Time to Incorporate Artificial Intelligence into High-Fidelity Patient Simulators for Nursing Education: A Secondary Analysis of a Pilot Study

High-fidelity patient simulators (HFPS) are wireless, computer-controlled, full-body mannequins developed to reproduce immersive learning experiences for healthcare students. Unfortunately, expert human resources are not always available to adequately set and manage the HFPS to obtain maximum realism. This issue inevitably threatens the achievement of high levels of learning outcomes, especially in postgraduate students who already possess an advanced level of competence and clinical experience. Starting from a secondary analysis of a previous study, this research discussed possible strategies to increase the realism using available computer technologies. Results confirmed that HFPS can positively affect individual learning outcomes with a moderate gain in self-confidence, self-efficacy, and performance, as well as guarantee high levels of students’ satisfaction with learning. However, even if the simulation has been quite effective, it does not mean that the cost of the provision is justified and sustainable for a large audience in a global framework with resource constraints. On this subject, reframing current learning experiences through the integration of new technologies could represent a disruptive solution to provide high-quality and efficient simulation-based education. In this regard, with the use of artificial intelligence, HFPS can respond autonomously both to verbal inputs and to nursing care allowing for heightened realism. In addition, the use of human resources before and during simulation sessions can be optimized with artificial intelligence, making faculty able to better guide students in their learning. Interdisciplinary collaboration is desirable to obtain results which are effective and calibrated for postgraduate students’ educational needs.