Natural language processing challenges in HIV/AIDS clinic notes.
In recent years, significant progress has been achieved toward increased structured data entry using standardized health care terminologies. Concurrently, the value of narrative as the clinician's rich description of the encounter and source of vital information has been reaffirmed. Natural language processing (NLP) offers a strategy for integrating these approaches to provide structured reports for further computer processing. As part of a larger project aimed at using narrative data to enrich the online medical record, we analyzed a small sample of documents in a corpus of progress notes to identify potential challenges associated with using NLP for HIV/AIDS clinic notes. We provide illustrative examples of five types of challenges.
Hyun
Sookyung
S
School of Nursing, Columbia University, New York, NY, USA.
Bakken
Suzanne
S
Friedman
Carol
C
Johnson
Stephen B
SB
D000163:Acquired Immunodeficiency Syndrome; D015658:HIV Infections; D006801:Humans; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D018875:Vocabulary, Controlled