Evaluating the effectiveness of four contextual features in classifying annotated clinical conditions in emergency department reports.

TitleEvaluating the effectiveness of four contextual features in classifying annotated clinical conditions in emergency department reports.
Publication TypeJournal Article
Year of Publication2006
AuthorsChu, D, Dowling, JN, Chapman, WW
JournalAMIA Annu Symp Proc
Pagination141-5
Date Published2006
ISSN1942-597X
KeywordsAcute Disease, Algorithms, Chronic Disease, Emergency Service, Hospital, Forms and Records Control, Humans, Medical Records, Natural Language Processing, Pilot Projects, Respiratory Tract Diseases
Abstract

OBJECTIVE: Determine how four contextual features (Validity, Certainty, Directionality, and Temporality) contribute to classification of respiratory syndrome-related clinical conditions as acute, chronic, or absent from manual annotations in Emergency Department Reports. Based on the results, we will direct our research towards automatic identification of the contextual features found to be discriminating.METHODS: A physician annotated all instances of 56 clinical conditions in 120 ED reports and encoded four contextual features for every annotation. We classified clinical conditions using the contextual features and measured agreement to reference standard classifications made by the physician using a weighted kappa (Kw).RESULTS: Kw was 0.518 when not using any of the features and 0.953 when using all of the features.CONCLUSION: Validity, Directionality, and Temporality all improved accuracy. Negation(Directionality) was the most important feature for improving accuracy. Using Certainty made the classification worse.

Alternate JournalAMIA Annu Symp Proc
PubMed ID17238319
PubMed Central IDPMC1839393
Grant ListK22 LM008301 / LM / NLM NIH HHS / United States