Working with Supplemental Qualifiers

a supplemental qualifier (sq) dataset can be used to add variables that are not available in an sdtm standard for example, if you want to add new variables to a standardised sdtm dataset a supplemental qualifier dataset provides the flexibility to store additional information on a subject or event each domain that has non sdtm standard variables needs a supplemental qualifier dataset so, if there are 10 datasets that contain non sdtm standard variables, 10 supplemental qualifier datasets would be created creating sq datasets can be challenging and time consuming the published sdtm ig standard contains the suppqual dataset this can be used as a starting point for building sqs you can clone and edit assets in the imported sq dataset to build your required variables see the video example below example best practice tips import the supplemental qualifier dataset the published sdtm standard contains a sq dataset that can be used as a starting point use naming conventions, for example ae + suppae this creates a link for these datasets in mapping configuration as well as displays a navigation link to the user the name of the supplemental qualifier dataset indicates the parent domain it is linked to for example the supplemental qualifier domain linked to adverse events is 'suppae' for more information, see docid 2uxs86nvf7mod4pfna3qu add the sq dataset you can import the sq dataset from one of the published standards once the sq dataset is imported, create a new sq dataset by docid\ z xijkcwtkkyl69ptnfpa (independent) independent cloning means that the new dataset does not have links to the parent sdtm sq dataset and allows you to create independent variables adding variables when you clone a dataset, referenced assets such as variables still retain their link to the parent dataset you must clone and replace each referenced asset independently clone and replace the variables and other assets within the sq dataset using the independent cloning option this means that variables have a one to one relationship with the new sq dataset and don't have links to another dataset for each cloned variable, edit identifiers to match the parent sq dataset for example, for a suppae dataset name usubjid identifier suppae usubjid adding values supplemental data is added using q variables, these variables are included in published sdtm ig sq dataset qnam qlabel qval qorig qeval create a value values are created manually to create a value, expand the variable view and click create value add selection criteria you can then add where clauses (selection criteria)