A research project from the University of Oxford analysed outcome data from IAPT patients to pinpoint aspects of services themselves that could predict variability in clinical results.
The project used publicly available data to identify predictors of variability in clinical performance. It then analysed the outcome data released by NHS Digital and Public Health England for the 2014–15 financial year, and developed a predictive model of reliable improvement and reliable recovery. It then tested whether these predictors were also associated with changes in service outcome between 2014–15 and 2015–16.
Analysis found that there were five organisational characteristics that predicted clinical outcomes, and that three of these – the percentage of cases with a problem descriptor, number of treatment sessions, and percentage of referrals recorded – positively correlated with outcomes, while waiting times and missed appointments negatively correlated with outcomes.
The paper stated that while efforts to improve outcomes have traditionally focussed on the development of new treatments, the way psychological therapy services are implemented could be similarly important.
IAPT’s session-by-session outcome monitoring system enables IAPT practitioners to obtain symptom scores before and after treatment, and the paper suggests that mental health services in the UK and abroad could benefit from adopting IAPT’s approach to recording and publicly reporting clinical outcomes.
Do you analyse your own service data for quality improvement? What sorts of things have you found that improve patient outcomes? We’d love to hear about and share your work, so get in touch.
