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.

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.

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.

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.

Jaime Delgadillo, Kim de Jong, Mike Lucock, Wolfgang Lutz, Julian Rubel, Simon Gilbody, Shehzad Ali, Elisa Aguirre, Mark Appleton, Jacqueline Nevin, Harry O'Hayon, Ushma Patel, Andrew Sainty, Peter Spencer, Dean McMillan.
Feedback-informed treatment versus usual psychological treatment for depression and anxiety: a multisite, open-label, cluster randomised controlled trial.
Lancet Psychiatry, 5,564-72. doi: 10.1016/S2215-0366(18)30162-7.

Most Popular Now

Do Fitness Apps do More Harm than Good?

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts may...

AI Tool Beats Humans at Detecting Parasi…

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially transforming how labs diagnose...

Making Cancer Vaccines More Personal

In a new study, University of Arizona researchers created a model for cutaneous squamous cell carcinoma, a type of skin cancer, and identified two mutated tumor proteins, or neoantigens, that...

AI can Better Predict Future Risk for He…

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack. The study, conducted by an international...

A New AI Model Improves the Prediction o…

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the...

AI System Finds Crucial Clues for Diagno…

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to interpret quickly...