dhis2-users team mailing list archive

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

I think 99.42 is the same as 9942%?

Anyway, the way to do this in DHIS2 is to define an "Indicator type" with a
factor of 100 (like this
<https://apps.dhis2.org/demo/dhis-web-maintenance-datadictionary/showUpdateIndicatorTypeForm.action?id=5982>
from
the demo site)

and then the indicator would be

(Doses used - Doses opened) / Doses opened

(60-35) / 60  = 60 = 0.41667  which is equivalent to 41.667%

Just be sure you indicator (if it is a percent) has an indicator type of
"Percent" (which you will need to create if it does not exist).

Regards,
Jason


On Thu, Aug 27, 2015 at 9:50 PM, Abyot Gizaw <abyota@xxxxxxxxx> wrote:

> Hi Seid,
>
> Selam's formula is correct - it works.
>
> 5965 / 60 is 99.42  not 9942 %
>
> To convert it to percentage probably you have to divide it by a
> denominator and then multiply it by 100. In this case the way the indicator
> is conceptualized, the fact that from a start something is subtracted from
> 100, the final result (99.42) is already percentage.
>
> If this value doesn't make sens, then we have to devise another
> expression. Otherwise, the formula is Selam gave you is correct (at least
> mathematically).
>
> And yes, in DHIS2 we can put any mathematical expression and handle
> complex things. We don't have to limit ourselves with the simple
> numerator/denominator expression.
>
> ---
> Thank you,
> Abyot.
>
> On Thu, Aug 27, 2015 at 1:25 PM, Seid Hussein <seid.hisp@xxxxxxxxx> wrote:
>
>> Hi Selam Abyot,
>>
>> I think the formula you wrote is not correct. I replaced the formula with
>> numerators and denominators and see what happens.
>>
>> Numerator     ==> a   (Doses used)
>> Denominator ==> b    (Doses opened)
>>
>> ((100 * b) - a)/b
>>
>> Let's assume a (doses given)  = 35 and b (doses opened) = 60
>>
>> ((100 * 60) - 35) / 60
>>
>> (6000 - 35) / 60
>>
>> 5965 / 60
>>
>> You get a figure of  9942%
>>
>>
>> Please check again before defining them.
>>
>> On Wed, Aug 26, 2015 at 11:59 AM, selam <selam_molla@xxxxxxxxx> wrote:
>>
>>>  Hi Seid,
>>>
>>> This is the summary of our discussions regarding the conversion factors
>>> and other issues
>>> 1) Regarding the conversion factor, we take the first option you
>>> suggested.
>>>
>>>    - Capturing the population and calculating each data elements for
>>>    each facility by multiplying it with its respective region's factor (hence
>>>    coming up with at least 49 data elements)
>>>
>>>
>>> 2) For the two level indicators of vaccine wastage rate, we use the
>>> expression  ((100*Dose opened)-Dose given)/Dose opened
>>> 3) The indicators should be revised. most of the denominators are
>>> defined because of lack population data and estimates
>>> 4) Seid please  contact those who are working with Phem (IDSR) regarding
>>> how often they collect data. If weekly, is that including Pagume. We should
>>> also ask if they are using the International or Ethiopian calendar when the
>>> weekly data collection. Because as IDSR is an international program, there
>>> is a possibility that they are using the International Calendar to compare
>>> data across countries
>>> 5) Seid please contact Solomon from gate foundation and respond to the
>>> emails of Dykki
>>> 6) Write your technical problems directly to the mailing list
>>>
>>> Keep on the hard work Seido.
>>>
>>> Best regards,
>>> Selamawit M. Mekonnen
>>> Tlf:+4741374246
>>>
>>>
>>>
>>>
>>> ------------------------------
>>> *From:* Abyot Gizaw <abyota@xxxxxxxxx>
>>> *To:* Seid Hussein <seid.hisp@xxxxxxxxx>; DHIS 2 Users list <
>>> dhis2-users@xxxxxxxxxxxxxxxxxxx>
>>> *Cc:* Selamawit Molla <selam_molla@xxxxxxxxx>; Sundeep Sahay <
>>> sundeep.sahay@xxxxxxxxx>; Jørn Braa <jornbraa@xxxxxxxxx>; John Lewis <
>>> johnlewis.hisp@xxxxxxxxx>
>>> *Sent:* Wednesday, 26 August 2015, 9:21
>>> *Subject:* Re: Conversion factors and their implications
>>>
>>> Dear all,
>>>
>>> Please see the forwarded mail if you can help Seid. He is asking how to
>>> provinces can apply conversion factors on national level data.
>>>
>>> Seid can provide more details if necessary.
>>>
>>> ---
>>> Thank you,
>>> Abyot.
>>>
>>>
>>>
>>> On Wed, Aug 26, 2015 at 8:54 AM, Seid Hussein <seid.hisp@xxxxxxxxx>
>>> wrote:
>>>
>>> Hi all,
>>>
>>> I think you are better positioned to comment on this on what approach we
>>> should use. In the file attached, you can see that there are 49 different
>>> conversion factors to come up with approximations of different data
>>> elements like expected pregnancies and infant population.
>>>
>>> If these factors were the same for all regions, we could have added them
>>> as constants and used them to define the denominators for the indicators.
>>> However, as you can see each region has different conversion factors and
>>> there's a big difference among them which makes defining indicators very
>>> difficult.
>>>
>>> I see two options here:
>>>
>>>
>>>    - Capturing the population and calculating each data elements for
>>>    each facility by multiplying it with its respective region's factor (hence
>>>    coming up with at least 49 data elements)
>>>    - Defining different indicators for different regions using
>>>    different constants as conversion factors (which I think may complicate
>>>    things)
>>>
>>> In my view the first option is the best option for us because once we
>>> capture the total population, it is easier to generate data for the other
>>> data elements using these conversion factors. Of course, as I stated in my
>>> mail yesterday, there are two sets of population data used in the structure
>>> (MoH uses the official data from Central Statistical Authority
>>> dis-aggregated by Wereda while the regions use data collected from the
>>> ground. The data the regions use may be the most accurate but we have to
>>> accomodate both options I think because the two parties use their own
>>> population data to come up with the population figures, effectively having
>>> two different population data (administrative population and facility
>>> catchment population)
>>>
>>> If we are using two sets of population data, we may have to define the
>>> same for all the 49 other data elements with the factors as well.
>>>
>>> Would you please deliberate over it and suggest? Once we have a concrete
>>> plan, we can discuss with M&E people here on how to proceed.
>>>
>>> Regards,
>>>
>>>
>>> Seid,
>>>
>>>
>>>
>>>
>>>
>>
>
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-- 
Jason P. Pickering
email: jason.p.pickering@xxxxxxxxx
tel:+46764147049