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Gary: I think this language is awkward, but I am unclear as to how it should be updated.

If a logically related grouping of data is in scope for a domain defined in this guide, but not all data can be represented using the domain variables, then data may be represented by adding variables from the SDTM to the domain or by using a Supplemental Qualifier dataset related to the domain. Prior to adding variables from the SDTM or considering a Supplemental Qualifier dataset, confirm that none of the existing domain variables will fit the need. Variables may be added to a domain and Supplemental Qualifier datasets may only used when data are different in nature and are not in scope for variables which already exist in the domain.  

Once confirmed, determine whether adding a variable from the SDTM will fit the need. If adding a variable from the SDTM meets the need, then a Supplemental Qualifier dataset will not be implemented. Supplemental Qualifier datasets will only be implemented for domains when data are not in scope for a variable defined in the SDTM.

The overall process for extending a domain is as follows:

  1. Select variables for the domain from the SDTM. Selection of variables must align with SDTM Usage Restrictions. The general approach for adding variables to a domain from the SDTM is to:
    1. Include applicable Identifier variables.
    2. Include applicable Qualifier variables in alignment with the SDTM General Observation Classes.
    3. Include applicable Timing variables.
    4. Apply the domain code to the variables as appropriate by replacing all variable prefixes (shown in the SDTM as “--“) with the domain code.
    5. Set the order of variables consistent with the order defined in the SDTM.
    6. Adjust the labels of the variables only as appropriate to convey their meaning in the context of the data in domain. Use title case for all labels.

    7. Ensure that appropriate standard variables are being properly applied by comparing their use in the domain to their use in related TIG domains.

  2. Place any non-SDTM variables in a Supplemental Qualifier dataset when variables cannot be selected from the SDTM. 

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