Department of Cardiology, Pulmonology, Nephrology and Hypertension, Ehime University Graduate School of Medicine, Toon, Japan.
Departments of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine Faculty of Medicine, Kyoto, Japan
BMJ Open. 2023 May 23;13(5):e072097. doi: 10.1136/bmjopen-2023-072097.
Although the ECG is an important diagnostic tool in medical practice, the competency of ECG interpretation is considered to be poor. Diagnostic inaccuracy involving the misinterpretation of ECG can lead to inappropriate medical judgements and cause negative clinical outcomes, unnecessary medical testing and even fatalities. Despite the importance of assessing ECG interpretation skills, there is currently no established universal, standardised assessment tool for ECG interpretation. The current study seeks to (1) develop a set of items (ECG questions) for estimating competency of ECG interpretation by medical personnel by consensus among expert panels following a process based on the RAND/UCLA Appropriateness Method (RAM) and (2) analyse item parameters and multidimensional latent factors of the test set to develop an assessment tool.
This study will be conducted in two steps: (1) selection of question items for ECG interpretation assessment by expert panels via a consensus process following RAM and (2) cross-sectional, web-based testing using a set of ECG questions. A multidisciplinary panel of experts will evaluate the answers and appropriateness and select 50 questions as the next step. Based on data collected from a predicted sample size of 438 test participants recruited from physicians, nurses, medical and nursing students, and other healthcare professionals, we plan to statistically analyse item parameters and participant performance using multidimensional item response theory. Additionally, we will attempt to detect possible latent factors in the competency of ECG interpretation. A test set of question items for ECG interpretation will be proposed on the basis of the extracted parameters.
The protocol of this study was approved by the Institutional Review Board of Ehime University Graduate School of Medicine (IRB number: 2209008). We will obtain informed consent from all participants. The findings will be submitted for publication in peer-reviewed journals.
尽管心电图在医学实践中是一种重要的诊断工具，但心电图解读的能力被认为是较差的。涉及心电图错误解读的诊断不准确可能导致不适当的医疗判断，并导致负面的临床结果、不必要的医疗检测甚至死亡。尽管评估心电图解读技能很重要，但目前还没有用于心电图解读的普遍、标准化评估工具。本研究旨在：（1）通过专家小组基于 RAND/UCLA 适宜性方法（RAM）的共识过程，制定一组（心电图问题）用于估计医务人员心电图解读能力的项目；（2）分析测试集的项目参数和多维潜在因素，以开发评估工具。
本研究将分两步进行：（1）通过专家小组基于 RAM 的共识过程选择心电图解读评估的问题项目；（2）使用一组心电图问题进行横断面、基于网络的测试。一个多学科专家小组将评估答案和适宜性，并选择 50 个问题作为下一步。根据从预计的 438 名测试参与者（来自医生、护士、医学和护理学生以及其他医疗保健专业人员）中招募的样本大小收集的数据，我们计划使用多维项目反应理论对项目参数和参与者表现进行统计分析。此外，我们将尝试检测心电图解读能力中可能存在的潜在因素。基于提取的参数，提出一组用于心电图解读的测试问题。
本研究的方案已获得爱媛大学研究生院医学院机构审查委员会的批准（IRB 编号：2209008）。我们将获得所有参与者的知情同意。研究结果将提交给同行评议的期刊发表。
