A practical consideration relating to palliative care emerged as politicians recently debated the ethical issues around assisted dying.
The parliamentary vote opened the conversation as to how we might improve the way we look after those nearing the end of life. Without getting into the ethics or politics of the central issue under consideration, it’s clear that the provision and delivery of palliative care remains a significant issue.
The current state of palliative care in the UK is – to put it mildly – far from ideal. Last year, for example, a report found the availability of end-of-life care to be “variable and inequitable” in England. This was exacerbated by increasing demand and workforce shortages.
Such a situation affects patient care but also puts a significant strain on the UK healthcare system. The financial implications are enormous. The charity Sue Ryder estimated that the total cost of hospice provision of palliative care services would average £947 million per year over the 10 years to 2032. If current trends continue, hospital-based palliative care costs could £4.8 billion by 2043.
Introducing technology
Without going into details, it was the provision of end-of-life care in a family setting which part-inspired the development of Digital Planning’s emerging Metis platform. Put simply, the experience exposed the inefficiency and waste of existing healthcare systems designed to support end-of-life care. There’s a large infrastructure, built with the best intentions. But it’s increasingly creaking.
This is why, for example, the Association for Palliative Medicine (APM) – speaking after the Parliamentary debate – reiterated the need for increased investment. APM President, Dr Sarah Cox, said more coordination is needed between hospitals, community NHS teams, care homes and hospices. “The UK is often held up as having the best palliative care in the world – but that is not the case any longer,” she added.
AI can clearly play a transformative role. Digital systems can analyse vast amounts of patient data, identify patterns, and provide valuable insights to healthcare professionals across different settings. They can also allocate limited resources. For instance, research is already showing how machine learning and other tools have significant potential to reduce the workload of palliative healthcare professionals. AI can automate routine tasks, allowing humans to instead spend more time on direct patient care.
There is an inevitable ethical consideration but – administratively – technology can help professionals become more productive. AI systems, for example, can reduce time spent on clinical documentation by up to 45%. This frees up time for direct human patient interaction. It supports more effective management of pain and other symptoms.
Our vision
Healthcare is one of three test areas we are planning for our emerging Metis platform. As mentioned above, this decision was based on our personal experience of palliative care.
Metis, which will launch in 2025, uses AI to provide near-instant solutions to complex resource allocation situations. The scale and speed at which it processes data makes it possible to tackle previously intractable challenges stifling productivity in complex organisations.
Through an ensemble of multi-dimensional neural networks and deep learning technologies, Metis is capable of contextually analysing real-time variables far beyond the capabilities of traditional table-based data. One usage we are already looking at is routinely matching end-of-life care professionals (with particular or unique skills or qualifications) to the patients who would most benefit from those skills and qualifications.
It’s about using digital technologies to unlock time, enabling people to be human.
