This commentary examines publicly available information on 2017–2018 outcomes in the UK government’s Improving Access to Psychological Therapies (IAPT) programme, a National Health Service (NHS) primary care mental health programme in England. In that year there were 1.4 million referrals into IAPT and over 500,000 people completed a course of treatment. The IAPT database collects routine session-by-session outcome monitoring data for this population, including outcomes for depression and anxiety in a stepped care model which includes a range of psychological therapies, among them Cognitive Behavioural Therapy (CBT) and Person-centred Experiential Therapy, known in the IAPT programme as Counselling for Depression (CfD).
In 2017–18, 32% of all referrals were for anxiety and stress disorders, 26% for depression, and 35% were unspecified. The definition of treatment completion is receipt of 2 sessions or more and on this basis 60% of all referrals in 2017–18 did not complete treatment, predominantly because they failed to attend the initial appointment, or ended after only one session. Four years of data on outcomes for CBT and CfD suggests these therapies are broadly comparable in terms of both recovery rate and average number of sessions, though the number of referrals to each therapy varied widely. Data on treatment choice and satisfaction was favourable but there were issues with low return rates and invalid data. Information on outcomes for ethnicity, sexual orientation, disability and religion, as well as a measure of local economic deprivation, indicate lower outcomes for a number of patient groups. Data on employment status outcomes suggest little overall change, including for the category of those on benefits payments.
The data published alongside the annual IAPT reports mean there is an increasing amount of information in the public domain about IAPT performance, but it is time consuming to extract and evaluate. This report highlights a number of points of concern which suggest the need for improvement on multiple axes. We suggest that improved researcher access to the huge IAPT dataset can allow for more detailed evaluations of IAPT that can inform policy/decision-making to improve outcomes for clients.