Identification of Patients with Heart Failure in Large Datasets.
Heart Fail Clin
; 16(4): 379-386, 2020 Oct.
Article
em En
| MEDLINE
| ID: mdl-32888634
ABSTRACT
Large registries, administrative data, and the electronic health record (EHR) offer opportunities to identify patients with heart failure, which can be used for research purposes, process improvement, and optimal care delivery. Identification of cases is challenging because of the heterogeneous nature of the disease, which encompasses various phenotypes that may respond differently to treatment. The increasing availability of both structured and unstructured data in the EHR has expanded opportunities for cohort construction. This article reviews the current literature on approaches to identification of heart failure, and looks toward the future of machine learning, big data, and phenomapping.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Sistema de Registros
/
Registros Eletrônicos de Saúde
/
Aprendizado de Máquina
/
Insuficiência Cardíaca
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Heart Fail Clin
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Estados Unidos