dhis2-users team mailing list archive

[Abyot Gizaw <abyota@xxxxxxxxx>]

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,
>>
>>
>>
>>
>>
>