Sarı Hasan, Uçar Ayşe, Kesriklioğlu Serhat, Sarı Memduha, Sertdemir Ahmet Lütfü
Mut State Hospital, Cardiology Clinic, Mersin.
Faculty of Nursing, Department of Internal Medicine, Necmettin Erbakan University.
Acta Cardiol Sin. 2025 Jul;41(4):501-509. doi: 10.6515/ACS.202507_41(4).20250324B.
Electrocardiography (ECG) plays a pivotal role in diagnosing certain cardiac pathologies. Interpreters receive significant training in this area; however, an electrocardiogram must be performed correctly for accurate interpretation. It should also be recorded and interpreted swiftly. The aim of this study was to assess the level of technical knowledge regarding ECG performance among healthcare professionals.
The study was conducted between June 2023 and September 2023. A total of 243 participants, including nurses, doctors, and medical and nursing faculty students, were enrolled. The participants were asked 16 questions via a Google survey. The participants were statistically compared based on their professions and workplaces.
The relationships between the descriptive characteristics of the participants and electrocardiography knowledge scores were not statistically significant in terms of age, gender, employment status, or duration of employment (p > 0.05). However, medical faculty students had significantly higher ECG knowledge scores compared to nurses (p < 0.01). Among the nurses, those working in surgical units had significantly lower scores than those working in internal medicine and pediatric units (p < 0.05).
In this study, 16 questions were used to evaluate ECG acquisition knowledge. The ECG knowledge scores of the participants ranged between 0-14 and the mean score was 6.95 ± 3.13, which is quite low for a simple and applicable test. A simple mistake or delay in performing an electrocardiogram can lead to catastrophic consequences. Although nurses are the primary personnel performing ECG, their technical knowledge in performing the procedure was not as proficient as doctors. Some areas of focus may lead to errors. Although research has consistently focused on interpreting ECG, we still do not know how to perform ECG properly. More emphasis should be placed on ECG training, with the potential for regular training throughout the year as needed. These simple and preventable errors can be more easily overcome with artificial intelligence-supported programs.
心电图（ECG）在某些心脏疾病的诊断中起着关键作用。解读人员在这一领域接受了大量培训；然而，为了进行准确解读，必须正确地进行心电图检查。它还应迅速记录和解读。本研究的目的是评估医疗保健专业人员在心电图操作方面的技术知识水平。
该研究于2023年6月至2023年9月进行。共招募了243名参与者，包括护士、医生以及医学和护理专业的学生。通过谷歌调查问卷向参与者提出了16个问题。根据参与者的职业和工作场所进行了统计学比较。
参与者的描述性特征与心电图知识得分之间的关系在年龄、性别、就业状况或工作时长方面无统计学意义（p>0.05）。然而，与护士相比，医学专业学生的心电图知识得分显著更高（p<0.01）。在护士中，外科病房的护士得分明显低于内科和儿科病房的护士（p<0.05）。
在本研究中，使用16个问题来评估心电图采集知识。参与者的心电图知识得分在0至14分之间，平均得分为6.95±3.13，对于一个简单且适用的测试来说这个分数相当低。心电图操作中的一个小错误或延迟都可能导致灾难性后果。虽然护士是进行心电图检查的主要人员，但他们在操作该程序方面的技术知识不如医生熟练。某些重点领域可能会导致错误。尽管研究一直专注于心电图解读，但我们仍然不知道如何正确地进行心电图检查。应更加重视心电图培训，并有可能根据需要全年定期进行培训。借助人工智能支持的程序，这些简单且可预防的错误更容易被克服。
