Your choice regarding cookies on this site
Our website uses cookies for analytical purposes and to give you the best possible experience.
Click on Accept to agree or Preferences to view and choose your cookie settings.
In sum, O’Neil says, the purpose of NHSX is “to accelerate digital transformation and professionalize digital throughout the entire health service.” Driving that is a wide-ranging vision of the future of healthcare akin in scope and scale to the tech-powered metamorphosis that the banking sector has undergone in recent years.
A key element of that is to establish interoperability standards right across the NHS That’s easier said than done when dealing with a complex behemoth of 1.3 million employees, 223 trusts (units responsible for the management of specific aspects of healthcare or a group of hospitals) and more than 1,000 hospitals — all crisscrossed by multiple, often-localized solutions, legacy systems and frequently outmoded tech practices. Such a move will, he believes, stimulate “a market for innovators to develop on top of,” as has happened in the financial services industry where fintechs and challenger banks have raised the bar for all players.
What’s more, it will help to put the health service’s users at the heart of everything, he argues. “When the move to open standards in banking came in, it allowed innovators to access underlying information and create some clever user-centered applications that targeted specific needs. In 10 years’ time, health has to look similar to that; a technology landscape that has shifted to something more recognizable in other [professional] environments.”
Healthcare’s new horizons
To be successful, this kind of innovation will need to draw on technologies such as the Internet of Things and artificial intelligence, in parallel with the gathering and processing of vast amounts of data.
By way of example, O’Neil points to an ongoing project around medical implants. He envisages a future scenario in which a smart unit implanted in the body is able to stay connected to the medical team responsible for it, enabling them to monitor patients and contact them if anything appears wrong.
In some high-profile cases in recent years in the UK, health professionals have had no way of tracing people when problems with a surgical implant became apparent, he highlights — often with very bad outcomes for the patients involved.
“The future of implantable medical devices is communication between the device, for example, in your knee (telling you how well you’re walking) and the application on your phone (through which your doctor or physio is recommending a helpful activity). So we’re planning for a future where data is moving around the system much more freely than it does today and is being actively used to co-ordinate care.”
It has become all too clear in recent years that such situations lend themselves well to the application of artificial intelligence, he continues. Indeed, NHSX has an AI lab where it can explore how to unlock AI’s potential application in healthcare, he says. There are obvious back-office use cases — such as in the scheduling of mobile screening or optimizing the deployment and routing of ambulances — but it is in the clinical space, where AI will be involved in patient-monitoring and decision-support, that its true value can be realized, he believes.
Understandably, that will always to be more difficult to implement due to the sensitive and disjointed nature of a lot of the data, he adds. “Success is dependent on us getting that underlying data piece right,” says O’Neil.
“AI is only as good as the data it gets — which goes back to the need for interoperability standards. We’ve got suppliers across the system who have their own proprietary ways of storing data, and we have to get around that somehow to unlock it. So the next few years have got to be about getting that data into a place, into a structure and into a format where we can use it effectively.”
Rapid innovation challenge
Like most organizations, NHSX has also been forced to react rapidly to the onslaught of Covid-19. Alongside the hugely negative consequences, there have been a few positives says O’Neil.
One upside has been the rapid acceleration — and public acceptance — of remote medical consultations, forced by the need for social distancing. That has smashed their targets. “At the start of this year, our goal for remote consultations was around 30% by 2023. By April of 2020, we were already at something like 99% of GP practices having the capability to conduct virtual consultations— because we had to be. As that shows, we’ve got people, [both medical staff and patients], using technologies for such activity who perhaps wouldn’t have done so before.”
But he also airs some ongoing frustrations. “Underlying those remote consultations, in some cases we might have a very tactical, proprietary data solution that could actually move us away from our long-term goal. The behavior change has been brilliant, but it doesn’t necessarily mean that we’re three years further forward everywhere.”
Another challenge that has been heightened by the pandemic is the need to innovate rapidly in an environment where, naturally, there is little or no tolerance for failure. “We’re dealing with people’s health and people’s health data,” says O’Neil. “When you’re talking about clinical decision support tools in AI, for example, you really don’t want to be testing and failing.”
However, balanced against this is the need to be able to try out new ideas that don’t have an initial guarantee of success, and this often requires a shift in attitudes.
“We have to encourage people to see that innovation is not a binary thing,” he says. “That we’re going to try some new things, some of them are going to work, and some are not. The things that don’t work, we’re going to stop doing. The things that do, we’re going to continue to invest in. And, as in any transformation project, we would want to be backing more than one horse.”
And he warns: “If you approach digital transformation from the perspective of a need to have a 100% success rate, then you are really going to stifle innovation and limit what people are willing to do.”
De-risking delivery
One solution, he says, has been to avoid risky ‘Big Bang’ approaches wherever possible. “For a long time, major healthcare projects have been focused around a particular launch date, where everything will go live. Our approach is to move the focus away from that and instead encourage a more iterative and agile approach to delivery.” This involves working through discovery and beta stages, and safely testing services and applications as they are deployed.
This de-risking process also involves completing different layers of assurance, both technical and clinical, by answering a whole series of questions: “Is it scalable? Does it work for the users and meet their needs? Is it accessible? Is it effective?”
When it comes to AI applications, however, such a need for certainty presents some difficulties. That’s because an AI service has the capability of updating its own algorithm based on the data it is ingesting. Currently, says O’Neil, the clinical assurance process is clear: “Here’s a fixed application or service, we can test it, we can say that it’s safe, and we put it out there. But when we put a machine-learning algorithm out there, it’s changing in front of our eyes as it’s testing and learning all the time. That is a big challenge that we have to overcome, and it’s going to require a different kind of assurance.”
Becoming a world leader
Of course, the English NHS — which is closely allied to its Scottish, Welsh and Northern Irish equivalents in the rest of the UK — does not operate in isolation. And O’Neil is always looking to learn from healthcare organizations around the world, as well as from other industries.
“We do a lot of horizon-scanning and are open to learning from others — internationally, locally, wherever,” he says. For example, he’s keen to observe how different countries’ healthcare systems have responded to the Covid-19 pandemic. “In places where there isn’t a national health service, like the US, we’ve seen private companies, with more to control over their domain, sometimes reacting faster than we could,” he says.
“And we learn from other sectors too [O’Neil himself was earlier a digital leader the media sector]. The NHS is one of the largest logistics operations in the country, so we speak to others who manage logistics, such as Amazon, the British Army and others.”
Notwithstanding the challenges and pressures, what drives O’Neil on is the thought of what’s possible when it comes to digitally transforming an organization with the scale and critical role of the NHS. “The reason I left the private sector for the NHS is that we’ve got all the raw material — the richness of data, the whole-population service model — to be a global exemplar,” he says. “And although there’s still a long way still to go, when we get this right, we can be.”
First published November 2020
Our website uses cookies for analytical purposes and to give you the best possible experience.
Click on Accept to agree or Preferences to view and choose your cookie settings.