A key aspect of the UMLS CORE (Clinical Observations Recordings and Encoding) Project is the collation and analysis of datasets collected from health care institutions that utilize controlled vocabularies for data entry. These datasets contain the list of controlled terms and their actual frequency of usage in clinical databases. The original subset was based on datasets submitted by 7 institutions – Beth Israel Deaconess Medical Center, Intermountain Healthcare, Kaiser Permanente, Mayo Clinic, Nebraska University Medical Center, Regenstrief Institute and Hong Kong Hospital Authority. These institutions are large-scale, mixed inpatient-outpatient facilities that cover most major medical specialties (including Internal Medicine, General Surgery, Pediatrics, Obstetrics, Gynecology, Psychiatry and Orthopedics). From the 2012-08 version onwards, problem list data from the Veterans Administration have also been incorporated. The most frequently used 16,874 terms that cover 95% of usage volume in each institution are mapped to UMLS concepts using lexical matching supplemented by manual review.
Through the UMLS, mappings from the local terms to SNOMED CT concepts are identified. This constitutes the CORE Problem List Subset of SNOMED CT. Unmapped local terms that are considered useful for the problem list are submitted to the International Health Terminology Standards Development Organisation (IHTSDO). If accepted, the new SNOMED CT concepts are added to the CORE Subset. As SNOMED CT is the designated U.S. standard terminology for diagnosis and problem lists, and one of the requirements of the ‘Meaningful Use’ criteria of the Electronic Health Record, we believe that identifying a frequently used subset of SNOMED CT concepts will be useful to users who want to implement SNOMED CT in their clinical systems.
PURPOSE AND USE OF SUBSET: The main purpose of the SNOMED CT CORE subset is to facilitate the use of SNOMED CT as the primary coding terminology for problem lists or other summary level clinical documentation. The use of a common list of SNOMED CT concepts will maximize data interoperability among institutions.