The term ‘participatient’ is about empowering patients to take part in their own healthcare, and I don’t think this has ever mattered more.
With an ageing population, increases in those with complex long-term health conditions, and growing evidence of the lasting effects of coronavirus - it’s safe to say that better-informed patients will have a smoother road to recovery.
It also means an easier process for clinicians if less time is spent struggling with less-informed and more advice-dependent patients.
As the healthcare system takes stock of the impact of the coronavirus pandemic, what will be left is the realisation that these solutions aren’t just helpful in times of crisis; they’re essential for the future of how we deliver healthcare
But what is the missing piece of the puzzle when it comes to turning the idea into reality?
The use of apps and remote care solutions is on the rise, and spring 2020 saw the rapid adoption of these practices.
And I am of the view that to really understand a patient’s data sufficient to offer effective, accurate and actionable advice requires AI-enabled systems.
There are just far too many data points to link into burgeoning evidence bases for any other stratagem.
But, as the healthcare system takes stock of the impact of the coronavirus pandemic, what will be left is the realisation that these solutions aren’t just helpful in times of crisis; they’re essential for the future of how we deliver healthcare.
Reaping the benefits
How would this idealised system of healthcare work?
Understanding that requires understanding the benefits to be gained from people playing an active part in managing their health – improved lifestyles and health maintenance, more-accurate self-care, and less information dependency upon clinicians.
Then, when people ‘enter the system’, clinicians also benefit from diagnostic and treatment decisions being aided by AI-driven guidance, like having a ‘second pair of eyes’ to support them – creating clear pathways and aiding the dialogue between clinicians and patients.
After diagnosis, ‘participatients’ can access personalised, intelligence-driven digital health services via apps and online systems, cutting down on calls to doctors and saving time.
‘Participatients’ with complex co-morbidities will also have better outcomes, due to the intelligence-driven pathways that inform their treatment.
If clinicians can use AI-driven solutions to see the link between the actual clinical outcomes people experience and their genomic attributes, diagnostic and interventional procedures and prescribed drugs – better pathways can be established and effectively communicated with the patient, leading to better outcomes.
A patient that is well-informed, from clear pathways set out by clinicians, is far more likely to take an active role in their own treatment
A patient that is well-informed, from clear pathways set out by clinicians, is far more likely to take an active role in their own treatment.
It takes a partnership between the two, enabled by AI, to make the best outcomes a reality.
Clarity of communication
Communication between clinician and patient is vital to making this happen, particularly in the management of long-term health conditions, and in a world where remote care is now a ‘must-have’.
A lack of face-to-face contact needn’t be a barrier to good communication any more.
Clarity of communication becomes stronger when all the data about a patient’s care – across major acute diagnostic hubs, local acute treatments, community and social care support and GPs – is easily accessible from a single source to clinician and patient alike. This is also far more valuable when clinicians and patients have access to AI to interpret that data.
It’s that combination of AI and the human touch that lies in the future for the NHS.
The AI-enabled participatient
AI-enabled digital solutions are the key to unlocking the true value of active patient participation.
It’s the combination of AI and the human touch that lies in the future for the NHS
Patients taking more of a role in managing their own health has been in our sights for a long time.
And, if both patient and clinician have access to their data across multiple settings, that is a good start.
If the clinician can use AI-enabled solutions to interpret the data and make recommendations, that elevates it to the next level, and then we can reach the true potential of the ‘participatient’.