Augmented Reality, Mixed Reality, and Hybrid Approach in Healthcare Simulation: A Systematic Review

Simulation-based medical training is considered an effective tool to acquire/refine technical skills, mitigating the ethical issues of Halsted's model. This review aims at evaluating the literature on medical simulation techniques based on augmented reality (AR), mixed reality (MR), and hybrid approaches. The research identified 23 articles that meet the inclusion criteria: 43% combine two approaches (MR and hybrid), 22% combine all three, 26% employ only the hybrid approach, and 9% apply only the MR approach. Among the studies reviewed, 22% use commercial simulators, whereas 78% describe custom-made simulators. Each simulator is classified according to its target clinical application: training of surgical tasks (e.g., specific tasks for training in neurosurgery, abdominal surgery, orthopedic surgery, dental surgery, otorhinolaryngological surgery, or also generic tasks such as palpation) and education in medicine (e.g., anatomy learning). Additionally, the review assesses the complexity, reusability, and realism of the physical replicas, as well as the portability of the simulators. Finally, we describe whether and how the simulators have been validated. The review highlights that most of the studies do not have a significant sample size and that they include only a feasibility assessment and preliminary validation; thus, further research is needed to validate existing simulators and to verify whether improvements in performance on a simulated scenario translate into improved performance on real patients.

Automated summary

Simulation-based medical training using AR, MR, and hybrid approaches offers an effective tool for technical skill acquisition. Most studies reviewed focus on custom-made simulators, with varying combinations and classifications of approaches. However, there is a need for further research to validate existing simulators and assess their impact on real patient outcomes beyond feasibility and preliminary validation assessments.