FGM is associated with serious health risks and is illegal in the UK. NHS England wanted us to help them understand the extent of the practice in London to enable them to reduce the likelihood of unsafe practices and associated long term health effects

Data collection in this area is new, so understanding the trends is very important for future planning. Since 2015, healthcare professionals and other agencies have by law been expected to record all suspected cases of FGM.

The project brought together stakeholders from the London Safeguarding Board and London CCGs via the London Information Exchange Group, the Department of Health, Metropolitan Police and NHS Digital. A number of new data sets needed to be managed, getting information from partners and shaping it into insight that could be used collaboratively to improve support for those affected by FGM.

We worked at scale across London to collect and analyse data, liaising with all the stakeholders to make sure the project ran smoothly. This was represented on maps for the 32 London CCGs, showing the type, age group, police reports and hospital reports. Our team extended the most recent research study on FGM prevalence to model the current and future cases by CCG over the next five years.

A number of new datasets needed to be managed,

These outputs allows the health and police services to target their interventions around FGM effectively across London, using the insight we generated

NHS England said: “NEL’s team helped the London FGM task and finish group translate and triangulate a range of data into a striking and attractive data model which gave us an opportunity to engage with stakeholders in London to stimulate discussion on FGM prevalence, health impact, engagement, commissioning and provision. The team quickly understood our ambition and were able to develop the model, adapt through the pilot phase and support the work in clinical forums during conception.  The model has been very well received and there are plans to offer to other regions and discussions about using similar model for other datasets”.