A study of design of a process indicator for anesthesia induction and its feasibility in self-directed simulation-based teaching
10.3760/cma.j.cn116021-20240219-01901
- VernacularTitle:面向自助式模拟教学的麻醉诱导过程性指标设计与可行性探索
- Author:
Rigele TE
1
;
Bo ZHU
1
;
Xiuhua ZHANG
1
;
Shaohui CHEN
1
Author Information
1. 中国医学科学院 北京协和医学院 北京协和医院麻醉科，北京 100730
- Publication Type:Journal Article
- Keywords:
Anesthesiologists;
Simulation-based teaching;
Anesthesia induction;
Anesthesia quality;
Coefficient of variation
- From:
Chinese Journal of Medical Education Research
2024;23(12):1625-1630
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the design of a process indicator for anesthesia induction and its feasibility for a self-directed simulation-based teaching system, and to provide an efficient information technology-based teaching tool that enhances the quality of independent learning and training for anesthesiologists.Methods:Big data derived from electronic medical records were used for the design of the process indicator. Specifically, the design incorporated the coefficients of variations for three hemodynamic features, namely, systolic pressure, diastolic pressure, and heart rate after anesthesia induction. This approach aimed to characterize the quality of anesthesia management. A survey questionnaire was designed and administered to 23 anesthesiologists-in-charge or those with higher positions. These anesthesiologists evaluated the outcomes of anesthesia in 30 cases, thereby investigating the feasibility of the proposed indicators and potential future applications. Analysis of variance and correlation analysis were performed using SPSS 24.0 software, with a significance level set at α=0.05. Results:Based on the range of values for the process indicator of anesthesia induction, five groups were defined: stable, relatively stable, moderately stable, relatively unstable, and unstable. There were significant intergroup differences in the anesthesiologists' ratings, with an F value of 250.66 ( P<0.001), indicating that the integrated coefficient of variation (ICV) effectively discriminated stability levels between groups. The designed indicator showed a significant correlation with the average ratings of the anesthesiologists, with a Pearson correlation coefficient of 0.886 ( P<0.05). This further indicated the great consistency between the proposed indicator and anesthesiologists' judgments. Conclusions:The process indicator for anesthesia induction proposed in this study serves as a feasible measure for assessing the stability of anesthesia. It can be applied in a self-directed simulation-based teaching system, offering new insights and methods for promoting the training and learning of anesthesiologists.
