SPEAKER_01: 0:00

Hello, this is Problems Worth Solving, the podcast where we meet people transforming health and care through human-centered design and digital innovation. I'm Sam Mentor, 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. Today, I'm joined by Dr. Vidaya Sharma. Vidaya is a practicing NHS doctor. He's clinical innovation lead at the University of Manchester. He's co-founder of Fava Health, where he's using genetics to personalize medicine prescribing. He holds a PhD in health informatics. And on top of that, he's a graduate of the NHS Clinical Entrepreneur Programme. Suffice to say, if you're feeling like an underachiever right now, you're not alone. In this episode, we'll be exploring Videa's fascinating journey from transplant surgery to technology and innovation. We'll discuss his groundbreaking work in pharmacogenetics, which promises to reduce adverse drug reactions and improve treatment outcomes by tailoring medicines to patients' genetic profiles. We'll also discuss the design-led approach that Videa has been applying across his work in transplant care and in driving genomic medicine innovation. Videa, it's an absolute pleasure to have you here. To kick things off, could you tell us a bit about what first drew you to medicine and how that journey has evolved into the work you're doing now?

SPEAKER_00: 1:31

Hi Sam, thank you so much for having me and thank you for the kind introduction. Really excited to be here. I am originally from the Netherlands. I'm from Rotterdam, but I'm now based in Manchester in the UK. I first came to the UK to study medicine and I trained as a surgeon. and did my rotations around the northwest of England. I was first attracted to training as a doctor and medicine generally, mainly because I have a younger brother who has special needs or a learning disability and autism. So growing up with him, I always observed him being looked after by health professionals as well as social care professionals. And that really attracted me to the idea of being able to help people and make a difference to people's lives. And that was something that stayed with me throughout my formative years and drew me to a career in healthcare. Following studying medicine, I had a very traditional medical career. I was very much focused, as many of my clinical colleagues are, on going through the medical training program. I trained as a surgeon, more specifically as a transplant surgeon, and I there are as you can imagine various exams and competencies that anyone that's training in these fields has to go through and I was very focused on achieving those and I didn't really experience much outside the hospital I loved the on calls the nights the weekends the organ donation you know all of those kind of unscheduled emergency experiences and that was really my world that I didn't really know any different and I loved it for that reason I didn't really think I wanted to do anything different or didn't really think of any other careers or opportunities for me in hindsight is because I wasn't really exposed to anything else so as soon as I finished medical school I straight went into this medical career and didn't really experience anything outside of the hospital really and that was the case until I did a PhD and I was reflecting as a now senior clinician on the fact that I was regularly using technology and IT systems as part of my everyday work. As much as I was seeing patients or delivering clinical care, a lot of my time was spent on computers, logging things on IT systems. And as I'm sure many healthcare professionals that work in the NHS will have experienced, a lot of these systems do not meet the needs and requirements of the end users. So fueled by that problem area, I wondered whether there was something that I could try to learn about and contribute to that space. As I was Realizing that I was using technology increasingly as part of my daily practice, I decided to do a PhD in health informatics and really try to understand why are these systems not meeting our needs and requirements? Why are they not able to allow us to deliver care in an improved way as we experience lots of other digital products? My PhD really focused on how do we therefore design and develop IT systems that are better at delivering care across organizational boundaries. And that's because modern medicine and modern healthcare is not delivered out of single care settings or single organizations. And we could talk a little bit more about what we learned through that PhD during the course of this conversation. But that really allowed me to become an expert in this thing called interoperability. So how do you get IT systems to speak to each other? And during my PhD, I also learned a lot about design, which for me has become increasingly part of my daily work now. And that brings me on to my current role, which is being a clinical innovation lead, where I try to support researchers or startups or even larger organizations to translate their ideas, research innovations into real world products or services that can help patients within a healthcare setting. We're also trying to build our own little startup where we're trying to use genetics to personalize medicines for people and trying to make medicines more safe and effective um as we try to make um healthcare systems more modern and give people a more individualized experience

SPEAKER_01: 5:42

so you've built up an incredible suite of professional skills as you've gone through your career i'm really interested in that move that you've made from surgery into technology and into design um To understand that a bit more, I'd really like to learn about what's it like when you're working as a surgeon? What did you enjoy about it and what were some of the challenges? What prompted you to move on from working as a surgeon?

SPEAKER_00: 6:05

I think it's really different practicing as a surgeon compared to practicing as a researcher or innovator or as a designer. And I think particularly as medicine has become more popular, complex, as the patients we care for have got more multiple diseases at the same time, the challenges are really quite varied. And I think as time has gone on, perhaps there is an increasing need to blur the lines between healthcare professionals and designers, because now some of the challenges are that complex that you really need to start to think differently. I think one of the reflections that I often think about is as a doctor, as a As a medical student, you know, we are taught as soon as the patient walks into the room, you try to analyze them from top to toe, look for any clues that might be able to help you identify what could be going on with this person. Changes of their nails. Do they have any scars anywhere? Do they walk in a particular way? Who have they brought with them? Almost like a Sherlock Holmes, you try to as quickly as possible go from a list of diagnoses to a single diagnosis. diagnosis as quickly as possible and you really have that kind of narrowing down looking down a magnifying glass type way of thinking and that works really well when you're trying to make a diagnosis if you know one of the things that doctors would aspire to would be able to make a diagnosis on the spot just by looking at someone something called a spot diagnosis that was you know that's what you're aiming for and in that pattern of thinking you're encouraged to go with your assumptions. Common things are common is a phrase that's often used. And that is, again, fine if you're trying to go from a long list of things to a single diagnosis as quickly as possible. But if you're trying to solve complex, knotty problems like how do we improve efficiency in an emergency department? How do you reduce costs in an administrative setting? How do we make medicines more safe or effective? These are not problems that lend themselves to thinking in that narrowing down way, we need to think like designers. We need to think about broadening our horizons. We need to think about engaging the people that are affected by the problem, either the healthcare professionals and all the patients and bring them into that thinking problem understanding process before we even move on to solution. So as I started to learn about the double diamond and started to learn about various design frameworks, I started to realize, gosh, these are really valuable things that are completely new to me, but are really relevant to the problems that we face in healthcare. And how do we work together across healthcare professionals and designers to be able to tackle these problems? Because in isolation, certainly healthcare on its own will not be able to solve these problems in the same way.

SPEAKER_01: 8:53

Vidaeus, some of the people listening won't know, for example, what the double diamond is. Can you give me a little example of how that's relevant to the work you're doing and what the double diamond is?

SPEAKER_00: 9:02

Sure. So the double diamond is a framework for problem solving and it describes a starting point where you've got a problem area and what traditionally, and we continue to do this, sadly, in healthcare and other settings, is that people will often go from a problem straight to a solution. I say, for example, to try to put some context to it, the waiting times in A&E are too high. We need more doctors. Problem is, waiting times are high. Solution, we need more doctors. And people will jump to that conclusion and might even go as far as writing a business case. They might even go as far as hiring more doctors to try to solve this problem that they have concluded is there. And with a double diamond solution, framework encourages thinkers or problem solvers to do is to say well before you go down that path take a pause broaden your thinking speak to the people that are affected by that problem immerse yourself in that world spend a day in the emergency department see what's happening try to understand what the other interdependencies of an emergency department could be and really broaden your thinking before you narrow down on what's called a problem statement or narrow down to what the core of that problem is so for example again if we go back to our emergency department situation if you went through that process of understanding the problem, what you might realize is at the end of that process is, gosh, actually, it isn't the fact that we haven't got enough doctors. The problem is that the wards are full. And the reason why the wards are full is because they're not able to discharge patients. That's why the waiting times in A&E are high. You can increase as many doctors as you want, but you're not going to solve the problem that you're hoping to affect. Then the second part of the double diamond, again, encourages us to rather than saying, okay, now that we've figured out that the problem is that there were waiting times in the ward and patients not being discharged, again, rather than jumping to a solution, again, take a moment of pause and say, gosh, there could be multiple ways of solving this problem. Let's try out different ways. Again, let's speak to the people that are affected. Now we're not speaking to people in the A&E department. Now we're speaking to people on the ward because that's actually where the problem lies. So now let's immerse ourselves in that world and work with those people to try to understand what potential solutions could be and prototype and test and ideate before we then finalise on a solution that we can then implement.

SPEAKER_01: 11:13

You talked about how different that is from the approach you would take as a clinician to a medical problem. Did you find that transition, that mindset, difficult to change having gone through clinical training?

SPEAKER_00: 11:25

Yeah, absolutely. I still struggle with it. I had a great conversation with someone at a UX conference a few years ago where they said, as a designer, when they enter a conversation with a client or with an end user, they try to enter that conversation as a blank slate. They leave all their biases, try to leave as many biases, as much of their prior knowledge behind as they enter that conversation and try to be as open and receptive as possible. This person said to me, but you as a doctor, whenever you have a conversation with people, People expect you to have all the knowledge and all the expertise. That's why they're engaging into a conversation with you. And that's the mindset that you're in, that you are there with the answers as opposed to with the questions. So I thought that was really interesting. And I still am transitioning. So when I try to put on my design hat, I am really conscious of trying to leave my biases behind and my prior knowledge behind. What I will say, and I don't know whether this is self-complimentary or whatever, but I do wonder whether having some of that background medical knowledge does allow me to potentially ask better questions or does allow me to perhaps lead a design practice that is more focused and is able to get out needs and requirements in potentially different ways compared to someone who did not have any healthcare experience. So I'm trying to combine those things and trying to make them into a synergy as opposed to really necessarily see them as clashes.

SPEAKER_01: 12:51

So you still work as a surgeon, but you're doing lots of other things now. I'm interested in what prompted you to start doing other things and move on to that focus.

SPEAKER_00: 13:01

Lots of sleepless nights, lots of talking to mentors, lots of getting advice and other people who have had these more diverse or portfolio type careers. Really wasn't easy to make that decision. As I said, I was very focused on my clinical career and it's not common for doctors or surgeons to deviate from that really well-trodden path. And that's combined with the fact that there isn't really a alternative, well-delineated path pathway for healthcare professionals to do different careers. Having said that I also very much appreciated the opportunity to be able to apply some of these additional skills that I had learned so whether that's technology whether that's design and try to have an impact not just for individual patient care but at scale and that's something that really excited me and really attracted me so that was one of the big drivers for me wanting to diversify my career. Having said that it still required lots of reflection, lots of introspection to be able to make that leap. And currently I'm able to combine things. So I still work as a clinician, maybe once a week or once every two weeks for a day. I mainly do outpatient clinics. I don't operate much, or even if I do, I usually just assist or help senior colleagues out as opposed to lead operations. I don't think that's quite right. So I'm still able to balance seeing patients and This way, I almost treat my clinical days as a day of user research. a day of being able to speak to those on the clinical front line that are seeing patients day in day out to understand gosh what are your challenges these days what are your problems and be able to even take some of the ideas or innovations that we're working on and say gosh we're working on genomics personalized prescribing have you ever heard of this before do you think that's relevant to your practice where do you think the nhs is up to with that and that's a really useful real world feedback that i'm able to gather on a regular basis which again is a bit of a unique situation to be in to be able to do that

SPEAKER_01: 14:59

do you I think that the way you approach those days has changed since you've been doing more work around design and the double diamond and that side of things.

SPEAKER_00: 15:07

Absolutely. On the one hand, I really look forward to these days because, as I said, I still love seeing patients. I still love engaging in the healthcare setting as a healthcare professional. But at the same time, I do kind of walk away from those days thinking, gosh, you know, I am energized to go and do my innovation work because there is still so much more that we can improve here. The systems that we use, the processes that we have in place, there's still a lot of work that, you know, people like myself or you, you know, people that bring different skills can really make a positive impact on how healthcare is delivered. And that is not just being healthcare professionals.

SPEAKER_01: 15:46

So this podcast is called Problems Worth Solving, and we try to find people who are driven to solve problems in the system or in healthcare through their work. I'm interested in how you would summarize the problem that you're trying to solve through your work and why it matters to you.

SPEAKER_00: 16:00

Certainly from my experience from my PhD, the problem that I very much focused on was this challenge that we have healthcare experiences, whether that's as people that deliver care or people that receive care that feels disjointed where not all the information for decision making that's relevant to that time point is available and that is really by and large technology and design problem because we have some of these it's not even a technology problem it probably is more of a design problem because we have a lot of the technology to be able to share data or move information around. We obviously all have smart devices. We use technology and data at all time and we have various. And in fact, that's how my whole PhD started. It started this conversation between me and my transplant professor, Professor Augustine. And we were talking about the fact how we have iCloud and we have our photos in the cloud and the fact that we're able to move, you know, go from one account to another account, the fact that our photos are always there. And this is the time that we were completely technology naive. So a good four or five years ago. So I learned nothing about technology at that point. And I said, gosh, how is it possible that we've got all of this stuff in the cloud and the IT system is not able to talk to each other. We get a referral from a hospital down the road and it's sent via email or faxed over or sent to the post and things like that. So we just said, gosh, we just need to stick it all in the cloud. That the solution. You know, again, like I said, this is pre-learning about how to think about problems, how to solve problems better, jumping to a conclusion and saying, yeah, we just need to put it all in the cloud and then we'll be able to solve the problem and then we'll just have all the data wherever we need it and we'll be able to deliver better care. And with that kind of idea, we went to one of the health informatics professors at the University of Manchester to say, yeah, we just want to put everything in the cloud. And he was very kind to humor us and say, okay, I can see this is certainly a problem worth solving. or thinking about. I don't think that you'll be able to put everything in the cloud, but why don't you come and do a PhD? You can learn more about this problem. And that was a great experience. So I think trying to understand how do we move away from this more siloed way of managing healthcare data to a way where we manage healthcare data so it's available across systems, settings, organizations is something that I'm extremely passionate about. And yeah, I think one of the main ways that we found that you're able to do that better is if you start to think about This phrase that people may have heard before, but this phrase separating the data from the application. So currently what happens is that each IT system will have the data locked within it all the way through from the database all the way to the user interface. Whereas a more contemporary or more modern approach would be to say, well, the data is stored in a vendor neutral or in an agnostic way. fashion. It's stored separated from the different applications where that data might be used. And then you start to move towards an ecosystem where people can develop and design user interfaces or applications that meet more specific needs or requirements or feeding off the same data.

SPEAKER_01: 19:12

So just taking a step back, you're working as a transplant surgeon and That world, I don't know much about the transplant world. It sounds complex. You know, you have donors, you have recipients, there are surgeons, administrative staff, there's lots of communication and lots of information that needs to move around. Can you tell me a bit about the mechanics of that world and how that relates to the work that you were trying to solve through your PhD?

SPEAKER_00: 19:38

So transplantation, like many other services, and I work specifically in kidney transplantation, is delivered out of specialist centers. So what that means is that there will be one single large organization which delivers transplant services but it will serve a large geographic area and multiple regional hospitals which will refer patients in this is sometimes also described as a hub and spoke model of care so for example in the uk we have 22 23 transplant centers but of course we have well over 70 or 80 kidney units where people with kidney disease are being seen and all of these then feed into these lesser number of transplant centers And this is the case for many other services. So cancer services are specialized or some certain surgical services are specialized. So this experience of referring patients across organizations is really common. For us specifically in Manchester, we have our own local unit and then we have two other large referral centers. And what we used to find is that the number splits about a third across each of the centers. But of course, our referrals that would come internally would be quite streamlined. They would maybe be referred electronically. There would be lots of information about those patients like test results or previous letters or previous diagnosis that we'd be able to access easily. But patients that were referred from the other hospitals would require the local teams to post us information at a certain time point or indeed fax us. pieces of information and more modern in the last few years maybe attach a pdf to an email that was as cutting edge as we got and then there would be an administrative team within the transplant center which often would be highly trained nurses who are experts in transplantation whose role rather than being looking after patients or trying to support clinical services would be an administrative would be to organize all of these different pieces of information that that are coming in from these different sites and creating Excel databases or Microsoft Access databases, or maybe a shared folder where each patient has a file about their information. And that's how we would manage our electronic data. That continues to this day because we haven't got IT systems that support information being transferred electronically across organizational boundaries. So even though we of course have one NHS, we haven't got one IT system. So we continue to have this experience of having to move data around manually, really. So what that would mean for someone like me, if I was in clinic and I was seeing a patient that had been referred, say from one of the other hospitals, in the absence of a single unified record for this patient, we would have a paper form that we would complete for each patient. And that paper form would consist of all the different data fields that are relevant for transplantation. So that could be the reason for their kidney failure, whether they are on dialysis or not, if they are, how many times a week that might be, what type of dialysis. There'd be loads of information that we need to capture. But because it's all disparate across different systems, you needed a human, someone like me, a highly trained healthcare professional, to fill in a paper form to summarize all that data so it's in one place. And that form, the transplant listing form, as it was called, would be the golden truth for that patient. It would be the most important piece of document that we would be able to look back at to say, well, this is the information about this patient. So that's the way the clinical service was delivered. And that's really what we wanted to try to improve.

SPEAKER_01: 23:21

And what did you decide needed to change? So

SPEAKER_00: 23:25

after lots of work, lots of speaking to patients, speaking to clients, clinical colleagues across different sites. We did a national survey of all the 23 transplant centers to try to understand, you know, is this a national problem, which it was. After doing all of that work, what we concluded was if you want to move to a world where IT does support services like this, you really need to fulfill two requirements. Firstly, any kind of IT system needs to be able to to surface data across organizational boundaries. So you need to be able to surface data regardless of where that data was collected. And secondly, you want your system to be able to provide a view of that data that meets the clinical workflow. So what it is that a healthcare professional is trying to do, so in this case, list a patient on the transplant waiting list, add a patient to the transplant waiting list, You want to get a view of the data in a way that allows that healthcare professional to complete that task. Sounds like pretty basic requirements, but at present we don't have any systems that are able to fulfill these needs, which is why we have all these workarounds.

SPEAKER_01: 24:41

So you built or designed thinking into the way you approached this problem. I'm interested in how that affected the work. And how do you think it would have been different if you hadn't taken this approach?

SPEAKER_00: 24:50

So basically, The best way that we were able to use design was firstly being at the University of Manchester within the informatics department. This was a strategic choice because originally there was this question mark about where I as a PhD student would sit. Would I sit within the transplant department or would I sit in the informatics department? I very purposefully selected to sit in the informatics department. And that's because I wanted to build a local network of people that are working in this space. So I very quickly built up a team of a user researcher, a graphic designer, and even a dev team and a technical project manager as well. And we actually went on to even start to build some small things. But certainly for that early ideation phase, having those people really close was really important. So they taught me a lot about design and taught me a lot about prototyping and drawing wire frames and all those kinds of things that are normal in the kind of design world, but were completely new to me as a healthcare professional. And then I think it was, again, that combination of being a healthcare professional within the system. I used to sketch out things, walk around the wards, grab a duty doctor and say, hey, gosh, what do you think about this? Go up to the consultant's offices and say, hey, can I show you something on my laptop? I've been thinking about this. What do you think? And really rapidly get that feedback, which I can then take back to the design team. And we could prototype ideas. We could draw things on Figma. We could put it into a little prototype on a little app or something and get people to really interact with it. And I think that was really, really helpful. If we had taken a less of a design-led approach, It's hard for me to really imagine whether we would have made any progress, certainly not in this kind of way, because I don't really think that you can really innovate without understanding what user needs are. Certainly, if you do, you're bound to fail. So I find it hard to imagine. And again, this is in retrospect, we're very lucky to have made those choices at the time and build that team around us to deliver the work in that way. Alternatively, I can't see us having had much success.

SPEAKER_01: 27:00

And where did you get to with the work?

SPEAKER_00: 27:03

So we were able to get far with the work, certainly in terms of there were two strands to it. One was the design and the user experience part. What do transplant healthcare professionals want to see on a screen that allows them to deliver that work? And that really drove also a lot of the... technical requirements. So if this is what users want to be able to do on the screen, well, what does a backend and a technical architecture need to look like to enable this kind of user experience? So we were really led by what is the workflow? What are those things that need to be done on the shop floor? And how do we then take that back as we want to try to think about a technical solution? We prototyped that. We built a mini electronic health record for transplants specifically. And we published that as a research paper and presented at a large conference as well. And then we went a step further to think, okay, well, if we do want to build a solution like this in the real world, you need to start to think about the data. You need to start to think about the database that drives a user interface like this. And we then mapped all those data points out, identified which one of those we had already within our systems and which ones we didn't. And then again, we wrote that up as a technical architecture document. as with lots of health IT projects in the NHS or lots of projects in the NHS or any kind of large system. Generally, there are lots of variables that come into play with regards to decision-making. So we got as far as speaking to a local shared care record provider about potentially trying to build this, but then our local hospital procured a new electronic patient record and a lot of the IT resource was shifted towards that implementation. So we never got to carry on with that and ultimately build that in the real world, but we certainly learned a a whole ton about how do you do this in the real world and how do you ensure being user-led and allow that to drive your technical requirements.

SPEAKER_01: 29:03

What would it take to actually make it happen? So you've done a lot of work to create this kind of ideal system that would really work for clinicians and staff. Can you tell me a bit about what you think would need to change for it to actually be implemented?

SPEAKER_00: 29:15

Yeah, really good question. So it's super complex and the layers of complexity are technical, social, organizational, and even beyond system level, at a political level and international level. So there's lots of layers of complexity there. I think from a technical level, one of the things that we need to start to do more and think more about is this concept of separating the data from application. And that really comes down to agreeing what stuff is called. We have lots of language that we use as humans, which are very comfortable with, but machines don't communicate like humans. So in order for us to be able to more seamlessly share information between different computer systems, we need to agree as humans that this is what stuff is called. So for example, something as simple as blood pressure, which is a concept that a lot of people will have heard of will be coded in these IT systems differently. In one system, it might be called BP. In another system, it might be called blood underscore pressure. In another system, it might be called systolic blood pressure. And there are ways of standardizing that. So that's where this term data standards comes in. And there are various data standards that exist. The important thing if we want to start to move to a world where we have better communication between systems is to use what's called open standards. And open standards really just refers to the fact that we have agreed a group of experts or domain people that work in that particular domain have agreed what stuff is called. And they have then published that openly and made that available for people that build IT solutions to use. As opposed to a company saying, having a proprietary, a closed way of storing data within their system, not making other people aware of how that data is stored. And what that means that if you did want to communicate with that system, you would most likely have to pay the owner of that system to say, gosh, can we please extract data or exchange data from your system that we do not know how it's stored? And therefore we need to do a bunch of translation and mapping and things like that to be able to exchange data with your system. So trying to encourage the adoption of open standards is certainly a something from a technical perspective that's really important.

SPEAKER_01: 31:38

And do shared care records have open data?

SPEAKER_00: 31:43

Not at present, no. So most shared care record systems are still proprietary. There are examples of people using open standards. A really good example is the Universal Care Plan in London, which uses the one London shared care record and particular pieces of data around the a person's wishes around their end of life or their personal wishes are stored using open standards. That's been really transformative because in a really short period of time, they were able to make this really important piece of clinical information available across the entire London ecosystem. Increasing this way of working is something that's perhaps opposed by the commercial entities who are already in place. As you said, there are already lots of companies that provide health IT solutions, electronic patient record solutions, and this way of working might not be in line with them, but it's certainly what is right for patients. So that's something at a technical level. I think there are still large cultural shifts that we need to make. So this is both amongst healthcare professionals as well as healthcare decision makers. where we need to, even though we recognize that there is an importance in data being available at the point of care, there is still a culture of organizations thinking about their individual interests before the interests of a region or perhaps the system. So, for example, the procurement of electronic patient records does not include considering how does this system share data with a wider audience. healthcare ecosystem. So even though procuring an electronic patient record might be transformative for a single organization, it does not necessarily mean that now suddenly the GP has also got access to the patient record from the hospital. Arguably, it might even be the opposite, that now there is less access to that information in a hospital. So I think these decisions are difficult. And I think we would benefit from having more of a system approach. And that doesn't need to be a national approach. I think probably national is too hard, but perhaps at a more regional or perhaps an ICS level to think more about, it's an integrated care system level. So at a regional level, think more about how do we design and implement IT solutions that benefit our region, not just our individual organisations.

SPEAKER_01: 34:12

You've also mentioned previously kind of resistance to change and how that can be difficult.

SPEAKER_00: 34:16

Yeah, and I think this is a challenge, right? Trying to get healthcare professionals or any kind of busy healthcare under pressure professionals to adopt new practices is challenging. And again, this is of course where design comes in and an ability to be able to convince your end users that this is going to enhance their experience of work is an argument that, you know, we can make better and this is I think really where people are drawn in or convinced by visual representation so using prototypes or using you know videos or using examples of real world that I think helps convince people that this is something that is worth adopting and will therefore have a positive impact on their work having said that in reality and again this is me being candid and reflecting on my own experience of having used lots of IT systems in healthcare care is that they don't always enhance the experience of delivering care. And they can detract from being an empathetic, caring professional because they are burdensome. They are clunky. They take a lot of time to load. They do not complement the workflow that healthcare professionals are delivering. And you have these experiences that people describe that are because of the IT system, I have to change my practice as opposed to IT system adopting to my practice and my workflow. There's a great New Yorker article by Atul Gawande. It's relatively old now, but it's titled Why Doctors Hate Their Computers, which I'd recommend people checking out. It's a real candid and honest analysis of how, as healthcare professionals, we are not necessarily trained to sit behind computers, right? That's not part of our training. That's not part of what we thought being a doctor or even a nurse is about. But it is a very big part of our work today. So there is a lot of change that we need to drive, maybe even through education, to make that adoption more successful.

SPEAKER_01: 36:23

I'd like to move on to talk a bit about your work around genomics now. You've been looking at the way genomics can increase the efficacy of medicine prescribing. Can you tell me a bit about the problem you've been trying to solve here?

SPEAKER_00: 36:34

Yeah, I really fall in love with this problem over the course of the last three or four years. And that's because we know that people respond differently to medicines. We know that a big part of that response is determined by our genes. We know that sometimes medicines work well, sometimes people have side effects, or sometimes medicines don't work at all. However, in reality, We don't prescribe medicines based on individual characteristics or individual genetic characteristics, certainly, which to me seemed like a huge health opportunity because we know that the science around this is mature, but the challenge is really how do you operationalize something like this? How do you make something like this part of everyday care? In other words, how to design a service that allows people to have their genes tested, for that information to be made available to a healthcare professional, to a healthcare system, so that it can inform prescribing at every given opportunity. And when I first learned about this problem, I had this great experience of being in a room full of incredibly smart people who are scientists and experts in this field. And, you know, were telling me all about the evidence base and the background of this and I was really impressed because it was about common medicines that we prescribe every day in the NHS. So things like medicines to lower your cholesterol, medicines for anxiety or depression, medicines for heartburn and reflux. So the types of things that are prescribed every day in a large healthcare system like the NHS could be improved potentially if we had genetic information about patients that influences their response. So this is not about general genetic information or testing all genes in people. It's specifically looking at genes that relate to how people respond to medicines. And that science that links your genes to how you respond to medicines is known as pharmacogenetics. So pharmacogenetics is that science that links those two. And when I first learned about this, I very quickly realized this is not a scientific problem. And the thing that I always say to my colleagues is like, it sounds like you've done the science. If anything, stop doing the science. This is an implementation problem. This is a how do you make this part of everyday care problem, which is, you know, very much in the space of design and technology and digital health. So that's how I first learned about this and realizing that I probably had skills and expertise that perhaps the team the laboratory, the scientists, the genetics teams that have been working on this historically did not have, we found that there was a real complement of skills and expertise that allowed us to start to think about, okay, how do we make this happen in everyday care? And that's what we've been working on over the last few years. But we are doing this at scale within the NHS at present. And at the same time, we're also thinking about how do we potentially In order to accelerate this, build something independently that supports the healthcare system to implement this more quickly.

SPEAKER_01: 39:45

So this would mean genetic testing for anyone who's going to be prescribed medicine?

SPEAKER_00: 39:48

That's right. So there are different ways of how this could be implemented. So people sometimes talk about pre-emptive genetic testing. So that's genetic testing, say, at a certain age or at a certain time point when you have a first medicine, for example, or when you have a diagnosis of something like heart disease, you're then on offered this genetic test as part of that. And then that information needs to be available at different time points when you're prescribed medicines in the future. So we know people that receive one medicine are more likely to receive a second medicine as part of their health journey. And together with that, we also know that the prescribing of medicines is the most common therapeutic thing that we do in healthcare. It's the most common thing that healthcare professionals do actively is prescribing medicine. So we think that the opportunity is huge if we're able to put this into practice. Of course, putting it into practice is really hard.

SPEAKER_01: 40:42

Have you had to do a calculation where you say, actually, if we're going to start doing this testing on all these patients, the benefit outweighs the extra costs of doing that genetic testing?

SPEAKER_00: 40:52

Yeah, absolutely. So there have been lots of calculations along that line. The challenge with this is multifold. And we have very clever health economists who are trying to work on some of these cost-effectiveness analyses. And it's complicated because the cost of genetic testing has been rapidly declining. So year on year, that investment would potentially change. The other thing that's really hard is that even though you could maybe quite accurately estimate how much it would cost to test an individual person say it costs 150 pounds per genetic test to do this for example that's quite predictable even if that's relatively stable might be 140 pounds next year or 125 pounds a year after or whatever that's or certainly if you start to scale that cost might even come further down but that's relatively predictable what's hard to predict is what would be the infrastructure investment to support the digital and data part of making this part of everyday care? So you could test people and you could have that data, you could have those genomic insights, but how do you then make that insight available within a prescribing workflow for a GP, for example, or how do you make that information available to a pharmacist who's dispensing a medication? And what would be the cost of developing systems that enable that information transfer. And that's hard to predict. It's hard to know exactly how much that would cost. As you know, integrating systems within the NHS is challenging, and this would again be a difficult challenge. One of the potential advantages that I think this space has, a reason why it attracted me, is compared to all the other data that we have in healthcare, Thinking back about the transplant example, so things like blood pressure or blood tests that we've been doing for 20, 30, 40 years and have been storing electronically, they're already trapped in all these silos. And it's really hard to unpick that. So potentially the place that we could innovate in this more open data way is in these new use cases. So genomic data, this pharmacogenetic data, has not been locked up. into all these electronic patient records for the last 20, 30 years? Can we take an approach that is interoperable by design? Can we think about and appreciate the fact that we're going to need this information across the healthcare system from the outset and therefore not lock it up into different silos? And again, to support that, we have ourselves developed the open data model for a pharmacogenetic test result, which we just published a couple of weeks ago. So we're super proud about that. And that is something that's publicly available. So anybody that does want to build an IT solution to store pharmacogenetic data can use this open data model to do that and therefore be, in theory, interoperable.

SPEAKER_01: 43:45

And have you got a percentage on how much more effective medicine can be with specific conditions if you take this approach into account?

SPEAKER_00: 43:54

Yeah, so a large study was published in The Lancet last year, which was an international study randomized controlled trial, so a very high level of scientific rigor in that approach, where they looked at people that were having pharmacogenetic testing versus those who weren't and were being prescribed medicines. And really the headline figure that people take away from that study is that people that were having pharmacogenetic testing had up to a 30% reduction in adverse side effects, so adverse events, which is a really high number. So 30%, and this again relates to the fact that A, these are commonly prescribed medicines. So these are things like antidepressants, statins for cholesterol. So the opportunity there to make a real impact is significant.

SPEAKER_01: 44:46

Are they able to measure outcomes as well as side effects? Does this impact outcomes or is it about making the medicine more effective in its day-to-day use?

SPEAKER_00: 44:55

Yeah, so... As I said, a lot of these things are complex because it's about different medicines which are given for different reasons. Measuring outcomes, for example, in something like depression might be harder because, again, there are multiple different factors that might lead to someone having low mood. Having said that, yes, absolutely, in the context of depression, there's lots of good scientific evidence that this does improve the number of medication switches that people have, the amount of time it takes for them to show an improvement in their depression scores. So there is evidence around that. And then perhaps another good example might be around something that we are again doing in the context of the NHS at the moment is trying to reduce the risk of something like a stroke. So we know that a good proportion of people within the UK population, around 32% of people, do not respond to the most common blood thinner that is given after a stroke. we give everybody this blood thinner, but if we were to do this genetic test, we'd be able to identify those people for whom it's not effective and therefore give them an alternative. And we know that people that do have the genetic changes that mean that that blood doesn't work, have a 42% higher chance of having another stroke after a first stroke. So again, that's a significant figure. So we know that this genetic testing can both improve outcomes and therefore reduce costs. So if you are preventing people having further strokes, of course, you're having an incredible impact on that individual person, but you're also having a huge impact on the health service because a stroke is a significantly expensive experience for health systems not just for the acute care but of course for a person who's unfortunately had a stroke will have likely a significant disability that they are left with and therefore be a cost to a social healthcare system. So being able to prevent those and improve the outcomes of things like stroke or heart disease is again something that we think are huge opportunities that they were looking forward to.

SPEAKER_01: 47:01

That must be hugely motivating once you start seeing the potential for the work.

SPEAKER_00: 47:05

Absolutely and certainly for me it's that motivation about the potential impact. And also it's the opportunity to work with real dynamic talented people from really different worlds so i get to interact with people that work in genetic laboratories i get to work with people that deliver stroke care on the ward i get to work with researchers at a university and being able to have that real diverse group of voices experts around me is really stimulating for me as an individual trying to learn and grow and develop

SPEAKER_01: 47:41

and how has your design thinking and your design-led approach influenced this work?

SPEAKER_00: 47:46

Yeah it's something I talk about all the time and maybe a really good anecdote I can share is as part of this work around personalizing prevention after stroke I've been leading a large-scale national pilot to implement this as a service across four sites. We've presented this to senior HS stakeholders. But the approach we presented is to take this design approach where we want to start small and incrementally learn. And even the phrase we've used is we want to design a minimally viable service. So we're not trying to design the perfect service, all kinds of phrases that might be quite common in the technology or in the design world, but certainly from an NHS perspective. system, NHS national perspective are still quite new phrases, new ideas, new concepts. And we've really enjoyed being able to bring those concepts to them. And I've worked really closely with a service designer called Emma Parnell on this, who's been really instrumental in being able to bring a designer into the project has been really, really helpful because that's really helped shape how this project's being delivered. But setting that tone from the outset was really important and then we did a similar exercise where we explained this to the pilot sites that we were working with so we said you know we don't want you to treat this as a project. We don't want you to wrap this up in cotton wool and try to make it perfect just for the sake of the pilot. We want you to try to do this as if this is a real world service. And we want you to try to think about this not as something that you're just doing for three months or six months or whatever. We want you to really try to think about how would this work in the real world. And we just had a joint workshop with all the three pilot sites last week and two out of three of them played exactly this back to us saying oh but you know as we've been trying to think about this we really want to try to think about this how this would work in the real world you know not just for the pilot but also beyond the pilot and it was really great to hear them basically take on the principles that we were trying to share with them and really go with it and really learn from that.

SPEAKER_01: 49:45

And what's been the impact of taking that approach?

SPEAKER_00: 49:49

Probably the best way to describe the impact of that approach is the fact that Within two months, one of the pilot sites has been able to go from having absolutely nothing never having done a genetic test before never thought about how this would work to just last week started genetic testing on patients who are coming into hospital with a stroke so within two months and of course we were able to provide that design support to them so Emma and myself visited all these different pilot sites we walked the shop floor we interacted with them we ran workshops with them and we constantly communicated with them and provided them with ideas and an opportunity to feedback and took that iterative approach but that did allow us to go from two months having you know within two months having nothing to starting to test patients and maybe put that into context you know in other settings it would comfortably take you at least six months if not longer to set something like this up and even then there would be lots of potential challenges whereas being able to really immerse ourselves in that world really get onto the shop floor really think about the nitty and gritty challenges allowed us to be far more rapid.

SPEAKER_01: 51:00

Would you refer to what you've been doing as a trial?

SPEAKER_00: 51:02

So it's not a research trial, which is maybe an important distinction. So I think I could definitely refer to it as a trial in the context of we are trying this out in the real world with a view of this transitioning into a real life service. I think that's another concept that we have been increasingly talking about today. which is a challenge within the NHS is that what we often do is we deliver projects without necessarily thinking about what is the outcome and the output of that project there might be an output but not necessarily an outcome whereas what i'm trying to encourage our teams to think about is that the outcome of this project should be either a service or a product that you leave behind or something that you leave behind that continues to run not something that starts and then finishes we need to be able to leave something behind that's sustainable and that's again a mindset shift But something I think is really important and something that will allow us to innovate in a far more sustainable way.

SPEAKER_01: 52:00

I mean, there's lots of parallels there with work in the government digital service, which has always emphasised funding teams rather than projects because of the, you know, you want to create change and continue to support that change on an ongoing basis. If someone were to hand you five million pounds after listening to you on here and going, that works amazing, we should be funding that. I'm curious as to what you would do with that 5 million and what would be the shape of the team you'd fund? What would you work on?

SPEAKER_00: 52:27

Great question. I would love to innovate at that intersection of genomics and digital health. So being able to put some of this preventative, personalised technology data and insights on individuals into practice. One of the things that we've been thinking a lot about recently with regards to where a big part of the problem is that people have talked for a long time about being able to go from data to insights. You'll have companies or innovators who'll say, oh, we create insight from data and that's really powerful. But actually the space or the gap that I think still remains in the space that we want to operate in is how do you go from insights to action? Okay, insight, you've now translated that data into something meaningful. Sometimes you can talk about actionable insights. Oh, we created actionable insights. We created a report of someone's genetic profile or we created an app or whatever. But how do you actually put that into action? And the action bit in the context of this personalized medicines, for example, really only comes to life if someone who is prescribing a medicine prescribes something that they weren't going to prescribe because of that action. actionable insight and until you realize that everything you did before is not meaningless but it does not provide a return on your investment until you realize an action how do you put that action into practice is really really hard and that's where we are working on so we're working on this concept called clinical decision support systems or CDS, which are things like alerts or pop-ups or things that appear within a workflow at the right time to provide information that allows an individual to take an action. And that's the place where we could innovate a lot more. You could make those actions easier to accept. For example, if someone needed to prescribe an alternative, you could have a one-click so they can automatically activate prescribe that alternative rather than have to go back in their workflow. So there's lots of innovation and user experience ideas that you could bring into that space to make that action more easy to do and therefore realize the benefit of all of that genetic testing or data to insight or translation or whatever that you've done before. I think the team to be able to deliver something like that absolutely needs to be design heavy. So, you know, we certainly would have to have a design team department, if you like. And that's not just from a user experience and a workflow perspective, but also from a visual and a graphic perspective. So I think that makes a big difference with regards to how users engage with their apps or with their solutions if something is visually designed in a way that makes that easy to do. And I think the other big part of the team that we'd have to develop would be around that technical, how do you store the data in an open way in order to make that data available in different places? So thinking about people that work with open data more regularly, and for example, the data standard that we work with is something called Open Air or Open EHR, which is a very well-known open data standard now. So people that are experts in that space would be attractive. And then you've got your usual people that can wear multiple hats that I think are always super attractive. So people that are comfortable with ambiguity. So this could be a clinician who maybe has done an MSC in design or maybe a clinician who's worked in a startup or maybe someone who's built a startup who now wants to build in healthcare. Those kinds of individuals I think are always really exciting and bring real energy and open-mindedness to teams.

UNKNOWN: 56:08

Yeah.

SPEAKER_01: 56:08

It feels like we're living in a time where things are moving really fast. Technology is changing. There's lots of new technologies on the horizon. What are you curious about in your work and what are you excited about? I

SPEAKER_00: 56:20

would love for us to be able to focus more and more on prevention and trying to move care upstream. As I even practice today, I still see lots of patients who I might be seeing for a year potential bowel cancer referral or for some kind of surgical problem, but who I can see have got lots of preventative or who have lots of diagnoses that could be managed much better. But we're failing to do that. And that's because the NHS, as healthcare systems around the frontline services. And that just leaves them incapable of being able to really innovate and shift the dial on moving care upstream. So a phrase that comes to mind is a Dutch phrase, which is dweile met de kraan open, which basically means we're mopping the floor whilst the tap's still running. So we are really focused on delivering services, trying to dry up that soppy wet floor, and we're focusing and we innovate and we're making robotic mops, we're making shiny mops, faster mops, etc. But I'd love for us to be able to move our attention to the tap and shift people's attention to, okay, how do we actually start to close this tap a little bit more? And that's not going to be overnight, of course, but I'd love to shift people's attention to that, which is really hard, of course, in the economic climate. That's something that I'm excited about and trying to work with more people on that.

SPEAKER_01: 57:54

And how do you see AI impacting both prevention and your work over the next few years?

SPEAKER_00: 58:00

So I think the main place where I see AI having an impact today would be around how do we improve data management and analytics around administrative data? So not necessarily clinical data, but how do we, for example, identify efficiencies in waiting times or in making clinics appointment times more streamlined? Or how do we reduce the number of people who might not attend their appointment by being able to automate certain processes around reminders or being able to identify patients that are perhaps more likely to not be able to make their appointment? So I wonder whether that's where I'm seeing AI perhaps making a difference today in the real world. Of course, there's lots of research and excitement and work going on in the AI space, but in terms of having an impact on the shop floor, I wonder whether that's a space where AI can make a difference today, alongside, of course, an impact in radiology and more image-based specialties, where I think AI also plays a big role. Certainly going forward, I would love for AI to start, you know, for us to be able to start to use AI to automate some of our workflows and simplify some of the manual data entry exercises that healthcare professionals have to do. So lots of healthcare is still around collecting bits of data that already exists somewhere in the system, but it's not available at the point where you need it. And I wonder whether certainly with Gen AI, perhaps this challenge around that data not being standardized across different systems perhaps there's an opportunity for AI to move to a world where it is able to interpret data a bit more like we do as humans and therefore you lose that need to be able to really system systematically translate and map between different IT systems and perhaps AI could play a really big role in improving that data sharing across different IT systems or different systems in healthcare setting and make that more readily available at the point of care.

SPEAKER_01: 1:00:06

You might have answered this next question through talking about AI, which is almost a bit magic, it feels like at the moment. But if you could wave a magic wand and change one thing about the health system now, what would you change?

SPEAKER_00: 1:00:16

If I had to choose one thing, I would probably love for healthcare professionals. So that's not just people that deliver to hospitals. work to deliver services but people that work in healthcare generally to be able to work more effectively together i wonder whether we still work too much in silos and that's could be between clinical departments that could be within administrative departments versus clinical departments managerial roles innovation offices etc i would love for us to be able to get to a space where we're able to work more effectively together I wonder whether the reason why it's really hard for us to work more effectively and collaboratively is because the system is just under such incredible strain at the moment. So even with a lot of the work that I do, I describe it as innovating under pressure because you are trying to do new things, you're trying to bring new ideas to the forefront, but the environment in which you're trying to do that is not really able to accept and adopt new ways of doing things. I'd love to be able to take the pressure off and I think that will then naturally allow an environment to flourish where people are able to work more creatively together and start to blur those boundaries because I think we all want the best for patients and we all want to try to deliver better care. Being able to work better across disciplines will allow us to do that far more effectively.

SPEAKER_01: 1:01:49

What's next for you, Vidya? And is there anything else that you'd like to share with us?

SPEAKER_00: 1:01:54

I'm looking forward to next year. I'm looking forward to 2025. I've had the opportunity to speak a lot this year and present my work and gather lots of feedback over the course of the last 12 months to 18 months, particularly around the work that we're doing around personalized medicines. Now we're looking forward to putting some of that work into action, some of that feedback into action and to start to build really. We've just been lucky enough to get selected for a small business development grant. So we've got a little bit of cash here. to build with. And yeah, we've just found a little team. We've got a developer that we've just onboarded a couple of weeks ago. So we're really looking forward to starting to build. And that's what I'm really excited about and continuing to hopefully speak to people like you and other creative people that are working in healthcare to continue to get feedback and learn and improve.

SPEAKER_01: 1:02:43

Fantastic. It's been a pleasure talking to you, Fidea. Thanks so much for taking the time to come along today. And I hope our paths cross in the not too distant future.

SPEAKER_00: 1:02:51

Thank you, Sam. Great to see you.

SPEAKER_01: 1:02:53

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