In DHIS2 there are three dimensions that describe the aggregated data being collected and stored in the database; the where - organisation unit, the what - data element, and the when - period. The organisation unit, data element and period make up the three core dimensions that are needed to describe any data value in the DHIS2, whether it is in a data collection form, a chart, on a map, or in an aggregated summary report. When data is collected in an electronic data entry form, sometimes through a mirror image of the paper forms used at facility level, each entry field in the form can be described using these three dimensions. The form itself is just a tool to organise the data collection and is not describing the individual data values being collected and stored in the database. Being able to describe each data value independently through a Data Element definition (e.g. ‘Measles doses given <1 year’) provides important flexibility when processing, validating, and analysing the data, and allows for comparison of data across collection forms and health programs.
This design or data model approach separates DHIS2 from many of the traditional HIS software applications which treat the data collection forms as the key unit of analysis. This is typical for systems tailored to vertical programs’ needs and the traditional conceptualisation of the collection form as also being the report or the analysis output. The figure below illustrates how the more fine-grained DHIS2 design built around the concept of Data Elements is different and how the input (data collection) is separated from the output (data analysis), supporting more flexible and varied data analysis and dissemination. The data element ‘Measles doses given <1 y’ is collected as part of a Child Immunisation collection form, but can be used individually to build up an Indicator (a formula) called ‘Measles coverage <1y’ where it is combined with the data element called ‘Population <1y’, being collected through another collection form. This calculated Indicator value can then be used in data analysis in various reporting tools in DHIS2, e.g. custom designed reports with charts, pivot tables, or on a map in the GIS module.