The Department for Education has been slammed for failing to fully understand what is driving demand for children's social care.
The National Audit Office also criticises the department for not having an understanding why there is such wide variation between local authorities in their children’s social care activity and costs, as it has not yet done the work to tie together available sources of information.
Head of the NAO Amyas Morse said: “Over two years ago we reported that the Department for Education’s progress in improving children’s services was not up to scratch. Since then the Department has adopted the target of giving all vulnerable children access to high quality support, no matter where they live, by 2022. The Department has started to build its understanding of variations in services, but it should know more than it does. Even with this understanding, the Department faces a tall order to achieve its goal within three years.”
The NAO highlights that in 2017-18 655,630 children were referred to local authorities because of concerns about their welfare - a rise of 7% since 2010-11. However local authorities carried out 77% more child protection assessments yet the reasons for this disproportionate increase in assessments compared with referrals are unknown.
Furthermore, cases where children are taken into care have risen by 15% since 2010-11 – more than double the rate of population growth.
The NAO outlines that:
- Local authorities expect to spend £4.2 billion on children in care in 2018-19 - £350 million (9.1%) more than they budgeted for in 2017-18.
- There has been an increase in the use of residential care, but local authorities often lack suitable placements.
- Only 32% said they have access to enough residential homes for children aged 14 to 15 years, and 41% for those aged 16 to 17.
- The rate of children in need episodes ranges from 301 to 1,323 per 10,000 children.
The variation in local authorities spend on children’s social care ranges from £566 to £5,166 per child per year across different local authorities.
"The Department does not fully understand what is causing increases in demand across all local authorities and, until recently, it did not consider this a fundamental part of its responsibilities," said the report.
"It has previously estimated that 41% of the increase in the number of children in need between 2009-10 and 2016-17 was due to population growth, however, it had not quantified the contribution of other causes to almost 60% of the increase. The Department has put in place a programme of reform. In late 2017 it commissioned with others external research which they hope will explain demand and variation, but this will not be ready before summer 2019," it added.
The NAO’s analysis suggests that local authority characteristics may account for 44% of the variation between different local authorities over time in how they respond to demand for children’s services. Different levels of deprivation could explain 15% of the variation between local authorities and a further 10% of this variation may be accounted for by changes which affect all local authorities equally at the same time, such as the introduction of a new policy.
The report found no link between local authorities’ spending per child in need and their Ofsted rating. Some services are rated “Good” by Ofsted with spending of £570 per head, while others receive the same rating with spending of £4,980.
The NAO also reveals that with local authorities’ spending power reducing by 28.6% since 2010, they have responded by reducing spending on preventative children’s services, including children’s centres, and increasing spending on statutory social work.
The number of Sure Start children’s centres has fallen by just over 500 since 2010. However, local authorities which have closed children’s centres have not had any consequential increases in child protection plans.
The NAO concludes by calling on the Department for Education to "promptly improve" its understanding of children’s social care and builds on the NAO’s own research and modelling to help it explain demand and local variations and improve the effectiveness of its decisions.
