How AI can support healthcare
Jenny Lewis, PA digital healthcare expert offers her thoughts on how AI can save the public healthcare sector.
How AI can support public healthcare
Healthcare costs are rising as personalised treatments come of age. We are close to a future where the number of care pathways being managed could be as numerous as the number of patients being treated. This is a phenomenal achievement of modern medicine but provides health systems with a significant challenge - how to safely provide significantly more individual care management within the constraints of a publicly funded system.
AI is key to a future of personalised care
Working out who, both staff and patient, needs to be where and when, receiving what treatment, can no longer be managed by human intuition alone. AI can compute and advise on the best permutations of patient, bed, theatre, clinician, diagnostic, in a way that humans will never be able to. Health systems are in the foothills of using the huge advances in AI technology to support these processes - for example, predicting when patients will decline, what their future clinical needs might be or when they need to change care settings. With this additional information, clinicians and operational staff can make informed choices about how to use limited resource to maximise clinical outcomes and patient experience.
How can we unlock the power of AI
As the delivery of clinical care is now mostly digitised and with the significant investments going into data platforms, including NHSE's Federated Data Platform and the Trusted Research Environment programme, we are now able to access the data we need to deliver on this personalised care future. The next step is to capture the potential of AI in actively driving future health system processes. AI is high up the agenda of the majority of health system boards, but often without an understanding of what needs to be done next. Trusts and local care systems should use their data to rapidly prototype algorithms to aid clinical and operational decision making. They must access skilled data scientists who understand health datasets. These are currently in short supply in public health systems so looking to other industries or bringing in expertise from private organisations is needed. Boards also need to bring the public and patients along with them - the fear of AI replacing Doctors is a real one, but easily overcome through engagement and sensible applications of AI to care pathway management.
Without AI, the future of personalised clinical pathways will neither safe nor affordable.