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How Microsoft is using AI in healthcare

How Microsoft is using AI in healthcare
By Victoria Vaughan, Editor
11 January 2024

Jacob West, managing director of Government, Healthcare & Life Sciences at Microsoft, tells Healthcare Leader’s editor, Victoria Vaughan, how Microsoft is developing AI to improve healthcare for patients and those who work in the NHS.

Victoria Vaughan (VV): What is Microsoft doing in terms of AI and healthcare at the moment?

Jacob West (JW): It’s an exciting time, particularly over the last year. There are two things Microsoft is doing in terms of AI. We are building generative AI capability into every part of our technology offering, from Teams and Outlook through to Bing and Xbox – every part of the Microsoft technology stack. We use the phrase ‘copilot’ to describe what that means. And really, it’s a new category of software, a virtual assistant to augment human capability in potentially every realm of life and it will have huge potential for healthcare, as for other industries.

The second part of our strategy is building bespoke AI capability with customers using both generative and other forms of AI. You can think of that as building copilots for customers themselves and it draws on the foundation models that we’ve developed through our partnership with Open AI.

VV: What kind of impact could copilot have on a GP or a system leader planning care?

JW: There are all sorts of different copilots. And not all of them are available yet to everybody, but I suppose the one that’s probably most relevant to people who are familiar with everyday Microsoft applications like Outlook, PowerPoint, Excel and Word is M365 Copilot.

That will allow you to comb all the data in what we call the Microsoft graph. You comb all of the data and all of those applications, and it then allows you to do some very cool stuff on top of that, like generate a PowerPoint presentation from a Word document or other input from scratch without any further input from yourself.

It could be your analyst by looking at Excel and telling you what worksheets might tell you, summarise discussions in Teams and lengthy email chains and propose a response. Both clinical professionals and other knowledge workers in the NHS could potentially benefit from that.

There are one or two others. Microsoft search capabilities are now powered by a large language model. So you could use it as both your own internal data and for external searches. And it is a new form of search. So that’s a powerful tool potentially.

And then one other I’d highlight is power platform. So that’s our low code, no code development tool, and it’s really popular in the NHS. How do you build an application to shrink a physio referral workflow? Something that might take quite a long time to do in analog or even in typically digital form, but you can shrink that right down to a very short process. And copilot allows you to essentially build an application without any programming skill and using very natural language. Those are some of our cross-industry copilot capabilities I think could have NHS specific productivity potential.

VV: Is Microsoft currently working with the NHS on tailored versions of copilot around specific projects?

JW: Firstly, as part of the national agreement with the NHS, there are some stepping stones towards introducing that capability. The first step is Teams Premium, which does things like intelligent recap and that’s part of what the NHS has bought through that agreement.

Microsoft is working with frontline NHS organisations to develop really exciting use cases, though I can’t get too specific about that because it’s commercially confidential. We do have a healthcare-specific copilot that’s already in the market; it’s not yet in the UK, but my hope is that it will be very soon. It’s called DAX copilot. It stands for Dragon ambient eXperience copilot. We bought a company called Nuance a couple of years ago, which is the world leader in voice recognition software and conversational AI. And they already work with the NHS, with GPs, hospital trusts and other parts of the NHS to take away the drudgery of writing up patient notes.

The DAX copilot takes that to the next level; it is an automatic transcription, in a very structured way, of the conversation between a healthcare professional and a patient. It turns them into accurate medical notes and writes them into the electronic patient record. It allows the healthcare professional to focus on the patient. It’s technology enhancing the patient care and experience. I suppose you can think of that as our first healthcare-specific copilot.

VV: Is the DAX copilot being used in the US?

JW: Yeah, it’s deployed in the US. We’ve integrated it into our partnership with Epic. So it’s built very slickly into their patient record now as part of our partnership. But it should be coming soon to the NHS.

VV: So, can you discuss some healthcare-specific examples?

JW: AI is not something we have only started looking at since ChatGPT launched. Microsoft has been working on some really exciting use cases with classic AI capability, which is probably worth touching on and then some more emergent work drawing on the power of generative AI.

It’s the sort of work that has a longer lead time. A great example is what Microsoft has been doing in Northumbria. A couple of orthopaedic surgeons have used machine learning techniques on historical data for surgical outcomes for orthopaedic surgery – hip and knee transplants and so on – to produce very individualised patient risk profiles that help anticipate the potential post-surgical complications. This also helps doctors and patients think about the best setting for a patient’s treatment, which is important at a time when waiting lists are super high.

VV: So this is moving further towards personalised care?

JW: That’s exactly the way to think about it. Another example is around breast cancer. There was a huge backlog in breast cancer screening built up during the pandemic. We know, generally, we’re not good enough in the UK at early diagnosis of cancer.

So we’ve been working with a company called Kheiron Medical Technologies who’ve built AI deployed initially in and around Aberdeen with NHS Grampian. They cover about 25% of the NHS now. It’s more accurate and more efficient than a radiologist on their own in looking for cancers.

There’s actually a new study out in Nature, using some data from Hungary, which showed that they identify 5-13% more cancers [early detection of mostly invasive and small cancerous tumours] through this technology. If you gross that up, that’s thousands of cases being identified.

We always say, ‘Keep a human in the loop’ when you’re thinking about AI technology and healthcare. It’s not about replacing the radiologists outright, but you could have MIA (Mammography Intelligent Assessment), which is their product, plus one radiologist rather than two radiologists. And if you think about the efficiency of the workflow, then again, that’s usually productivity-enhancing.

Those two examples predate some of the more recent work on generative AI. And then we’ve got a whole host of emerging use cases, both in the UK and overseas. That brackets into a few different areas: giving time back to clinicians, engaging patients in more meaningful ways, removing some of the administrative drudgery, and enhancing research and supporting medical training.

In every part of that healthcare value chain, I would say there is an opportunity for this technology, particularly generative AI, to allow us to think differently and more efficiently about how we approach healthcare.

VV: There are concerns around the risks of AI, including the security of data, as the NHS is a target for cyber attacks. How do you make sure that the clinicians and patients have confidence and trust in it?

Security is hugely important to us. It’s part of our USP in terms of our technology offerings. All of our work on AI is underpinned by the best-in-class security infrastructure. We’re working with our customers to be able to, you know, absolutely minimise the risk of any issue there. And obviously, we’ve got a strong track record, working with the NHS, particularly after the WannaCry incident in 2017, in terms of enhancing their security controls.

It’s important for customers working on AI – or who have an appetite to experiment with it – to think about making sure they have the right technology infrastructure with the right security controls, much like they need to think about the wider infrastructure. You can’t do AI if the basics don’t work and you don’t have control of your data. And part of that is having the right security provisions in place. That’s fundamental.

We make commitments to our customers around the security of their data – that their data remains their data. That data is not going to be feeding back into the foundation models. 

We’ve made very significant investments into the whole agenda around responsible AI over the last several years and published standards in that field. More recently, we’ve written white papers on governing AI and getting into the regulatory area.

In some ways, that leads into clinical competence. The principles that we articulate in our responsible AI standard – so things like fairness, reliability, inclusive inclusiveness, transparency, and accountability – are all of the questions that people typically raise when they’re experimenting or thinking through whether they might deploy AI in some form, whether in healthcare or any other industry. And all of those are baked into our approach to responsible AI.

In Northumbria, they are using our responsible AI dashboards. It’s not just words on a page. It allows the clinician to explain to patients how they have reached the risk score; part of the tooling we work on with customers is transparency and fairness to allow practitioners to understand how an algorithm has reached a conclusion or prediction. It has to make sense.

VV: How much does data protection get in the way of bringing the information together to help healthcare professionals and patients?

It’s certainly part of the set of issues that customers raise with us. Ultimately, those are the issues that they’re solving. My view is it’s all solvable, and there are examples of it having been solved. That doesn’t necessarily make it easy, but I think somewhere in the NHS, we’ve solved most problems; it’s just about doing it at scale. I’m quite optimistic about that.

But there are hard yards of information governance in the NHS and they’re not to be trivialised. It’s difficult work. And you need to think about that just as seriously as you do about the technology choices you make. And there is the wider process change you’re trying to achieve. It’s technology, people, process – that’s the way we normally think about it. You’ve got to think about all three aspects. If you over-index on one, you’re unlikely to have success.

VV: How do you approach finding solutions to issues faced by healthcare professionals?

JW: We’re already working with more or less every part of the NHS, through the ubiquity of our technology so we’re not hammering down people’s doors, there’s a lot of interest.

These are discussions that are fermenting, bottom up, if you like, from our engagement with all of these healthcare systems – some ICBs, some acute trusts, some other parts of the system. And we’re still learning as well. We want to focus on use cases where we’re consistently hearing people tell us this is an issue we want to solve. We don’t need hundreds of different approaches to these use cases, we need to do it once for the NHS ideally.

VV: How do you work with the healthcare market?

JW: Essentially, Microsoft is a platform software company. So while we have increased our investments and capabilities in healthcare in the life sciences and other industries through things like the acquisition of Nuance and the development of what we call cloud for healthcare, which is a set of capabilities specific to healthcare, we are also primarily led by customers who articulate the biggest pain points in

And, indeed, by our partners, from small software innovators who are building on top of our technology stack – they might be building specific capabilities for the healthcare industry. Kheiron Medical technologies, as mentioned, are a really nice example of that and a great British success story in terms of software innovation, and there are many others. There are also big system integrator companies who help customers think about how all this technology knits together, often working not just with one vendor but with many; that interoperability issue is key.

Microsoft has invested in industry capability. I came from industry myself. We have bioinformaticians, public health doctors and others who help us have more meaningful and deeper conversations with customers, alongside our technologists and others in the business, to be able to really understand the goals and the problems they’re trying to solve. So it’s a two-way process. But ultimately, we’re not a sort of hammer in search of a nail – that’s the fallacy we’re trying to avoid.

VV:  What’s the future potential of AI in healthcare? Where do you think this could take the clinician and patient in terms of how they can deliver and receive care?

JW: There is opportunity at every stage of the patient journey for every part of the healthcare system. If I were to boil it down, I’d highlight four things.

Firstly, we talk a lot about giving time back to care – making that specific DAX copilot technology that can give hours back to busy doctors and nurses. Healthcare systems around the world, not just the NHS, can’t hire enough people, and they can’t hold onto people. People have got pretty burnt out, and giving them time back is a hugely important currency. The new kind of capability we’ve seen in recent years, and through some of the things we’ve been talking about today, has the potential to do that in ways that we couldn’t have foreseen previously.

The second area is how we personalise care. It’s engaging with patients and citizens in different kinds of ways. For example, the average reading age of each patient in the NHS is nine, yet most medical jargon is really difficult to understand, even for people with a reading age much higher than that. This kind of technology can, at a very low cost, address that by turning discharge summaries or other medical outputs into plain English or presenting it very imaginatively for children. That really enhances care.

The third less exciting area is around administration. How do you take away the administrative cost tasks? How do you automate repetitive tasks? How do you make email management easier? How do you make scheduling easier? It is really important and allows more time for the patient-clinician encounter. And looking beyond that, healthcare has been plagued by issues of data interoperability. It can potentially make those sorts of friction costs in healthcare significantly less.

And the fourth is around research and the life sciences. AI is probably more advanced there – in drug development and clinical trial design, for example – than in healthcare delivery. Again, at every stage of the value chain, there are really exciting opportunities.

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