Informatics tools to implement late cardiovascular risk prediction modeling for population management of high-risk childhood cancer survivors.

David H NoydSixia ChenAnna M BaileyAmanda E JanitzAshley A BakerWilliam Howard BeasleyNancy C EtzoldDavid C KendrickWarren A KibbeKevin C Oeffinger

Published in: Pediatric blood & cancer (2023)

Clinical informatics tools represent a feasible approach to leverage discrete treatment-related data elements from PFC or the EHR to successfully implement previously validated late cardiovascular risk prediction models on a population health level. Concordance of CCSS, COG, and IGHG risk groups using real-world data informs current guidelines and identifies inequities in guideline-adherent care.

Keyphrases

electronic health record
big data
healthcare
palliative care
childhood cancer
machine learning
quality improvement
data analysis
gene expression
combination therapy
artificial intelligence
drug induced
deep learning