The use of SNOMED CT simplifies querying of a clinical data warehouse.
The usefulness of digital clinical information is limited by difficulty in accessing that information. Information in electronic medical records (EMR) must be entered and stored at the appropriate level of granularity for individual patient care. However, benefits such as outcomes research and decision support require aggregation to clinical data -- "heart disease" as opposed to "S/P MI 1997" for example. The hierarchical relationships in an external reference terminology, such as SNOMED, can facilitate aggregation. This study examines whether by leveraging the knowledge built into SNOMED's hierarchical structure, one can simplify the query process without degrading the query results.
Lieberman
Michael I
MI
Oregon Health & Sciences University, Portland, OR, USA.
Ricciardi
Thomas N
TN
Masarie
F E
FE
Spackman
Kent A
KA
D002318:Cardiovascular Diseases / Q000145:classification; D006801:Humans; D016247:Information Storage and Retrieval; D016347:Medical Records Systems, Computerized / Q000145:classification*; D039061:Systematized Nomenclature of Medicine