Automatic generation of repeated patient information for tailoring clinical notes.
Generating clear, readable, and accurate reports can be a time-consuming task for physicians. Clinical notes, which document patient encounters, often contain a certain set of patient information including demographics, medical history, surgical history, examination results or the current medical condition that is propagated from one clinical note to all subsequent clinical notes for the same patient. To this end, we present a system, which automatically generates this patient information for the creation of a new clinical note. We use semantic patterns and an approximate sequence matching algorithm for capturing the discourse role of sentences, which we show to be a useful feature for determining whether the sentence should be repeated. Our system is shown to perform better than a simple baseline metric using precision/recall results. We believe such a system would allow clinical notes to be more complete, timely, and accurate.
Meng
Frank
F
Medical Informatics Group, University of California, Los Angeles, 924 Westwood Blvd., Suite 420, Los Angeles, CA 90024, USA. fmeng@mii.ucla.edu
Taira
Ricky K
RK
Bui
Alex A T
AA
Kangarloo
Hooshang
H
Churchill
Bernard M
BM
D004282:Documentation; D006801:Humans; D016347:Medical Records Systems, Computerized / Q000458:organization & administration*; D009323:Natural Language Processing; D012660:Semantics; D014481:United States