خانه / Science / Medical / New technology helps to improve treatment for NHS patients with depression

New technology helps to improve treatment for NHS patients with depression

“Outcome Feedback” uses patient feedback to rapidly identify patients at risk of deterioration

New technology helps to improve treatment for NHS patients with depression

A new web-based “feedback” technology which allows therapists to accurately monitor how patients with depression are coping has been found to reduce the probability of deterioration during psychological treatment by 74%, a new study has found.

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

Psychological therapy is offered to many people with depression and anxiety who seek treatment in the NHS, but while roughly half of these patients respond well to the treatment, up to 10% actually get worse.

Patients at risk

Known as “Outcome Feedback”, the new technology was developed by an international team of researchers from UK, German and Dutch Universities, in partnership with PCMIS, a patient case management information system used widely by mental health services.

“Outcome Feedback” uses patient feedback to rapidly identify patients at risk of deterioration by tracking their symptoms and monitoring their response to treatment.

The team behind the technology have now received a grant from the Wellcome Trust to implement the software across the NHS with the aim of improving the quality of psychological care. The grant will also enable the researchers to develop an e-learning programme to train NHS therapists to use the technology effectively.

In tune

Lead author of the study, Dr Jaime Delgadillo, who conducted the research while at the Department of Health Sciences at the University of York, and is now based at the University of Sheffield, 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 which measure the frequency and intensity of typical depression and anxiety symptoms; such as lethargy, low mood, disrupted sleep cycle, loss of appetite, restlessness, constant worry and difficulty relaxing.

Intervention

The therapist enters this information into the patient case management system, which plots a graph showing changes in the patient’s level of symptoms from week to week.

The system searches for other patients with similar symptoms to assess if the current patient is responding to treatment in a typical way, flagging up “atypical” cases that are not on track. Therapists can then intervene and adapt their plans for treatment, while continuing to track the patient’s progress using the feedback technology.

Co-author of the study, Dr Dean McMillan, Reader in Mental Health Services Research at the University of York, said: “this trial was made possible by our unique ability to link great ideas with the technology we have developed in the University of York. the PCMIS system has been developed to support the care of people with depression and anxiety in the NHS. We are able to test innovative methods of patient care using rigorous research methods.”

Co-author of the study, Professor Simon Gilbody, director of the Mental Health and Addiction Research Group at the University of York, added: “This is the largest trial of its kind and the results will lead to improvements in NHS care. The study is a result of the strong ongoing collaboration with our partner White Rose University – the University of Sheffield.”

source: University of York

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درباره ی Mohammad Daeizadeh

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