|
|
|
|
Why should I use rules to create data mappings?
Because data mappings behave like global variables, you can create data mappings to classify and query data more easily in rules. Any rule in a study can refer to any item that is part of a data mapping in the study.
Using data mappings for rules also simplifies the process of looking at arrays of data, such as data that is collected over time. When a single item is used in multiple forms, you can use the array of data collected for the item in rules. For example, you can check that dates of visits are sequential or calculate aggregate values for the data.
Useful structure for rule creation
The first data mapping that you create for the purpose of rule creation should contain subject information, as you are most likely to need this information to be available for all rules. Over time, you will probably add and subtract information in the data mapping. The following data sets provide a useful structure:
- A data set for single-item data series.
In this data set, include items for which the data does not change in the study, including enrollment-type items, demographics items, and any other items that are static for a subject. Examples of items that you might include in the data set include Initials and Date of Birth.
When a data series contains an item on a single form, and the item is not part of a repeating form or a repeating section, the data series is treated as an alias for the item itself and can be accessed as if it were a single global variable.
- A data set for ongoing, per-visit information.
In this data set, include items with values that change for the subject from study event to study event. This type of information is an array of data. For example, you might include items that appear on a Vital Signs form or a Physical Exam Results form, or items that are related to adverse events or concomitant medications.
Mappings and data extraction
Mappings can also be used for data extraction.
