Use Case:
While investigating an Atlas study which returned very few Persons, I found the Units for the specified Measurements in the inclusion criteria did not align with the Units for those Measurements in our source data. Upon further inspection of the source data, I found a Measurement could have 11 different unit_concept_ids. The Units for the Measurements of interest in Altas aligned with LOINC’s example Units for Measurements, as Dmytry links in this thread, however, real world data doesn’t always align with the suggestions.
Background:
@Vojtech_Huser completed a network study, Facilitating analysis of measurements data though stricter model conventions: Exploring units variability across sites, on the most frequent Unit used for a Measurement. He has created a csv of the results for the preferred single units for 375 tests He presented his work to Themis and it was ratified a couple years ago.
Open issues:
- How do we implement the “preferred” unit? Per Dima, “we need to create relationships from Measurement to preferred unit in concept_relationship table”.
- The original numeric result & unit_source_concept_id aren’t represented (numeric_source_value and unit_source_value) in the Measurement table. See Vojtech’s github issue found here.
Recommendations:
Standardize the Unit for the top 375 Measurements identified in Vjotech’s study. Then as use cases arise, the community can submit issues to Github to include additional Measurements for Unit standardization.
- Create relationships to preferred concepts in the Concept Relationship table.
- Create a solution to store the original numeric results and units in the Measurement table.
- Provide ETL guidance, on how to implement the value_as_number transformation for a unit_source_concept_id to the standardized unit_concept_id.
a. Community sourced conversion math? Researchers currently have to convert numeric results into a standard to run studies. We should glean this information from available resources. - Create DQD checks on the above.
Tagging: @Christian_Reich, @mik, @Alexdavv, @gregk