The data element above called "Measles doses given", although capturing the core essence of what the data is can be further elaborated and disaggregated into what is called data element categories. The system administrators of DHIS are free to define any data element category dimensions to data elements using the user interface for this in the data element maintenance section, but here are some examples of possible categories to use.
Given the example of Measles vaccination, if you want to know whether these vaccines were given at the facility (fixed) or out in the community as part of the outreach services then you could add a dimension called e.g. "Place of service" with the two possible options "Fixed" and "Outreach". Then all data collected on measles immunisation would have to be disaggregated along these to options. In addition to this you might be interested in knowing how many of these children who were under 1 year or above 1 year of age. If so you can add an Age dimension to the data element with the two possible options "<1 y" and ">1 y". This implies further detail on the data collection process. You can also apply both categories Place of service and Age and combine these into a data element category combination e.g. called "EPI disaggregation" and thereby you would be able to look at 4 different more detailed values in stead of only 1 as in the example above for the data element "Measles doses given": 1) "Fixed and <1 y, 2) Fixed and >1 y, 3) Outreach and <1 y, and 4) Outreach and >1 y. This adds complexity to how data is collected by the health facilities, but at the same time opens up for new possibilities of detailed data analysis of Measles immunisation.
Table 23.2. Example of detailed storage of data values when using data element categories "Place of Service" and "Age" (simplified for readability compared to the actual database table)
|Organisation Unit||Data Element||Place of service||Age||Period||Value|
|Gerehun CHC||Measles doses given||Fixed||<1 y||Dec-09||12|
|Gerehun CHC||Measles doses given||Outreach||<1 y||Dec-09||4|
|Gerehun CHC||Measles doses given||Fixed||>1 y||Dec-09||4|
|Gerehun CHC||Measles doses given||Outreach||>1 y||Dec-09||2|
|Tugbebu CHP||Measles doses given||Fixed||<1 y||Dec-09||10|
|Tugbebu CHP||Measles doses given||Outreach||<1 y||Dec-09||4|
|Tugbebu CHP||Measles doses given||Fixed||>1 y||Dec-09||3|
|Tugbebu CHP||Measles doses given||Outreach||>1 y||Dec-09||1|
While the data element categories and their options described above dictated the level of detail (disaggregation) at the point of data collection and how data values get stored in the database, the data element group sets and groups can be used to add more information to data elements after data collection. E.g. if looking at a lot of data elements at the same time in a report you would want to group these based on some criteria, e.g. if looking at all the data captured in a form for immunisation and nutrition you might want to separate or group data elements along a programme dimension (called group set) where "Immunisation" (or EPI) and "Nutrition" would be the two groups. Expanding the report to include data from other programs or larger themes of health data would mean more groups to such a group set dimension, like "Malaria", "Reproductive Health", "Stocks". For this example you would create a data element group set called "Programme" (or whatever name you find appropriate), and to represent the different programmes in this dimension you would define data elements groups called "EPI", "Nutrition", "Malaria", "Reproductive health" and so on, and add all these groups to the "Programme" group set. To link or tag the data element "Measles doses given" to such a dimension you must (in our example) add it to the "EPI" group. Which groups you add "Measles doses given" to does not affect how health facilities collect the data, but adds more possibilities to your data analysis. So for the group set dimensions there are three levels; the group set (e.g. "Programme"), the group (e.g. "EPI"), and the data element (e.g. "Measles doses given").
Indicators can be grouped into indicator groups and further into indicator group sets (dimensions) in exactly the same way as data elements.
|Organisation Unit||Data Element||Programme||Period||Value|
|Gerehun CHC||Measles doses given||EPI||Dec-09||22|
|Gerehun CHC||Vitamin A given||Nutrition||Dec-09||16|
|Tugbebu CHP||Measles doses given||EPI||Dec-09||18|
|Tugbebu CHP||Vitamin A given||Nutrition||Dec-09||12|
|Gerehun CHC||Malaria new cases||Malaria||Dec-09||32|
|Tugbebu CHP||Malaria new cases||Malaria||Dec-09||23|