You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
In some datasets the drug exposure table is very 'dirty', with drug_concept_id's from other domains. This can give a long list of different classes in the Drug Mapping Level table (section 4.4, table 6), making hard to interpret. See example below.
I propose to filter the mapping level query by the drug domain (domain_id = 'Drug'). The only caveat is that this hides that there are concepts from other domains. Although it is the purpose of the DataQualityDashboard to flag those quality issues.
The text was updated successfully, but these errors were encountered:
In some datasets the drug exposure table is very 'dirty', with
drug_concept_id
's from other domains. This can give a long list of different classes in the Drug Mapping Level table (section 4.4, table 6), making hard to interpret. See example below.I propose to filter the mapping level query by the drug domain (
domain_id = 'Drug'
). The only caveat is that this hides that there are concepts from other domains. Although it is the purpose of the DataQualityDashboard to flag those quality issues.The text was updated successfully, but these errors were encountered: