Identifying Terms of Interest in Radiology Reports
Synopsis
This query finds all terms labelled as disease, findings, and morphologic abnormality SNOMED entity types in the IMPRESSION section of Radiology reports. Entity type searches are less specific than concept search but are useful for finding entities for further analysis and filtering.
Processing Requirements
This query assumes that at least the following emtellipro-db-client processing options were enabled:
--feature snomed-ontology--store-sections-and-sentences
For this query, Radiology imaging studies were processed with the following document type:
--category Radiology--subcategory CT
Clinical Context
Medical ontologies like SNOMED classify their concepts into semantic types such as disorder, morphologic abnormality, findings, substance, procedure, etc. The NLP API reports this information separately from the concept itself as the entity_type field in its output, which allows users to filter for concepts based on this information retrospectively.
A common data science or clinical application scenario is one where a clinician wants to know, very generically, what medical problems a patient has had in their past. One simple way is to just search an Output Database for any concepts that are asserted, which have a SNOMED semantic type of disorder, morphologic abnormality, or finding. While this is a somewhat broad definition of medical problems (as many findings may be benign), it can be used with high-recall to identify almost any medical issue of concern that NLP API has coded with SNOMED CT. The results return can be reduced by searching for disorder only, or disorder and morphologic abnormality if higher precision is required.
SQL query
SQL
Microsoft SQL Server
Snowflake
Next steps
To refine the query, one practical strategy that may be explored is to limit the search to specific report sections only. The section of the report where a diseased is mentioned typically provides important context that alters the interpretation and significance of the disease mention.
The NLP API normalizes a large set of recognized section headings into standardized section names. To see a list of normalized section names present in your data, you can use the provided here. Select one or more section names to use as a query constraint.
To search for these entity types in a specific section, simply relace the fe.section_name WHERE clause with appropriate section name.

