ORIGINAL ARTICLEEvaluation of the Content Coverage of SNOMED CT: Ability of SNOMED Clinical Terms to Represent Clinical Problem Lists
Section snippets
Problem Set
Mayo Clinic has a long history of manual record-keeping. The terms used in the problem set for this study were from the Mayo Master Sheet Index (MSI). The MSI documents the diagnoses associated with clinical episodes of care (both outpatient and inpatient),31 which, at Mayo Clinic, are defined as ending when the ongoing care of a patient is changing minimally. Often this is after the diagnoses have been established or after the major interventions have been completed. At this time, the
RESULTS
SNOMED CT was judged as to how well 2 expert reviewers could use it to represent the content contained in 4996 problem statements. SNOMED CT correctly represented 4568 terms (true-positive [TP] results) (Figure 2, A). Thirty-six terms were not believed to be sensible expressions or were misspelled and were not matched by SNOMED CT (true-negative [TN] results), 9 were believed not to be sensible but were matched by SNOMED CT (FP results), and 383 terms were believed to be sensible but were not
DISCUSSION
Clinically meaningful interoperable data require codification with a robust reference terminology and methods for supporting composition. Compositional expressions are organizations of concepts connected using relationships (eg, “pneumonia” “has etiology” “Streptococcus pneumoniae”). Problem list data are an important type of data that require a robust general medical reference terminology.
In the current study, we showed that SNOMED CT performed well, representing 92.3% of common clinical
CONCLUSION
Our study shows that SNOMED CT, when used as a compositional terminology, can exactly represent a large portion (92.3%) of the terms used commonly in medical problem lists. Improvements to synonymy and the addition of missing modifiers would lead to greater coverage of common problem statements. The use of composition significantly improved the ability of SNOMED CT to exactly represent terms from the MSI problem list (51.4% vs 92.3%; P<.001). Health care organizations should be encouraged and
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This work was supported in part by grant LM06918-A2 from the National Library of Medicine and by a Mayo Clinic Department of Internal Medicine MIDAS Award.