outcomes of supervision orders: how can data be used to
TRANSCRIPT
Outcomes of supervision orders: how can data be used to understand children’s pathways?
Professor Judith Harwin, Dr Bachar Alrouh, Lily Golding, Tricia McQuarrie, Professor Karen Broadhurst & Dr Linda Cusworth
Data visualisation in children’s social care 10.12.18, Coram, London
What the talk will cover
• Completing a national study on the contribution of supervision orders and special guardianship to children’s lives and family justice’*
• Will draw on the issues relating to supervision orders
• Study uses both national (Cafcass) administrative data and local authority casefile data
• We will examine the pros and cons of each data source
• Central question
– are there any messages regarding data collection and usage from our study that will be of benefit to local authorities?
– Could anything be done differently by local authorities?
*Funded by the Nuffield Foundation
Aims of the study
• Study has used Cafcass (England) administrative database to provide the first national analysis of supervision orders and special guardianship orders:
– to ascertain their use over time and by region
– Their risk of breakdown
• evidenced by children returning to court for further S31 proceedings because of significant harm
• Case file study in 4 local authorities
– 210 children from 127 families
– Cases collected from April 2013-March 2015
– Tracked for 4 years after SO was made to follow up child outcomes
• Both our data sources use administrative data (i.e. not collected for research purposes)
National administrative data
Source: https://mva.microsoft.com/en-us/training-courses/sql-database-fundamentals-16944
Use of legal orders over time
0%
5%
10%
15%
20%
25%
30%
35%
40%
2010/11 2011/12 2012/13 2013/14 2014/15 2015/16 2016/17
Perc
enta
ge o
f ch
ildre
n
Year S31 proceedings ended
CO
SGO
PO
SO
RO/CAO
ONO
Designated Family Judge area variation in the use of supervision orders
0%
5%
10%
15%
20%
25%
30%
0 500 1000 1500 2000 2500 3000 3500 4000 4500
SO
rate
as a
pe
rcen
tage
of S
31
ch
ild p
roce
ed
ings
Number of S31 child proceedings
National rate 95% control limit 99.7% control limitLONDON MIDLANDS NORTH EASTNORTH WEST SOUTH EAST SOUTH WEST
The pros and cons of the Cafcass dataset for local authorities
The pros: a very rich source of long and thin data
• Can help LAS understand the national picture on use of SOs and where they fit into it.
– Is your LA in line with the national/regional picture re usage of SOs over time? Is it an outlier?
– Are return to court rates in line? Different?
– It starts a conversation
The cons: can’t shed light on pathways to further S31 proceedings
• Can’t tell us what happened at the end of proceedings if the case did not return to court
• If case returned, it can’t tell us what happened between proceedings, other problems & triggers
Children on supervision orders - tracking over time (child problems)
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Pregnant
Self Harm‡
Absconding
Risky Sexual Behaviour‡
Autism
Substance Misuse‡
Offending‡
School Exclusion‡
Learning Difficulties‡
School Attendance Concerns‡
Special Educational Needs‡
Sexual Abuse†‡
Developmental Delay
Physical Health Problems‡
Emotional & Behavioural Difficulties‡
Physical Abuse†‡
Emotional Abuse†‡
Neglect†‡
Start of proceedings End of proceedings Follow up (4 years)
Children on supervision orders - tracking over time (exposure to parental problems)
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Prison†
Physical Disability†
Physical Health Problems†‡
Learning Difficulties
Offending†‡
Alcohol Misuse†‡
Drug Misuse†‡
Financial Difficulties†‡
Housing Difficulties†‡
Lack of Support Network†‡
Mental Health Problems†‡
Domestic Violence†‡
Relationship Difficulties†‡
Non Engagement†‡
Start of proceedings End of proceedings Follow up (4 years)
Child maltreatment vs parental problems during the supervision order
0%
10%
20%
30%
40%
50%
60%
70%
0 1 2 3 4 5 6+
Pro
bab
ility
of
child
mal
trea
tmen
t
Number of parental problems
The pros and cons of the intensive case file datasets for local authorities
The pros
• A rich data source on a wide range of problems
• Helps us understand the inter-relationships between problems and over time
• Can fill in many of the missing links to help understand why the case went back to court and which cases had good outcomes
The cons
• Case numbers are small
• Getting the data can be difficult and time-consuming because it’s not structured
• It’s not possible to establish what is missing data or not recorded because there wasn’t a problem
Tracking recurrence of neglect for children on SOs: data issues • If the case was dealt with or escalated to child
protection, then neglect and abuse were tracked by the LA using Working Together framework.
• But children on supervision orders are mostly dealt with as children in need
• We did not find that neglect data was routinely recorded
• The result: neglect rates may be underestimated from LA data
• Neglect was an important pathway for return to court
How we handled this problem
• Used the CAFCASS and NSPCC neglect tool as a systematic way of tracking neglect which:
– divides neglect into 4 main sub-areas (physical care, safety, emotional and developmental care)
– differentiates between mild, moderate and severe neglect
– But it’s not a standardised measure
• Read every record to categorise the cases but time-consuming and impractical
• Solutions?
– Develop ‘a form’ which the LA fills in with categorical data?
– Place all children on SOs on child protection plans rather than CIN?
Issues around services data: the need for structured data • Duty of the SO is to ‘advise, assist and befriend’
• Was difficult to know if services set out in the court care plan were offered, received & whether the parent attended, partially, fully or disengaged
• The data was not routinely available in the Children in Need reviews
• Why it matters
• Issues:
– Can this data be collected?
– Where should it be recorded?
– How should it be classified?
Discussion points and conclusions
• If we are to be able to understand pathways and use data to best effect to protect children and promote their well-being are there more systematic & structured ways of collecting the data?
• How to prioritise what data should be collected in light of scarce resources?
• It’s the start of a conversation!