Objective: This research investigated the use of SNOMED CT to represent diagnostic tissue morphologies and notable tissue architectures typically found within a pathologist's microscopic examination report to identify gaps in expressivity of SNOMED CT for use in anatomic pathology. Methods: 24 breast biopsy cases were reviewed by two board certified surgical pathologists who independently described the diagnostically important tissue architectures and diagnostic morphologies observed by microscopic examination. In addition, diagnostic comments and details were extracted from the original diagnostic pathology report. 95 unique clinical statements were extracted from 13 malignant and 11 benign breast needle biopsy cases. Results: 75% of the inventoried diagnostic terms and statements could be represented by valid SNOMED CT expressions. The expressions included one precoordinated expression and 73 post-coordinated expressions. No valid SNOMED CT expressions could be identified or developed to unambiguously assert the meaning of 21 statements (ie, 25% of inventoried clinical statements). Evaluation of the findings indicated that SNOMED CT lacked sufficient definitional expressions or the SNOMED CT concept model prohibited use of certain defined concepts needed to describe the numerous, diagnostically important tissue architectures and morphologic changes found within a surgical pathology microscopic examination. Conclusions: Because information gathered during microscopic histopathology examination provides the basis of pathology diagnoses, additional concept definitions for tissue morphometries and modifications to the SNOMED CT concept model are needed and suggested to represent detailed histopathologic findings in computable fashion for purposes of patient information exchange and research. Trial registration number UNMC Institutional Review Board ID# 342-11-EP.
|Original language||English (US)|
|Number of pages||8|
|Journal||Journal of the American Medical Informatics Association|
|State||Published - 2014|
ASJC Scopus subject areas
- Health Informatics