Right care, at the right time: How data-driven technologies can help bridge the access gap for mental health services
This week Reform published a research paper examining the role that data-driven technologies will play in improving mental health services. The report finds that data-driven tools, such as Artificial Intelligence (AI), are not a ‘silver bullet’ to the challenges facing the NHS but hold great potential to help address gaps in provision, improve access to services and increase efficiency.
An area where data-driven technologies could have a significant impact is in the planning and allocation of care. Out-of-area placements (OAPs), where patients are treated outside of their local area due to capacity issues or lack of beds, are a longstanding problem in mental health services. In England, over 800 patients access treatment outside of their local areas, with 350 travelling between 100 to 200 km to get the care they need. OAPs are expensive to the NHS, costing the Service a hefty £112 million last year.
They also have a huge impact on patients who will often see their recovery delayed when treated outside of their communities. Increasingly data-driven technologies are being adopted to stamp out inappropriate OAPs and treat patients closer to home. The MERIT programme uses electronic patient records to estimate the demand for services, re-balance resources across the area and allocate beds to those with the greatest need for treatment. Delivered as a partnership between four mental health trusts in the West Midlands, the programme is not only about allocation and prioritisation, but about the intelligent use of data to create better clinical pathways by understanding how patients ‘move through the system’.
Data-driven tools can also help bridge barriers in service provision. Waiting times for Improving Psychological Therapies (IAPT) services have narrowed in recent years, with around 89 per cent of people starting treatment within six weeks from referral. Yet, these figures mask wide geographical variations in the length of time patients wait for assessments and treatment. Technology can provide clinicians with information to refer or ‘triage’ patients faster and to the most appropriate levels of support.
Contrary to what some suggest, this is not about an AI system making decisions on behalf of a clinician but about clinicians using data-driven insights to make better decisions. For instance, the NHS has begun trials of a conversational ‘chatbot’ to support patients experiencing symptoms of depression and anxiety. Using natural language processing, the bot can identify patterns, such as language associated with depression, helping GPs determine which patients require a referral to specialist services.
The system also makes routine tasks more efficient, saving time for both patients and practitioners. Paper-based processes, such as PHQ-9 depression test questionnaires, can be administered through the bot without patients having to attend the GP practice. Moreover, the bot is built as open source and in compliance with interoperability standards to enable integration with NHS systems.
The shift towards data-driven mental healthcare is happening. Many of these technologies are being trialled and tested within services and effort is being put into building a robust evidence base and promoting their adoption. If harnessed correctly, data and technology will change the way the NHS delivers mental health services. More importantly, they could help ensure that patients access the best possible care, at the right time.
This is not about an AI system deciding on behalf of a clinician but about clinicians using data-driven insights to make better decisions