12 minute read
DISRUPTIVE HEALERS
How Texas Nurses Can Navigate the AI Frontier
By Stephanie H. Hoelscher, DNP, RN, NI-BC, AIMP, CPHIMS, CHISP, FHIMSS
AS TEXAS NURSES CONTINUE TO ADAPT to the evolving technological landscape of healthcare, a new “digital health” player has fully emerged: Artificial Intelligence (AI). You might have heard the term ‘AI’ tossed around in webinars and conferences or seen it in the latest healthcare journals or podcasts. You might be experiencing the early stages of “AI fatigue,” having heard the term thrown around ad nauseam over the past two years. But what does it truly mean for you in the nursing profession? With all the other healthcare hot topics in the news, like virtual nursing, clinician burden, and the worsening nursing shortage, the AI explosion is proving to be a pivotal moment in history where healthcare and nursing will change forever. But will it be for the better?
In this article, we will discuss the basics of AI, breaking down its core concepts and exploring how it transforms nursing practice in the Lone Star State. Whether you are tech-savvy or just looking to increase your AI literacy, this introduction is your gateway to understanding how AI is reshaping the future of nursing.
UNPACKING THE BASICS
Before diving into AI and clinical practice, the basics to consider are what AI is and how can nurses use it. Let us start by asking the former: What is AI? Through the National Artificial Intelligence Act of 2020, the definition provided to us is as follows:
“The term ’artificial intelligence’ means a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations or decisions influencing real or virtual environments” (para. 2).
AI, specifically a subset called generative AI (GenAI), refers to computer systems that mimic human intelligence, human thought patterns, human speech, and human writing (amongst a few other human things). AI can analyze data, recognize patterns, and make decisions. GenAI can create content, such as text, graphics, music, or code, by learning from vast amounts of existing data (Hoelscher et al., 2024). GenAI, like OpenAI’s ChatGPT, is trained on profoundly large amounts of data (think trillions and trillions of data points) and is powered by large language models (LLMs). The LLMs can be used as predictors of patient outcomes for critical metrics such as readmission rates, mortality rates, and hospital-acquired injuries and infections (Siwicki, 2023). For Texas nurses, this means tools that can help with clinical decision-making, care plan development, electronic documentation, treatment planning, and patient care management by providing insights drawn from extensive patient data. See Figure 1 for more key AI concepts and applications.
THE IMPACT OF AI ON NURSING PRACTICE
One of the most significant impacts is already underway, though nurses might not yet realize it. Several electronic health record (EHR) vendors, such as Epic and Oracle Cerner, are already working on using GenAI within their platforms and patient portals to help improve patient care, clinical workflow, and decision-making (Bruce, 2024a; Nelson, 2023). This includes multiple Texas health systems. Joining forces with GenAI vendors (e.g., Google, OpenAI, Microsoft), the integration of AI functionality in healthcare is expanding rapidly. This is beyond the daily clinical decision support (CDS) nurses use within EHRs, such as “pop-ups” or reference text. The goal is to enhance the overall end-user (clinician) experience by integrating a more natural language into the EHR conversation, automating administrative and repetitive tasks, and sometimes even providing AI-dictation services—or what we would call ambient listening applications (Bruce, 2024b; Galloway et al., 2024; Nelson, 2023; Shah, 2023)
Vendors are also working on using GenAI for burden-reduction issues like inbox maintenance, which is often the bane of both physicians’ and nurses’ existence. Using the natural language processing (NLP) ability of GenAI—well-written, easy-to-understand, and applicable responses could be written for patient questions via a patient portal. After the clinician reviews and amends the AI output, the message could then be sent to the patient. Another popular, time-saving functionality is the speedy review and summarization GenAI can provide nurses regarding the contents of a patient’s chart. At the touch of a button, GenAI could crawl through the entire patient record and review the latest and greatest regarding your patient’s current health status—as succinct or detailed as you need. In less than five seconds, laboratory results, radiology reads, provider notes, and messages—you name it—GenAI can create a report for your viewing pleasure.
PATIENT EDUCATION
Speaking of patient portals, another usage of GenAI that nurses would find of great benefit while helping to address health literacy is the ability for patient education to be translated into a more digestible, easy-to-understand version
All this and more, including the aforementioned CDS, personalized care plans, and patient education.
IMPACT ON NURSING EDUCATION
EDUCATION FOR NURSES IN THE CLASSROOM
Part of the issue with the nursing shortage is related to nursing education. Nursing schools have difficulty with having enough nursing faculty, which trends down to being able to educate the next generation of nurses. De Gagne (2023) discusses some of the concerns and controversies surrounding the adoption of AI in nursing education. An essential worry with utilizing AI tools like GenAI and chatbots for academic purposes is their potential to unintentionally promote violations of academic integrity, ethics, and intellectual property rights. There are concerns about how students’ use of the advanced capabilities of these systems might lead to inappropriate copying or plagiarism without proper attribution (Anthropic, 2023; De Gagne, 2023; Sun & Hoelscher, 2023). Currently, there is no foolproof method of detecting AI-generated writing (Sun & Hoelscher, 2023). Educators have to make a tough decision on whether they support student use of GenAI with established parameters or are against it and are in the never-ending fight to try to catch students using it. Organizational policies and syllabi verbiage need to be updated or created. Many Texas higher education organizations already utilize AI-centric policies and syllabi to help faculty and students use AI in the classroom.
There are various other factors, good and bad, to consider in education. There is concern about protecting student privacy, as AI sometimes requires access to personal information. Ethical issues related to GenAI, data bias, lack of equal student AI application access, and blatant inaccuracies of AI output (such as hallucinations) can exacerbate existing inequities (De Gagne, 2023; Sun & Hoelscher, 2023). Not unlike using AI to personalize patient education, GenAI’s versatile functionality can assist with administrative work and facilitate customized plans to address each student’s learning requirements. By automating routine tasks, such as rubric development, grading, case scenario development, note-taking, and student progress tracking, nurse educators could gain time to focus on more complex teaching tasks requiring unique insight and expertise and that human, personal touch. AI technology can also create more sophisticated and complex simulations that:
“…help nursing students develop critical thinking skills and prepare for real-world patient care situations. Such simulations can provide students with realistic scenarios that mimic patient care situations, allowing them to practice their clinical skills” and decision-making in a safe environment (De Gagne, 2023, p. 4884).
As GenAI becomes increasingly intelligent and well-trained, its abilities to provide realistic and engaging learning experiences will also be enhanced. The further development of GenAI’s capabilities will permit it to offer more detailed, life-like simulations and interactions for education.
EDUCATION FOR NURSES IN PRACTICE
Much of the focus of AI education has been on new nurses or the academic lens. Priority must also be given to bedside nurses or nurses already in practice. Recommendations do not differ too much from nursing student’s learning experiences. A significant shift will be to update your knowledge and stay up to date, which, of course, can be challenging. Some items to focus on for nursing professionals include (Glauberman et al., 2023; Hoelscher et al., 2024):
Improved AI literacy. At a minimum, it is vital to have a basic understanding of AI and AI tools being used at the workplace and their impact on professional and patient care.
Ethical use of AI tools. Working with nursing organizations to develop toolkits, policies, and overall guidance around AI usage (ANA, 2022).
Overreliance on AI technology. This is a big one. As with CDS, there is the potential to ignore AI recommendations. Alternatively, rely on them without thought. AI output should always be reviewed. This will be directly tied to one of the most essential nursing skills: critical thinking.
CDS/predictive analytics tools. CDS is not new, but AI-enhanced CDS is. Nurses already in the profession and those who work to keep them informed will benefit greatly by being proactive and transparent about new AI tools being introduced into the workplace.
Continuous learning. Nurses are lifelong learners. This will be another competency from here on out that you can add to your list of nursing skills to develop and maintain. Overall, this helps to maintain your AI literacy.
Cool new toys. Finances permitting, this is an excellent opportunity to introduce new learning methods like simulation and virtual or augmented reality.
THE GROWING ADOPTION OF AI IN TEXAS NURSING
Nurses in Texas have often taken the lead on issues such as health information technology. This has been clear during the pandemic, with multiple efforts to help investigate and reduce the burden, including the Texas Nurses Association, Texas Organization for Nursing Leadership, and others (Holub & Giegerich , 2023; Hoelscher, McBride, et al., 2024; McBride et al., 2021; Padden, 2020). Between nurses exiting the workforce due to dissatisfaction and retiring, the shortage outlook does not look to improve soon. Aside from this, it is also important to note the issues with AI and its rapid development in healthcare. There are biased data issues, a lack of transparency with vendors and organizations, a lack of AI literacy with clinicians, and data privacy/security issues to contend with—all impacting Texas very much this year alone.
In the bustling hospitals of Texas, the Moxi robot and its counterparts are not just machines; they symbolize a paradigm shift in nursing care, offering a helping hand to the compassionate heroes in scrubs.
So, without losing the “nurse” part of healthcare, how can we use technology to maintain and improve patient safety and outcomes while lessening the nursing burden? After asking a chatbot what they thought readers would want to know in the end about the future of AI in Texas healthcare, ChatGPT replied with the following (OpenAI, 2024):
“As the sun sets over the Lone Star State, a new dawn in healthcare and education rises, powered by the relentless march of AI technology. In the bustling hospitals of Texas, the Moxi robot and its counterparts are not just machines; they symbolize a paradigm shift in nursing care, offering a helping hand to the compassionate heroes in scrubs. Meanwhile, similar initiatives are redefining how nurses are trained, blending traditional care with cutting-edge simulation and AI. This fusion of human touch and artificial intelligence is revolutionizing patient care and opening doors to a world of AI-driven job opportunities. As Texas leads the charge, its educational institutions are equally dynamic, crafting new AI programs and curricula to equip the nurses of tomorrow. The future is here, and it is being written in the heart of Texas, where tradition meets innovation and where nursing care is being reimagined for a brighter, smarter world.”
I could not have said it better myself.
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