1.) Has anyone used the Tracker Capture App to enter Aggregated Data instead of the Data Entry App? I’m receiving aggregated data from labs and will continue to receive data from them over time. Therefore, I was wondering if the Tracker Capture App would be most useful, even though it’s designed for individualized data.
2.) A similar question would be: What’s the best way to track aggregated data received over time? Can the data entry app link aggregated data entered at various times (as long as I provide the 3 dimensions).
3.) Lastly, are all visualizations/reports available for aggregate data as are for individual level data? Are there any limitations of reports by using the data entry app?
I guess my first question is why would you want to use Tracker capture instead of the aggregate data entry app if you are receiving aggregate data? Do you get a single report every month from the lab?
Maybe if you can describe in a bit more detail why you chose to use Tracker Capture as opposed to normal aggregate data entry and maybe give some examples of the type of data you receive, we might be able to provide some additional guidance.
Thank you for your quick response. Here are additional details:
I am attempting to utilize DHIS2 to capture aggregated laboratory data from many labs that I receive ~monthly. The data is typical numerical aggregate data, such as # of isolates, # of various supplies, # of facilities satisfying X, etc.
The only reason I ask is because through the trainings, it appeared that Tracker Capture was more robust and allowed for more functionality. That was why I was asking whether Tracker Capture could be used for aggregated data. However, if not I can certainly use the Data Entry App.
-To summarize into 2 more clear questions: Is there a use case for using Tracker Capture for entering aggregated data?
Once aggregated data is entered via the data entry app (with associated periods), are all visualizations and reports within DHIS2 able to be used on these aggregated data? Also, will I be able to link to associated individual level data that may be entered at a later time? (I think the answer to the last questions is yes based on this webpage: [Tracker and aggregate data integration - DHIS2 Documentation].
So, tracker capture is intended for following an entity (it might be a person but could also be a lab sample) through a program. Lets use labs as an example. A sample might be taken at a clinic, and then its tracking number is entered into DHIS2. It is then sent to a lab, and tested. The lab could enter the specific test results. Tracker allows then for entities to be tracked over time.
This lab might then aggregate the total number of samples per month they have received:
Total number of tests
Number of HIV tests
Number of HIV tests which were positive
Number of malaria tests
Number of positive malaria tests
…etc etc…
This is aggregate data. We don’t have any information on the specific samples themselves, just their total number.
So, I think in your case, unless you are getting event based data from the lab on each sample, you should be using aggregate data and not tracker.
Tracker data can be transformed into aggregated, but in your case, it sounds like the data is already aggregated, and therefore you should not try and enter this data into tracker, since it is already aggregated.
Thank you very much Jason for your detailed reply! I appreciate the explanation. This makes a lot of sense. I will proceed to use the aggregate data entry app for this purpose.
Just one last piece to ask you about: Skip Logic. Is it possible to incorporate skip logic when entering aggregate data into the data entry app without any customization?
If not, would this be a use case where I should utilize the tracker app? Or would I have to create a custom form (incorporating JavaScript) within the aggregate data entry app?
Usually however, for aggregate data entry you would use validation rules as well, in order to ensure that what the skip logic in the user interface attempts to enforce, is actually valid. There are many ways to get data into DHIS2 (Android, Import, API), and a JavaScript form would only help if people were actually entering data through the Web. Validation rules will not prevent invalid data from being entered, but users can be alerted to potential situations directly in the data entry interface, to help to prevent data entry errors.