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External validation of a claims-based model to predict left ventricular ejection fraction class in patients with heart failure

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  • Mufaddal Mahesri
  • Kristyn Chin
  • Abheenava Kumar
  • Aditya Barve
  • Rachel Studer
  • Raquel Lahoz
  • Rishi J Desai

Abstract

Background: Ejection fraction (EF) is an important prognostic factor in heart failure (HF), but administrative claims databases lack information on EF. We previously developed a model to predict EF class from Medicare claims. Here, we evaluated the performance of this model in an external validation sample of commercial insurance enrollees. Methods: Truven MarketScan claims linked to electronic medical records (EMR) data (IBM Explorys) containing EF measurements were used to identify a cohort of US patients with HF between 01-01-2012 and 10-31-2019. By applying the previously developed model, patients were classified into HF with reduced EF (HFrEF) or preserved EF (HFpEF). EF values recorded in EMR data were used to define gold-standard HFpEF (LVEF ≥45%) and HFrEF (LVEF

Suggested Citation

  • Mufaddal Mahesri & Kristyn Chin & Abheenava Kumar & Aditya Barve & Rachel Studer & Raquel Lahoz & Rishi J Desai, 2021. "External validation of a claims-based model to predict left ventricular ejection fraction class in patients with heart failure," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-8, June.
    • Handle: RePEc:plo:pone00:0252903
    DOI: 10.1371/journal.pone.0252903
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