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In the face of a global pandemic, IAPT has scored some small gains in performance in the past year. Sadly, that’s in the context of a depressingly familiar pattern of high levels of attrition. Here, we present the broad findings, and profile the IAPT Interactive Dashboard that allows you to explore your local data.
The latest data: overall referrals and endings
In the year 2020 – 21 a total of 1,456,446 new referrals were received. This figure was down by 14% from 2019 – 20. Given the impact on services of the pandemic over that period, this is hardly surprising. 1,024,014 of those referrals (70.3%) are recorded as having entered treatment, a figure which has remained relatively consistent over the past five or six years.
In the same period 1,439,603 referrals were recorded as having ended. This figure represents a 12.6% reduction over the previous year.
As a side note, this year the challenge of analysing and presenting this data has been significantly more difficult than in previous years. 2019 – 20’s data was accompanied by 19 pages of analysis presented in PDF format. That’s absent so far this year. Maybe it’s still to come. For now all we have is top line figures from the NHS Digital website, some virtually impenetrable data sheets, and an admittedly cool interactive dashboard which we encourage you to explore (more on this later).
How did clients move through the system?
Other key data, (some represented in the graphic above and graph below) are as follows:
Of the 1,439,603 that ended in the year, 412,449 (28.7%) ended without having been treated by the service. That’s a reduction of three percent on 2019 – 20.
A total of 1,027,154 referrals (71.4%) that ended were seen for treatment. This represents a nearly five percent increase in the numbers of referred clients seen for treatment over the previous year.
Of those seen, 634,649 (61.8%) were recorded as ‘Ended having finished a course of treatment’ (i.e. had two or more treatment sessions). This figure is a more than six percent increase on the 2019 – 20 year.
392,505 (38.2%) of referrals that were seen for treatment ended having had only one treatment appointment. This represents a just over six percent decrease over the previous year.
Of the 634,649 clients that had two or more sessions, 597,257 (94%) were at or above ‘caseness’ level and could potentially achieve recovery (see definitions below).
Of the 597,257 clients above the caseness threshold, 306,990 were recorded as having moved to recovery. This represents 51.4% of eligible referrals, a 0.3% increase on the previous year.
What’s gone up, gone down, and what’s stayed the same?
In the context of an overall reduction in referrals and ended cases of 14 and 12% respectively, there are some small but encouraging signs in the data for 2020 – 21. The proportion of referrals that entered treatment was fractionally up on the previous year. The proportion of referrals that ended without treatment fell.
Of the clients that started a course of treatment, a greater proportion of those that had two or more sessions ended it. And of those that ended treatment and were at the level of caseness, a fractionally higher proportion recovered that in the previous year.
Small gains in the context of still woeful attrition
Let’s not get ahead of ourselves. The small improvements that we’ve seen in the data over the past year don’t represent the sunlit uplands that we were promised a decade and more ago. They come in the context of a still depressingly high pattern of attrition that we’ve highlighted before.
Overall, nearly four in ten clients that start treatment have one session only. I’m not prepared to believe that one session was all they required. Clients that achieved recovery (at 51.4%) only slightly outnumber those that did not. They also represent just 21.3% of those that were referred to IAPT, and 29.9% of those that started treatment.
It’s important that we don’t lose sight of the people behind these statistics. Each of them is a person, with a particular story, and a particular set of needs. IAPT met the needs of some, but arguably not of the majority. There is still a mountain to climb.
Go explore the Interactive Dashboard!
While the lack of a written report to date is frustrating, we’re going to give a big shout for the very cool interactive dashboard which has been added to the published data in the past two or three years. This has enabled some much finer grained analysis of the top-level data than has previously been easily possible.
Over the years I’ve spoken to many services interested in knowing how their performance data compares to local IAPT provision. Now, if you want to know the recovery rates for your local Clinical Commissioning Group, or for a particular local provider, this is where you can find out.
Similarly, if you want the mean waiting time for referrals entering treatment in your area, or the percentage of clients finishing treatment that waited less than six weeks, that information is available through the dashboard. It takes a little getting used to, but with practise you can learn a great deal about your local picture. We’ll be profiling its use further in a forthcoming blog.
As ever, we’d love your thoughts on any of the points above, and to hear your perspectives.
4 replies on “Small gains disguise a miserable picture: IAPT 2020 – 21”
I don’t understand how they’ve arrived at the statement of 7.5 sessions of treatment on average, up from 6.9 sessions in 2019-20 looking at the mean number of therapy figures by therapist role figures, page 25, there’s an 8 but most seem quite low, can someone please clarify?
I wish I could help you Michael. I’m guessing it’s the same calculation as shown in the PDF report for 2019 – 20: “The proportion of referrals starting treatment within 6 weeks, mean treatment sessions, and the recovery rate are based on referrals completing a course of IAPT treatment in the year.” That covers the 6.9 sessions from 2019 – 20. Without this for reference it would be anyone’s guess, however!
one methodology doc I just read said IAPT put a new method in place to but referrals on hold, so not to count them as live between time 0 to time 1 for treatment. If this is the case, time to treatment from referrals is meaningless.
Also, as I and others have written about in papers, the meaning of ‘moving to recovery’ is pretty meaningless, if you have anxiety disorder every notch down the ladder of scores means something to you – no doubt, but the patient should be involved in deciding if they have recovered. IF you take a run of the mill CBT trial, in academia, even with a clinical setting, scores fall but once you remove the CBT they rise, showing strong treatment effects. You could score a 9 and be deemed no caseness for depression at end of IAPT treatment, if lucky to get full CBT, but leave care and be a 10 overnight. This is a problem for all psychotherapies ofcourse, but when we shine a light on the meaning of ‘moving to recovery’ I think we can clearly see an effort by IAPT to present a mkind of marketing gimmick, rather than scientific data on recovery. IAPT are fighting for funds, its new shift is to employment return, and again I worry here about the focus of therapy trying to get you to state you returned to work, or the pressure on data counters to do the same. We have seen CBT therapists talk about the pressures put on them to fudge data. In areas I look at, LTCs, one cant say a patient is recovered based on depression and anxiety scores alone – as IAPT do – so lots of other problems besides the obvious small improvements seen in data IAPT present to us.
Thanks for the comments Keith. It sounds like ever more inventive ways to obscure the real picture of what’s happening in the flow of referrals through the system! I’m not surprised – the level of reporting in the annual reports has shrunk hugely over the years I’ve been watching this.
I agree with you on the issue of recovery as a definition. Before IAPT I always understood recovery to involve both clinical AND reliable change, which is an altogether higher bar for change. So I think the IAPT definition is not only confusing but potentially misleading.