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Development and Implementation of Augmented Reality Enhanced High-Fidelity Simulation for Recognition of Patient
Matthew W Zackoff1, Bradley Cruse, Rashmi D Sahay
1From the Department of Pediatrics (M.W.Z., R.D.S., L.F., M.K., G.L.G., K.T.), University of Cincinnati College of Medicine; and Division of Critical Care Medicine (M.W.Z., K.T.), Center for Simulation and Research (B.C.), Division of Biostatistics and Epidemiology (R.D.S., L.F.), Center for Professional Excellence (J.Sa., J.Sc.), and Divisions of General and Community Pediatrics (M.K.) and Emergency Medicine (G.L.G.), Cincinnati Children's Hospital Medical Center, Cincinnati, OH.
Introduction:
Simulation is a core aspect of training and assessment; however, simulation laboratories are limited in their ability to visually represent mental, respiratory, and perfusion status. Augmented reality (AR) represents a potential adjunct to address this gap.
Methods:
A prospective, observational pilot of interprofessional simulation assessing a decompensating patient was conducted from April to June 2019. Teams completed 2 simulations: (1) traditional training (TT) using a manikin (Laerdal SimJunior) and (2) AR-enhanced training (ART) using a manikin plus an AR patient. The primary outcome was self-assessed effectiveness at the assessment of patient decompensation. Secondary outcomes were attitudes toward and adverse effects during the AR training.
Results:
Twenty-one simulation sessions included 84 participants in headsets. Participants reported improved ability to assess the patient's mental status, respiratory status, and perfusion status (all P < 0.0001) during ART in comparison to TT. Similar findings were noted for recognition of hypoxemia, shock, apnea, and decompensation (all P ≤ 0.0003) but not for recognition of cardiac arrest (P = 0.06). Most participants agreed or strongly agreed that ART accurately depicted a decompensating patient (89%), reinforced key components of the patient assessment (88%), and will impact how they care for patients (68%). Augmented reality-enhanced training was rated more effective than manikin training and standardized patients and equally as effective as bedside teaching.
Conclusions:
This novel application of AR to enhance the realism of manikin simulation demonstrated improvement in self-assessed recognition of patient decompensation. Augmented reality may represent a viable modality for increasing the clinical impact of training.
