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

Jennifer Hornung GarvinYoungjun KimGlenn Temple GobbelMichael E MathenyAndrew ReddBruce E BrayPaul A HeidenreichDan BoltonJulia HeavirlandNatalie KellyRuth ReevesMegha KalsyMary Kane GoldsteinStephane 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