dhis2-users team mailing list archive

[Marta Vila <martavila@xxxxxxxxx>]

Hi Damien!

there is no magic formula for all these config decisions, but one pretty
generic good practice would be that the aggregation of your cat. combo
options into a data element should be meaningful. As it is the value that
users will get when they select the DE in data visualizer or pivot table
without details.

>From your example: I would say that using two different data elements for
Malaria and Malaria (deaths) is correct. If you put them under one unique
Malaria DE with a category (cases/deaths), the total number will be mixing
cases and deaths, which is most likely incorrect from an analysis point of
view and very easy to misinterpret by the users.

Another generic good practice advise is to design your configuration
thinking of your desired output (analysis).

Hope it helps!
Marta

On Wed, 14 Nov 2018 at 20:17, Damien Scarlett <
Damien.Scarlett@xxxxxxxxxxxxxxxx> wrote:

> Hi Calle,
>
>
>
> Thanks for your 2c worth (we say 20c from where I am from J). I may be
> explaining a different perspective here even still being a part of the
> wider MSF posse but we (the Brussels office) have some indicators (e.g. %
> of Morbidity / Mortality) that we have created additional related Data
> Elements that map to the disease e.g. we have different DEs for ‘
> *Malaria’* & for ‘*Malaria (death)*’ to use for Mortality-type
> indicators. Mind you this is mapping to the aggregate data capture.
>
>
>
> I’m unsure if there are any Best Practices for these types of indicators &
> how to set them up (I would presume they are common) but if there is any we
> would be happy to know them & how organisations have configured these.
>
> From reading the below it may be wise to create Cat. Combos instead of
> additional DE’s but other people may have experience in which is best to
> capture this & easier to manage over the long term.
>
>
>
> Have a good evening,
>
> *Damien *
>
>
>
> *From:* Dhis2-users <dhis2-users-bounces+damien.scarlett=
> brussels.msf.org@xxxxxxxxxxxxxxxxxxx> *On Behalf Of *Calle Hedberg
> *Sent:* Wednesday, 14 November 2018 6:02 PM
> *To:* Jaime Bosque <Jaime.Bosque@xxxxxxxxxxxxxxxxx>
> *Cc:* DHIS 2 Users list <dhis2-users@xxxxxxxxxxxxxxxxxxx>; dhis2-devs <
> dhis2-devs@xxxxxxxxxxxxxxxxxxx>
> *Subject:* Re: [Dhis2-users] [Dhis2-devs] Filtering indicators by OU
>
>
>
> Jaime and others,
>
>
>
> Using category combos (or attribute combos) are fundamentally/conceptually
> the same as having multiple data elements, because at the end of the day
> you will have the same number of physical records in your database (e.g.
> the datavalue table). Or in other words, the level of "granularity" in your
> data remains the same. (The main advantage in using catcombos is a
> reduction in the amount of meta-data records you maintain: so instead of
> creating and maintaining let us say 300 data elements, you create and
> maintain 50 data elements with 2 gender catoptions and 3 age catoptions (55
> meta-data items) -> 50x2x3=300 dataelement&catoptioncombos variants.
> (Maintaining 55 items is presumably easier than 300 - although for many
> users it's also more difficult to fully grasp and I have seen a lot of
> databases where the catcombos have become really messy over the years.
> Typical examples are multiple changes in e.g. age groups over time).
>
>
>
> There are situations where you can use for instance orgunit groups to get
> "ou-dependent" indicator values, but I would in general not recommend them
> except when the relation between orgunit(type) and indicator is an inherent
> and stable dimension of every indicator at a particular orgunit level. A
> practical example:
>
> 1.
>
> If you collect data per hospital, and the hospital have 8 different wards
> (1 maternity, 2 medical, 2 surgical, 1 paediatrics, 1 ICU, 1 orthopaedics),
> and you need e.g. Bed Utilisation Rates for each ward type, you would
> typically create one data element & catcombo set for each type:
>
> Inpatient days - maternity, inpatient days - medical, inpatients
> separations - maternity, inpatient separations - medical, inpatient death -
> maternity, inpatient death - medical, etc.
>
> 2.
>
> If you on the other hand collect the same data per hospital ward (i.e.
> expand your orghierarchy to the sub-facility level), and these are grouped
> per ward type, you need only
>
> inpatient days, inpatient separations, inpatient deaths
>
> and you would do analysis per ou group. NOTE, though, that such a model
> means you cannot change a ward's orgunittype without messing up the
> historic data analysis. So if a ward is changed from a medical to a
> surgical ward, you would have to close the medical ou and open a surgical
> ou.
>
>
>
> Another perspective on the same is to say that the higher granularity you
> have in the geographic/administrative dimension (orghierarchy), the less
> granularity tend to be required in the fact dimension (data
> elements/indicators). When implementing something like option 2, though,
> you must also consider aggregation of data - if for instance some of your
> indicators are using higher level data (e.g. district totals) for some
> denominators, you might end up struggling to get that.
>
>
>
> Jaime do not provide any specifics about exactly what A,B,C is and whether
> each of them are firmly and permanently bonded to specific outypes only so
> it is difficult to know if "transferring" some of the granularity to the
> orgunit dimension is advisable (as indicated above, aggregated analysis
> needs might also play a role). As a general rule, I would only recommend
> such shifts if the artifact/event/measurement that the data elements
> represent is firmly and permanently linked to orgunit types (as is the case
> with ward-specific indicators) - and even then users have to understand the
> inherent restrictions like limits to changing the outype group over time.
> In the case of MSF type health units, it might mean that e.g. an MSF unit
> grouped under "emergency trauma centre" cannot be kept as the same orgunit
> if the unit changes from e.g. emergency trauma to long-term rehab. (Not
> sure if the example is good, but hope you get my drift).
>
>
>
> My 2c worth...
>
>
>
> Calle
>
>
>
> On Wed, 14 Nov 2018 at 16:44, Jaime Bosque <Jaime.Bosque@xxxxxxxxxxxxxxxxx>
> wrote:
>
> Dear Barnabas,
>
>
> Thanks a lot for your response. In the end what we were doing is not
> exactly what you were saying (no Category combinations). So after checking
> with a couple of colleagues here we realized that this was not a
> possibility and so we are not merging the data elements in the production
> environment.
>
>
>
> Kind regards,
>
>
>
> Jaime Bosque Torrecilla
>
> Applications Technician, eHealth & Operations Applications (‘Apps4OPS’)
>
> *Projects & IT Unit*
> *Médecins Sans Frontières (MSF) Spain – Barcelona Office*
>
> Fixed: +34 935 213 048 – Skype: msfe-healthdatatech2
>
> Email: jaime.bosque@xxxxxxxxxxxxxxxxx – www.msf.org
>
>
> ------------------------------
>
> *From:* Barnabas Akumba <akumbabarns@xxxxxxxxx>
> *Sent:* 13 November 2018 17:46:26
> *To:* Jaime Bosque
> *Cc:* dhis2-users; dhis2-devs
> *Subject:* Re: [Dhis2-devs] Filtering indicators by OU
>
>
>
> Hello Jaime,
>
>
>
> If I understand you correctly, you have three Data Elements that are all
> disaggregation of a particular Data Element X.
>
> Your initial design was that you created each of the DEs (A, B, C) as
> individual Data Elements.
>
> My understanding is that you merged them by creating a Category
> combination with a Data Dimension Type "Disaggregation" A, B and C as
> options and assigned to the Element Called X. If that is the case, during
> data entry, the system will disaggregate the Data Element X into X(A), X(B)
> and X(C).
>
> If you have gone this way, your analysis won't be an issue.
>
>
>
> Please verify and confirm if this is similar to what you want.
>
>
>
> Regards
>
>
>
> On Tue, Nov 13, 2018 at 5:34 PM Jaime Bosque <
> Jaime.Bosque@xxxxxxxxxxxxxxxxx> wrote:
>
> Hello and thanks for the quick response... it seems it might have not been
> really clear.
>
>
>
> I will try to put an example.
>
> We had 3 Data Elements (A,B and C) that have been merged in one (let's
> call it X). The reason they have been merged is because A,B and C belong to
> a Medical Service called Nutrition and as they could be filtered later by
> that service (Nutrition A, Nutrition B and Nutrition C) it simplified the
> data input and analysis.
>
>
>
> So, for example, now in the OU Nutrition A people will fill the Data
> Element X. And when doing the analysis they will select Data Element X
> filtered by service Nutrition A. Same for B and Same for C.
>
>
>
> These three indicators were used before separately in several indicators,
> sometimes we needed A+B+C/100. In those cases we don't need to do anything
> as they have already been merged and we can use X/100.
>
>
>
> However, and here is the issue. We have realized that when calculating
> Deaths, the only valid deaths are those coming from Nutrition A and
> Nutrition B. So before, we would have the indicator Nutrition A + Nutrition
> B.
>
>
>
> Ideally, I would like to be able to create an indicator where Data
> Elements can be filtered, so I could create an indicator like X (Nutrition
> A) + X (Nutrition B).
>
>
>
> If this is not possible it obliges me to keep the old model with A, B and
> C separated instead of the X. I hope it is clear... I will happily provide
> more information if requested.
>
>
> Thanks,
>
>
>
> Jaime Bosque Torrecilla
>
> Applications Technician, eHealth & Operations Applications (‘Apps4OPS’)
>
> *Projects & IT Unit*
> *Médecins Sans Frontières (MSF) Spain – Barcelona Office*
>
> Fixed: +34 935 213 048 – Skype: msfe-healthdatatech2
>
> Email: jaime.bosque@xxxxxxxxxxxxxxxxx – www.msf.org
>
>
> ------------------------------
>
> *From:* Barnabas Akumba <akumbabarns@xxxxxxxxx>
> *Sent:* 13 November 2018 16:48:02
> *To:* Jaime Bosque
> *Cc:* dhis2-users; dhis2-devs
> *Subject:* Re: [Dhis2-devs] Filtering indicators by OU
>
>
>
> Hello Jaime,
>
>
>
> Could you be more detailed? Let's understand your implementation (eg. of
> DEs).
>
>
>
> Regards
>
>
>
> On Tue, Nov 13, 2018 at 4:44 PM Jaime Bosque <
> Jaime.Bosque@xxxxxxxxxxxxxxxxx> wrote:
>
> Good afternoon. First email to the list looking for some help...
>
>
>
> We are revising our data model and we have come out with a simplification
> on the number of Data Elements. For example, before we were using three
> Data Elements that we have realized they can be joined and then filtered by
> Organisation Unit when doing the analysis.
>
>
>
> This works wonder in data analysis, however we have realized that this
> will not work for the indicators as there is no possible way of filtering
> by OU in the indicators. Am I correct? Is there a way that this could be
> done somehow?
>
>
>
> Thanks a lot,
>
>
>
> Jaime Bosque Torrecilla
>
> Applications Technician, eHealth & Operations Applications (‘Apps4OPS’)
>
> *Projects & IT Unit*
> *Médecins Sans Frontières (MSF) Spain – Barcelona Office*
>
> Fixed: +34 935 213 048 – Skype: msfe-healthdatatech2
>
> Email: jaime.bosque@xxxxxxxxxxxxxxxxx – www.msf.org
>
>
>
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>
>
> --
>
>
>
> Barnabas AKUMBA
>
>
>
> *Mobile:* +2348036195778
>
> *Skype:* barnabas.akumba
>
>
>
>
> --
>
>
>
> Barnabas AKUMBA
>
>
>
> *Mobile:* +2348036195778
>
> *Skype:* barnabas.akumba
>
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>
>
>
> --
>
> *******************************************
>
> Calle Hedberg
>
> 46D Alma Road, 7700 Rosebank, SOUTH AFRICA
>
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>
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>
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>
> Email: calle.hedberg@xxxxxxxxx
>
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>
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>
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