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| Application of intelligent simulation technology combined with case-based learning in difficult airway teaching for anesthesiologists |
| WANG Huijun1 XIONG Jun2 BAO Yin1 WANG Guyan1▲ |
1.Department of Anesthesiology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China;
2.Department of Anesthesiology, Shenzhen University General Hospital, Guangdong Province, Shenzhen 518055, China |
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Abstract Objective To explore and evaluate the application value of combined application of intelligent difficult airway management simulator assessment system and case-based learning (CBL) in the teaching for anesthesiologists to deal with difficult airway. Methods Forty anesthesiologists trained in the Department of Anesthesiology, Beijing Tongren Hospital from September 2021 to February 2022 were divided into control group and observation group, by block randomization grouping method, with 20 anesthesiologists in each group. The control group trained by the traditional teaching methods of skill operation theory training and clinical practice training, the observation group was taught by CBL with intelligent difficult airway management simulator assessment system for teaching and training. The training content included the treatment of four different difficult airway modes: normal airway, closed teeth, stiff neck and mandibular deformity, and the application of airway tools. Evaluate The effect of teaching and training was evaluated by relevant theoy, clinical operation assessment and satisfaction questionnaire. Results There were no significant differences between the two groups in the theoretical examination results, the operation results of normal airway, and the examination results of using airway tools (P ＞ 0.05); the scores of the observation group in the three difficult airway modes of closed teeth, stiff neck, and mandibular deformity was higher than those of the control group, and the differences were statistically significant (P ＜ 0.05). The satisfaction of the observation group was higher than that of the control group in enhancing the awareness of airway management, deepening the understanding of treatment principles, improving clinical operation self-confidence, improving clinical treatment ability, and enhancing learning interest, and the differences were statistically significant(P ＜ 0.05). Conclusion Combination of intelligent simulation technology and CBL is effective to improve the interest and enthusiasm of anesthesiologists in difficult airway training, and further improve their ability to deal with difficult airway.
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