Northwestern University, Department of Surgery, Chicago, Illinois 60611-2908, USA.
J Surg Res. 2012 Sep;177(1):27-32. doi: 10.1016/j.jss.2012.03.047. Epub 2012 Apr 11.
Prior work using simulation for assessing intubation skills has largely focused on the use of observer-generated performance measures in the form of checklists and global ratings scales.
The purpose of our work was to investigate whether patient-centered simulation data could be used to quantify learner's performance during direct laryngoscopy.
We designed a pretest/posttest prospective intervention study of residents' (n = 25) intubation skills.
When assessing validity, all of the patient-centered simulation variables showed significant correlations with the previously validated observer-generated performance measures (r = 0.331-0.463, P ≤ 0.001). When assessing reliability, there were significant correlations between all of the sensor variables, confirming moderate to high inter-item reliability (r = 0.259-0.794, P ≤ 0.05). The observer-generated performance measures showed significant improvement in use of the Macintosh blade (T1 = 2.10/5.00, T2 = 3.64/5.00, P = 0.001). However, this was not the case for the Miller blade (T1 = 1.30/5.00, T2 = 1.75/5.00, P = 0.119). Overall, the patient-centered simulation variables provided a high level of detail regarding performance improvement areas.
This study presents a multilevel analysis of sensor-generated simulation data. As the sensors provide sound, formative data regarding patient contact, the outputs may be used for specific criterion measures and detailed performance feedback.
先前使用模拟评估插管技能的工作主要集中在使用观察者生成的表现评估量表,如检查表和整体评分量表。
我们的工作目的是研究是否可以使用以患者为中心的模拟数据来量化学习者在直接喉镜检查期间的表现。
我们设计了一项对住院医师(n = 25)插管技能的预测试/后测试前瞻性干预研究。
在评估有效性时,所有以患者为中心的模拟变量与先前经过验证的观察者生成的表现评估量表显著相关(r = 0.331-0.463,P ≤ 0.001)。在评估可靠性时,所有传感器变量之间都存在显著相关性,证实了中等至高度的项目间可靠性(r = 0.259-0.794,P ≤ 0.05)。观察者生成的表现评估量表在使用 Macintosh 叶片方面显示出显著改善(T1 = 2.10/5.00,T2 = 3.64/5.00,P = 0.001)。然而,在 Miller 叶片方面并非如此(T1 = 1.30/5.00,T2 = 1.75/5.00,P = 0.119)。总体而言,以患者为中心的模拟变量提供了有关绩效改进领域的高度详细信息。
本研究提出了传感器生成的模拟数据的多层次分析。由于传感器提供了有关患者接触的声音和形成性数据,因此输出结果可用于特定的标准衡量和详细的绩效反馈。