Concept-value pair extraction from semi-structured clinical narrative: a case study using echocardiogram reports

The task of gathering detailed patient information from narrative text presents a significant barrier to clinical research. A prototype information extraction system was developed to identify concepts and their associated values from narrative echocardiogram reports. The system uses a Unified Medical Language System compatible architecture and takes advantage of canonical language use patterns to identify sentence templates with which concepts and their related values can be identified. The data extracted from this system will be used to enrich an existing database used by clinical researchers in a large university healthcare system to identify potential research candidates fulfilling clinical inclusion criteria. The system was developed and evaluated using ten clinical concepts. Concept-value pairs extracted by the system were compared with findings extracted manually by the author. The system was able to recall 78% [95%CI, 76-80%] of the relevant findings, with a precision of 99% [95%CI, 98-99%].