Disabling Data elements

Dear Community,

We are having issues related to new UPDATED data elements where the system allows data to be entered in the previous years while the updates of the data entry form was done currently eg like form updated in Jan 2019 but still 2018, 2017,2016…allows the data to be entered.

Is there any way to disable these variables only to allow the date of update to be entered only eg. Using the same approach for Org. unit date where it opend the data entry forms based on the Opening date of health facility and this affects data entry period probably we need an option on the data elements that only allow it to appear in that period that is updated.

Andrew M.

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Hi @muhireandrew2020,
I do not think this exists at the moment.
However, if you created a feature requirement on Jira other users can contribute and vote to the necessity of this requirement.


That’s true @Emma_Kassy. We can also vote for it from here by clicking the blue VOTE button next to the topic header

vote for it to be prioritized by the team.


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Hi Andrew,

I’m not 100% sure what you are looking for, and thus why the “Data Input Period” setting you have for any data set do not suffice:

Do you want the data set to enable data VIEWING and/or EDITING for older data, but only enable data CAPTURING for newer data?

If you want to simply block users from adding to or editing older data, you can use the approval & lock mechanism.

If you want to both view and edit older data but NOT add additional older data, you could consider using several near-identical data sets with different data input periods. For example:

  • Dataset “Child Health 2019” can be set up to allow only data from 2019 to be captured.
  • DataSet “zz Child Health 2015-18” can be identical except it only allows data from 2015-18, and the zz prefix will sort it to the bottom

These are just loose guesses, since I don’t know exactly what you are looking for.

Regards (and greetings to the Kigali gang!)

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Hi Calle,

What @muhireandrew2020 was trying to say is that once you add a new data element to a data set that was being used, that it is should not allow people to enter historical data to that particular newly created data element, possibility to enter should only be limited to when that data element was created, onward.

Eric D.


Thanks Calle and Eric,

Well explained Eric, What i meant is already used data sets and some of us we review our reporting system annually where you add and remove some data elements without creating new data sets. Eg. like adding one or two data elements in 2019 and you don’t want people to enter data in those new added data elements in an existing data set for the previous years or period but in the same data set we have old data elements that already has historical data and still used for future reporting.

But the issue, you added new data elements in data sets in 2019 but like after one year you find 2018, 2017…are partially filled and unfilled previous years may be considered as incomplete while its an issue of when data element was added.


Thanks Emma,

Sure sure

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Hi @muhireandrew2020,
@Calle_Hedberg has some really good suggestions, especially using the dataset lock mechanism after a given period might work for you.

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Hi Andrew,

if @duserik 's interpretation is correct, I think in this case you could consider creating a new data set for the new form revision. You can basically replicate the original data set, then do the additions/modifications and save it as a new data set.

As Calle explains well above, you can then ensure that the original data set is open up until the revision was to take effect, and that the new data set is only open from that time onwards. You can achieve that through the use of data set expiry days and “data input periods”. You can use the revision e.g. as a suffix in the data set name.

This way, it becomes explicit which data elements are part of which form revision.

As you know, in DHIS 2, data elements can be part of multiple data sets without creating duplicate data, so this should not affect your underlying data values. You should probably make sure that the data sets containing the same data elements have the same period type to avoid issues in aggregation, approval etc.




Much apppreciated Lars
Its now clear.

Thanks @Calle_Hedberg @duserik

Your comments made it much clearer…let us test it and see how it works.

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