Automating Quality Measures for Heart Failure Using Natural Language Processing: A Descriptive Study in the Department of Veterans Affairs.

Jennifer Hornung Garvin Youngjun Kim Glenn Temple Gobbel Michael E Matheny Andrew Redd Bruce E Bray Paul A Heidenreich Dan Bolton Julia Heavirland Natalie Kelly Ruth Reeves Megha Kalsy Mary Kane Goldstein Stephane M Meystre

Published in: JMIR medical informatics (2018)

The CHIEF provided complete data for all patients in the cohort and could potentially improve the efficiency, timeliness, and utility of HF quality measurements.

Keyphrases

heart failure
end stage renal disease
ejection fraction
newly diagnosed
peritoneal dialysis
quality improvement
prognostic factors
acute heart failure
patient reported outcomes
machine learning