SPEAKER_00: 0:00

Imagine passing down your health data as a family heirloom. Not just a record of illness, but a rich personal history that could help your children and grandchildren live longer, healthier lives. But right now, the way we treat health data is messy. Governments across the world are investing billions in electronic patient records and digital infrastructure. But if the data itself is inaccessible, siloed or ignored, what are we really building? It's a bit like building a library and locking all the books away. Hello, this is Problems Worth Solving, the podcast where we meet people transforming health and care through human-centred design and digital innovation. I'm Sam Mentor, founder and managing director at Healthier, the Collaborative Service Design Consultancy. If you enjoy listening, you can subscribe to this podcast and the accompanying newsletter at healthier.services. In today's episode, I'm joined by Professor Rachel Dunscombe, one of the most influential figures in digital health today. Rachel is Chief Executive Officer at Open Air International, also known as Open EHR, and was previously Chief Executive of the NHS Digital Academy. Thank you very much. why your health data might outlive you and why that matters, how decades of NHS data could unlock life-saving insights if we get serious about access and standards and what it really takes to build a digital health system that's fit for the next 100 years. Rachel, it's a pleasure to have you here. Thank you so much for taking the time to come and speak with me.

SPEAKER_01: 2:06

Thank you for inviting me. It's a privilege to be here.

SPEAKER_00: 2:10

Before we get into the electronics, I'd like to start with a bit about your story. I'm wondering what you were curious about as a young person and just a potted history of how that evolved into the work you're doing today.

SPEAKER_01: 2:21

I've always been a curious person and I've always been a person that has wanted to investigate things. So it's not just in this space that I feel this way. I'm curious about things to the point where my kids bought me a Geiger counter for Mother's Day because I'd got really interested in nuclear decay and various other things. And I think that came from my childhood when my dad, he was interested in so many different things in aviation. in science, in psychology, in economics. You've been at LSE. And I was just taught that you should poke the box and find out how things work. And I felt very grateful for being given that kind of upbringing where it allowed me to do that. Yeah, it's probably a family thing, I think, because I see that in a lot of my family members.

SPEAKER_00: 3:08

It's a bit early in the interview to go off at a tangent, but you've got a Geiger counter. Tell me more about that. I don't know anyone else that's got a Geiger counter.

SPEAKER_01: 3:16

One is broken. The joke was the cat actually broke one of my Geiger counters by knocking off the sort of radiator cover. So I now have one that actually tells me which isotope is decaying, which I find fascinating, really fascinating. But I'll tell you the funniest story of my Geiger counter. It was in my bag and we were driving along the M62, passed a van with a radiological symbol on it. And this thing goes off the charts to the point where I'm thinking, is that poor driver okay? So we stay parallel on the M62. We take the radiation readings, take the name of the company and contact them and say, I don't think your shielding is quite up. And it was actually a medical isotope that was in that van. But anyway, that's just one of the rabbit holes I like going down because the kids learn as well about radiation and about nuclear science. And if I had another life, I would love to go into nuclear physics or volcanology, I think. I'd love to be a volcano expert. I've got a friend that's got a PhD on the volcanic activity on Mars. So, yeah.

SPEAKER_00: 4:17

So, slight tangent. Bring it back to your patient records. Sorry, tangent at the beginning, yes. Your curiosity led to you studying. Do you have a medical background? Did you study

SPEAKER_01: 4:27

medicine? No, so I was in biomedical science originally, but then I got on the... It was back in the 90s, the Python train of data. So I got really engrossed. Shortly before Linux came out, we were using BSD and things like that, and I got really interested in the data. And that's what kind of led to that overlap of the kind of scientific background, but also the programmatical data background as well. I was really interested in what data tells us, what we can learn from it, and starting to see that beginning of the internet as well. We were getting collaborations with data from different places and it just felt I could see the future emerging at that point.

SPEAKER_00: 5:10

And how did that evolve into working at the NHS?

SPEAKER_01: 5:13

So I actually went and I spent a number of years in Europe working with actuaries looking at risk with data based on human health care group risk and that sort of thing. That was interesting. And I actually had a personal experience and a family experience with the NHS where I felt it needed to be improved. And it was one of those moments actually where I found a guy that had worked for me much earlier in my career who had moved into the NHS. I actually met him in a hospital where we were patients. And he said, yeah, I work in the IT function here. It's really interesting. I said, tell me more about it. And I just had this process where I felt it was something that with the risk piece I'd done with actuarial, there must be something we could do in healthcare that was similar. I didn't really realise that I would be landing in a space that would be perhaps a long way behind that, which is the reality of what I'd landed in.

SPEAKER_00: 6:10

And you went on to be chief information officer.

SPEAKER_01: 6:13

Yeah, I did.

SPEAKER_00: 6:15

Hands-on responsibility for a lot of data in that role.

SPEAKER_01: 6:19

Huge amounts of data. So I have more than one role as a CIO. And we're talking about hundreds of systems. We're talking about very complex enterprises here. Thinking about Salford NCA Group, you know, nearly 20,000 employees, one and a billion turnover in terms of pounds. So huge amounts of activity because, you know, that size corresponds to the activity. They're very complex, mind-blowing environments. And I think healthcare is probably the most complex environment you can work in. Because there is so much data, but there are also so many humans and human stories and human aspects around that data as well that need to be considered. It's not, say, aviation, where an aircraft creates data. There's also a person behind this that has thoughts, needs, values, everything else. So for me, it was incredibly challenging, rewarding, but also in many aspects behind the times of The Art of the Possible.

SPEAKER_00: 7:21

How much is that complexity part of the attraction of working here?

SPEAKER_01: 7:26

The complexity is both an attraction and a headache, if you like, because sometimes it just feels that there are things you can't solve. It takes time. The attraction is also humans, as in there are a few other places where you can improve lives and save lives. Somebody once said that a data analyst or a programmer in healthcare could... cause huge amounts of harm to life or could save a huge amount of life. And that is absolutely true. As a vocation, this is as important as doctors and nurses.

SPEAKER_00: 8:06

Let's go on to talking a bit about electronic health records. So I'm hoping we have listeners who are outside the health system to Problems Worth Solving. So I wondered if you could explain a bit about EHRs or electronic patient records, which is another name for them, what they are, where they've come from, what they do and how do they benefit patients and staff?

SPEAKER_01: 8:28

Absolutely. Electronic patient records, EHRs, started around about 30 or 40 years ago. And they started really as systems where you could record things like lab results or put in orders or make notes about a nursing encounter. And they have grown in terms of what they do. They go right the way through now to every function you can think of, billing, managing bloods, managing labs and pharmacy and everything else. But the evolution has really been based on the functionality. So it's all been about how do we add some more functionality to this product? And health systems have really compared that functionality, front-end user functionality, or what it can do in terms of interacting with pharmacy. And as a result of the fact that the market is crept in this way, you have all these different vendors who have evolved their front-end functionality to be somewhat equivalent, but have bolted things onto this back end, which maybe got its origins in the 80s or 90s and was never designed to do all of these things and all of these functions. You know, some countries they've bolted on billing. In the UK, we've bolted on activity and patient administration. We've bolted on bed management. And as a result, these things are architected based on older technologies and the way that they've evolved them has been to basically just keep the market happy. And that has built really a technical debt into the backend. So as a CIO, trying to get your data out and make sense of it from one of these things is not the easiest task.

SPEAKER_00: 10:18

What sort of data would you be trying to get out?

SPEAKER_01: 10:21

I'll give you a really simple example. Say you're doing a study of patients that have heart failure and you just want to pull out their blood pressure across time. Do a time series, something like that. What you find within these EMRs is the blood pressure is stored in all sorts of different places in different formats with fields that don't match. We call that lossy data because you're losing some of the context. And to actually get a time series out for my data scientists, it would have been at Salford. You have to do all of these mappings, which don't fully map. And the way each of those bits of functionality that record blood pressure, one might be a device here, one might be nursing here, one might be a ward around here. I remember doing an audit of one EMR that had 47 different ways of just recording blood pressure, right? There's a hell of a lot of work. And the lossiness and the context loss, the provenance that data is lost because you've got all of these different places where the same concept is stored. And as soon as you get into this world of data science and AI, you realize the underlying data models and the underlying data are just not built for the next generation of solutions that we're going to need or starting to need now. We lovingly used to call some of the people that did the work on the data quality to bring it all in line. So manually manipulating things, the cardigans, because they would come in, I'm wearing a cardigan today so I can laugh about this, hang the cardigan or the jacket on the back of the chair and do a whole day's work on data quality. And that really, prevention is better than cure. But we're curing the fact that these systems have data in such disparate ways, what we should really be doing is preventing that by having the right back end data infrastructure. So yeah, it's been an organic thing and it also hasn't helped that the NHS has always really been money conscious to the point where it's always said buy the cheapest system and that has never considered how good the data is in the back end.

SPEAKER_00: 12:25

So as I mentioned earlier, the government has been funding huge investment into these EHRs over the past few years. Where does all that money go and what's the real return on investment for the system?

SPEAKER_01: 12:36

So to be clear, you know, these systems do fulfill the needs of a hospital typically, and they allow a hospital to function. So the money goes into providing that incredibly complex functionality that allows a hospital to operate, along with a very big infrastructure that enables it. What I would say is many of these systems are actually US systems that are reprovisioned for the UK. So we're also buying a huge amount of billing and things that we don't use in the UK. And that's always been a bit of a question for me. But if you think about every process in a hospital moving from the analog or from old systems through to a single unified system, that's sort of what the EHRs are. The nearest analogy, if you're not from the healthcare industry, is the ERP and what that does for a business in terms of automating one of the processes. The thing is that these are very costly, not just because of the software, because the software is costly. It is training every single member of staff. If you take my old organization, 18,000 people to train, and it's a good few hours training each, and they need updates on that training. It's a very big program. And obviously, you have to train them well, because this is about clinical risk. It's about clinical safety. It's about all of those things. So really, these very big projects... are very big bits of software which have to be taken in one lump because they're monolithic systems, yeah? You have to take this big monolithic system and you have to implement it. And I think that's where these things get really difficult because they're massive projects and programs and it's really, you have to leap into it. There's no kind of staging, you know, your sort of deployment of these things.

SPEAKER_00: 14:21

Are we building these systems in the right way?

SPEAKER_01: 14:23

My view increasingly is is no. I've done some work actually with Jordi Piera in Catalonia to look at the generations of EHR. And the first generation was where we just built or bought lots of systems and tried to strap them together. That was the 80s, 90s. So that was best of breed. You'd buy lots of things and try and put them together. Second generation is this big EMR where you have to leap into it and do everything. But now what we know is that data is going to be used for so many different purposes. If you're born with a chest problem and you're put into NICU, high dependency for babies, that data is going to bear out for your chest health for the rest of your life. And that data has to be accessible for decades in a meaningful format. And what we're learning now is is that we need a data-centric architecture because your data is going to be used in algorithms to help restratify you. It's going to be used to help make decisions about you in different institutions, indeed internationally, you know, with the international patient summary. It may travel with you so that you can be treated abroad when you need it. And so this data-centric architecture would say you separate your data from application because one thing I can bet is that in 10, 15, 20 years time, how doctors, nurses, and those in healthcare systems operate will not be via the keyboard and typing. It will be via voice, gesture, who knows what, right? It will be things we haven't even imagined now. If you record a really good date set now, That will last through that journey. But what we're doing instead is recording the data driven by the interface. The interface says this, so we're going to record this data. What we need to do is, no, we need to look at human, what we need to record, and actually keep that in a format that is consistent across time. And that data-centric architecture and separation of data from application you see in other industries, but it absolutely makes sense because I believe somebody should be able to carry their digital twin with them, which is all of their data about them. And you've got a human right really to your digital twin because you can learn about yourself from your data. You can take it with you. So yeah, so the future is really about the citizen having access Every actor that they need to have access in their healthcare journey should have access. But it shouldn't preclude people from actually providing care because they don't understand the data.

SPEAKER_00: 17:05

And this is what you mean by thinking of data as the foundation, not a byproduct of these systems.

SPEAKER_01: 17:11

Absolutely. Data is not a capital asset, yeah? It's something that will have value over decades or even 100 years of somebody's life or beyond. If you can imagine in the future... 100 years of data in your life, you may actually give that to your family for informing their health care. I certainly know in my family there's breast cancer, there's bowel cancer, there's other things. If that data was available to me, it would help to stratify my health care. So this could become something that is a legacy that's passed on through families and generations.

SPEAKER_00: 17:44

What would it mean to design systematically around data rather than trying to retrofit the system?

SPEAKER_01: 17:51

That's very much the space that I'm in now, is designing what is needed for a human's healthcare record for their life, yeah? And designing it in a non-duplicative, semantically harmonized, as we call it, way, which means we take blood pressure, as we talked about earlier, there is one concept of blood pressure, not 40, are different concepts. And In order for that to be used in different places, we use something called templates, which are a layer that allow it to be used in different places. So the idea here is well-engineered data is a combination of clinicians and those that work in the technical space working together to optimally work out what data is needed for a human in the most efficient way and the most representative way for it to be used for all of the use cases today and tomorrow.

SPEAKER_00: 18:45

So you're the Chief Exec at OpenEHR. Can you tell me a bit about the organisation, where it's come from, and how does it fit into this landscape and the work you're doing?

SPEAKER_01: 18:58

You know, I've not been on the journey with OpenEHR since its beginning. It's nearly 24 years that it's been running. And it started actually as a collaborative between both clinicians and technologists at UCL in London. with the input of some of those clinicians being from Australia as well. So it's an Anglo-Australian initiative and it's incredibly powerful. It took me a while to get this concept, I've got to say, because certainly on my journey, I've not always appreciated how important the data is. So 24 years ago, they had this kind of epiphany and light bulb moment about data and they set up open air and Professor David Ingram was pivotal in this happening at UCL. And that community has grown and grown as a not-for-profit community of interest that actually defines and develops these standards. Around about half or just over half of the community are clinicians. The rest are technologists and leaders. And it has a governance where it's almost a Delphi, if you like, of people who go through these processes and work out what the optimal data engineering is for any aspect of human healthcare. And as that grows, that modeling, as we call it, data modeling and clinical modeling continues so that we can actually grow the sort of data architecture that is enabling human healthcare.

SPEAKER_00: 20:31

So this was what attracted me to invite you onto the podcast today because it's all about problems worth solving I wonder how you how would you summarize the problem that you're trying to solve as an organization

SPEAKER_01: 20:42

I will summarize this from my experience I think others will have different views but I was involved in data saves lives in Manchester and we saw that as we improved data quality and access lives were being saved and improved it was quite a scorecard that literally had a huge massive impact on me And that made me realize that as we have a single source of truth for human life, and as we make that available as appropriate to different endpoints, you can have really big impacts on lives saved and lives improved and quality of life. And what I see in the community is a set of people who have seen that too. They've seen that we need to engineer data better and make it available to particularly to the citizen and to the healthcare settings that may not be the primary healthcare setting to the citizen, because it is a quality and safety issue. One thing that I came to, and I'd like to do some research on this, I haven't had the opportunity yet, is there is a link between unwarranted variation in data and unwarranted variation in care. And we know that unwarranted variation in care causes harm. And so this is all about harm, quality and safety. It's a set of people that can see an ability to do much better in health and care.

SPEAKER_00: 22:08

Imagine you're immensely successful, which of course you're going to be in the work you're doing. What does that success look like for the system?

SPEAKER_01: 22:18

I think the success for the system for us looks like every citizen, hopefully globally, let's say we're really successful, let's say globally, every citizen having their data available to them and the care providers that they want to treat them, and those doing research, you know, all of the actors in the system, when they want it, where they want it, in a format where you can get speed to value by putting AI, intelligence, apps on top of it. So it is really about removing the friction of data today to enable a much better healthcare system of tomorrow. And also one personal thing for me, we were talking about EMRs. EMRs reinforce the hospital walls, which pushes more and more activity into the hospital. And so we do more in hospitals now. I would really like to see OpenAir being part of the solution to allowing a record that is available anywhere, which means we can deliver care in the home via apps, devices, and citizens can self-care. So there's this aspect of stop reinforcing the hospital walls and start allowing care to be delivered in the most logical place.

SPEAKER_00: 23:29

What's the implication of that for innovation and kind of the wider system changes?

SPEAKER_01: 23:33

So if you think about that, There are lots of things that play against us actually innovating. And by innovating, I'm going to take that as meaning you models for operating healthcare systems. Yeah. So if you want to start operating healthcare systems where you have distributed services, you have self-care, self-management, you have management by exception from medical devices, you have apps and wearables that support a citizen to self-care and prevent all of that. requires a single source of truth about the patient. And it requires that data can be managed across the entire set of organizations in the experience. The average patient back in Manchester would have been known to five organizations. That's just an example. So for me, for the future, this ubiquitous pathway allows those innovations because there's not any of the frictions of stovepipes, data silos, if you give the citizen the ability to control their record as appropriate as well, you can allow things like citizen science and innovation to happen in that way, which is a new avenue. I think that's really interesting, allowing citizens to participate in trials and studies and contribute. I'm seeing some good example of that. And for me, just taking away all of the friction of actually wrangling this data into the right shape, having it lossy, not allowing certain actors access to it, we could really speed up the innovation. I was just with Lord Darzi yesterday and he said the answer to the next generation of the NHS, the NHS's future, is all in the data.

SPEAKER_00: 25:25

There's lots of hype around AI in health at the moment. I'm curious about what you think we're skipping over when we go straight to the shiny stuff.

SPEAKER_01: 25:34

So coming back to the Paris AI Summit back in February, they said in all sectors, it's about great data and it's about good governance. I couldn't agree more. I'm afraid it's a lot of really hard work to get our data right and to work out how we govern in the age of AI. And that's fairly boring stuff. So risk frameworks in AI governance is something I've got deep into. It's not going to grab any headlines, is it? But it's the work that needs to be done. I would also say that another thing that we're missing, jumping straight to the shiny, is the platform approach to AI. We're looking at hospitals that have got tens of different AI algorithms. In the US, it may be a lot more. But for each of those algorithms, you have to monitor it, you have to audit it, you have to understand how it's using data, you have to look for bias, you have to look for cases where it's not been effective. And if you're going to have humans do that, that is not scalable. So these oversight platforms, which we're starting to see in the marketplace now, I think are an essential component because they will help us to govern and ensure the safety of these algorithms. What we can't do is allow hundreds of algorithms to be out there without this kind of oversight platform and management platform. And I think that kind of middle ground marketplace, if you almost like, where you can actually monitor those algorithms and their performance is going to be an essential part of the future.

SPEAKER_00: 27:10

And that would involve having a human in the loop.

SPEAKER_01: 27:14

Absolutely. Human in the loop, but to manage exceptions. At the moment, we just don't get that data. It has to be a human go in and look at the performance of the AI and check it on a regular basis. Humans in the loop always, right? The reason you need humans in the loop are multiple. One, you need that human judgment there. Two, There will be exceptions that are valid. If you look at certain hospitals or health systems that deal with the most problematic cases, you will see things that are spurious in terms of outcomes and results there. It needs that human interpretation to actually understand why things are exceptions.

SPEAKER_00: 27:54

What do you feel the role of data is in population level insights and personalised care?

SPEAKER_01: 28:00

I'm a huge fan of social determinants of health. And the biggest factors that actually determine your health over time are your education and work status over a population. For me, there is an awful lot more that we can do to actually find out how we can help our populations stay well and intervene and prevent disease. ill health before it happens. And a lot of that does reside in non-healthcare data. And a lot of the questions around that are the ethics. So I certainly know that in the US, certain health systems have got agreement to access the financial history of their patients. They've consented that. That's going to take a lot of thinking if we ever wanted to do that in the UK. Is that something we would do? Maybe not. But there is a whole domain here that we need to explore in terms of pulling together that data. But some, again, coming to the US, I've just said that, we may or may not want to do it. But in terms of actually using some of those tools, social determinants of health and the wider data, I've seen some excellent examples where they've taken people that haven't turned up for their breast cancer screening, as an example, for five years and managed to get 65% of them to do that within six months.

SPEAKER_00: 29:31

How did they do

SPEAKER_01: 29:32

that? They analysed all of this data, found out their motivation, found out demographics of these people and put nudges out that were tamered to them, that would appeal to them, and would speak to them about why breast cancer screening was important. And that just blew me away. Really blew me away. Yeah.

SPEAKER_00: 29:51

And was that driven by AI?

SPEAKER_01: 29:52

Partly by AI, partly by the great data, partly by psychologists, and partly by some great public health clinicians, some of whom are from the UK.

SPEAKER_00: 30:03

Is it a false split to say there's health data and there's social data involved? Actually, you want to look at the whole picture. Yes.

SPEAKER_01: 30:09

And it's beyond just social data. It may be lifestyle data. It may be one thing I'm very keen on is what is your preferences as well as a human? We should be asking that. That should be put in.

SPEAKER_00: 30:20

And that surely leads to the responsibility for ownership of that data needs to be with the individual. Yes.

SPEAKER_01: 30:26

Were possible, it does need to be with the individual. And we've seen lovely examples like One London at the moment where citizens can now contribute via the NHS app to their care plans. We need this to be a partnership with our citizens. They need to be able to contribute to their record. And I think that the true future of healthcare is a partnership between the NHS and our citizens. Obviously, there'll be some people like my late father who'd had two strokes and had lost his speech who wouldn't be able to do that. We need arrangements for people where it's not suitable. But for those that want to and need to, especially with the coming generation of people who expect digital services, I think we need to do this in collaboration together.

SPEAKER_00: 31:12

The data becomes increasingly valuable when it's being used in all these other different ways. Who should be responsible for governing that data?

SPEAKER_01: 31:22

That's a very good question. And that's a very interesting question when the citizen is contributing, you know, your lifestyle, your garment, your Apple Watch, whatever else. It becomes a spectrum of data that is co-owned. I think for me, anything that is created in the clinical domain needs to be owned by the health system, but also organized. a copy of that owned by the citizen. It's a dual responsibility. The reason is that the health system needs to own it to make sure it is safe, it's secure, it's audited, all of those things. It has a responsibility to keep that. But then there needs to be a synchronized copy in the health record. In terms of lifestyle data and potentially some aspects of social determinants of health, I think there really is an ownership by the citizen. If we come to financial data, There are certain patients who may choose to share that with their healthcare system because they believe it will improve their outcomes or it will improve the population's outcomes. I think those sorts of pieces of data should be down to the citizen to choose to share. And really what I see as a longer-term goal is the ability for a citizen to go in and say, do you want to share this data? This is how it will be used. This is what we intend to do with the data. And then a bit like we have with blood products now, if you donate blood in the UK, you've got a lovely text message and say it's been used in a paediatric hospital or whatever. You know that you've given back. I think there should be sort of postcards back to the citizen to say, these are the insights we've found using your data, or this is the research we've done and this has been the outcomes. And that kind of data donatorship bit, as you said, data's got value. And if you're giving back to others or you're helping others with that data, we need to close that loop.

SPEAKER_00: 33:29

What do you think health can learn from other sectors like banking around trust, access and usability?

SPEAKER_01: 33:35

Oh, trust, access and usability. I think let's take access. I think with banking, access is... ahead of most industries. I've worked with Barclays Digital Eagles and the way in which they are trying to make things more accessible to different groups, older populations, populations that may not have been digitally excluded. I think there is a huge amount we can still learn from financial services in terms of that. Although one thing I would say is that We're still not seeing banking in multiple languages, which we need for healthcare. That is one consideration that we have to make and one aim I know that health systems have got, which is to make your information available in your language of choice eventually, which is really important. In terms of trust, I think the Financial Conduct Authority has done a very good job of ensuring trust within the financial sector. And I once jokingly said, I'd love to see the NHS as kind of having a Bank of England-like function that was independent and could assure things and make decisions about things. But I think we need a very similar construct. Some of the things we have seen are what are called data trusts, and they are senses of third sector academia, patient groups. assuring the use of data on behalf of citizens. So if you think about a cooperative or a data trust, might assure the use of your data in a geography and kind of be your appointed party to do that. I think we need this kind of third entity that helps build trust because there are so many actors in the system And while it is the NHS's job to prove that data is used correctly, I don't think they can operate these sorts of groups that cohes everyone together and help assure how the wider system is using data. And I think that's a construct that's needed. Be it a FCA type piece, be it data trust, there's something that's needed in the middle.

SPEAKER_00: 35:42

Is that something that you can help with in your work?

SPEAKER_01: 35:45

I'm actually working with one of the leaders of... one of the data trusts at the moment? Yes, we absolutely can. And I think... The nice thing about open air and everything else is that being a standard that is used globally, it's a lot easier to put transparency toolings on top to see how it's been used and what's been done with that data. Outside of my open air work, I'm helping chair some research groups into this, particularly with patients that have got chronic long-term conditions, mental health conditions, looking at how they want their data to be used. So I'm finding, again, the human aspects of it. this. I continue to learn and I continue to want to know more about how we should interact with citizens and allow them to really determine their preferences for use of data.

SPEAKER_00: 36:37

What would massive success for open air? I'm saying it in the right way now. I was saying open EHR.

SPEAKER_01: 36:43

Either way is fine.

SPEAKER_00: 36:44

I've learned that you're saying open air. What would massive success of your ambitions mean for the big EHR vendors?

SPEAKER_01: 36:51

Some of them may well embrace this. It may be their next generation offer. For some of them, they grow a technical debt or a data debt. If governments mandate this, then that will be an issue for them. My view actually is that there should be incentives to help vendors move towards standards like this because we have to recognize that they've done good service as EMRs in hospitals and everything else. But where we are now, future forward, there is that day-to-day in the back end. And I think certain governments may want to work with those vendors to incentivize them or support them in moving towards supporting these standards. Because what you don't want to do is undermine a market that you have already. You want to help it evolve with you.

SPEAKER_00: 37:42

Do you work quite closely with the vendors in your work?

UNKNOWN: 37:45

No.

SPEAKER_01: 37:45

I work with a number of vendors. Some of the big EMR vendors, yes. Some of them, no. So they split into two camps. Those that feel that this is the future and are looking at the ways that they can start to enable this. And then some of them that say, no, just buy one big monolithic system, which I don't think is going to be the future.

SPEAKER_00: 38:08

How do you think we get the balance right between partnership and dependency?

SPEAKER_01: 38:12

Yeah. And I think... Partnership is key. Partnership with industry and a symbiosis with industry is absolutely key. But dependency, dependency is not good. And we have become dependent on certain vendors because of their bespoke data and their lock-in. They become the only people that can do certain things of the data because the way it's been curated. Data and dependency, for me, I think it's a difficult one because... If you don't want to be dependent on vendors for decades, you don't build in data locking. You don't build in data use standards. However, what I will say is the flip side of that is that the health system needs to be the intelligent client and be able to describe what it wants to buy and procure and how it will work. And they also need to recognize customers. As I said earlier, that there is an existing market that you want to take on a journey with you. So you have to influence the existing vendors. And I think in certain geographies, we're seeing intelligent clients emerge in healthcare. They're really understanding this and they're really driving it forward. But perhaps in some other geographies, less so, which means that they're not really building for a well-engineered data future. they really don't understand the importance of that asset or how to build it for their geography.

SPEAKER_00: 39:39

And what about getting NHS support and then global support for these standards?

SPEAKER_01: 39:45

So we have a huge amount of global support at the moment. You know, increasingly I'm in with governments from different countries, working with the AIDH in Australia at the moment, and they invited me onto their digital health advisory board. Ireland is moving to open air for its integrated record. We've got Greece moving in the same direction. We've got other countries I can't mention because the governments aren't ready to talk about it, but we have the Nordics who've traditionally used open EHR within their standards. You've then got countries like Jamaica that are using this and some of the African countries. So, you know, Jamaica's data model is open air. This is moving forward, but Obviously, with Opener being very small, not for profit, very frugal, this isn't done by selling anything. This is just done by talking through the logics of why you would do it and the successes that other people are having and just really getting people involved in a global community. It's really amazing that we've got as far as we've got and we're continuing to go on because we are a not-for-profit open source community. Anyone can take this and use it for free. It's a global good, a bit like Linux. It's very much an open source good. And so for me, it is the community that permeates the future. It is the community. It is the word of mouth. It is an ophthalmologist in one country talking to an ophthalmologist in another. It's somebody in one ministry talking to a ministry in another country and saying, look, we've done this work. We found that a data asset has got value for us. We are going to actually architect our data well. I'm going to base it on OpenAir and these other standards for the future. And actually, coming back to this, she talked about the NHS. There was work done around about 2019, I think, that valued the data of the NHS. This is not selling the data. This is not giving the data away. This is the value of being able to use the data and deliver the services effectively within the NHS. That was billions. It was around about six billion a year, potentially up to nine billion a year. Data has value. And people are realizing that now.

SPEAKER_00: 42:04

It's coming across that you think about data from the human perspective. Yes. I was wondering how much you think about data as a tool for social change and how we shift from seeing data as just a side effect of the activities.

SPEAKER_01: 42:17

So that's why I mentioned earlier the science collaboratives with the citizens, because citizen science, and I'm thinking about one example I've been involved with where we have doctors, we have patients, we have data, and they all collaborate around the data and the outcomes. I think that this is a huge opportunity for social change. On the other side of it, if we look at... I've just been reading a book on Facebook and how they use data globally to get the outcomes they want from people. If we use that science of being able to find out what people want or need from the data and actually nudge them, coming back to this, getting an uptick in breast screening, the things that have been used to market to us from the internet as a kind of dark science... could be turned into a light science of helping people and nudging them and supporting them with what they need to see, hear, or act on that's appropriate for them, yeah? And this whole piece for me, social change, we have to be transparent about how we're doing all of this. I think absolutely transparent. But the idea that we can actually allow citizens to drive more of this, it really interests me actually that in Finland, they have citizen assemblies that drive their healthcare system that see data and decide, make the difficult decisions about haves and have-nots with the budget. But is our future healthcare system going to be data-driven in that way, where you have a transparency of what there is, a transparency of the problems, transparency of the opportunities, tools that show you where you could put your money and what outcomes you could get, and you can make decisions as a set of citizens. I think there's an awful lot that could be done. And I'm also seeing global rare disease groups who are aggregating their data and taking action as a citizen group and approaching life sciences companies about finding different repurposing of drugs, whatever else. And you think healthcare really traditionally going back to the old NHS had the patient in the child state. And the clinicians in the parent state, and it was a parent-child, you did what you were told, you turned up when you turned up, you were given what you were given. Medicine of the Future, I think, is about the adult, which is about an adult relationship between the clinician and the patient and roles for both of them.

SPEAKER_00: 44:49

What are you most optimistic about right now?

SPEAKER_01: 44:52

There are a few things I'm optimistic about, and particularly today, because yesterday I was with a cohort of graduates from the Digital Health Leadership Programme. I am really optimistic that we can use data, technology, and human change to create the next generation of the NHS. I sometimes work with board leaders and I say, okay, let's sit down and imagine when you retire 20 odd years time, what does your healthcare look like in 20 odd years time? You're living by yourself, potentially, what do you want around you that helps you to be independent and feel confident? And we just describe what the what their ideal health system looks like. And then we look at how they get there, right? And I think people are starting to see what that future health system looks like and are starting to see how we get there. So I'm feeling quite heartened that actually we have the ingredients. We've got to wait for this whole change with NHS England and the Department of Health and everything else to play through. But if there's one thing I would say to the great leaders out there that I've seen, you will be part of delivering that future and we really need you.

SPEAKER_00: 46:00

What do you think that future health system looks like?

SPEAKER_01: 46:03

Again, going down rabbit holes. I talked about going down rabbit holes. One that I've been down recently with a couple of former colleagues is this idea of you have the capacity of the NHS and you manage the capacity and demand across the whole system. And there's no such concept anymore of referrals into a pathway. It's always next best action. using the whole capacity of a system. And I think we can get to a point where we can leverage every part of the NHS and know what capacity we need as a system, know what actions we need to take, and can bring in that efficiency across the whole system. So I've got this view that this intelligence that we're talking about for the future will really allow us to optimize what we have today? Because there is an opportunity to optimize, but that will also allow us to invest in the technologies for the future. One thing's for certain, we will always need our wonderful NHS staff because this is about a service that is really human-faced, has empathy, can put things into context. AI is never going to put a cancer diagnosis into context for you as an individual, right? that human contact, that human emotion, you need that. But what it will do is be able to augment our doctors, our nurses. And another thing I've been looking at is agentic AI. So what if you can actually take all of the knowledge that's out there, all the procedures within an organization, and for a nurse that's actually working on a night shift, he or she is able to actually ask it questions and get the knowledge of a huge body of knowledge, but instantly, you know, via a headset or via whatever else. Those sorts of things, I think, will really assist the NHS in revolutionising. I don't quite know how it's going to play out, but all I know is that in that 15, 20 year timeframe, we're going to have to have got there and the tools are there to get there. And that I see enough good leaders working and potential leaders for that journey to be taken.

SPEAKER_00: 48:16

And what about more immediately? So if you could wave a magic wand right now and change one thing about the way the system works, what would you change? I

SPEAKER_01: 48:23

think leadership needs to change. I don't mean take leaders away. What I mean is how people lead, how people in leadership are trained. So for me, just a basic example, if you go to youraverageboard.com in a healthcare organization, quite traditionally you'll have an estates director on there because that's something that delivers healthcare. You won't have somebody on there that's a CIO or equivalent because they're still thinking in terms of bricks and mortar for everything. I think the leadership needs a change of mindset and I have some hope that the future NHS will do this. The basis says we're going to deliver healthcare a new target operating model of care. So if there's one thing I could change, it would be changing the leadership's mindset to say, we need to look at operating model 2.0 for the NHS.

SPEAKER_00: 49:20

What's next for you, Rachel?

SPEAKER_01: 49:23

I think more open eye. Lots and lots to do. That said, I still do help the NHS. I still do spend time with the NHS. I'm very passionate that I will help the NHS going forward. But I think for me, I think I will just keep going down rabbit holes that I find. I keep finding problems and need to find out more. And so for me, this is an emerging journey and being engaged with data, AI, intelligence and the human aspects of that are something that are going to keep me busy for the next couple of decades at least.

SPEAKER_00: 49:59

I'd like to end on something thought-provoking. So what's One belief that you hold that others might not agree with, but you believe is true.

SPEAKER_01: 50:08

Does this have to be to do with healthcare or not?

SPEAKER_00: 50:13

No, just anything.

SPEAKER_01: 50:14

Okay, I'm just going to be slightly out there then. But again, I've been watching some of the hearings from Congress in the US and it appears that they have disclosed that there's non-human intelligence.

SPEAKER_00: 50:32

That's really interesting. I've also been following those hearings and it does seem incredible.

SPEAKER_01: 50:37

Absolutely, but hang on. In Congress, multiple people have said there is non-human intelligence.

SPEAKER_00: 50:43

I'm slightly mystified as to why this hasn't had more coverage.

SPEAKER_01: 50:46

Right.

SPEAKER_00: 50:47

It seems like quite a big deal.

SPEAKER_01: 50:48

And there is emerging evidence from huge numbers of military people in the US, that is true. Now, bear with me, this does relay back to healthcare. Because what does it mean to be human? If there are others, what does it mean to be human? And what does it mean to be human? We also have to consider in healthcare in terms of how we want humans to live going forward with the AI and increasing automation. We've got questions about the future of work, what happens when jobs are automated. I think the two things come together for me to say, we really need to consider what it means to be human in this current environment.

SPEAKER_00: 51:27

rachel it's been fascinating talking to

SPEAKER_01: 51:29

you i didn't think i'd be talking about that there you go

SPEAKER_00: 51:33

we must talk more but it's been great to talk to you thanks so much for taking the time to come and share your thoughts and i've learned lots about the work that you're doing and open air and hopefully our paths will cross at some point in the future

SPEAKER_01: 51:44

thanks for the opportunity

SPEAKER_00: 51:49

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