Use of a Clinical Electrocardiographic Database to Enhance Atrial Fibrillation/Atrial Flutter Identification Algorithms Based on Administrative Data

J Am Heart Assoc. 2021 Apr 6;10(7):e018511. doi: 10.1161/JAHA.120.018511. Epub 2021 Mar 15.

Abstract

Background Administrative data have limited sensitivity for case finding of atrial fibrillation/atrial flutter (AF/AFL). Linkage with clinical repositories of interpreted ECGs may enhance diagnostic yield of AF/AFL. Methods and Results We retrieved 369 ECGs from the institutional Marquette Universal System for Electrocardiography (MUSE) repository as validation samples, with rhythm coded as AF (n=49), AFL (n=50), or other competing rhythm diagnoses (n=270). With blinded, duplicate review of ECGs as the reference comparison, we compared multiple MUSE coding definitions for identifying AF/AFL. We tested the agreement between MUSE diagnosis and reference comparison, and calculated the sensitivity and specificity. Using a data set linking clinical registries, administrative data, and the MUSE repository (n=11 662), we assessed the incremental diagnostic yield of AF/AFL by incorporating ECG data to administrative data-based algorithms. The agreement between MUSE diagnosis and reference comparison depended on the coding definitions applied, with the Cohen κ ranging from 0.57 to 0.75. Sensitivity ranged from 60.6% to 79.1%, and specificity ranged from 93.2% to 98.0%. A coding definition with AF/AFL appearing in the first 3 ECG statements had the highest sensitivity (79.1%), with little loss of specificity (94.5%). Compared with the algorithms with only administrative data, incorporating ECG data increased the diagnostic yield of preexisting AF/AFL by 14.5% and incident AF/AFL by 7.5% to 16.1%. Conclusions Routine ECG interpretation using MUSE coding is highly specific and moderately sensitive for AF/AFL detection. Inclusion of MUSE ECG data in AF/AFL case identification algorithms can identify cases missed using administrative data-based algorithms alone.

Keywords: ECG; administrative data; atrial fibrillation; atrial flutter; identification algorithm.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Atrial Fibrillation* / diagnosis
  • Atrial Fibrillation* / epidemiology
  • Atrial Flutter* / diagnosis
  • Atrial Flutter* / epidemiology
  • Canada / epidemiology
  • Clinical Coding* / methods
  • Clinical Coding* / standards
  • Clinical Decision Rules
  • Data Accuracy
  • Databases, Factual* / standards
  • Databases, Factual* / statistics & numerical data
  • Diagnosis, Differential
  • Electrocardiography* / methods
  • Electrocardiography* / statistics & numerical data
  • Humans
  • Incidence
  • Quality Improvement / organization & administration
  • Sensitivity and Specificity