A study has found that a form of web-based feedback technology known as Outcome Feedback, which enables therapists to accurately monitor how patients with depression are coping, can reduce the probability of deterioration during psychological treatment by 74%.

The largest controlled trial of its kind, the study is used data from over 2,000 mental health patients treated across multiple NHS Trusts in England.

Roughly half of the patients who are offered psychological therapy as a form of treatment for depression and anxiety on the NHS respond well to the treatment but up to 10% get worse.

Outcome Feedback was developed by an international team of researchers from UK, German and Dutch Universities, in partnership with the patient case management information system PCMIS which is widely used by mental health services. The team has since received a grant from the Wellcome Trust to implement the software across the NHS and also help create an e-learning programme to train NHS therapists to use the technology effectively.

The technology uses patient feedback to rapidly identify the patients who are at risk of deterioration. It does this by tracking their symptoms and monitoring treatment responses.

Lead author of the study Dr Jaime Delgadillo, who conducted the research while at the University of York, said: “There are many complex reasons why some patients get worse during treatment, including difficult life circumstances and sometimes unresolved difficulties in their relationship with their therapist.

“Patients who don’t respond well to therapy usually drop out of treatment after only a few sessions. The outcome feedback technology we developed accurately identifies problems early on and allows therapists to be more in tune with their patients’ difficulties and obstacles to improvement.”

The technology uses data from weekly patient questionnaires to measure the frequency and intensity of depression and anxiety symptoms. The therapist then enters this information into the patient case management system, which plots a graph showing changes in patient symptom levels from week to week.

The system is able to search for other patients with similar symptoms to assess if the way a certain patient is responding to treatment is typical and can flag up patients that are not on track. This allows therapists to intervene early and adapt treatment plans, while continuing to track the patient’s progress.