Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
Curr Probl Cardiol. 2023 Nov;48(11):101989. doi: 10.1016/j.cpcardiol.2023.101989. Epub 2023 Jul 22.
The interpretation of electrocardiograms (ECGs) involves a dynamic interplay between computerized ECG interpretation (CEI) software and human overread. However, the impact of computer ECG interpretation on the performance of healthcare professionals remains largely unexplored. The aim of this study was to evaluate the interpretation proficiency of various medical professional groups, with and without access to the CEI report. Healthcare professionals from diverse disciplines, training levels, and countries sequentially interpreted 60 standard 12-lead ECGs, demonstrating both urgent and nonurgent findings. The interpretation process consisted of 2 phases. In the first phase, participants interpreted 30 ECGs with clinical statements. In the second phase, the same 30 ECGs and clinical statements were randomized and accompanied by a CEI report. Diagnostic performance was evaluated based on interpretation accuracy, time per ECG (in seconds [s]), and self-reported confidence (rated 0 [not confident], 1 [somewhat confident], or 2 [confident]). A total of 892 participants from various medical professional groups participated in the study. This cohort included 44 (4.9%) primary care physicians, 123 (13.8%) cardiology fellows-in-training, 259 (29.0%) resident physicians, 137 (15.4%) medical students, 56 (6.3%) advanced practice providers, 82 (9.2%) nurses, and 191 (21.4%) allied health professionals. The inclusion of the CEI was associated with a significant improvement in interpretation accuracy by 15.1% (95% confidence interval, 14.3-16.0; P < 0.001), decrease in interpretation time by 52 s (-56 to -48; P < 0.001), and increase in confidence by 0.06 (0.03-0.09; P = 0.003). Improvement in interpretation accuracy was seen across all professional subgroups, including primary care physicians by 12.9% (9.4-16.3; P = 0.003), cardiology fellows-in-training by 10.9% (9.1-12.7; P < 0.001), resident physicians by 14.4% (13.0-15.8; P < 0.001), medical students by 19.9% (16.8-23.0; P < 0.001), advanced practice providers by 17.1% (13.3-21.0; P < 0.001), nurses by 16.2% (13.4-18.9; P < 0.001), allied health professionals by 15% (13.4-16.6; P < 0.001), physicians by 13.2% (12.2-14.3; P < 0.001), and nonphysicians by 15.6% (14.3-17.0; P < 0.001).CEI integration improves ECG interpretation accuracy, efficiency, and confidence among healthcare professionals.
心电图(ECG)的解读涉及计算机化心电图解读(CEI)软件和人工复查之间的动态交互。然而,计算机心电图解读对医疗保健专业人员表现的影响在很大程度上仍未得到探索。本研究旨在评估不同医学专业群体在有和没有 CEI 报告的情况下的解读能力。来自不同学科、培训水平和国家的医疗保健专业人员依次解读了 60 份标准 12 导联 ECG,其中包括紧急和非紧急发现。解读过程分为两个阶段。在第一阶段,参与者在有临床陈述的情况下解读了 30 份 ECG。在第二阶段,同样的 30 份 ECG 和临床陈述被随机排列,并附有 CEI 报告。诊断性能基于解读准确性、每份 ECG 的时间(以秒[ s ]为单位)和自我报告的信心(评分为 0[不自信]、1[有些自信]或 2[自信])进行评估。共有来自不同医学专业群体的 892 名参与者参加了这项研究。该队列包括 44 名(4.9%)初级保健医生、123 名(13.8%)正在培训的心脏病专家、259 名(29.0%)住院医生、137 名(15.4%)医学生、56 名(6.3%)高级执业医生、82 名(9.2%)护士和 191 名(21.4%)辅助卫生专业人员。纳入 CEI 可使解读准确性显著提高 15.1%(95%置信区间,14.3-16.0;P<0.001),解读时间减少 52 秒(-56 至-48;P<0.001),信心增加 0.06(0.03-0.09;P=0.003)。所有专业亚组的解读准确性都有所提高,包括初级保健医生提高了 12.9%(9.4-16.3;P=0.003),心脏病学研究员提高了 10.9%(9.1-12.7;P<0.001),住院医生提高了 14.4%(13.0-15.8;P<0.001),医学生提高了 19.9%(16.8-23.0;P<0.001),高级执业医生提高了 17.1%(13.3-21.0;P<0.001),护士提高了 16.2%(13.4-18.9;P<0.001),辅助卫生专业人员提高了 15%(13.4-16.6;P<0.001),医生提高了 13.2%(12.2-14.3;P<0.001),非医生提高了 15.6%(14.3-17.0;P<0.001)。CEI 整合可提高医疗保健专业人员的 ECG 解读准确性、效率和信心。