Extraction of left ventricular ejection fraction information from various types of clinical reports.
Efforts to improve the treatment of congestive heart failure, a common and serious medical condition, include the use of quality measures to assess guideline-concordant care. The goal of this study is to identify left ventricular ejection fraction (LVEF) information from various types of clinical notes, and to then use this information for heart failure quality measurement. We analyzed the annotation differences between a new corpus of clinical notes from the Echocardiography, Radiology, and Text Integrated Utility package and other corpora annotated for natural language processing (NLP) research in the Department of Veterans Affairs. These reports contain varying degrees of structure. To examine whether existing LVEF extraction modules we developed in prior research improve the accuracy of LVEF information extraction from the new corpus, we created two sequence-tagging NLP modules trained with a new data set, with or without predictions from the existing LVEF extraction modules. We also conducted a set of experiments to examine the impact of training data size on information extraction accuracy. We found that less training data is needed when reports are highly structured, and that combining predictions from existing LVEF extraction modules improves information extraction when reports have less structured formats and a rich set of vocabulary.
School of Computing, University of Utah, Salt Lake City, UT, USA; VA Health Care System, Salt Lake City, UT, USA. Electronic address: youngjun@cs.utah.edu.
Youngjun
Y
Kim
VA Health Care System, Salt Lake City, UT, USA; Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
Jennifer H
JH
Garvin
VA Palo Alto Health Care System, Palo Alto, CA, USA; Stanford University, Stanford, CA, USA.
Mary K
MK
Goldstein
VA Palo Alto Health Care System, Palo Alto, CA, USA.
Tammy S
TS
Hwang
VA Health Care System, Salt Lake City, UT, USA; Division of Epidemiology, University of Utah, Salt Lake City, UT, USA.
Andrew
A
Redd
VA Health Care System, Salt Lake City, UT, USA; Division of Epidemiology, University of Utah, Salt Lake City, UT, USA.
Dan
D
Bolton
VA Palo Alto Health Care System, Palo Alto, CA, USA; Stanford University, Stanford, CA, USA.
Paul A
PA
Heidenreich
Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA; Medical University of South Carolina, Charleston, SC, USA.
Stéphane M
SM
Meystre
D006333:Heart Failure / Q000175:diagnosis* / Q000628:therapy; D006801:Humans; D016247:Information Storage and Retrieval; D009323:Natural Language Processing; D013318:Stroke Volume
Heart failure; Medical informatics; Natural language processing; Ventricular ejection fraction