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

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

PLOS ONE, 2021, vol. 16, issue 6, 1-8

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

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0252903

DOI: 10.1371/journal.pone.0252903

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