The Datamonger
Etazo Performance Data's newsletter
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Dear <<First Name>>
Introduction and update
It’s been a busy few months for Etazo and our focus has largely been on supporting organisations in making sure they have the right performance frameworks. In this issue of The Datamonger we look broadly at how disadvantage affects children; either in the looked after children system, through mental health problems, or through offending, and link that to recent research on adults with severe and multiple disadvantage.
Do get in touch if there’s anything with which we can support you, or if you have any comments on this issue.
Georgia and Jo
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In this issue
~ Data publications
~ Requesting data from data teams
~ Etazo researches:
Independent visitors
Severe and multiple disadvantage
Children Looked After and
Offending
CP plans and deprivation
CAMHS data
~ Useful links
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Requesting information from data teams – tips to get the best service
- Check what you already have first – perhaps the information you are looking for is in a previous report.
- Talk through why you need the information you’re asking for and what you’re going to do with it. This helps the team to provide the right sort of information and in the right format. There may be something you haven’t thought of that’s relevant to what you’re looking at. Understanding the point of what you’re asking for may also help the data team to learn what the service needs, and to prioritise it in their workload – we all prefer to do tasks that we see a point for.
- Define your terms as clearly as you can. For instance, what does “in time” mean? If you want to know what % of assessments have a particular outcome, do you want to exclude assessments without a recorded outcome from the denominator? Xx another example
- If you want the data in a particular format, be clear about that at the start.
- Refer to national definitions when you can.
- Give as much notice as you can and be aware of peak pressures on data teams (eg national return deadlines, monthly or quarterly internal deadlines).
- If you think you might want a further breakdown of the same data (eg by gender or team), mention this at the start of the request so that the data staff can make sure they include the additional data rather than having to add it in later.
- Appreciate your data teams – they will often pull out all the stops to get what you need.
- Use the information to improve services and let your data teams know you’ve done so.
- If it’s appropriate, build on the information by requesting future updates.
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Etazo researches
Independent Visitors
The National Independent Visitor Data Report (2016)
Barnado’s, The Tudor Trust and National Independent Visitor Network
Barnado's
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This relatively short report (29 pages) is based on a Freedom of Information request made to local authorities.
Local authorities have a responsibility to consider whether Children Looked After (CLA) should be offered an independent visitor (IV) when contact with the child’s family is infrequent, or where the LA considers it may be in the child’s best interests. (See www.familylawweek.co.uk for a discussion of the legislation and guidance.)
The report authors found that most LAs outsource their IV services, with only a fifth managing the services internally. Around 2,200 children nationally have an IV, 3% of the CLA population. 2% of children are on a waiting list. 12% of LAs have no children currently matched with IVs (excluding the Isles of Scilly, where there are currently no CLA).
The report discusses the reasons why children may be waiting to be matched with an IV, and the eligibility criteria being used by LAs. It looks at the benefits of extending the IV service to care leavers. And it makes recommendations to the DfE, LAs and providers of IV services about how to increase the use and impact of IV. Data colleagues will note that one of the recommendations is that the DfE collects data on children who have an IV.
Severe and multiple disadvantage
Hard Edges: Mapping severe and multiple disadvantage (2015)
LankellyChase Foundation
This report (48 pages) from the charity the LankellyChase Foundation uses a range of data sources to look at people experiencing severe and multiple disadvantage (SMD). They define this as adults who meet at least two of these three criteria: offenders or in contact with offender services, misusing drugs or alcohol, and homeless. They used three national datasets: the Offender Assessment System, the National Drug [and Alcohol] Treatment Monitoring System, and Supporting People and In-Form databases for homelessness. They also look at data from the Multiple Exclusion Homelessness (MEH) survey in 2010.
The report authors estimate that, over a year, around 58,000 people meet all three criteria (are offending or in contact with offending services, misusing drugs or alcohol and are homeless). About two-thirds of people offending are also misusing drugs or alcohol or are homeless, or both. Similarly, about two-thirds of people who are homeless are also offending or are misusing substances, or both. The pattern is a bit different for people who misuse substances, depending partly on differences between people who misuse drugs and those who misuse alcohol. This is discussed in more detail in the report.
In the average LA, the authors estimate there will be around 1,470 people with SMD in a year, but they found a lot of variation across the country. Rates of SMD are much higher in northern urban areas (eg Middlesbrough and Manchester), in coastal areas (Blackpool, Bournemouth) and in central London Boroughs.
People experiencing SMD are most likely to be white men aged 25-44. Data from the MEH Survey indicate that around 18% were in care as children and 25% report being abused as children. The Offender Assessment System indicates that 19% were first convicted aged under 14 and that 47% had significant absence from education. The report discusses the possible causes of SMD in some detail.
Most of these people are not living in families with children – perhaps around 10%, but in total the report authors say that almost 60% either live with children or have contact with their children. They conclude that children related to people with SM are “potentially affected by chaotic lives, economic and housing insecurity, and social stigma”, as well as being at increased risk of abuse or neglect.
Children Looked After and Offending
In Care, Out of Trouble: How the life chances of children in care can be transformed by protecting them from unnecessary involvement in the criminal justice system. Report of an independent review chaired by Lord Laming
Prison Reform Trust
This lengthy report (174 pages) is the result of Lord Laming’s review into CLA in the criminal justice system. One of the sources of information the report panel used was a request to all LAs for information about the number and proportion of CLA who had offended or were in custody. Slightly under 60% of LAs responded. The panel also looked at YJB data based on the Placement Information Form and at HM Inspectorate of Prisons’ (HMIP) survey data for 2014/15, as well as the CLA return to the DfE.
Much of the report is based on qualitative evidence to the panel from children, from adults who were in care and from professionals. Data colleagues will be interested in the direct findings from the data. It is well known that children looked after are much more likely to offend or be in custody. The report has been able to make these figures much more striking and to add detail. They found that 1% of CLA were in custody at the end of 2014/15, and estimate that “up to half” of all children in custody are, or have been, looked after. Where CLA do come to the attention of the criminal justice system, they appear more likely to be convicted rather than cautioned than their peers who are not looked after.
The report also found that CLA in custody have different experiences to children who are in custody and not looked after. Anecdotal evidence suggests that they are more likely to be detained overnight in police stations. Figures from HMIP’s survey show that CLA are less likely to be visited, more likely to be restrained whilst in custody, more likely to report that they had felt threatened or intimidated by other children and more likely to have been placed on report. They were also more likely to consider themselves disabled, to have mental health problems and substance abuse issues. This report makes challenging reading in the light of the research discussed above on severe and multiple disadvantages; these children have many of the factors which contribute to SMD in adults.
As well as practice recommendations, Lord Laming recommends major changes to the way in which information about CLA who offend is collected. This includes collecting data on offending of all CLA, not just those looked after for a year or more. He notes that data are especially poor around ethnicity, gender and children with learning disabilities. He recommends that HMIP should publish disaggregated data on children in custody who are or were looked after, and that the DfE and YJB should work together to publish regular data about CLA in the justice system, broken down by ethnicity, faith, gender and disability. There is also a useful table from the YJB of local good practice, much of which relates to data and information sharing.
Child Protection Plans and deprivation
Is there a relationship between deprivation and need? (2016)
Neil Powling
CP and Deprivation Clustering
Worth looking at this data presentation by Neil Powling (independent data analyst and fellow Google Group member). Neil has reviewed the data on rates of children subject to CPP and looked at how it correlates with the level of deprivation in individual LAs. His interactive graphs show that although the rate of CPP is linked to the level of deprivation, the relationship is much weaker than it was 10 years ago – and the variance across LAs in the number of CPPs is much more than it was. The rate of CLA, on the other hand, continues to be strongly linked to deprivation. Neil can be contacted on neilpowling@googlemail.com.
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CAMHS data
Mental Health Services Monthly Statistics: Final July, Provisional August 2016 (20 October 2016)
NHS Digital
Since January this year, data on children and young people’s mental health services (CAMHS) have been submitted by providers to the NHS as part of the Mental Health Services Monthly Statistics. A separate data file for children’s MH services has been published each month since May with data at provider, CCG and national level, so we now have some information to use to start looking at services locally.
These datasets are currently classed as experimental services, and are not yet at all easy to use and interpret. The executive summary usefully discusses some of the data issues and gives pointers to areas where analysts could easily be tripped up. For instance, some information is at service level and some at person level (some people use more than one service). Some information is less reliable than others – ward stay data is an undercount of the number of people recorded in hospital, but both measures are given as, where ward stay data are available, they enable additional analysis such as distance between ward and home. Note also that some data on children is in the main MH datafile, not just the CAMHS file, and that some older young people may be receiving support from Adult MH rather than CAMHS, even if they are under 18. The metadata file is helpful in unpicking some of these issues. In some cases the executive summary seems to contradict itself (figures of 1,273,233 and 1,220,257 for the number of people in contact with MH services at the end of July). Considerable amounts of local data are suppressed. Note also that CCG figures are (we think, and are checking with NHS Digital) based on activity by home residence, or GP surgery, of child, not necessarily activity commissioned by that CCG.
We suggest putting a decent amount of time aside if you are trying to get out useful local level information, and, ideally, talking to the local data providers about any accuracy or reporting issues.
We’ve picked two CCGs more-or-less at random (we avoided ones where most of the data are suppressed) to show the sort of local level analyses one can start to put together from the data. This uses figures from the May and July final children’s datafiles (data are published first as provisional and then as final). Our comments should not be taken as analysis of performance in these localities, as we don’t know the local context there, but as indicative of the possibilities in the data.
We can see in both these CCGs that the number of people in contact with CAMHS at the end of the month went up:
| Month |
CCG |
People in contact with CAMHS (CYP01) |
| May |
Hartlepool & Stockton-on-Tees |
2395 |
| May |
Warrington |
505 |
| July |
Hartlepool & Stockton-on-Tees |
2410 |
| July |
Warrington |
525 |
It would be possible to express this as a rate per 10,000 of the population of the age group for CAMHS (probably 0-18, depending on local policy). This enables local areas to start to look at how their levels of need and service provision compare to similar CCGs.
We can also look at the flow of new referrals and referrals closed:
| CCG |
People with referral starting in July, aged 0-18 (MHS39a) |
People discharged from
a referral in July,
aged 0-18 (MHS57a) |
| Hartlepool & Stockton-on-Tees |
350 |
385 |
| Warrington |
115 |
95 |
You can see that in July in Hartlepool & Stockton more referrals were closed than opened, whilst in Warrington the reverse is true. Although there are likely to be many factors affecting the numbers of referrals and of closures, looking at patterns over time either at CCG or provider level can give an indication of how services are managing demand and whether levels of need are changing.
There are some additional measures where figures are very rarely available in the published dataset at CCG or provider level, because low numbers are suppressed. In these cases, professionals in local areas should be able to get actual figures for their region from CAMHS providers, A key one might be the number of bed days spent by under 18s on adult wards (MHS24a+b+c). In May this year it was 665 nationally, and in July 946. The apparent increase nationally may represent more complete data rather than changes in performance. Local areas might also want to look at the data on specific vulnerable groups referred to CAMHS. Nationally in May and July these were:
| Month |
Looked after children
(MHS40) |
Children and young people
with a child protection plan
(MHS41) |
Young carers (MHS42) |
| May |
364 |
129 |
83 |
| July |
283 |
125 |
69 |
The largest of these groups, children looked after, makes up around 2% of all referrals to CAMHS in the period. Again, staff in local areas should be able to access their own data via providers to see what the patterns are in their area.
Another key measure may be the reason appointments did not take place. The data allow you to see the proportions of appointments where service users did not turn up (DNA) compared to those cancelled by the service provider.
Although, as we’ve said, the data now published can be frustrating to work with, having them available is a really important step in allowing us to understand need, service provision, and hopefully eventually outcomes, for this vulnerable group of young people.
Other CAMHS data sources
It’s worth looking at local Healthwatch websites to see if they have reported on CAMHS. Several Healthwatches have done this and their reports often contain data as well as qualitative information (eg Healthwatch Wakefield)
The Child Health Profiles give information on numbers and rates of hospital admissions for mental health and self-harm reasons, but the 2015/16 data will not be available until May 2017.
Public Health England
The national review of Local Transformation Plans contains national and regional data.
NHS England
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Useful links
Watchsted – this free online resource from Angel Solutions (colleagues in Education data will know the company) provides maps, charts and word clouds of recent school inspections by school type and judgement. The site says analysis of inspections of other provider types is coming soon.
Ofsted’s Data View – again, just about schools so far, but useful for looking at inspection judgements over time.
Consultation on the future of social care inspection – contribute your views here by 9th September.
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Children's Social Care Data Google Group
We administer the email group for local authorities to discuss children's social care data. Membership is recommended by the DfE and Ofsted as a good resource for performance staff to discuss interpretation of data, definition of indicators and year-end returns, and is of course completely free.
One group member recently told us that the group has been "a real help" with tips and pointers, such as problems with the DfE website and experiences of inspections. The group member also said, referring to end of year returns, "It’s been reassuring to know that as I plough through 903 errors, others are going through the same process".
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