Running head: Assignment-M 2
Artificial Nurse refers to artificial intelligence system in nursing that will be used in making more complex and accurate decisions and interventions in nursing. As a whole, artificial intelligence encompasses a wide range of developing technologies that aim to analyze and synthesize information from a wide range of medical data. The technology aids and, in certain situations, enhances the human ability to perform a given task. This day and age, clinical knowledge is enormous in scope; it’s constantly evolving, and it takes highly specialized abilities to apply in the field. High-quality nursing care is increasingly dependent on rapid processing and decisive response when dealing with large volumes of information. Indeed, the desire for real-time analysis, consumption and action against amounts of clinical information has become a new standard in nursing care. Artificial intelligence (AI) has great promise for the future of nursing with this new standard. Because of the wide range of specialties and nursing work contexts in which AI can be used, there is a significant potential for nurses to learn how to effectively use this technology. It’s no secret that nurses have long held a sway over the way medical technology is implemented in the clinical setting. As a new member of the care team, one must learn how to work with machines and acquire new skills and knowledge in the process. A growing number of healthcare organizations are using artificial intelligence (AI) to speed up work, aid in clinical decisions, and enhance patient outcomes. Each of these new technologies has the potential to make a significant impact on patient care. In the future, efficiency, capacity, quality, and healthcare transformation can all be improved by combining these technologies and training nurses on the best ways to connect with machines (Ronquillo et al, 2021).
In most scholarly work, the major focus has been the impacts of artificial nurse in nursing service in relation to provision of quality health care services. Nurses who use AI and EHR data to analyze and translate signals into precise patient monitoring have also honed their reading and interpretation skills. This machine learning technology is relevant to nursing because it reduces alert fatigue by condensing alarm signals into less frequent but still meaningful usable information. Neural networks have been utilized to advance the field of deep-learning machine learning, allowing for the examination of new data sources such as speech recognition and picture analysis. Artificial intelligence (AI) can be used to effectively personalize medicines to the exact genes, lifestyles, and therapeutic preferences of individual patients by incorporating data from a variety of sources. Deep learning applications can help nurses identify patients who are at risk for adverse health outcomes, such as sepsis or hospital readmission, and who might benefit from clinical treatments. The employment of artificial intelligence (AI) in the nursing profession benefits both patients and doctors. However, as artificial intelligence (AI) technology advances, nurses will need to engage in an open conversation about the technology’s future growth and implementation in healthcare. As they participate in the development and testing of new apps that will influence the future of patient care, nurses will play a critical role in assisting companies in integrating and adapting to AI technology developments (Clancy, 2020).
Despite the scholar works in the past, there has been a research gap in that no prior scholar work has focused on the effect of artificial nurse on transformation health care system. The real-time flow of patient health information is important to the success of these projects and the ultimate goal of a reformed health-care system. Better access to patient health data is widely acknowledged to be critical for improving the quality and safety of healthcare services. 3,7 Little progress has been made in the study of how healthcare information, both administrative and clinical, might be exchanged electronically in real time between and among physicians, across treatment contexts, and with consumers, patients, payers, and other third parties. There is a lot of ambiguity when it comes to federal and state rules that protect the privacy of patient health information. Certain characteristics of the health-care delivery system indicate a transition. Among the fundamental components of this transition are new frameworks for integrating and coordinating services, a renewed emphasis on patient engagement and patient-centered care, and new payment mechanisms based on the value of population-based health outcomes rather than the volume of services provided. In this period of transformation, new and improved strategies to enhance population health are emerging (Buchanan et al, 2020). As healthcare advances, so do nurses’ responsibilities. Nursing has seen numerous changes over the years, but one constant has remained: nurses are critical to providing high-quality healthcare. This is a crucial aspect in nursing as it has to be maintained despite the expected changes in nursing. For this reason, there is a need to determine what impact artificial nursing will have towards the outlined nursing roles. This would be the foundation to determining the effect of artificial nurse in transformative health care system.
Buchanan, C., Howitt, M. L., Wilson, R., Booth, R. G., Risling, T., & Bamford, M. (2020). Predicted influences of artificial intelligence on the domains of nursing: scoping review. JMIR nursing, 3(1), e23939.
Clancy, T. R. (2020). Artificial intelligence and nursing: the future is now. JONA: The Journal of Nursing Administration, 50(3), 125-127.
Ronquillo, C. E., Peltonen, L. M., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., … & Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative. Journal of advanced nursing, 77(9), 3707-3717.