In DMW you can blind data in your study using different levels of blinding types (table, column, row, cell), and you can specify how the blinded data should be masked, e.g. using hardcoded ‘999999’ for numeric values, or ‘XXXXXX’ for character values. But more advanced blinding can also be accomplished, e.g. blinding of data using random date within FPFV and LPLV, random values from a codelist applied for field validation, e.g. simple Yes/No, or AE relation to trial product: LIKELY, UNLIKEY, POSSIBLE, PROBABLE.
You can use the Oracle database package DBMS_RANDOM and its function to generate a random value, e.g. random integer from 0..6, and then use the DECODE to set a value depending on the random value generated.
Example: Random value generated from codelist for Action taken to Trial Product in SDTM-AE (Adverse Events):
| Random value | Codelist Value assignment |
| 0 | DRUG INTERUPTED |
| 1 | DRUG WITHDRAWN |
| 2 | DOSE REDUCED |
| 3 | DOSE INCREASED |
| 4 | DOSE NOT CHANGED |
| 5 | UNKNOWN |
| 6 | N/A |
Note: For random date you will need to write a function to lookup and return a valid date from within FPFV to LPLV.
If you want to know more or need help to implement more advanced blinding solutions in Oracle DMW, please contact us.