Grouping and Sorting Columns

Grouping and sorting data is an important consideration when reporting outcomes. These pieces of functionality enable users to categorize and order the data being reported and ensure a consistent flow of information from one row to the next.

By default, data is sorted and ordered first by Group Name, then Performer Name, and then Chart Name. This means all the sorted chart names of each performer are shown in each group by default, with each chart’s conditions time-ordered based on the order of the condition on the chart. 

If the groups functionality is not being utilized, the sorting of the “Group Name” has no effect on the output and instead shows an ascending order of all the chart names for each performer. Users can change the way data is sorted and grouped at any point in time within the grid.

There are 2 options for grouping and sorting data: 1) sort on one column, or 2) group and sort by multiple columns.

Sort on One Column: click the column label to select the sorting method you want to apply.

  • If the column label area has no up or down arrow to the right of the label (i.e. users have not clicked the column yet), this means no defined ordering has been applied to the data.
  • If the label is clicked once, users will see an up-arrow to the right of the column label. This means the data is sorted in ascending order (A to Z).
  • If the label is clicked twice, users will see a down-arrow to the right of the column label. This means the data is sorted in descending order (Z to A).

Group/Sort by Multiple Columns: press shift + click the next column label, which can then be sorted in ascending or descending order. Users can continue grouping and sorting columns as much as necessary. The numerical hierarchy of the grouping applied will always be provided next to the column label.

Example Use Case of Multi-Column Grouping:

After sorting the first column, users can view the data consecutively at a certain level (such as pinpoint, chart, or condition-level).

This functionality can be used when investigating whether a change in clinical programming has led to better outcomes for the performers in users’ groups. Users can first sort performers, then group each performer’s data by the pinpoint tags to categorize each performer’s data based on the different programming delivered. From here, there is a clear view of each performer’s data in each program, which allows users to directly compare metrics to understand if the new programming has resulted in the desired outcomes.

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