence in healthcare: past, present, and future. *Stroke and Vascular Neurology, 2*(4), 230-243.
4. McCoy, M. J., & Darlington, T. (2019). Artificial intelligence in nursing: Automating the predictable, personalizing the human. *Nursing Management, 50*(2), 28-33.
5. Morley, J., Machado, C. C., Burr, C., Cowls, J., Joshi, I., Taddeo, M., & Floridi, L. (2020). The ethics of AI in health care: A mapping review. *Social Science & Medicine, 260*, 113172.
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This format provides a structured and detailed overview of the chosen topic, with relevant peer-reviewed sources that emphasize the importance and potential of AI in nursing to enhance quality and safety standards.
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