Risk Adjustment Model for Preserved Health Status in Patients With Heart Failure and Reduced Ejection Fraction: The CHAMP-HF Registry.

Andy T Tran Gregory Y H Lip Suzanne V Arnold Phillip G JonesLaine E ThomasC Larry Hill Adam D DeVoreJaved ButlerNancy M Albert John A Spertus

Published in: Circulation. Cardiovascular quality and outcomes (2021)

Through leveraging data from a large, outpatient, observational registry, we identified key factors to risk adjust sites' proportions of patients with preserved health status. These data lay the foundation for building quality measures that quantify treatment outcomes from patients' perspectives.

Keyphrases

machine learning
big data
end stage renal disease
electronic health record
deep learning
chronic kidney disease
ejection fraction
prognostic factors
peritoneal dialysis
heart failure
cross sectional