Automated classification of encounter notes in a computer based medical record.
Harvard Community Health Plan is exploring emerging information technologies for means to use the text portion of its 25 year old computerized medical record system. The Center for Intelligent Information Retrieval is developing systems to answer the question: to what extent can automated information systems replace manual chart review of encounter notes? INQUERY, a probabilistic inference net information retrieval system, and FIGLEAF, an inductive decision tree text classifier are applied to the problem of classifying electronic encounter notes to identify acute exacerbations in pediatric asthmatics. Both systems achieve average precisions of greater than 80%, with a new enhancement to INQUERY's relevance feedback, the top performer. Refinement of the systems and plans for their integration are discussed.
Aronow
D B
DB
Center for Intelligent Information Retrieval, Lederle Graduate Research Center, University of Massachusetts, Amherst MA 01003 USA.
Soderland
S
S
Ponte
J M
JM
Feng
F
F
Croft
W B
WB
Lehnert
W G
WG
D001249:Asthma; D002648:Child; D006801:Humans; D008487:Medical History Taking; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing