The challenges and how to overcome them (3/4)
Challenge n°3: Harmonisation of indicators for the data landscape exercise
Different survey instruments may collect data on the same indicator. For example, stunting is typically collected by DHS, MICS, NNS, local SMART surveys, and routine data from health centres. Be aware of the fact that the indicators are not necessarily directly comparable across the surveys because:
- The definition of the indicator can be different. For example, stunting prevalence is measured in children aged 0-59 months in DHS and MICS while it is measured in children aged 6-59 months in SMART surveys.
- For survey data, the sampling frame is important. Sub-national data from a survey data that is designed to be representative at the national level may not be directly comparable to sub-national data from a survey that is designed to be representative of the sub-national level.
- The geographic level may vary if administrative demarcation has changed over time.
- Routine data and survey data, even when using the same indicators, cannot be directly combined. Population-based survey data is designed to be representative of a population group while routine data is representative of the individuals using a service or programme.
The question of harmonisation of indicators is addressed at the data analysis stage. However, when conducting a data landscape exercise, it is important to include information on indicator definitions, routine vs survey data, and geographic scope in the indicators matrix to identify challenges ahead.