SPEAKER_01: 0:00

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, 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. So today I'm joined by Dr Jonathan Gregory. Jonathan is a cancer surgeon by background who worked in the NHS for over 20 years and held several management positions. He now works to improve patient care and outcomes using data, digital and AI via his consultancy Pivotal Health. He's National Clinical Advisor at Macmillan. He's digital theme lead at a national institute for health and care research and he's an honorary research fellow at Imperial College London. We've split this episode into two parts because we had lots to discuss. You're listening to part two where we explore Jonathan's work with Macmillan where he's using AI to improve patient communication. We will also dig into his groundbreaking work to understand the experiences of cancer survivors in the community and discuss his vision for the future. In part one, previously published, we explored Jonathan's background, what it's like working as a surgeon and practical experiences of health inequalities. We also dug into Jonathan's work to improve cancer pathways and the critical importance of getting the right balance between digital and human support. Part of being a doctor and a surgeon is, of course, your medical expertise, but it's also your communication and the way that you can communicate with that patient around their condition and reassure them or support them and that side of things. You've been doing some work with Macmillan looking at communication and the end of treatment summary side of things. Can you tell me a bit more about that work?

SPEAKER_00: 2:08

Yes, so it's based in cancer care and actually across really all care but there's what are called pillars of personalised care and they relate really to things like having support and information that you can access They're about having your holistic needs, your needs greater than the medical needs being addressed. And they're about, at the end of treatment, having what's called a treatment summary that sort of tries to wrap everything together. And these sort of pillars of care are very big in cancer, certainly a big priority for Miller. And so we tried a variety of things, but around treatment summaries, Things had really failed, which probably sounds terrible to the listeners, you know, why it's a letter at the end. This letter is meant to be slightly different. It's meant to be a letter that really tells the patient where they were, where they are today and where they're going. So it's subtly different from a standard clinic letter, which makes it slightly hard for doctors and nurses perhaps to generate those letters. Most letters we write are to other medics. So even if you're meant to be writing to the patient, it's not always second nature. But also time. If you say to me, John, there's five patients here who need their treatment summary left to doing. Okay, do you want me to do that or go see the 10 patients who just need to be diagnosed with cancer now? The front of the pathway will always win because that's where they need. So this has been stubbornly learned. The national average completion rate is about 8%. Now, the data, I think, can be questioned, but I think we can say it's very low. So I happened to, you know, that place I sit in, I'm always looking for ideas to beg, steal and borrow and bring across. I was at a conference and I saw someone talking about RPA, robot process automation. I thought, I think we could use that to deliver treatment summaries. So that started the seed of an idea. And over time, I've managed to build a collaboration that now consists of two cancer alliances, which cover 11 integrated care boards, Macmillan Cancer Support, the NHS Automation Accelerator and six acute NHS trusts. We've started work at the moment to try and build an automated solution to deliver these treatment summaries for patients.

SPEAKER_01: 4:30

So this end of treatment letter is a really important thing. And essentially what you're saying is it's not happening because there are other pressures on the surgeons to make more people better. When it does happen, what does that kind of end of treatment conversation and letter look like from a patient's perspective?

SPEAKER_00: 4:48

I think where it's done well, it is brilliant and actually is very hard to improve upon. I've had some meetings with clinical teams and I'm amazed at what they're delivering. You know, let's be clear, there's some absolute real excellence out there. But at a lot of places, it's either not happening or Really, the letter that goes out is very medicalised. It still begins with the list of your diagnosis in very medical terms, all about the receptors that were wrong and the chemotherapy drugs you've had. And in the workshops we've done with patients, they all say, I would just like a letter I can look at that perhaps makes me feel a bit less like the done-to piece of me, Tucker. I could look at it without perhaps shuddering. I mean, we know that, you know, again, back to our previous conversation about people's cognitive bandwidth. A lot of people, as they're going through their initial cancer diagnosis and treatment, all the letters, all the booklets, they really get put in a drawer somewhere out of the way, like the dining room. And they try very hard not to go back in there because it really takes you back to that moment. And we've heard in our workshops a real desire to have a letter that almost allows them to close the chapter. But they need somewhere to go back to, you know, for two months' time. Something's hurting. What am I meant to do? I've got a new cough. Or my daughter's asked me about, could this have a problem for our grandson? Where do I go? So eventually I've got a slightly friendlier letter. I won't mind going back to that. And those conversations I don't think happen widely at the moment. Not that they don't happen at all. But I think in that, perhaps using accessible language, flagging to local resources, we're looking at doing something that delivers far more in terms of signposting outside of the hospital to areas of support and resources that can be used to signpost to things that probably seem obvious to the clinical team. If I've told you, Sam, during your surgery and chemotherapy, stop smoking, lose weight, that's it. I don't really imagine I need to tell you again. But the reality is you were too worried or too ill or hadn't got the cognitive bandwidth to make those life decisions at that moment. But now that treatment's finished, it's a teachable moment again. And patients have said to us, I'm actually ready now, but no one tells me to do anything now. No one's saying lose weight. I can't remember where I put the stop smoking leaflet. So some of it is just about, in an automated way, recycling stuff. in the hope that it just lands on slightly more fertile ground this time round. So I think the conversations that happen now, and where they happen are brilliant, but we're trying to build something that compensates for where they don't happen or where the excellence is predicated on a group of highly motivated, highly skilled individuals. And of course, sickness or staff turnover can shake that. And what we want is something that at least delivers a good enough for everyone every day. And to put it in context, it's 330,000 people diagnosed with cancer a year. So that should be approximately 330,000 of these treatment summary letters going out a year. So the impact is potentially very large. Even if only 1% of people that letter has an impact for, I'll still take that number as being meaningful.

SPEAKER_01: 8:27

And from a practical perspective, how does this tool or this system you're working on work?

SPEAKER_00: 8:32

So we're currently building it. So I started off with high ideals and all projects. I'm compromising those as I go along. So the aim was to build something where we'd ideally need next to no human involvement because that's how we most release clinical staff and remove barriers to adoption and scaling. But because we're trying to drive this off data that clinical teams receive, of catching anyway. That was the plan. If you're doing all this stuff anyway, can we use those bits of data to drive letter content? It transpires we can and can't. So we're needing to probably bring in a couple of human-driven prompts to just help the system. But at this stage, we're using 1970s-style AI, Sam. AI that people don't think is AI. So it's logic. It's if it says this, then write that. So, for example, if the medical records say breast carcinoma, let's say breast cancer in the letter. If the document, if the medical records say stage T10, T1, N0, M0, we'll just put you had a very small cancer in your breast. So it's very like that. Now, that's been done deliberately because it will build confidence. It's human written information. We have no risks. So we've got a low barrier to trust. It does mean our initial product is going to probably be a little bit clunky. But once we've got it working sound and trust built in it, then we could look at using perhaps a very constrained large language model to round it off, to soften the edges. But so that's a phase two, whereas having seen already when some trusts have thought that what we're doing up front is, AI, the antibody response has been extremely large, Sam, and caused a lot of problems. So, which reaffirms that I think we're right to start with this technologically not very sexy solution, but being really clear, that's to get to Everest Base Camp. And how are you keeping the human in the loop on this? So, the trigger will be, at this stage, will be a human will say, will trigger the bot, the virtual worker, to generate the letter. And it will come back to that human to be sort of checked or signed off. Over time, as reassurance, we validate it. Then hopefully we can get less and less human needed. Because even checking 25 letters a week is still checking 25 letters a week, isn't it? It's another job to do. But I think people, the teams we speak to see the value in that they recognize that they can't possibly remember every support center and every piece of useful information resource they flag to. So for example, by knowing your postcode and your diagnosis, I can flag the nearest lung cancer support group to you is here. And someone else's postcode is there. A doctor or nurse filling one of these in, they've not got that on the tip of their tongue. So we can lean in that way around health inequalities is one of the drivers here, because if you're a very activated patient, being very engaged through your clinical course, I don't think this letter will make much difference to you, being honest. But if you find, you know, health literacy is not so good, English is a second language, then actually these sorts of letters, that's a single place to go that summarises clearly what I need to do, I would hope is helpful. But also it opens the door to us taking steps towards translation. You know, there's lots of people who have good spoken and listening skills English skills, but their reading of English is challenging. So even if we can, using the automation, identify their preferred language. So at the top of the letter, we can put in their preferred language, just an explanation of what the letter contains and lets us know if you need us to translate this or it's to be called to access. That's a start. It means they're not waiting for a friend or a neighbor or someone to read this letter for them. We can then, of course, move over time to translate them fully with a large language model. But again, the risk of that is slightly higher at this stage. But we can at least make a step, and that's a step we're not generally making routinely across the NHS today.

SPEAKER_01: 12:59

And this is work you're doing with Macmillan. So have you been able to make use of their huge network to come and get this out there?

SPEAKER_00: 13:06

Yeah, and certainly I think so. And I think the other thing I'd say is that Macmillan's is helping me to try and hold people to account on the project. It's like a poacher turned gamekeeper, isn't it? I think I'm well positioned to both sympathise with clinical teams and say, that's never going to work, that's too big a ask, but equally to channel into clinical teams to say, you and I both know that's not true, or sorry, that's not good enough, you need to come back again. And I think that Macmillan is of a trusted person. brand by a lot of people in that space I think help is helping us keep everyone on board being honest I sense everyone is supportive and everyone wants to do it but you can imagine the visions people are holding of course subtly different but of course Macmillan as well with its work previously around you know information for patients and carers We can draw on that resource of how should we explain this to people? Well, they've got material that's been tested widely with patients and the public. So we can draw on that to support the project. And we've got, let's say, we've got current patient partners supporting the project. And where that's invaluable, and I'm sure a lot of people recognise that listening to this, is they often have lower wants than everyone would assume. So we asked a group of specialist nurses what they thought should be in the letter. And then we asked a patient workshop. The patient workshop wanted about half the content the nurses thought they'd want. And that's really a principle of values-based healthcare, isn't it? Actually, if you measure value at the level of the patient, make sure you deliver that. And often that value may well be easier or smaller than we in the system imagine it to be.

SPEAKER_01: 14:56

So you've been taking a user-centred approach by involving patients and nurses in this process. Can you tell me a bit more about the process you've gone through in designing this?

SPEAKER_00: 15:05

Yes, and shall we say it's still very much actively in construction. So the way we've done it to date is identify the stakeholders and I've just ground them into submissions, Sam. Lots of one-to-one meetings at the start, trying to build a relationship, build a coalition. and gradually bringing more and more people in together. So I suppose going from that, and sorry, I'm making myself sound like Machiavelli here, but trying to make individuals feel bought into the project at a one-to-one level. And then you bring into a group and trying to use that both ways. Firstly, so people realise they're part of a bigger whole and this is hopefully going to scale through the whole NHS. So positive spin. It's also... you can use that to reduce a bit of pressure. Because if you're the one hospital out of six who's not done something, no one likes to be in that place. So he's trying to use that tension, I think, and hold that. And then with patients, we've run three patient workshops to date. So we started off surfacing their experiences around this, trying to surface their wants. What would they like from this? And then Some of these letters, some parts are generic. Do we want the letter to begin with dear Mr. or Mrs. So-and-so? Or do we want first name? Let's pair it right back. What's wanted there? So we've got a generic component where we're exploring with them and got a meeting next week exactly doing this. So how do you want the letter to sign off? And then we've got more specific content. So if we've got content that's really about the lived experience after prostate cancer, Then we've got some more smaller focused groups to say, how would you feel about it being explained this way? Does that feel right? I had the pleasure to take one of the patient information forum classes, PISS classes a couple of years ago about plain English writing for medical communication. I'm no expert, but it's really trying to bring it in there. National reading age 9 to 11. If everyone picks the easy read, shall we just make it an easy read then? We don't need the hard read. And I think a lot of this is hopefully bringing other experts in who know more than me, but me perhaps just holding enough of these little bits to know when we need help from people at which times to bring their expertise in.

SPEAKER_01: 17:31

So this work has been around the letters that people receive at the end of treatment. And obviously lots of those people have recovered and they are then out of the system. You're doing some work to understand the experiences of people who have recovered. What are you doing and why is this important?

SPEAKER_00: 17:48

Yeah, myself and my colleagues at Imperial College London, we've launched a national research trial to try and understand the experiences and outcomes of people who have recovered from cancer, but it's still affected by it, obviously. And so trying to do that at scale is difficult. So there's lots we know about patients after their treatment for cancer. But most of that relates to surveys done in hospitals, studies that were maybe attached to a drug trial or something like that. When you actually look at it, we don't know very much about people's lives when they're just getting on. And it might shock people to know, but we know very little about the services they use to try and minimize any impacts of cancer or its treatment. If you had radiotherapy to your neck, for example, You may have difficulty swallowing for the rest of your life. You may see a dietician intermittently. If that all happens outside of hospital, that's unseen really to the NHS, that cost, that need. So what we've done is design a survey to try and surface this. But that in itself, I appreciate, doesn't sound very exciting. But what we've tried to do is design this in such a way that it scales quickly and easily. So at its core, We designed it to be very easy for GP practices and people to support. We tried to think, you know, what's the value proposition to GPs? So how do we deliver that? We worked with some patient partners to design the initial survey. So we surfaced what they felt was important. And we worked with a couple of people who got deep experience really of questionnaire surveys after cancer. But then we tested the survey with 50 people from a variety of places to get feedback, trying to understand what questions worked. And then we ran the study as a pilot. So we piloted it in Northwest London and had 2000 people participate. And we then reviewed their answers, looked at the questions that didn't work so well, where the answers went right, had more formal usability testing, brought along eight more fresh faced patient partners. to refresh and review every proposal we made for the new one. And then we launched it nationally last week. And we've got 3,000 participants in only eight days nationally. So potentially this is going to be the largest study of its type in the world. And we've got people in the study who were diagnosed and treated in 1970 all the way through to diagnosed and treated in 2023. Our oldest participant today is 94. Our youngest is 18. We've got a real mix in there and every cancer type. That's one of the things is a lot of work today perhaps is focused on one group. But by making this available to every cancer, anyone diagnosed over the age of 16, you're sort of hoping to try and identify groups of people who have more problems with a particular thing than another group because then maybe we can identify coalitions. Maybe actually people who are treated for kidney cancer And for a blood cancer, some of their lived experience after treatment is really similar, even though they're very different diseases. But perhaps the support services could help or marry up there. Or is there anything we can spot that seems to particularly predicate a good outcome or a good feedback? So it's been really interesting. And within the survey, we ask people to provide feedback on what they think is good about the survey, bad about the survey. we encourage free text responses because we're curious to see whether do free text responses encourage people to take part? I think we might imagine they do because it's like saying, tell us, we really want to know. But maybe the blank space is intimidating to people with lower literacy skills. Maybe people do fill the free text in and ends the survey. It's like a mic drop. Told you all I want to know, I'm off. And I'm not sure We know that.

SPEAKER_01: 22:03

I think one of the really exciting things about AI, I mean, it's a small detail, but the chat GPT and the large language model is its ability to interpret thousands of free text responses in a survey. It's something that has never been done well before. And that suddenly opens up a whole new branch of kind of, it's qual research at scale, which has never existed before.

SPEAKER_00: 22:23

Absolutely, Sam. And we've actually, that is one of our, we've got lots of hidden aims in this study. predominantly it's a methodology study. How do you reach people living their lives to find out about their long-term effects of treatment for cancer? But hidden in it are, yeah, how accurate are large language models at producing translations? Can large language models interrogate the free text into categories and buckets? We're also asking about, does the sequencing of questions, how much does that influence people's responses? So we asked a very I think a complex question about whether people are happy or sorry, whether people consent for us to access their NHS records to look at their cancer treatment to hospital. And you're participating in this study because you received an SMS message or you saw it on social media. So you can think there might be some scepticism or concern. So we wanted to test whether if we ask that question near the start, are people a bit apprehensive put off and say no and is it different if you ask at the end when they've built up maybe some trust through the project through the server and so we've got lots of these interesting I'd say almost design pieces within it and certainly what we're trying to advocate here is really iterative research trial design it's not we've got a protocol we can't waver from this we're going to deliver it we're changing and dropping questions as we go with this study, as we see what works, what was better. And there's a common theme that will be the same, but we're quite happy to change it in light. And just this morning, I've had a message about a particular difficulty science habits survey, and you look at it and go, oh yes, I hadn't spotted that. So virus small amendment, we can change that. So I think it's trying to, as I say, deliver at scale, cheaply, representative data. that can then be used to design services, to audit services and to improve care. When you think, you know, so we've now got 5,000 responses and we have had a very small research grant for this. And yet most studies at that sort of scale, you'd be at half a million pounds, probably a million pounds. We're a fraction of that because we took a commercially available customer satisfaction platform

SPEAKER_01: 24:55

And what will you do with the results once you've got those in? Is this a long-term study or is this you're going to do a piece of research and then share the insight? What's next for it?

SPEAKER_00: 25:03

Yeah, so the study is open until December. And if anyone's interested, if they go to computationaloncology.net forward slash indigo, it's the indigo study. And the aim here is, Sam, is I think multiple in that, firstly, if this proves to be a way to reach people, We want to be able to give advice that says, if you're looking to find people aged 20 to 40 who have been affected by these cancers, we found Facebook liberated the most returns and participation. If you're looking for 50 to 70 with this, then actually it was SMS from the GP practice. That sort of piece to support others. But then looking at the service use, I mean, that data is actionable almost immediately. We know what lifestyle behaviours people have wanted to change. We've got these other things. So we'll be looking at trying to present that at a simple level to integrated care boards as soon as we're able. And then they say we'll work through the meat of it. But these numbers are going to be large. We've already got a thousand participants who have breast cancer, for example. So once we can get their NHS England data and to say, about 80% of people are agreeing to that. So it goes to show if you build trust and understanding, people will share their healthcare data. It's just you've got to build trust and understanding. Then suddenly we can go five years down the line, the people whose life looked like this, is there any commonality in their treatment that could be causing that? What drug did they receive or was it oh my gosh, there's a difference between people in this part of the country and this part. So we'll use it. Realistically, this is the start, not the end. We can use it to drive an interventional study or some other thing. So for example, this could become a treatment where you're sent a survey and you complete it and the results are interpreted in real time. And if you score a certain thing, it could signpost you to particular resources. It could say, do you want a phone call from a specialist nurse? It could Some hospitals are developing late effects clinics, but maybe this could be a front door to that and try and get people to the right place at the right time. So I think this is just the starting point, but quite a large starting point.

SPEAKER_01: 27:27

How are you distributing the survey?

SPEAKER_00: 27:30

So the survey at the moment is scaling through primary care. So GP practices who want to take part in the research look at their patient lists and send out an SMS to people who qualify. That finishes around Easter time. And at that point, it's social media scaling. So we've got charity partners and anyone who remotely wants to share a link to participate. And we're snowballing that because you can imagine particularly disease charities, if you push this into your community, you're getting your cancer's voice louder in this data set. So we're quite hopeful there. And we're trying a variety of platforms. So Instagram, Facebook, Google, in a variety of places and monitoring which people come from which platforms, when, what the completion rates, et cetera, and looking to iterate the content we have on social media, which we've developed with the public. But actually, is it working the way we want? Does it speak to all groups equally? You know, there'll be a process, I think, subsequently of sort of enrichment where We look at the demographics of our study and realise who we've not heard loud enough, and then directly going out and trying to work to engage more people from that community. I always say, if we're in a room, who's not in the room? Who's not here? Who's not in this data set? We know who should be in the data set. We know there's, what, 2.2 million people living beyond the diaspora cancer in the UK, and we've got crude figures. We need ethnicity, gender, sex, cancer type to look like the national picture for the data set to help everyone. And that's essentially what our drive will be.

SPEAKER_01: 29:16

And what about low digital skills? Because obviously a lot of people will be older who've had cancer. Have you got specific techniques for reaching those people?

SPEAKER_00: 29:23

You undoubtedly, that is a weakness of the study in that we don't offer a hard copy version. It is, in terms of participation, people are allowed help to take part, etc. So it's been designed and the platform it's on automatically works with iPad readers and some of these other things. So there's sort of, shall we say, I think it has good accessibility, but it is far from perfect. For example, we're currently working on translations, but you're undoubtedly right. My counter to that is accessibility. I know that there are going to be people who can't take part because of digital literacy, maybe digital exclusion. Equally, though, we know currently most people don't take part in these trials because they don't go to hospital very often or they're not asked when they're in hospital. So I think whilst there's undoubtedly going to be a bias in our data set, my sense is it should be smaller than in other studies and we actually ask questions about people's educational attainment and things because we know again digital confidence often relates to academic attainment levels for example so I think we're under no illusions that there are groups of people who will find it harder to take part in this but I suppose we at least are trying.

SPEAKER_01: 30:48

And worth pointing out that you're doing this on a small research grant. You're not NHS England going out and surveying the population. And you've got huge ambitions for this piece of work. And it sounds like you're making great progress with it.

SPEAKER_00: 30:59

Yes. Thank you. Yes. To date, I think we've spent about£50,000 to date. And that's probably slightly the disruptive element of me and my colleagues, Matt Williams and Curlander Calvez. I think we quite like if people say you can't do it. I think we'd quite like to try and show that we can.

SPEAKER_01: 31:16

Yeah, get stuff done. It's a good attitude. I'd like to talk a little bit about the future. So this is the closing section of the podcast where we go on to what you're thinking about and where you're going. What are you excited about, Jonathan?

SPEAKER_00: 31:29

I'm excited about lots, Sam. It doesn't take much to get me excited, I have to be honest. I am excited about AI coming into healthcare, but I think for reasons different than most people. I often give a talk where We're talking about bias in AI. And I say, well, I'm the most biased thing in the clinic room. Because as a doctor, most doctors are good because they've become highly biased algorithms. I'm looking as you walk in. What's your gait? Who's with you? Got a walking stick? What's the heels of your shoes? Have you got nicotine staining on your fingers? They're all feeding into my algorithm of what might be wrong with you. And that, to large amount of the time, works really well. It's why the medical student goes, Gosh, how did the consultant know it was that within a minute? Because it's all the unspoken stuff. But I think we're using AI to challenge our bias. Because whilst my bias works well in certain patient groups, it doesn't work all the time. Does it work as well at 4 a.m. for a man of black ethnicity aged 75 as it does for a 21-year-old white female? Maybe it does, but it probably doesn't. And I'm not suggesting that's... We're talking about bias at the level here of deliberative. It's really, we're talking about our heuristics here, our recall bias, what's our most recent episodes and recollections. And so I think having AI can maybe point out, you think this person's having a stroke, but given their age and this, that, and the other, the most likely thing is this. It's not that we need AI to tell us what it is. It's just AI to go, just checking. Do you think it's like the nice colleague who's just going, oh, it's interesting. I've seen one of those, but it turned out to be this. And I think that narrative is firstly less challenging to clinicians, but I think it puts AI is biased because the data that goes into it and guess where that came from, humans. And so it's more about admitting that. that it's impossible really to have anything that's not biased. But you just need that bias to not overlap over the same domains. And then we can challenge each other's bias. So that really interests me in dealing with decisions under uncertainty. In medicine, you go through a phase where when you're a young doctor, you think, I'll be great when I know everything. Can't wait. Then you're this sort of registrar doctor and you think you do know everything because you're currently sitting in loads of exams, professional exams, so you're quite bright. Then you become exultant and you feel like you know nothing again. But it's because you're faced often with the edge cases, with the nuance where there's true equipoise. And using AI to look at future possibilities and map those, we can sit down and say, should we start your chemotherapy today or hold off? And at the minute, that's built on maybe a research paper, my understanding of that paper, what I'm remembering today and talking to you. But what would be nice is to go, actually, Sam, we can look at the AI goes, if we start today, this and this and that, this isn't saying definitely will happen, but it just structures our conversation. You say, well, actually, John, for me right now, most important thing is I stay at work. And option B looks like for a hundred Sam's, more would stay at work doing that. And that is true informed decision-making, I think. So those sorts of changes, I think, Sam, to me feel like real paradigm shifts. I don't think they're coming immediately, but I think they'll come. We know from studies presently, at least, that patients all want AI to be, shall we say, subservient to the doctor. I think it'll be one of my colleagues, Danny Rutter, said, gave the analogy of lifts and I think you go back to whatever the 1920s, there was always a bellboy or a Lyft operator because we didn't trust the Lyft. And then now you'd think it was madness if you saw an operator in the Lyft buttons. And I think he's probably right that maybe for the next 20, 30 years, there's a doctor in front of this. And then gradually everyone goes, I don't know why I'm waiting for it. He just tells me what's on the computer anyway. And then using it more in the back office to get rid of low value, high volume, repetitive tasks like doctors checking blood test results that are normal and having to do a letter to the GP to say it was normal. That could all be vanishing out, you know, via an AI, couldn't it? So are you optimistic? Good question. I'm a pessimistic optimist. I think everything will happen in the end. Do I think it'll be easy? No. To put it in context, this treatment summaries project, we might be talking about individual NHS trusts needing to pay two to five thousand pounds a year for the platform beyond the pilot. And a lot of them have said, no, we can't afford that. So that's the sort of barrier to use and implementation. That's obviously concerning. I think being devil's advocate, I think we've got a big forcing function coming. because the NHS, as it is, is not going to be able to cope with the scale of demand. And so in a funny way, I think automation will, a bit like through COVID, will be pushed rapidly on us. And so I think it'll feel like nothing's happening and then suddenly, like dominoes, it will go. I think I am hopeful. I'm hopeful as well that I do sit in far more conversations now where social determinants of health inequality are actually considered a thought about Not enough and not adequately, but when I compare that to, say, five years ago, I do feel that it is different. So I think I'm hopeful.

SPEAKER_01: 37:20

If you could wave a magic wand and change one thing about the way we treat cancer today, what would you change?

SPEAKER_00: 37:29

Oh, you've stumped me, Sam.

SPEAKER_01: 37:31

Or it could be change about the health system.

SPEAKER_00: 37:33

Yeah, yeah. You've silenced the surgeon, Sam. Amazing. You need to keep this in the podcast. The world will be like, so much for him being an innovator. Is that because

SPEAKER_01: 37:47

there's so much that you would change? Or is that because it's so perfect?

SPEAKER_00: 37:52

I think it's because I'm searching for, if I've got one wish, it's got to be the most impactful. And that's probably, I'm then thinking, oh, what do you know what I mean? That like, oh, what does that look like? I think, and this perhaps sounds, well, it's not innovative. I think if every person going through cancer treatment didn't have to worry about their finances, I think there's something that would just make a big difference for a large number of people and actually doesn't rely on technologists or other things. But to be worried about putting the eating on when you're on chemotherapy, to be thinking how are we going to get stuff for the kids, just that to me on top of everything else I think is That is something that we couldn't, society could choose to alleviate.

SPEAKER_01: 38:41

So it's a policy thing. It's not a medical thing. It's a policy thing.

SPEAKER_00: 38:44

Yeah,

SPEAKER_01: 38:44

I think so. What's next for you, Jonathan? Where are you going this year?

SPEAKER_00: 38:48

So hopefully finish scaling the trial, delivering the end of treatment summaries project. And then really, I think I'd like to be, I'm thinking about doing a piece of work around racism in healthcare. And I've had the, recently read the book, Divided. by Annabelle Suemio and that's opened my eyes to how baked some of that is into the way healthcare is delivered and I'd be interested in perhaps trying to bring some of that into my conversations and my work to perhaps challenge looking around and challenging and finding where we're I think nowadays I would say accidentally perpetuating what has happened certainly when I read Annabelle's book I was completely unaware of most of this so I think it's about surfacing it and then trying to work to address that. So I think that will be a feature for the next year. But then say my work with the Health Tech Research Center with Macmillan and my own consultancy is really about working with companies to develop products that meet an unmet need, that are safe, that work, that can prove they work and have a value proposition that means they can be procured be adopted and scaled in the NHS. And I think if that's what I'm trying to do, there's probably going to be enough for me to do this year, Sam. Not a bit worried I might have run out of things to do next year, but we'll cross that bridge when we come to it.

SPEAKER_01: 40:17

A year's quite a long time really, isn't it? Trying to think what you're going to be doing in 12 months' time, let alone five years.

SPEAKER_00: 40:22

I suppose the only thing that I had noted down about the future, but I don't think it's probably worth the bit, but it ties in, I think, with what you would be doing It's trying to bring behavioral science and design and human psychology much more into the foreground of healthcare. It feels to me a bit like outside of public health, where we think about public health messaging. I'm not sure we really apply it properly to everything. I don't think we use it when companies or people are designing things for clinicians or nurses to use. I don't think we use it when we commute to work. public or with patients and system design. So I'm always looking for opportunities where try and surface that into the foreground of the way services are designed and delivered and rather less than perhaps being either an afterthought or not thought of at all.

SPEAKER_01: 41:23

It still feels quite novel. We work with lots of different departments and often the work also involves a communicating the why you're doing what you're doing as well as doing what you're doing which is that's a big overhead but it's an education piece as well

SPEAKER_00: 41:38

yeah I agree as I've said I don't I honestly don't believe I'm an expert in anything I just read a bit of stuff and listen to people and try and yet some of this I think I think I'm the only person who's in this room who's mentioning behavioural science or whatever you think we should be beyond that now Kahneman's work was what the 1970s And I think because it got listed under behavioral economics, everyone thinks it's only economics. It's about decision-making. And as we actually didn't mention in the talk, the scarcity book from Sundell Millarison, that's the same. It's decision-making under uncertainty and cognitive load, isn't it? And I think that should all be mandated into healthcare's awareness if we just followed those principles and some basic human psychology. I think we'd get an uplift on our services that would be far greater than the amount of effort that went in.

SPEAKER_01: 42:34

Jonathan, it's been a pleasure talking to you. Thanks so much for taking the time to join me today.

SPEAKER_00: 42:38

Thank you very much for having me, Sam.

SPEAKER_01: 42:51

Problems Worth Solving is brought to you by Healthier, the collaborative service design consultancy for transformation in health care and public services. Find out more about how we can help you deliver user-centered change at healthier.services.