Imagine two organisations storing similar documents in filing cabinets.
The first cabinet has many carefully labelled drawers, each for a very specific category. The second uses fewer, broader drawers and organises the same information in a different way.
Both systems work. But their drawers do not automatically correspond.
One drawer may match another exactly. One may cover only part of a broader category. Several drawers in the first cabinet may lead to a single drawer in the second. And sometimes there is no reliable destination at all.
A ConceptMap describes those relationships.
In healthcare, one hospital may use local laboratory codes while another uses LOINC. A clinical system may record a detailed SNOMED CT concept, while a reporting process requires an ICD classification. The information may refer to the same underlying reality, but the concepts are not automatically interchangeable.
A ConceptMap makes explicit how concepts from different systems relate. It can indicate that one concept is equivalent to another, broader, narrower, related in a particular way or impossible to map reliably.
That last part matters.
A ConceptMap should not force two concepts to appear identical simply because a connection is needed. Its purpose is to describe the relationship honestly, including the conditions, limitations and reasoning behind it.
Because one concept may relate to several possible targets. A detailed clinical concept may lose specificity when connected to a classification. A local term may contain contextual knowledge that was never made explicit in the code itself.
The drawers can be connected.
That does not mean they contain exactly the same meaning.
Perhaps the quality of a mapping is not determined by how confidently it produces a relationship, but by how honestly it represents the difference.
Connecting codes is one thing.
Connecting meaning is another.
Next week: Expansion
A ValueSet defines the rule. Expansion makes it usable.
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