[hen-ui-list variant=”unordered” bullet-style=”bullet”] [hen-ui-list-item][hen-ui-text variant=”b4″]AI technology allows a computer system or robot to learn, reason, communicate, and make decisions like humans or better than humans. [/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″]Nursing schools already use chatbots to create mock simulations that resemble real-life nurse/patient interactions, and there are talks of robots that will work and interact in clinical nursing environments.[/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″]Despite fears, AI health technologies (AIHTs) are intended to support nursing students and nursing staff members and improve patient care.[/hen-ui-text][/hen-ui-list-item][/hen-ui-list][hen-ui-text variant=”b4″]AI is all the rage. Ever since ChatGPT started helping the general public generate written answers to just about any question, its current and potential applications have exploded. [hen-ui-link href=”https://www.bestcolleges.com/news/ai-nursing-education/”]Nursing schools[/hen-ui-link] already use the chatbot to create mock simulations that resemble real-life nurse/patient interactions.[/hen-ui-text][hen-ui-text variant=”b4″]Electronic medical records (EMRs) are already ubiquitous in healthcare, with [hen-ui-link href=”https://www.healthit.gov/data/quickstats/adoption-electronic-health-records-hospital-service-type-2019-2021″ target=”_blank”]96% of general acute care hospitals[/hen-ui-link] and [hen-ui-link href=”https://www.healthit.gov/data/quickstats/office-based-physician-electronic-health-record-adoption” target=”_blank”]88% of office-based[/hen-ui-link] clinics using the tool, many of which have some form of AI capability.[/hen-ui-text][hen-ui-text variant=”b4″]Tiffany Kelley, Ph.D., is the Frederick A. DeLuca Foundation Visiting Professor for Innovations and New Knowledge in Nursing and director of the Healthcare Innovation Certificate Program at the University of Connecticut School of Nursing. She is also the founder and CEO of two healthcare technology companies. With nearly 20 years of nursing informatics and health IT experience, she believes digitizing patient health data opens the door for innovations in healthcare.[/hen-ui-text][hen-ui-text variant=”b4″]“It can create advanced health insights using AI tools that were not possible in the paper-based world,” Kelley points out.[/hen-ui-text][hen-ui-text variant=”b4″]For example, AI tools can help determine your risk for specific health conditions or larger-scale population risks following a major event like a disease outbreak. AI tools will only get more sophisticated and are predicted to transform nursing practice, Kelley says.[/hen-ui-text][hen-ui-text variant=”b4″]However, confusion abounds over how and when to use AI and its use in patient care. Indeed, not all AI is welcomed by the nursing community. There can be a huge learning curve, especially for nurse educators, and some nurses may resist trying new technologies.[/hen-ui-text][hen-ui-text variant=”b4″]Learn more about AI’s role in healthcare, nursing fears around it, and the future of AI in nursing.[/hen-ui-text][hen-ui-heading variant=”h2″]AI’s Role in Healthcare[/hen-ui-heading][hen-ui-text variant=”b4″][hen-ui-link href=”https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328269/” target=”_blank”]AI is defined[/hen-ui-link] as technology that can allow a computer system or computer-controlled robot to learn, reason, perceive, infer, communicate, and make decisions like humans or better than humans.[/hen-ui-text][hen-ui-text variant=”b4″]“AI technologies depend on data, information, knowledge, the building blocks of informatics, to ensure the algorithms are providing reliable and accurate insights,” Kelley says.[/hen-ui-text][hen-ui-text variant=”b4″]There are also AI tool subsets that support AI technologies, including:[/hen-ui-text][hen-ui-list variant=”unordered” bullet-style=”bullet”] [hen-ui-list-item][hen-ui-text variant=”b4″]Machine learning[/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″]Deep learning[/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″]Predictive analysis [/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″]Remote patient monitoring[/hen-ui-text][/hen-ui-list-item][/hen-ui-list][hen-ui-text variant=”b4″]These AI subsets can improve patient care by analyzing large amounts of data to improve decision-making among healthcare providers.[/hen-ui-text][hen-ui-text variant=”b4″]As one recent example, [hen-ui-link href=”https://www.prnewswire.com/news-releases/google-cloud-collaborates-with-mayo-clinic-to-transform-healthcare-with-generative-ai-301844437.html” target=”_blank”]Google’s cloud business[/hen-ui-link] recently partnered with the Mayo Clinic in Minnesota to create new AI patient care solutions. The collaboration allows Mayo Clinic to use an app known as Gen App Builder to more quickly identify patient information typically found in different formats and locations. This app can save time for clinicians and researchers, make predictions about a patient’s health, and help prevent or slow the course of health conditions.[/hen-ui-text][hen-ui-text variant=”b4″]Chatboxes and social robots also are growing in popularity in healthcare. Not only are they being used to accompany nurses in practice, but they also are helping the general public, especially the older population. Chatboxes and social robots simulate human conversations and provide companionship for older individuals in long-term care facilities.[/hen-ui-text][hen-ui-text variant=”b4″]Specifically in nursing, AI can play a huge role in helping nursing students and nurses make better clinical decisions about their patients.[/hen-ui-text][hen-ui-text variant=”b4″]“Answering questions to support the patient’s specific questions about a condition, dressing change, or medication, to name a few, could be a supportive AI tool, especially in the inpatient setting,” Kelley says.[/hen-ui-text][hen-ui-flex gap=”xl” align=”left” direction=”column”][hen-ui-flex gap=”xs” align=”left” direction=”column”][hen-ui-heading variant=”h2″]Popular Online RN-to-BSN Programs[/hen-ui-heading][hen-ui-text variant=”b4″ color=”subtext”]Learn about start dates, transferring credits, availability of financial aid, and more by contacting the universities below.[/hen-ui-text][/hen-ui-flex][hen-ui-dynamic-experience placement=”belowTheFold” /][/hen-ui-flex][hen-ui-heading variant=”h2″]AI In Nursing[/hen-ui-heading][hen-ui-text variant=”b4″]AI and technology are beginning to [hen-ui-link href=”/articles/technology-changing-nursing-roles/”]change the role of nursing[/hen-ui-link] significantly. In 2022, nurse executives across the U.S. participated in a panel on artificial intelligence and the future of nursing.[/hen-ui-text][hen-ui-text variant=”b4″]Two recent use cases have made waves as potential boons to nursing practice:[/hen-ui-text][hen-ui-list variant=”unordered” bullet-style=”bullet”] [hen-ui-list-item][hen-ui-text variant=”b4″]A patient triage system for the emergency room (e.g., [hen-ui-link href=”https://mednition.com/solutions/” target=”_blank”]KATE[/hen-ui-link])[/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″]An algorithm to detect a patient’s health condition in real-time using data from the EHR (e.g., [hen-ui-link href=”https://www.perahealth.com/the-rothman-index/model-development-and-scientific-validation/” target=”_blank”]Rothman Index[/hen-ui-link]).[/hen-ui-text][/hen-ui-list-item][/hen-ui-list][hen-ui-text variant=”b4″]KATE and the Rothman Index are clinical decision support systems or tools nurses and other providers use to get real-time clinical information on patients. KATE’s AI capabilities can help [hen-ui-link href=”/careers/er-nurse/”]emergency room nurses[/hen-ui-link] triage patients efficiently, getting the higher-risk patients to the right care quickly.[/hen-ui-text][hen-ui-text variant=”b4″]Two other examples of AI tools currently being used, Kelley points out, are supporting the detection of patients at risk for falls and readmission.[/hen-ui-text][hen-ui-text variant=”b4″]“I fully expect the use of AI to significantly grow as we come to further understand its capabilities and identify where AI tools can be effective in supporting the delivery of quality nursing and healthcare,” Kelley says.[/hen-ui-text][hen-ui-heading variant=”h2″]AI Concerns[/hen-ui-heading][hen-ui-text variant=”b4″]Technological advantages in nursing are designed to support the needs of nurses. But there is still fear surrounding the use of AI in healthcare, specifically in nursing.[/hen-ui-text][hen-ui-text variant=”b4″]“With any prospective new technology, there is often a tendency to resist because it means changing the status quo,” Kelley says.[/hen-ui-text][hen-ui-text variant=”b4″]Nursing educators have [hen-ui-link href=”https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10049425/” target=”_blank”]expressed concerns[/hen-ui-link] about the potential impact of AI on their workload and their roles as teachers.[/hen-ui-text][hen-ui-text variant=”b4″]Another potential disadvantage of AI is that technologies are being developed quickly. This risks us needing to fully understand the potential benefits and unintended consequences of these tools, Kelley points out.[/hen-ui-text][hen-ui-text variant=”b4″]“Additionally, we will need internal policies and likely regulations to effectively use such tools for the delivery of quality care,” Kelley says.[/hen-ui-text][hen-ui-text variant=”b4″]Fears like breaches in HIPPAA and computer security are real risks. Having consumer health AI tools that are as reliable and accurate as those that get adopted within healthcare settings are equally important with the rise of AIHTs, Kelley says.[/hen-ui-text][hen-ui-text variant=”b4″]Robust training and guidance should help ease the fear of AI.[/hen-ui-text][hen-ui-heading variant=”h2″]Future of AI in Nursing[/hen-ui-heading][hen-ui-text variant=”b4″]AI technology can give new insights to help form better care decisions. Kelley believes some of the movement toward AI requires nursing as a profession to be willing to look toward what could be possible instead of a focus on how it will change.[/hen-ui-text][hen-ui-card variant=”background-white” border=”stroke” padding=”lg”] [hen-ui-card-content] [hen-ui-text variant=”b4″]Here are a few suggestions to successfully incorporate AI into nursing:[/hen-ui-text][hen-ui-list variant=”ordered” bullet-style=”check”] [hen-ui-list-item][hen-ui-text variant=”b4″]Nurse educators should increase their knowledge and comfort levels with the concept and basics of AI through courses and workshops. [/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″][hen-ui-link href=”https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328269/” target=”_blank”]Research suggests[/hen-ui-link] adding nursing informatics into the nursing curriculum with courses that include data literacy, technological literacy, systems thinking, critical thinking, genomics and AI algorithms, ethical implications of AI, and analysis and implications of big data sets.[/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″]Nursing leadership should incentivize nurse educators to adopt the need for changes in nursing curriculums to prepare nurses and nursing students to use these emerging technologies.[/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″]Add informatics and digital health technology competencies into all areas of nursing education.[/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″]Have nurses play a role as co-designers of AIHTs.[/hen-ui-text][/hen-ui-list-item] [hen-ui-list-item][hen-ui-text variant=”b4″]To get students up to speed, nurse educators should become familiar with the [hen-ui-link href=”https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193400/” target=”_blank”]TIGER Nursing Informatics Competencies Model[/hen-ui-link], published in 2009. It is intended to help integrate technology into nursing curriculums.[/hen-ui-text][/hen-ui-list-item][/hen-ui-list] [/hen-ui-card-content][/hen-ui-card][hen-ui-text variant=”b4″]Kelley believes we need nurses, especially informatics nurses and nursing leaders, to not only conceptualize [hen-ui-link href=”https://nursejournal.org/articles/the-future-of-nursing-ai-admin-tasks/”]AI’s use in nursing and healthcare[/hen-ui-link] delivery but also identify appropriate and effective use cases that support nursing and patient workflows.[/hen-ui-text][hen-ui-text variant=”b4″]The potential for any AI tool and integration into nursing is limitless but will require critical evaluation. It will also take time to become fully comfortable with AIHTs becoming fully blended into nursing programs.[/hen-ui-text][hen-ui-text variant=”b4″]But, it is essential to point out that AIHTs can improve clinical decision-making and influence the traditional nurse-patient relationship by enhancing the teaching and learning process.[/hen-ui-text][hen-ui-text variant=”b4″]“We must ensure and emphasize that these AI tools are intended to support or assist and not replace the critical thinking of our nurses,” Kelley says.[/hen-ui-text][hen-ui-heading variant=”h2″]Meet Our Contributor[/hen-ui-heading][hen-ui-flex direction=”column” gap=”lg”][hen-ui-expert-bio name=”Tiffany Kelley, PhD MBA RN-BC” img-src=”https://res.cloudinary.com/highereducation/images/e_grayscale,c_fill,h_300,w_300,g_face/v1688048902/NurseJournal.org/Tiffany-Kelley/Tiffany-Kelley.jpg?_i=AA” img-alt=”Tiffany Kelley, PhD MBA RN-BC” layout=”horizontal” background=”white” /][hen-ui-text variant=”b4″ slot=”contentRight” class=”text-base”]Tiffany Kelley, PhD MBA RN-BC, has nearly 20 years of nursing informatics and health IT experience. She earned her Ph.D. specializing in nursing informatics from Duke University. Dr. Kelley leveraged her nursing informatics knowledge and experience to create two entrepreneurial ventures: Nightingale Apps and iCare Nursing Solutions. Dr. Kelley is also the Frederick A. DeLuca Foundation Visiting Professor for Innovations and New Knowledge in Nursing at the University of Connecticut School of Nursing.[/hen-ui-text][/hen-ui-flex][hen-ui-accordion variant=”no-background”] [hen-ui-accordion-item title=”Sources”] [hen-ui-text-stack gap=”sm”] [hen-ui-text variant=”b4″][hen-ui-link href=”https://www.healthit.gov/data/quickstats/adoption-electronic-health-records-hospital-service-type-2019-2021″ target=”_blank”]Adoption of Electronic Health Records by Hospital Service Type 2019-2021[/hen-ui-link]. (2023). Health IT[/hen-ui-text][hen-ui-text variant=”b4″]Buchanan, C et al. [hen-ui-link href=”https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328269/” target=”_blank”]Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review[/hen-ui-link]. (2021). NIH[/hen-ui-text][hen-ui-text variant=”b4″]Gagne, J. [hen-ui-link href=”https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10049425/” target=”_blank”]The State of Artificial Intelligence in Nursing Education: Past, Present, and Future Directions[/hen-ui-link]. (2023). NIH[/hen-ui-text][hen-ui-text variant=”b4″][hen-ui-link href=”https://www.healthit.gov/data/quickstats/office-based-physician-electronic-health-record-adoption” target=”_blank”]Office-based Physician Electronic Health Record Adoption[/hen-ui-link]. (2023). Health IT[/hen-ui-text] [/hen-ui-text-stack] [/hen-ui-accordion-item][/hen-ui-accordion]