AI in Simulation – Clinical Intelligence at NCLEX Standards

Over the past few years, the National Council Licensure Examination (NCLEX) has been updating its standards and is now ready with new 2023 standards for nursing. But if the changes (to language used in class and the structure of exams) are to be carried forward more widely within the nursing community, they must be incorporated within the wider training strategy. This article will cover some of the NCLEX changes regarding the conceptualization of Artificial Intelligence (AI), and demonstrates some of the clinical simulation AI training tools already utilizing advanced technologies improving outcomes. This article was submitted by Peter Marotta, RN, Nasco Healthcare Senior Clinical Simulation Educator US/International.

Why did NCLEX update its standards?

Due to the core problem of medical errors and avoidable deaths. A 2016 Johns Hopkins University School of Medicine study1 suggested medical errors are the third leading cause of death in the U.S. Analyzing data over an 8-year period, researchers suggested that 10% of all U.S. deaths are due to medical errors.1 In response, NXCLEX did its own self-evaluations and research related to training and improving patient outcomes, which, prior to 2022, had been carried out by third parties.


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They concluded that knowledge- and skill-centered training, the backbone of nursing and medical education, was not adequate. A new third element contextualizing skills and knowledge was needed. This “Clinical Awareness or Intelligence” would improve patient outcomes2-4 and would be tied to the ability to develop the critical thinking skills needed.

NCLEX Recommended Clinical Intelligence

There are three teaching domains that students go through as part of their nursing training – the Classroom, the Skills and Simulation Lab, and the Clinical Setting. The classroom is the common starting point. The clinical space is the main training space after nursing school. With time, the Classroom and the Clinical Setting became siloed from each other leading to students having a ‘pump and dump’ approach. This served them poorly when treating real patients after graduation, as attested by the study on medical errors.

To overcome these gaps, Skills and Simulation Lab evolved. As demands on training increase and clinical experiences become harder to access or limited to a small timeframe within nursing programs, simulation becomes crucial. But we need more. Just like incorporating simulation helps hone skills and knowledge, we need to incorporate clinical intelligence to improve contextualizing those skills and that knowledge.


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Factor in Key Variables

As we try incorporating Clinical Intelligence, we need to identify the key variables that affect the Clinical Setting. The patient is one of the key variables that defines how the clinical context changes.

  • Traditional approaches to introducing patient variability:
    • Standardized patients: Can be effective, but require training, support and may present a limited and inconsistent training on a day-to-day basis.
    • Instructor/scripted speech through a manikin: Can provide increased consistency but can burden the training staff and can also lead to talking around the patient rather than to the patient.

Although simulators provide an improved alternative to standard manikins, they do not provide a sufficiently realistic patient experience or training tool. The poorly trained nurses, when faced with real patients are performing inadequately, as attested by the study on medical errors.

Using AI to Drive Simulation

With the advent of artificial intelligence (AI) driven by cloud computing we can now present different patient profiles that are not solely dependent on physiological changes. We can include psycho/social dynamics that can provide the much-needed patient variability. Using Clinical Intelligence prepares trainees more thoroughly for clinical engagement and real-life patient care.

The ALEX Patient Communication Simulator

The ALEX Patient Communication Simulator developed by PCS and Nasco Healthcare represents this new training dynamic. Via a browser-based interface, instructors can use most Wi-Fi devices from phones to computers to access and control the simulation. The AI used in the ALEX simulator allows the instructor to select various patient personalities that can be cloned and modified to present any physiological material being covered in the nursing program.

This allows the instructor to have several personalities that can be used with students to provide different responses for the same material, so that the student can adapt to the context of the patient. The student is no longer just reacting to the physiological dynamic changes. Rather, they must incorporate the interaction with the patient into the treatment. Since the AI responds to the student and can be augmented by the instructor, the student is required to focus on the patient.

Thereby the risk is reduced. Talking around the patient is reduced. The interaction with the ALEX simulator is more organic, more comparable to the clinical interactions they would face in real, allowing the student to refine their Clinical Intelligence.

AI Advantages for Instructors

With the automation, the instructor also can focus on the students’ interactions rather than the management of the system. Second, it increases both consistency and availability that standardized patient methodologies can struggle with. The ALEX simulator is not just limited to nursing instructors.



It can be used across multiple disciplines for medical students and pharmacology trainees. At a session of the Society for Simulation in Healthcare (SSH) Learning Lab Webinar in July 2022, Professor Jonathan Davies, Liverpool John Moores University discussed how the ALEX simulator has been adapted to meet the clinical development needs of students, allowing them to train on communication interactions with patients.

AI Enhances Multiple Modalities of Training

Since the ALEX simulator is browser-based, it lends itself to being used outside of the Simulation Lab silo and supports cross educational domain training. Addition of the SPARK Plus system allows the creation of avatar-based modality. Using these avatars, instructors and students can leverage the AI and telemetry with or without patients, in the Classroom or the Clinical Setting. Given the challenges of the last few years, this added capacity to provide increased flexibility to access and use helps provide programs a more robust and less fragile training environment. The system also helps programs move the objects out of the Classroom and move towards a more sustainable training environment.

Conclusion

Training is key to saving lives. A 10% rate of medical errors1 calls for change. The NCLEX has recommended incorporating Clinical Intelligence into training curriculums. Clinical Intelligence would improve patient outcomes2-4. The need of the hour is for AI to meet NCLEX standards so that Clinical intelligence can be incorporated in the Classroom, Simulation Lab, and Clinical Setting. Nurses need to Be READY to reduce medical errors, Be READY to save more lives.

References:

  1. Makary MA, Daniel M. Medical error-the third leading cause of death in the US. BMJ. 2016;353:i2139. Published 2016 May 3. doi:10.1136/bmj.i2139
  2. Thomas MH, Baker SS. NCLEX-RN success: evidence-based strategies. Nurse Educ. 2011;36(6):246-249. doi:10.1097/NNE.0b013e3182333f70
  3. Romeo EM. Quantitative research on critical thinking and predicting nursing students’ NCLEX-RN performance. J Nurs Educ. 2010;49(7):378-386. doi:10.3928/01484834-20100331-05
  4. Bonis S, Taft L, Wendler MC. Strategies to promote success on the NCLEX-RN: an evidence-based approach using the ACE Star Model of Knowledge Transformation. Nurs Educ Perspect. 2007;28(2):82-87.

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