Inside the AI-driven revolution at NHS 24 with Ann-Marie Gallacher

In this episode of The Digital Lighthouse, host Zoe Cunningham is joined by Ann-Marie Gallacher—Chief Information Officer at NHS 24 Scotland—to explore how AI and digital transformation are revolutionising healthcare delivery while maintaining clinical safety and patient care standards.

Discover:

• How to balance private sector innovation speed with public healthcare’s safety requirements
• Why COVID-19 accelerated digital transformation in healthcare
• The practical applications of AI in healthcare
• How AI is enhancing quality control through voice analytics and automated call reviews
• Why Microsoft Copilot and similar AI tools are revolutionising administrative healthcare operations

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Episode Highlights:

• [05:28] Public vs. private sector innovation
• [08:47] How COVID accelerated improvements
• [11:36] – AI in action at the NHS 24
• [17:45] Microsoft Copilot in action
• [20:38] Advice for tech leaders adopting AI

About our guests

Transcript

[Zoe Cunningham] (0:02 – 1:35)

Hello and welcome to the Digital Lighthouse, where we get inspiration from tech leaders to help us navigate the exciting and ever-evolving world of digital transformation. We believe that meaningful conversations can illuminate the path forward, helping us harness the power of technology for innovation, scalability and sustainability. Today, I am absolutely delighted to welcome Ann-Marie Gallagher.

Ann-Marie is the Chief Information Officer at NHS 24 Scotland, with an impressive career spanning both the private and public sectors. She’s an experienced leader in IT strategy and digital transformation, having worked with organisations such as National Trust Scotland, AGBAR and Peak Scientific before taking on her current role in digital healthcare. In this episode, we’ll be diving into the exciting and often complex world of AI in healthcare.

We’ll explore the difference between public and private sector tech innovation, the surprising benefits COVID-19 brought to digital health services and how AI is already making an impact at NHS 24. Ann-Marie will also share her insights on AI’s potential for the future of healthcare, how it’s reshaping the workforce and why leading tech in the NHS can be so rewarding. So Ann-Marie, welcome to The Digital Lighthouse.

[Ann-Marie] (1:24 – 1:26)

Thanks, Zoe. Nice to meet you again. 

[Zoe] (1:26 – 1:35)

Could you start by maybe giving us a little bit of background on your journey and tell us how you ended up leading digital transformation at NHS 24?

[Ann-Marie] (1:35 – 5:07)

I originally started out life decades ago as I trained as a nurse initially as my parents desire for me to become a nurse. I wanted to be a scientist or an engineer. So having newly qualified and married with children, I took the opportunity to go back to education and I took my degree, a Bachelor of Engineering in Software Engineering, one of the first female Bachelor of Engineering in Software Engineering in Scotland, the very first cohort. So that was quite an achievement. I’m proud of myself. 

I worked my way through the ranks, through the roles of programmer, systems analyst, leader, head of software development and then to IT management and then European roles and manage projects and programmes.

So pretty much done for the coding right through to three to five years strategic planning. And this was across different sectors. When I left university, I started as a fresh faced software engineer.

I started out in the private sector in manufacturing electronics. I moved into working in banking in the finance sector, looking after the data warehousing across four banks across Europe. I managed software development and general IT management across then back into manufacturing across European sites.

I then worked with, a headed up, digital and technology for Glasgow City Council as well as head of all of that space, which was absolutely massive. It’s one of the biggest councils in the UK. And I also worked for a few years with a software company and it spanned across New York to Stock Exchange and the SEC and the Stock Exchange in London.

So producing software, looking after technology, all areas around that. More recently, at Peak Scientific, I implemented a wholesale global system across 16 different countries. That was a big bang piece. So that was quite a massive activity. 

And hot on the heels from that. I was approached to consider the role at NHS 24 because they needed someone to do virtually the same thing, but only in one country this time. So that was eight years ago.

I was only going to come into the NHS briefly for a year to 18 months to do this activity. But I thoroughly, thoroughly enjoyed being in NHS 24 and being part of something that’s for the greater good. I wasn’t chasing earnings per share and shareholders. It was nice to be on the side of the angels. And it took me right back to the start of my career when I initially trained as a nurse. So I had to pull that back in from the decades previously.

And it was just because I understood the language, I’d worked in the hospitals, I’d done all of that stuff. So it was a nice coming home, if you like. I could use all that medical training and knowledge that I had gained doing my nurse training. And then I had decades of technology, all of the activity across sectors. So it all comes into the round. And then it’s a very well-rounded understanding of how all the different aspects of bringing technology into our workplace works.

Because if you cover every sector, you can cover all the nuances about what’s important. So I think I landed in a very well-rounded, very experienced space to then bring on the transformation that’s needed in NHS 24.

[Zoe] (5:07 – 5:29)

All the dots connected. That’s a really good place to start. So looking at your roles kind of across private companies, and then NHS 24, how do you think the approach to AI and innovation differs between the private and public sectors?

And I suppose what are the lessons from the private sector that you found most useful in your current role?

[Ann-Marie] (5:29 – 7:14)

I think the major difference is there are many, many bureaucratic hurdles in the public sector. They’re trying to get a financial case to prove that it’s well worth doing it. You can have a solid financial case. But if the money isn’t there to be allocated, the money isn’t there to be allocated, no matter how powerful your business case is and your financial case for bringing on AI or doing that kind of technology. 

The other aspects, certainly in the NHS and in the clinical space, is clinical safety. In the private sector, if you introduce some new technology, new digital solution, you may lose some money. Your profits may drop slightly. You may lose some of your customer base. And all the time, many of the roles I’ve had in the past in those private sector, the comment will be, oh, well, at least nobody died.

In the NHS, you cannot say that because somebody may very well die because of something that’s been done. So the funding can be a hurdle and it is a very bureaucratic process. Even once funding is allocated, it can be a very cumbersome bureaucratic process for procuring.

Once you’ve made your business case, then the procurement is onerous and excruciatingly governed for all the right reasons. And then jump through all of those fiery hoops. It’s a clinical governance piece and quite rightly so, because it has to be very, very, very tightly governed from a clinical safety perspective.

So it’s quite different where you can fail fast and try again in the private sector. It’s quite a different world in the public sector.

[Zoe] (7:14 – 7:23)

Is there anything you’d say you’ve been able to kind of bring across that changes how you view doing your job, having had that experience elsewhere?

[Ann-Marie] (7:23 – 8:25)

Yes, I think being able to apply what’s critical, what’s material, what’s mission critical to getting things done. I also think it may help accelerate some of the activities around the bureaucracy and things. So I think there can be a little bit more targeting of creation of business cases.

I am accused often of being a naturally very impatient person, but I think that works to the good when other people are not so impatient. So bringing a little bit of impatience, and I think that may come from decades of time is money. When you work in manufacturing, you can put a pound or a dollar sign on every second of every day.

So if your machinery is down for one hour in one site in California, is this hundreds of thousands of dollars. So time is money. Every second of every minute of every hour has a cost associated with it, either in a hard cash loss or you’ve missed an opportunity to do something else.

[Zoe] (8:25 – 9:00)

Exactly. And that’s not a common way of thinking in the health service, but it’s the same thing, right? If the services aren’t there, people aren’t being treated and can have negative outcomes as well.

Well, talking of negative outcomes, let’s talk about COVID. So obviously, COVID-19 had a profound impact on the healthcare sector, and many private organisations accelerated their digital strategies as a result. So were there any kind of surprising or unexpected benefits from the pandemic that helped advance NHS 24’s technological development?

[Ann-Marie] (9:01 – 11:15)

There are many things that was very positive, but I think from a whole system perspective, there was a national contract undertaken for NHS with a national Microsoft contract to roll out Office 365 in totality across all boards. One big contract, we could all leverage from that. And initially, pre-COVID, this rollout was going to take potentially up to about three years for everybody to get Microsoft Teams to communicate and all that good stuff, and it was not moving at any great pace.

COVID came into the mix in the discussions, and within months, three years worth of programme delivery was undertaken to deliver the whole Office 365 upgrade and new contract and rolling out Teams to everybody because it was really the only way there would be as much effective communication as needed with everybody working from home, from the corporate support functions, etc. So that across the whole, not just for the health board I work for, but across the whole system, that was massively impactful at a national level. And also, again, across the board between Scottish Government and their health boards and other agencies they deal with, acceleration of decision making and the breaking down of communication barriers and speed of decision making and getting things done, that was quite significant.

Pulled Teams together quite tightly, forged very strong working relationships when we had to roll out things like the vaccine app and all of that good stuff. I was part of a silver command team for data and disease surveillance, the information around that, and you get very strong working relationships with people that you would not normally have worked with, and those have been very beneficial for me to go on and do new initiatives because you forge such a good working relationship. So whilst COVID was a challenging and awful time, it actually really bulldozed its way through finding new ways of working and delivering in a much more faster, much more integrated way.

[Zoe] (11:15 – 12:02)

It’s kind of something we wouldn’t choose to have been through it, but actually to recognise that there are positives, I think that’s kind of life, isn’t it, really, that there’s always a lot, you know, in these complex systems, there’s so much going on and finding the ways to take advantage of the good things, I think is really important. We are going to have to get on to AI, so let’s go straight there. So because AI is becoming more present in healthcare, but often it’s talked about in theoretical terms.

So what could we do? Or maybe this could happen in the future. Have you got any kind of practical examples of how AI is already being used, you know, maybe within NHS 24 to, like you’re saying, do good and improve patient outcomes or service delivery?

[Ann-Marie] (12:03 – 17:24)

Simplest end of things. We introduced workflows and automated workflows, more from a corporate perspective and picking that up. But we also use a clinical reasoning engine.

So it will take a whole number of aspects and responses to questions and different external factors and arrive at a conclusion, an end point. So it’s a clinical reasoning engine that we use to get outcomes. So if you ask a set of questions and these are the responses you get, 98-99% of the time, this is the outcome.

You need to go to a fracture clinic or you need to go to the pharmacist and get something from your own pharmacy. And that can allow then for patients to take a wholly digital journey or allow for a non-clinician person to guide the patient through that pathway and arrive at a very clinically safe and governed outcome. So it leaves the clinicians and the very experienced clinical people to deal with the more complex things that would not readily work.

We do that to a fair extent and we call that advise and refer. So it’s something fairly simplistic, patient journey or one that the conclusion is pretty much nearly 100% of the time the same outcome. Then we do deliver that through a digital pathway, but without needing to have a clinician to deliver that.

So that is very impactful. That is something that we are developing and going to do more and more of on how we extend our clinical pathways and use more and more of reasoning engines in that space. So that’s going to be really quite an adventure for us over the next year or two to really exploit and optimise that capability.

The other piece that we have in that we will be delivering, we’ve investigated and will be delivering possibly around this time next year is automating our call reviews. So NHS 24, we don’t have any clinics with beds or stethoscopes. We do everything digitally or over the phone.

So it’s contacts. We have digital contacts, but primarily 80 plus percent of the contacts is telephony. So we do voice and call recording, which we quality control and check, but by somebody listening in and doing the quality checks.

We’re implementing technology now whereby we could do 100 percent of the calls checked through in no time at all through using AI voice analytics. And that should give us some direction on quality service. Are we offering the right tone, for example?

What’s the performance per call handler? So there’s a lot in that. So we can look at 100 percent of our performance, 100 percent of the time without taking anybody’s time up to do it.

And it will give us really great insights into how the staff are managing to deliver the service and bring improvements for the patient and the staff and maybe some training opportunities if needed. But it also lets us see other areas for improvement in there. So that’s going to be quite an exciting thing.

So it’s exciting times ahead. We have some AI, but I think we’re just laying the foundation stones. We’re at the bottom of the mountain which we can climb.

We have all we have next generation technology getting implemented during this year. So we are ready to take more and more steps into this place. On a corporate support piece, the AI that we have implemented over the past six months or so is a full evaluation exercise on the use of CoPilot.

There is some absolutely fantastic capabilities in Microsoft CoPilot and what started out as an evaluation exercise has ended up with every individual who was given the licence to do this evaluation. I think I’ll have to, I think the term you’ll have to prize this out of my hands if you want it back. So being able to take a number of documents and have AI summarise all the salient points.

It can take weeks out reading and evaluation and just give you that summary piece. The creation of documents as a standard, obviously they need to be refined. It doesn’t do the whole thing for you, but it can take hours and days and weeks of laborious tasks away, straight away.

CoPilot recording of meetings that we’ve got in place. We don’t need an administrator or a PA to sit for hours afterwards with summary notes and then preparing the notes and the actions all generated during the call. Instantly shareable.

There’s no dubiety about who said what, when. And so it is very powerful. It frees up people’s time to do more value add activities.

It takes the kind of drudge bits away. So there’ll be a lot more, a lot more focus on what else we could have CoPilot do or corporate type automations to help support staff so we could do more with the same people.

[Zoe] (17:25 – 17:55)

I mean, I think that’s the common thread, isn’t it? That because all of the clinical stuff is so exciting and this idea of getting better results that are still safe and still clinically proven while freeing up these very expensive and in-demand clinicians, right? If you can get more time for the more acute problems, it’s really, really exciting.

And I think that’s the real benefit. People are kind of always scared about losing jobs, but actually it’s more about freeing up the people to do more work.

[Ann-Marie] (17:56 – 20:17)

Exactly, because there’s a never-ending queue of people, certainly in the clinical space, that people need help and support. So it allows the people-to-people, human-to-human interface and contact with the users of the service that we provide, that human-to-human connection where it’s needed because of complexity. Or it could be that somebody might be digitally disadvantaged, you know, they may not have a smartphone, they may not have an internet connection, or it may be people who not everybody in the country can read, not everybody has English as a first language.

There are all of those things. It allows us to address the more complex needs of people using the service, and it also gives a choice, a digital option as a choice for people who would rather have that. Because there are so many individuals who don’t particularly want to speak to a human being, especially if it’s something a bit embarrassing, you know, it’s like you may want to just run through an app or go onto a website or just some voice recognition piece.

You may just want that because it’s quick, it’s easy and you’re instantly referred and you don’t have to wait in a queue to speak to somebody when you could just self-sit. You could maybe want to do it in the middle? Yeah, at any time of the day or night because there is no boundaries.

It’s infinitely scalable. It’s like bringing on an additional 300 call handlers for one hour when you’re at your busiest, if you can manage that through a digital channel, you know, digital pathway. So it just gives a service offering at the right time to the right people in the way that they would like to access it, with minimum delays and disruptions.

So there’s exciting times ahead. I mean, as I said, we’ve laid the foundation stones where NHS 24 as an organisation are quite ambitious and they’re keen to utilise as much of the digital capabilities that are available as possible. And I would expect over the next two, three years’ time, we should be leading on quite a few bodies and to things that not necessarily are there at the moment for people seeking healthcare digitally.

So it’s exciting for this organisation.

[Zoe] (20:17 – 20:38)

It really is. And so finally, for tech leaders who are listening, whether they’re in private or public sector, who want to start embracing AI, what advice would you give to them? So what are the kind of first steps they can take to bring AI into their organisations, effectively, but also responsibly?

[Ann-Marie] (20:39 – 21:38)

I think if it’s completely and utterly new, pick a pathfinder AI initiative that helps you understand how to use it, what the potential unintended consequences can be, until you understand how to deploy it and what the potential impact is and the unforeseen things could be. It’s very tempting to go for an AI solution for your greatest need may cause massive risk. And the highest risk of that is the organisation will then baulk at the thought of doing further AI initiatives because people say, oh, well, remember we tried that before and it all went horribly wrong.

I think a pathfinder initiative to start with, to say we wanted to do an AI initiative. Here’s what we did. Here’s what we hope to get out of it.

And proven this has worked the way we expected it to. Now we’ve cut our teeth on that piece. What do we really want to do?

Where’s the big thing that we want to do?

[Zoe] (21:38 – 21:53)

So it’s not just about getting the AI right and implementing the AI itself, kind of correctly. It’s more about the systemic. How are you bringing it into your organisation and looking at all the different factors?

[Ann-Marie] (21:54 – 23:16)

And it’s understanding the things that are a little bit more complex, more than you’d think at the beginning. Things like cybersecurity, information governance and security. You can get tied in all kinds of knots with things like that.

If there isn’t anything that’s particularly sensitive from an information governance perspective, then probably not such a big problem. But you could imagine with health service and people’s health information things, it’s quite a big item there. So it’s the unintended consequences or added areas of complexity around AI.

Because sometimes you can just get caught up in that, oh, we can save all these man hours, or oh, we can reduce the opportunity of error for manual input by all of these things. It’ll be great. But then what you don’t realise is you’ve maybe massively increased your carbon footprint.

You’ve maybe massively increased your, you maybe experienced a cloud burst if you’ve got cloud storage and things like that. It’s gone and cost you a fortune. You might have saved three people’s full-time equivalent effort, but it’s costing you a lot more money than their wages over here.

It’s really thinking it through. And it might be okay for the first few months, but think it through a financial year and that bit after that. So it’s just thinking it through.

So start with something not massively impactful, but till you get your head around it, and then go for the thing that will really make a difference.

[Zoe] (23:16 – 23:26)

Thank you so much, Ann-Marie. There’s so, so, so much more we could talk about here. And unfortunately, that’s all we’ve got time for.

Thank you so much for coming on and sharing all this expertise with us.

[Ann-Marie] (23:27 – 23:28)

Nice to talk to you, Zoe. Thank you.