AI offers three advantages over traditional methods: However, manual risk calculation is time-consuming and vulnerable to human error, leading to inaccurate predictions. Fall risk prediction, for instance, involves regular assessment and fall precaution implementation. The concepts behind these tools aren’t new. AI-based clinical decision support includes automatically generated nursing diagnoses, fall risk prediction, and guided decision trees to prevent catheter-associated urinary tract infections. When coupled with AI, clinical decision support can offer predictions and suggestions with accuracy and specificity beyond human capacity. Clinical decision support also may be integrated into other tools, including mobile health applications beyond the EHR. They may supply the end user with information or provide actionable options based on the data. (For an introduction to AI, including definitions of machine learning, deep learning, and other related terms, visit /how-artificial-intelligence-is-transforming-the-future-of-nursing.) Clinical decision supportĬlinical decision support tools (including alerts in the electronic health record, clinical practice guidelines, order sets, reports, and dashboards) enhance nurses’ ability to make clinical decisions. Nursing AI tools include clinical decision support, mobile health and sensor-based technologies, and voice assistants and robotics. However, precisely defining AI can be challenging because of its breadth of applications, including risk prediction algorithms, robots, and speech recognition-all of which augment nursing practice and are on a fast track to changing healthcare as a whole. In healthcare, AI typically refers to the ability of computers to independently convert data into knowledge to guide decisions or autonomous actions. Nurses should be involved in the conceptualization, development, and implementation of AI, especially when it impacts nursing practice.Īrtificial intelligence (AI) comprises many healthcare technologies transforming nurses’ roles and enhancing patient care.In fact, it’s currently used in many ways that are relevant to nurses. Artificial intelligence (AI) in healthcare isn’t new.Practical implementation in clinical settings.Įditor’s note: This is an early release of a web exclusive article for the January 2022 issue of American Nurse Journal. Author Guidelines and Manuscript Submission.
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