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Natural language processing and the representation of clinical data
1Courant Institute of Mathematical Sciences, New York University, NY 10012, USA.
Objective:
Develop a representation of clinical observations and actions and a method of processing free-text patient documents to facilitate applications such as quality assurance.
Design:
The Linguistic String Project (LSP) system of New York University utilizes syntactic analysis, augmented by a sublanguage grammar and an information structure that are specific to the clinical narrative, to map free-text documents into a database for querying.
Measurements:
Information precision (I-P) and information recall (I-R) were measured for queries for the presence of 13 asthma-health-care quality assurance criteria in a database generated from 59 discharge letters.
Results:
I-P, using counts of major errors only, was 95.7% for the 28-letter training set and 98.6% for the 31-letter test set. I-R, using counts of major omissions only, was 93.9% for the training set and 92.5% for the test set.