Abstract
AbstractSNOMED CT is a clinical terminology that describes the meaning of terms by logical axioms. This requires an ontological commitment, i.e. precise agreements about the ontological nature of the entities referred to. We provide evidence that SNOMED implicitly supports at least three different kinds of commitments, viz. (i) independently existing entities, (ii) representational artifacts, and (iii) clinical situations. Our analysis shows how the truth-value of a sentence changes according to one of these perspectives. We argue that a clear understanding of to what kind of entities SNOMED CT concepts extend is crucial for the proper use and maintenance of SNOMED CT.
Highlights
SNOMED CT1 is the inheritor of a dynasty of medical nomenclatures and coding systems[2] which had been constructed to provide 1. semantic descriptors to annotate and encode clinical procedures, diagnoses, etc.; 2. standardized medical terms in different languages; 3. guidance for the construction of composed terminological expressions
As long there is no agreement on which SNOMED CT concepts extend to objects in clinical reality, to patients, to situations, or to documentation objects, different users may want to express different things by using the same expressions, and misinterpretations may lead to erroneous conclusions
SNOMED CT provides the means to represent situative scenarios that include negative contexts and other contextual “moods”. This extends the boundary of what a clinical terminology should represent and overlaps with the realm of information models
Summary
SNOMED CT1 is the inheritor of a dynasty of medical nomenclatures and coding systems[2] which had been constructed to provide 1. semantic descriptors to annotate and encode clinical procedures, diagnoses, etc.; 2. standardized medical terms in different languages; 3. guidance for the construction of composed terminological expressions. The meaning of semantic descriptors was given by the intuitive understanding of the terms they were linked to and it was assumed that they were correctly interpreted by the (human) language users in the communication process. None of these systems made any attempt to formally represent any reality beyond a rough mapping of controlled terms to shared concepts with the aim to reduce the high variability of human language through a set of controlled terms or to support the encoding of medical data by means of a coded thesaurus of procedural and administrative terms for the electronic health record. We will discuss the pros and cons of the inferences they enable and discuss them in the light of competing ontological commitments
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