Stephen McMillan, solutions leader at Philips UKI, and Charlotte James, business manager CT, AMI, and radiation oncology talk to Jennifer Trueland about the benefits that AI solutions are bringing to patients, staff, and to the NHS as a whole
Ask Charlotte James what drives her, and the answer is simple: it’s seeing the difference that healthcare technology can make, both now and in the future. As business manager for CT, AMI (advanced molecular imaging) and radiation oncology with Philips UKI, she originally studied law, but was drawn to healthcare because of the opportunity to improve people’s lives.
“It’s very tangible,” she says. “You can imagine your mother, your grandmother, your children, sisters, aunts and uncles all having the care that we deal with every day. A big part of my role is knowing I’m making an impact on my family’s future health.”
It’s a similar story for solutions leader Stephen McMillan, who, before joining Philips, spent 20 years working as a management consultant for Big Four firms, most of the time in healthcare. He worked with the NHS helping to drive change but wanted to have a greater role in delivering change as well as advising on it. Philips gave him the opportunity to do that, and he clearly relishes his current job.
“It’s what I’d call applicable innovation – it’s about taking innovative solutions, and actually applying them in a way that makes a difference, right away, across all the needs of the NHS,” he says. “This applies whether it’s to help patient outcomes, retaining staff, or putting in changes that are going to save the NHS money.”
Technologies based on AI – which he prefers to describe as Augmented Intelligence, rather than Artificial Intelligence – are a case in point. These are already making a huge difference in healthcare and have the potential to do much more.
“For me, AI is about working with the human to augment and improve their experience in some way,” says McMillan. Lung cancer screening is a good example of this, he says, where AI can help with nodule identification and cancer classification, as is digital pathology, where it is even picking up cancers that a pathologist might miss.
He cites Philips’ own technology, SmartSpeed, which is helping to revolutionise MRI scanning – and which uses cutting edge AI to reconstruct MRI images. The technology builds on the already successful Philips compressed SENSE and further accelerates the MRI acquisition, delivering fast high-quality imaging, without compromise, in less time. This is good for patients, clinicians, and health services, he says.
Faster MRI scans
“What it means in practical terms is that when you use this solution, it allows you to do a much, much quicker sequence of MRI. Nobody enjoys an MRI – it’s an unpleasant experience, it’s noisy, it’s claustrophobic, and it’s uncomfortable to stay still for so long, and many people struggle with that. So if you can make a reduction in the time the patient has to be in there, and at the same time provide a better image than if they’d been there the standard amount of time, then that’s great.”
Depending on the area being scanned, it can be between 40 and 60 per cent faster, he adds. “It’s a better experience for patients – there’s less time on the table and less discomfort. It costs less, and allows you to see more patients in the same time. It’s better for staff, because they have better quality results, patients like it, productivity and staff satisfaction are better, and with better quality scans, you’re ultimately going to have better patient outcomes and care.”
For James too, AI isn’t about taking over from humans – rather it’s providing clinical support to help people do their job, keeping the human approach at the centre. She gives the example of Philips’ CT Smart Workflow, which uses AI to assist the radiographer to achieve the best and most consistent results, while allowing them to focus more attention on the patient beside them. “The preparation of the patient, the scan of the patient, and the post-processing of the patient can all be set up whilst that radiographer is standing next to the patient, and can focus more specifically on that patient care and intimacy.”
The AI-led workflow will suggest things like the best parameters for the scan – but crucially, the radiographer has to agree, and can over-ride if necessary. The technology is improving patient and staff experience and reducing scan times by around a fifth, which has a huge impact on productivity, she adds. But importantly, it means that results are more consistent across the board, with a corresponding impact on patient care more generally. “It’s about AI being a kind of clinical assistant to get the right kind of outcomes,” she says. “And that’s not just about productivity and seeing more patients – it can also mean better care for that patient.”
AI tackles workforce crisis
The AI-driven technology can also be used to tackle the current workforce crisis in radiology, she adds, because creating capacity in the system can allow staff to be upskilled, for example, training radiographers to read certain scans. “This is great because it’s helping with the reporting backlog, but it’s also improving staff satisfaction,” says James. “It’s a hugely powerful tool to retain and develop talent in your organisation.”
Of course, challenges remain – not least current NHS procurement rules that often seem to focus on productivity to the apparent exclusion of other factors – as well as the perennial thorny issue of interoperability. But both James and McMillan are fierce advocates of the actual and potential benefits of AI-backed technologies for the NHS and ultimately for patient care.
And, of course, it’s also helping to retain and optimise the workforce, and allowing services to be delivered in a more sustainable way, which is better for the environment. “It’s making improvements across the board,” says James. “It’s win-win.”