In the LOINC distribution csv file, the column "status" can indicate a number of concept states:
ACTIVE
TRIAL
DISCOURAGED
DEPRECATED
For example, has a status of 'DISCOURAGED'.
The equivalent property in SNOMED CT concepts, is the "active" flag, but this can only take a 1 or 0 value, which maps to the ACTIVE and DEPRECATED LOINC statuses respectively.
TRAIL concepts are considered available for use, and so this status is not expressed in the SNOMED CT transformation of LOINC concepts.
DISCOURAGED, however, is represented using an Annotation (starting from Release 2.0 Effective Time 20250921). These are expressed in the ComponentAnnotation file eg der2_scsRefset_ComponentAnnotationStringValueSnapshot_LO1010000_20250921.txt with the column for referencedComponentId set to the SCTID of the relevant concept, and the annotation text "Discouraged" in the value column.
In the LOINC SNOMED Browser, this annotation is represented on the "details" tab:

The LOINC release specifies whether each LOINC concept is Orderable, Observable, or Both in the ORDER_OBS column of the Loinc.csv file. This classification helps healthcare systems determine which concepts can be used for test orders versus those that are strictly for observations. In the LOINC Ontology, this information is provided in two simple type reference sets.
In SNOMED CT, subsets are represented using simple reference sets (Refsets), allowing implementers to filter and retrieve LOINC terms based on their orderability or observability. This structured approach facilitates the integration of LOINC terminology within SNOMED CT implementations.
For example, implementers can query:
“Show all LOINC concepts that are Orderable.”
“Show all LOINC concepts that are Observable.”
To support this, the LOINC Ontology includes two distinct reference sets:
635121010000106 | LOINC Observation Reference Set | – Contains LOINC terms classified as Observable.
635111010000100 | LOINC Orderable Reference Set |– Contains LOINC terms classified as Orderable.
The reference sets are distributed in a file named according to SNOMED CT conventions: der2_Refset_SimpleRefsetSnapshot_INT_20250321.txt
Each row in this file corresponds to a LOINC term and includes a refsetId that determines whether the term belongs to the Orderable or Observable subset.
Some LOINC terms are classified as both Orderable and Observable. In such cases, the term will appear in both reference sets, ensuring that it is available in queries for either category.
LOINC Observation Reference Set (first 4 rows)
LOINC Orderable Reference Set (first 4 rows)
The counts for the Observation and Orderable Reference Sets can be seen in the browser, in the left-hand panel, and clicking on the "Refset" tab:
Clicking on either of these concepts will bring them up in the right-hand panel:
Note that the concept that represents the reference set does not have any children (these would be different, more specialised reference sets if they existed), but the reference set does have members. These can be listed by clicking on the members tab:
Now we can also obtain this list, or even something more interesting, by going into the "Expression Constraint Queries" tab. For this example, we're going to look for the intersection of these two sets. That is, the LOINC concepts which are BOTH orderable AND observables. The ECL for this query is: ^ AND ^
Note that the counts here refer purely to those LOINC concepts that successfully translated into The LOINC Ontology at time of publication. The full LOINC release in it's original format contains additional codes for each.
226581010000109
faf3eff6-5c15-4b9d-ae72-953d06a80391
20250321
1
11010000107
635121010000106
189881010000107
781fbd14-8883-456a-a324-3d56584edf8e
20250321
1
11010000107
635121010000106
179681010000102
8286c793-0c9b-434e-a4c4-f3ca1d79d67a
20250321
1
11010000107
635121010000106
200271010000103
189881010000107
ccabfb4b-2353-4a8e-bdd7-2e75d9759e62
20250321
1
11010000107
635111010000100
200271010000103
699290e8-15bc-4895-ad9b-fda371465526
20250321
1
11010000107
635111010000100
617571010000101
33a2cb27-47fa-4751-9f6e-8e580cba17f5
20250321
1
11010000107
635111010000100
189931010000103
16864455-3679-4543-a360-1f0b5f5dca1d
20250321
1
11010000107
565a60d6-7ee2-4699-a62a-3b1228761693
20250321
1
11010000107
635121010000106
635111010000100
LOINC Concepts feature a number of logical properties - beyond their text descriptions and parts - that required some creative way to surface in a SNOMED CT format.
Two examples of these are the ORD/OBS flag (which indicates if a LOINC Term should be used in the context of an Order, and Observation, or Both), and a status of "Discouraged" which indicates that a LOINC Term is still active, but its use should be avoided.
Both of these flags exist as columns in the published LOINC distribution csv file and the method for exposing them in a SNOMED CT format is described in the following pages.
LOINC groupers are included in the LOINC Ontology to allow more general test ordering, and also to support navigation and querying by enabling identification of related tests that share the same property, system, and component.
Grouper concepts are modeled using a subset of defining attributes, typically Property, System, and Component. Attributes such as time and scale are intentionally not included. This approach ensures that more specific observables, which differ by time (for example, point in time or 24 hours) or scale (for example, quantitative or ordinal), are subsumed under a common parent concept.
The concept 711861010000108 | Measurement of calcium in urine (observable entity) |
is defined using the following three attribute-value pairs:
370130000 |Property (attribute)| = 685451010000100 |Measurement property (qualifier value)|
704327008 |Direct site (attribute)| = 122575003 |Urine specimen (specimen)|
246093002 |Component (attribute)| = 5540006 |Calcium (substance)|
The concept does not contain the time or scale attribute. As a result, all observables representing measurements of calcium in urine are classified under this concept, regardless of differences in timing or scale.
As shown in the image above, this modeling allows all the specific tests of urine calcium levels to be subsumed by this concept.
