Using a statistical natural language Parser augmented with the UMLS specialist lexicon to assign SNOMED CT codes to anatomic sites and pathologic diagnoses in full text pathology reports.
To address the problem of extracting structured information from pathology reports for research purposes in the STRIDE Clinical Data Warehouse, we adapted the ChartIndex Medical Language Processing system to automatically identify and map anatomic and diagnostic noun phrases found in full-text pathology reports to SNOMED CT concept descriptors. An evaluation of the system's performance showed a positive predictive value for anatomic concepts of 92.3% and positive predictive value for diagnostic concepts of 84.4%. The experiment also suggested strategies for improving ChartIndex's performance coding pathology reports.
Lowe
Henry J
HJ
Center for Clinical Informatics, Stanford University, Stanford, CA, USA.
Huang
Yang
Y
Regula
Donald P
DP
D059019:Clinical Coding / Q000379:methods*; D057286:Electronic Health Records / Q000145:classification*; D006801:Humans; D009323:Natural Language Processing; D010340:Pathology, Surgical; D039061:Systematized Nomenclature of Medicine; D017432:Unified Medical Language System