by Dr. James Reed, Physician Executive, InterSystems
Access to timely, consistent mental health care remains a major challenge for many people across England. A recent Care Quality Commission survey of more than 14,000 people using community mental health services found that 40% reported waiting too long for care, with a third of respondents saying they have waited three months or more for their first treatment, and four in ten people saying they received no support at all while they waited.
Long waiting times are a clear indication of the amount of pressure that mental health services are under as they struggle to meet the demands placed upon them. Services are constantly looking for ways to reduce this pressure, and in particular to remove avoidable delays (such as waiting for clinical information). Mental health services were early adopters of Electronic Patient Records (EPRs) to assist with information sharing inside their organisations.
The next logical development now, is to use shared care records to bring information together from across the whole health economy (including crisis teams, community workers, GPs, and acute hospitals) to provide a unified view of a patient’s health pathway. This reduces the need for repeated questioning of patients, flags safeguarding or medication risks in real time, and gives clinicians more capacity to listen to what each person wants from their care. With the full picture at hand, clinicians can shift their focus from chasing information to hearing what patients value most.
Recent developments in technology are offering new opportunities to reduce time spent on routine tasks, such as transcribing notes or writing reports. Digital tools open opportunities for more meaningful conversations, and these discussions often uncover underlying factors that lead to better treatment outcomes. Live transcripts and summaries of clinical encounters remove much of the perceived administrative burden which can come with digital systems, and instead they will become resources that strengthen decision-making and support genuine empathy at the bedside, or during virtual appointments.
Once good quality clinical information is captured routinely with minimal effort, it will become possible to explore what insights can be gained from the data and how this can be used to improve the nature and quality of care delivered. There are opportunities to introduce AI-driven analytics to spot patterns, predict patient outcomes, and guide care strategies.
Predictive models can flag individuals at higher risk of crisis or relapse, prompting earlier interventions. Such capabilities work best in environments with reliable, well-established workflows and strong data governance, ensuring that technology reinforces rather than complicates clinical practice.
Building solid foundations for personalised care
However rich the functionality of the underlying technology, these new advanced systems won’t succeed unless robust processes are put in place so they can function optimally and deliver enhanced levels of patient care. Establishing clear and understandable clinical processes and workflows not only makes life easier for the staff delivering the service, but also allow the systems to be designed to fully support those workflows and ultimately deliver a better standard of patient care.
In addition to this, AI-assisted models, built on EPR data, can effectively identify patients that are displaying heightened risk markers and are in need of additional specialised support. By correlating risk factors with hospital stay patterns, analytics tools could provide recommendations around preventive measures such as extra community follow-up calls or other crisis intervention which could help reduce potential escalation.
Personalisation in care is essential to ensuring that patients are given the level of support they need. However, it is dependent on having technology that is both fuelled with accurate, up-to-date data and that is accessible to diverse patient populations. While some individuals feel comfortable using online portals for therapy plans and care instructions, others prefer printed summaries or in-person explanations. The key is to provide a broad choice of platforms and services – for some people, a video call or even a text message exchange is more accessible than a face-to-face appointment and could yield better clinical outcomes.
Designing digital platforms with multiple user needs in mind guards against disparities in care. Equally, staff at all levels should benefit from concise training that demystifies new systems. Clear language, whether explaining encryption protocols or AI-based alerts, fosters trust and smoother adoption – allowing the power of the technology to be best utilised.
Empowering clinical teams for sustainable impact
Achieving long-term success in caring for patients suffering with mental illness hinges on confident frontline mental health professionals. Continued system training which is repeated regularly is of great importance, so that staff are fully informed of the latest developments and know to use them. Targeted training sessions that illustrate real-world scenarios, such as detecting a subtle drug-interaction, or suicide risk warning during a busy shift, highlight how digital systems can boost patient safety. Feedback loops allow teams to request improvements and refine workflows, increasing enthusiasm for innovation. Strong clinical leadership of clinical systems, working alongside IT and technical departments is also of great importance.
Leadership can set the tone here by promoting technology as an enhancer of humane, patient-centred mental health care. If digital platforms are viewed primarily as cost-cutting tools, clinicians will resist them. Additionally, when staff see how integrated data and streamlined record-keeping reduces errors, and helps keep patients safe, acceptance will grow.
Over time, shared data enhances collaboration, improves continuity of care, and clarifies population-level trends, allowing resources to be deployed more effectively. Well-trained teams equipped with user-friendly solutions ultimately shorten wait times, reduce administrative burdens, and enable deeper person-to-person engagement.
Balancing innovation and compassion
The path to better mental health care involves combining modern solutions with time-honoured values. Recent developments in technology, including the use of AI, will allow staff to use tools
to augment personal interaction rather than replace it. The stereotype of the staff member spending more time looking at their computer rather than the patient will be replaced by a direct interaction where the technology takes a back seat, without compromising the quality of the information gathered. By focusing on empathy, robust training, and solid clinical processes, healthcare organisations can deliver safer, more efficient, and more compassionate mental health services.
Real success depends on improving clinical outcomes for patients with serious mental illnesses, who are often among the most marginalised and vulnerable groups in society. There is a clear opportunity to use technology to improve the quality of care delivered to them, which will in turn improve the outcomes and reduce distress, suffering, and clinical risks. When technology and the human element reinforce each other, rather than working in isolation, patients will receive the best possible standard of care, which is what all working the field aspire to deliver.
