dhis2-devs team mailing list archive

[Jason Pickering <jason.p.pickering@xxxxxxxxx>]

Hi Jim,

Yeah, I see what you mean. Somehow it seems confusing for some reason.

However, I still cannot get it to work. In most cases, these "Yellow fever"
cases are data entry errors, and this is why we need to try and keep an eye
on them in particular. So, I found a facility where I know the value is not
equal to zero. I altered the data validation rule so that it only included
a single data element, where I know there is data not equal to zero.
Regardless of the combinations which I tried (<, >, ==, !=, etc) I could
not get it to work.

I think there is also something strange with the rule creation dialog,
perhaps a bug. When I create a surveillance rule the first time, I see a
different dialog for the rule. I press save, and it looks fine. I attempt
to do an analysis (no hits yet) and then I go back and edit the rule. When
I press save the second time, I now see the "Validation" dialog, and not
the "Surveillance" one. The "Rule type" has not apparently changed to
"Validation" from "Surveillance". Was able to reproduce this on the demo
site.

Will keep trying, but I think we need to fine-tune the documentation a bit
(as well as test the functionality) as I am not getting the result I
expect.

Regards,
Jason



On Tue, Oct 22, 2013 at 8:32 PM, Jim Grace <jimgrace@xxxxxxxxx> wrote:

> Hi Jason,
>
> Thanks for the feedback.
>
> For surveillance rules, like other validation rules, the equation
> effectively tests for "the usual conditions." When FALSE, an alert is
> generated. When TRUE no alert is generated. (Maybe we could improve the
> documentation about this!) So if you want to see an alert when yellow fever
> cases are >= 1, then you define the equation as yellow fever cases < 1.
>
> You are right that 'if "Skip for missing values" is not checked, that the
> NULLS would be handled effectively as zeros'. This seems to be why the
> rules are showing up with your NULL yellow fever case counts reporting as
> zero. The main problem is that you were using ">= 1.0" (when you want to
> see the alert) instead of "< 1.0" (when you don't want to see the alert.)
>
> If the yellow fever cases count is a single data element value, and you
> are testing for "< 1.0", then it shouldn't matter whether "Skip for missing
> values" is checked or unchecked. If checked, the rule will be skipped on a
> NULL value, so no alert will be generated. If unchecked, a NULL is
> converted to 0.0, which is less than 1.0, so no alert is generated in this
> case either.
>
> However if the left side of the equation adds up yellow fever cases from
> several data element values (like yellow fever counts by age group), then
> it might matter whether "Skip for missing values" is checked or not. If
> "Skip for missing values" is checked and any value is missing, the rule is
> skipped. But if "Skip for missing values" is unchecked, then any missing
> values are replaced with zeros. This could be useful if one age group count
> is NULL but another age group count is 1. It could still trigger an alert.
>
> I hope this helps.
>
> Cheers,
> Jim
>
>
>
> On Sat, Oct 19, 2013 at 4:18 AM, Jason Pickering <
> jason.p.pickering@xxxxxxxxx> wrote:
>
>> I defined a new validation rule for "Total number of yellow fever cases"
>>
>> Left side was a sum of all yellow fever cases (OPD, IP discharge, deaths)
>> dis-aggregated by three age groups each (Total of nine data elements).
>>
>>  Right side was defined as a constant (1.0). "Skip for missing values"
>> was unchecked for both sides. Operator was >=. Period type was set to
>> monthly (Same as the data collection frequency). Other options (Sequential
>> sample count, etc) were left blank.
>>
>> I run the validation rule analysis and get violations basically everywhere
>>
>>  Organisation unit     Period     Importance     Left side descriptionValueOperatorValueRight side descriptionDetails ce
>> Foo Orgunit September 2013Medium Total yellow fever cases0.0 >=1.0 Zero
>>   ... (many more here)
>>
>>
>> What I do not understand is why this rule is being tripped. For this data
>> element, (Yellow fever) we are not recording zeros, and the values
>> therefore should always be NULL, unless there happens to be a value entered
>> greater than zero.
>>
>> Maybe again, this is a misunderstanding on my part of how the validation
>> rule analysis handles blank values. In this case, I would expect that if
>> "Skip for missing values" is not checked, that the NULLS would be handled
>> effectively as zeros, so that when the multiple data elements are summed
>> up, the left hand side is zero. It seems that is not the case, or else I am
>> missing something.
>>
>> This use case is quite common for disease surveillance, whereby data
>> elements will typically be NULL (or perhaps zero), but most likely null,
>> since the values are almost always zero, and it does not make sense to
>> record anything other than non-zeros here.
>>
>> What am I missing?
>>
>> Regards,
>> Jason
>>
>>
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>