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Jack Cattell

Jack Cattell

Get the Data analyst and PbR probation expert

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CRC Reoffending Rates: Who’s striving, who’s struggling?

Jack Cattell of Get the Data takes a deep dive into the first set of published reoffending rates from the new private Community Rehabilitation Companies.

Should we all move to the North West?

Last month the MoJ released the interim Community Rehabilitation Companies (CRCs) proven reoffending rates for cohorts that started orders or licences between October and December 2015. As it is now 12 months since the first payment by results cohort started, I thought it would be interesting and helpful to review the performance of the CRCs – the final results will be available in October 2017. If you don’t know, the CRCs are privately run probation services set up in 2014 to manage less harmful offenders and to reduce reoffending rates. As such, part of their payment from the Ministry of Justice is based upon how well they reduce reoffending compared to a 2011 baseline. If the reoffending rate increases the CRC’s contract could be terminated.

The payment mechanism is complex – see here for the important documents. The basics are that if the CRC’s reoffending rate is lower than the 2011 baseline rate, having adjusted any differences in offenders’ likelihood of reoffending, then the CRC will receive a payment. Being just 0.1% lower would not be good enough to trigger a payment – the CRC’s rate must be statistically significantly lower (I have not found in the public domain information on how significant the reduction must be – do contact me if you know of a source).

Not enough data have been released to estimate which CRC will receive a payment (the 2011 baseline rates have not been published for example) but there are enough published data to assess the relative performance of each CRC. Each CRC’s published reoffending rate cannot be directly compared because the CRCs’ offenders will present with varying likelihoods of reoffending. Fortunately the OGRS4 expected one year reoffending rates were published. With this information, I estimated what each CRC’s proven reoffending rate would be if likelihood of reoffending was exactly the same in company (the adjusted rate – I used the average OGRS4 rate across all CRCs which was 45.7%). The results are in the chart below.

Figure 1: Interim and adjusted reoffending rates in the 21 CRCS (Oct to Dec 2015 Cohort, reoffending rate to December 2016).

Table showing Interim and adjusted reoffending rates in the 21 CRCS
Source: Interim proven reoffending statistics for the Community Rehabilitation Companies and National Probation Service supporting tables January 2017. See table for bases.

There is a large 17.2% spread in interim proven reoffending rate in the MoJ data. This is reduced to a 9.5% spread in the adjusted reoffending rate. The lowest adjusted rate is in Merseyside (34.4%) and the highest is in Warwickshire & West Mercia (43.9%).  There appears to be regional clustering at the top and bottom of the chart. Three of the four CRCs with the lowest adjusted rates are in the North West – Merseyside, Cumbria and Lancashire and Cheshire & Greater Manchester – and the neighbouring areas South Yorkshire, Humberside, Lincolnshire & North Yorkshire, and Durham Tees Valley make up three of the four areas with the highest adjusted rates. This clustering could be due to police practice, the CRCs’ effective work, efficient court processes or in or an unknown factor altogether.

These results do not mean the providers in the North West can expect a payment to come their way. We do not know the baseline to which they will be compared and there is another 6 months of convictions data to be included (the proven reoffending measure includes offences within 12 months that are convicted within 18 months). Also there is likely to be an area effect that is not included in the OGRS4 measure but will be in the 2011 baseline rate. However, the differences do suggest that persons interested in how to reduce reoffending rates should visit the North West to understand if they are doing anything different there.

Table 1: Results in all 21 CRCs

Table Showing Results in all 21 CRCs

Source: Interim proven reoffending statistics for the Community Rehabilitation Companies and National Probation Service supporting tables January 2017.

Jack will be analysing each set of the CRCs’ proven reoffending statistics as they are published by the MoJ, so do please keep a look out for his posts.

2 thoughts on “CRC Reoffending Rates: Who’s striving, who’s struggling?”

  1. This is potentially interesting but I’m quite confused by the technicality of the account, which could do with a clearer account of how you made your calculations and what your variables were. Could you also clarify your terms of references, e.g, what are the interim re-offending rates, what is OGRS4 and what was the reasoning behind your methodology in making the adjustments as you did? You are to be commended for working through a slew of data with little meaningful information (e.g. The lack of baseline 2011 rates) and weasel formulations such as ‘adjustments for offenders’ likelihood of reoffending’, but the thicket of technicality simply reinforces the feeling that all is smoke and mirrors on this issue.

  2. Hi Mary

    The proven reoffending rate is an MoJ defined measure that uses police convictions data to state whether an offender committed an offence within 12 months of his/her order or licence commencing for which he/she was convicted within 18 months of the same date. Please see: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/541195/proven-reoffending-definitions-measurement.pdf

    OGRS4 is a NOMS predictor of likelihood of reoffending within 12 of commencing an order or licence. It is based upon offending history sourced from the police national computer. Please see this link for more information: http://socialwelfare.bl.uk/subject-areas/services-activity/criminal-justice/ministryofjustice/175154research-analysis-offender-assessment-system.pdf

    Adjusting the published reoffending rate using OGRS4 allows us to make a better (but not perfect) comparison of CRC performance. Each CRC’s cohort will present with a different risk of reoffending and any differences in reoffending rate might reflect this rather than varying performance.
    because each CRC’s cohort will

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