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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 when data are not in scope for a variable defined in the SDTM.

When applicable, the The overall process for extending a domain is as follows:

  1. Select variables for the domain from the SDTM. Selection Variables may only be selected from General ObSelection of variables must align with SDTM Usage Restrictions. As illustrated in the following figure, the The general approach for selecting adding variables for to a custom domain from the SDTM is to:
    1. Include applicable Identifier variables. Identifier variables STUDYID, USUBJID, DOMAIN, and --SEQ are required in all domains based on the general observation classes. Additional Identifiers may be added as needed.
    2. Include the Topic variable from the SDTM general observation class (e.g., --TESTCD for Findings). 
    3. Include applicable Include the relevant Qualifier variables from the identified SDTM general observation classGeneral Observation Class.
    4. Include the applicable SDTM Timing variables. In general, the domain must have at least one timing variable.Determine the two-character domain code.The domain code add domain naming rules here
    5. Apply the domain code to the appropriate variables in the domain by replacing all variable prefixes (shown in the SDTM as “--“) with the domain code.
    6. Set the order of variables consistent with the order defined in the SDTM for the general observation class.
    7. Adjust the labels of the variables only as appropriate to convey their meaning in the context of the data in the newly created domain. Use title case for all labels.
    8. Ensure that appropriate standard variables are being properly applied by comparing their use in the custom domain to their use in related TIG domains.

  2. Place any non-SDTM variables in a Supplemental Qualifier dataset. 

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