A checklist manifesto: Can a checklist of common diagnoses improve accuracy in ECG interpretation? Academic Article uri icon

Overview

abstract

  • OBJECTIVE: To determine whether a checklist of possible etiologies for syncope provided alongside ECGs helps Emergency Medicine (EM) residents identify ECG patterns more accurately than with ECGs alone. METHODS: We developed a test of ten ECGs with syncope-related pathology from ECG Wave-Maven. We reviewed the literature and used expert consensus to develop a checklist of syncope-related pathologies commonly seen and diagnosed on ECGs. We randomized residents from three New York EM residency programs to interpret ECGs with or without a checklist embedded into the test. RESULTS: We randomized 165 residents and received completed tests from 100 (60%). Of those who responded, 39% were interns, 23% PGY2s, and 38% were PGY3s or PGY4s. We found no significant difference in overall test scores between those who read ECGs with a checklist and those who read ECGs alone. In post-hoc analysis, residents given a checklist of syncoperelated etiologies were significantly more likely to recognize Brugada (96% vs. 78%, p = 0.007), long QT (86% vs. 68%, p = 0.03) and heart block (100% vs 78%, p = 0.003) as compared to those without a checklist. Those with a checklist were more likely to overread normal ECGs (72% vs 35%, p = 0.0001) compared to those without a checklist, finding pathology where there was none. CONCLUSION: Using a checklist with common syncope-related pathology when interpreting an ECG for a patient with clinical scenario of syncope may improve residents' ability to recognize some clinically important pathologies; however it could lead to increased interpretation and suspicion of pathology that is not present.

publication date

  • March 29, 2019

Research

keywords

  • Cardiovascular Diseases
  • Checklist
  • Electrocardiography
  • Emergency Medicine
  • Internship and Residency
  • Syncope

Identity

Scopus Document Identifier

  • 85063588567

Digital Object Identifier (DOI)

  • 10.1016/j.ajem.2019.03.048

PubMed ID

  • 30952602

Additional Document Info

volume

  • 38

issue

  • 1