We have a ProgramType.WITH_REGISTRATION, AnalyticsType.Enrollment program indicator, and we want it to use the org unit of the most recent event of a certain program stage for that tracked entity in the given period.
E.g. if a patient is enrolled at Facility A but has a treatment event at Facility B this quarter, we want our treatment program indicator to count them under Facility B this quarter. The most recent treatment event location is more important to us than the enrollment location or any other event locations.
In our use case, we need to aggregate by enrollment (rather than event) because the indicator uses values from multiple program stages. And we don’t necessarily want to refer the whole enrollment’s ownership to Facility B for a one-time visit.
Ideally we would be able to select the event we want to use for the org unit in the program indicator configuration. Mockup:
I was thinking of submitting this as a Jira feature request but wanted to get feedback here first - Am i missing a different way to handle this? Does anyone have experience reporting with enrollment aggregation and event location?
It seems that this is a recurring or significant point in your use case so I’m wondering if it’s possible and would be a good solution to add an OU data element in the program stage where it’d be assigned the current OU wherever the stage takes place and thus provides the ability to filter out based on its value?
Thanks for your response! We originally had a location selector on the form and are trying to find an alternative to it, because it adds quite a bit of complexity to our program-to-aggregate workflow using the PDAC tool (from DHIS2 App Hub) .
If we can use the event’s org unit as the program indicator’s org unit, we can set up a single PDAC configuration per indicator, extract it with the correct OUs from the datavaluesets API, and import to to the aggregate data set.
If we use a data element to capture the org unit, our best solution so far has been to set up a different PDAC configuration for each organisation unit for each indicator, and externally transform the data to the correct org units before pushing to the aggregate data set. There’s a lot of overhead and maintenance with this method that we are trying to avoid if we can.
