This case study is taken from a local area with a large proportion of their EHCPs in mainstream settings. Given this was one of their priority areas to identify opportunities for improvement, they decided to investigate how this caseload varied by two different characteristics:
Graph 1 shows a clearly defined peak around the primary transition (ages 4-5) which has been highlighted. Transition from Early Years to Primary became a focus of this LA. When these cases were analysed further, Graph 2 demonstrates that SLCN and ASD emerged as the most prevalent primary needs for this cohort of children.
However, by taking a similar approach to the smaller spike of cases at ages 11-12, this local area noticed that the split of primary needs between Primary and Secondary transitions is not the same. This is important – by taking the Primary spike in isolation, they could have missed SEMH as an emergent primary need in the Secondary transition years.
Similarly, ASD is a more significant driver of EHCP starts than SLCN at the Secondary transition. This is different to the distribution in Primary years, where SLCN is the more prevalent than ASD. This presented some key questions for the LA to consider in the next steps of their diagnostic:
By understanding nuances such as this one, it gave them useful insight into how best to improve outcomes for these “high-impact” cohorts.
This case study walks through an example of a metropolitan borough council carrying out more detailed analysis on children and young people being supported with an EHCP in INMSS. Given that an increase in expenditure in this provision was forecasted to continue long term, it was an area they wanted to investigate to maximise the impact on outcomes for children and young people and mitigate further expenditure growth.
The LA first investigated whether rising caseload was due to the number of children with a new EHCP starting in INMSS or the number of children with an EHCP moving to INMSS, as per Graph 1.
They found that, although it was equally weighted between 2019-2020, there was a significant change in 2021 identifying moves from another provision as the key driver of growth. The LA then investigated the provisions from which most of these moves were coming and found a large proportion were from MSS and mainstream settings, as seen in Graph 2.
Primary needs were also investigated in Graph 3, and SEMH emerged as the biggest driver for provision moves to INMSS settings.
By looking at individual child level data, this LA was able to further prioritise their area of focus from children being supported in INMSS to understand that children with SEMH, transitioning from MSS and mainstream are the highest priority cohort within INMSS.
Focusing on the key areas derived from the financial and caseload analysis will ensure that when drawing conclusions from CYP analysis, you have confidence that targeting these areas will have the greatest impact on improving outcomes for children and young people. They are the “high impact areas” for focus during the rest of the diagnostic.
