Interrater agreement between student and teacher assessments of endotracheal intubation skills in a self-directed simulation learning environment.

BACKGROUND: Practical skill assessment is an important part of the learning process to confirm competencies in acquired medical knowledge. OBJECTIVE: This study aimed to compare the assessments of endotracheal intubation skills using the HybridLab® methodology between students and teacher in terms of interobserver reliability. METHODS: Reliability analysis was performed with observational data (data are reported according to STROBE guidelines). The study was conducted in two countries, the Lithuanian University of Health Science (LUHS) and Pennsylvania State University (PSU) in the US, between 1 January and 30 June 2020. A total of 92 students (60 from LUHS and 32 from PSU) were trained in endotracheal intubation using an algorithm-driven hybrid learning method. At the end of the training session, the participants had to complete the evaluation scenario, which was assessed by one of the students and evaluated remotely by a single teacher. The student assessment of the endotracheal intubation procedure was compared with the teacher's assessment using correlation and estimation of the intraclass correlation coefficient. RESULTS: Overall, the medians of the student and teacher assessments were both 100% (0%). Spearman's correlation coefficient between the student and teacher assessments was 0.879 (p = 0.001). The intraclass correlation coefficient used for interobserver variations between the students and teacher was 0.883 (95% confidence interval from 0.824 to 0.923). CONCLUSIONS: The algorithm-driven hybrid learning method allows students to reliably assess endotracheal intubation skills to a level comparable with that of the teacher's evaluation. This learning method has the potential to be a cost-effective and efficient way to provide high-quality education while also saving human resources.

A novel algorithm-driven hybrid simulation learning method to improve acquisition of endotracheal intubation skills: a randomized controlled study.

BACKGROUND: Simulation-based training is a clinical skill learning method that can replicate real-life situations in an interactive manner. In our study, we compared a novel hybrid learning method with conventional simulation learning in the teaching of endotracheal intubation. METHODS: One hundred medical students and residents were randomly divided into two groups and were taught endotracheal intubation. The first group of subjects (control group) studied in the conventional way via lectures and classic simulation-based training sessions. The second group (experimental group) used the hybrid learning method where the teaching process consisted of distance learning and small group peer-to-peer simulation training sessions with remote supervision by the instructors. After the teaching process, endotracheal intubation (ETI) procedures were performed on real patients under the supervision of an anesthesiologist in an operating theater. Each step of the procedure was evaluated by a standardized assessment form (checklist) for both groups. RESULTS: Thirty-four subjects constituted the control group and 43 were in the experimental group. The hybrid group (88%) showed significantly better ETI performance in the operating theater compared with the control group (52%). Further, all hybrid group subjects (100%) followed the correct sequence of actions, while in the control group only 32% followed proper sequencing. CONCLUSIONS: We conclude that our novel algorithm-driven hybrid simulation learning method improves acquisition of endotracheal intubation with a high degree of acceptability and satisfaction by the learners' as compared with classic simulation-based training.