This topic is under construction for the 17.3 release of LabKey Server. For current documentation of this feature, click here.
a study, you can randomize or hide specified protected health information (PHI) in the data, to make it more difficult to identify the persons enrolled in the study. You can alter published data in the following ways:
- Replace all participant IDs with alternate, randomly generated participant IDs.
- Apply random date shifts/offsets.
- Exclude columns marked as containing various levels of PHI (protected health information) from being copied to the published study.
- Mask clinic names with a generic name to hide any identifying features in the original clinic name.
The wizard used to publish a study
includes these options:
Use Alternate Participant IDs
Selecting this option replaces the participant IDs throughout the published data with alternate, randomly generated ids. The alternate id used for each participant is persisted in the source study and reused for each new published study. Admins can set the prefix and number of digits used in this alternate id if desired. See Alternate Participant IDs
Shift Participant Dates
Selecting this option will shift published dates for associated participants by a random offset between 1 and 365 days. A separate offset is generated for each participant and that offset is used for all dates associated with that participant, unless they are excluded as described below
. This obscures the exact dates, protecting potentially identifying details, but maintains the relative differences between them. Note that the date offset used for a given participant is persisted in the source study and reused for each new published study.
individual date/time columns from being randomly shifted on publication:
- Go to the dataset that includes the date column.
- Edit the dataset definition.
- In the designer, select the date column, then the Advanced tab.
- Check the box to Exclude From Shifting.
- Click Save.
Remove PHI Protected Columns
Select this option to exclude columns that are tagged
at the same PHI level or higher. After you select Remove PHI Protected Columns
, specify a specific PHI level to exclude, as shown in the screenshot below.
For example, if the study is published with the option "Full PHI", then any column tagged
at "Full PHI" or "Restricted" will be removed (i.e., excluded) from the published version of the study. The following table shows the results of each combination of column tagging and publishing options:
|Remove PHI Protected Columns...||...Not Selected||...Limited PHI||...Full PHI||...Restricted|
|Column is tagged as Not PHI||Published||Published||Published||Published|
|Column is tagged as Limited PHI||Published||Not Published||Published||Published|
|Column is tagged as Full PHI||Published||Not Published||Not Published||Published|
|Column is tagged as Restricted||Published||Not Published||Not Published||Not Published|
To tag a column at a specific PHI level, see Field Properties Reference
Mask Clinic Names
When this option is selected, actual clinic names will be replaced with a generic label. This helps prevent revealing neighborhood or other details that might identify individuals. For example, "South Brooklyn Youth Clinic" is masked with the generic value "Clinic".
All locations that are marked as a clinic type (including those marked with other types) will be masked in the published data. More precisely, both the Label and Labware Lab Code will be masked. Location types are specified by directly editing the labs.tsv file. For details see Manage Locations