Functioning Emergency Transport System
Indicator Phrasing
English: % of target communities with a functioning emergency transport system
French: % de communautés cibles ayant un système de transport d'urgence en fonctionnement
Portuguese: % de comunidades-alvo com um sistema de transporte de emergência em funcionamento
Czech: % cílových komunit s funkčním systémem záchranné dopravy
What is its purpose?
The indicator measures the proportion of the target communities with an effective system for the emergency transport of pregnant women (and/ or other cases) requiring urgent, life-saving medical care (for example, during complicated deliveries).
How to Collect and Analyse the Required Data
Determine the indicator's value by using the following methodology:
1) Define the main features each emergency transport system needs to meet in order to be considered as “functional”. This can include, for example:
- the transport is available 24 hours per day
- the transport arrives within X minutes of being requested
- the transport reaches a health facility with a skilled health attendant within X minutes/ hours
- at least X% of local women of reproductive age are aware of the emergency transport system’s availability and know how to request it (either know it directly or know someone who can request it)
- at least X% of local women of reproductive age say that its price is affordable
- other realistic criteria depending on your project
2) Collect the required data by conducting key informant interviews with the transport operator and its recent users and by conducting individual interviews with a representative sample of local women of reproductive age.
3) Calculate the number of communities, which have an emergency transport system, that meets the pre-defined “functionality criteria”.
4) To calculate the indicator’s value, divide the number of your target communities with a functioning emergency transport system by the total number of surveyed communities. Multiply the result by 100 to convert it to a percentage.
Disaggregate by
Disaggregate the data by location (remote communities/ communities nearby health facilities, etc.).