Natural language processing and the representation of clinical data.
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.


METHODS
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.


METHODS
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.
Sager
N
N
Courant Institute of Mathematical Sciences, New York University, NY 10012, USA.
Lyman
M
M
Bucknall
C
C
Nhan
N
N
Tick
L J
LJ
D003936:Diagnosis, Computer-Assisted; D006801:Humans; D008037:Linguistics; D008490:Medical Informatics; D008499:Medical Records; D009323:Natural Language Processing; D011786:Quality Control; D017432:Unified Medical Language System; D014825:Vocabulary