Inductive creation of an annotation schema for manually indexing clinical conditions from emergency department reports.
Evaluating automated indexing applications requires comparing automatically indexed terms against manual reference standard annotations. However, there are no standard guidelines for determining which words from a textual document to include in manual annotations, and the vague task can result in substantial variation among manual indexers. We applied grounded theory to emergency department reports to create an annotation schema representing syntactic and semantic variables that could be annotated when indexing clinical conditions. We describe the annotation schema, which includes variables representing medical concepts (e.g., symptom, demographics), linguistic form (e.g., noun, adjective), and modifier types (e.g., anatomic location, severity). We measured the schema's quality and found: (1) the schema was comprehensive enough to be applied to 20 unseen reports without changes to the schema; (2) agreement between author annotators applying the schema was high, with an F measure of 93%; and (3) the authors made complementary errors when applying the schema, demonstrating that the schema incorporates both linguistic and medical expertise.
Chapman
Wendy W
WW
Center for Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA. chapman@cbmi.pitt.edu
Dowling
John N
JN
D000043:Abstracting and Indexing / Q000379:methods*; D001185:Artificial Intelligence; D004282:Documentation / Q000379:methods*; D004636:Emergency Service, Hospital; D016247:Information Storage and Retrieval / Q000379:methods*; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing