Fraser, Nick and Peter discuss health data and measuring medical outcomes with special guest Neil Bacon.

Things mentioned in this podcast:

• Neil Bacon’s web page
• Doctor’s Net UK
• iWantGreatCare
• Asthma facts and statistics
• Sir Muir Gray
• AI 'outperforms' doctors diagnosing breast cancer

For more information on Aleph Insights visit our website https://alephinsights.com or to get in touch about our podcast email [email protected]

Hello and welcome to the Cognitive Engineering Podcast produced by me, Fraser McGrure, for Aleph Insights. In this series of podcasts, we take a look at interesting topics and discuss what we think they tell us about analysis and decision-making. I'm here with Nick Hare and Peter Coghill of Aleph Insights. Also with us this week, we have our special guest, Neil Bacon, who is a health outcome specialist. This week, we're discussing health data. Due to lockdown, unusually, we are recording this remotely. Nick, could you tell us why we're talking about health data and perhaps also introduce us to our special guest, Neil?

Sure. Well, weirdly, this is not what you'd expect. You'd expect us to have Neil on because of the global COVID-19 pandemic. Actually, we booked him before that became a thing. Usually, with the guests, I normally say I've known them for 10 years. With Neil, we were introduced by a mutual friend of ours, Trish and Panch, who is the chief medical officer for a US healthcare technology company called Wellframe. Neil and I met up and it was clear that we both had interests. Obviously, Neil comes from a health background and I come from a defense and security background. Actually, you see the same problems. You see the same issues. You know, there are lots of experts but not necessarily enough data to cover all of the uncertainties that we have. Neil has done a lot of actual practical work in different aspects of healthcare and creating healthcare information, sharing health information as importantly. And yeah, so I thought, well, that would be really interesting to have someone who really knows about the healthcare data side so we can think about the parallels. And then what happened, of course, is a global pandemic. How fortuitous. Exactly. And so I think it would be interesting certainly to start by asking, well, I mean, there's enough about COVID-19, but it would be interesting to just talk about the data side of

it, I think, to begin with. Okay. Sounds good. So Neil, before we go on, just tell us a little bit more about yourself. Go a bit more in depth if you could. Thank you. Thank you, Fraser. Thank you, Nick. My background is a clinician originally. I was a nephrologist, a kidney doctor for all those non-Greek scholars, nephron, the filter. I was a kidney doctor. I trained in Oxford and Nottingham. Then I was over in Harvard. This was 93, 94. So time flies. So just when the internet was happening, literally, I was busily doing clinical medicine and loving it in the States and back in the UK, I thought this internet thing is going to change everything and apologies for the cliche, but turned out to be true. And I resigned a molecular biology PhD that I was doing actually in the lab of Peter Ratcliffe. And Peter's the chap who just won the Nobel Prize for Medicine last November. So suddenly from, I was in a lab, actually, I now can tell everyone I was in a Nobel Prize winning lab. And the one paper I produced out of my aborted PhD is one that is actually quoted by Professor Ratcliffe in his work. So that's as close as I get to a Nobel Prize. And despite that lucky brush with a life of research, I escaped because I set up a business called DoctorsNet UK. And DoctorsNet UK was, or is, the very first online community for physicians. And the focus of it was knowledge sharing, learning. First people to do, globally, the first people to do online learning to online collaboration. Not that being first in this instance necessarily means the best. Anyway, I did that for 10 years whilst carrying on doing some clinical work. Had a couple of years doing consultancy after that. Digital health, again, very, very new field. That took me all over the place. Best piece of work I did there was probably with Don Berwick in the Institute for Healthcare Improvement, helping set up what was the Open School, an international online learning platform. And then I set up a business called I Want Great Care. And that was essentially the TripAdvisor Health, enabling patients to rate and review their healthcare, their medicines, their doctors, but then to use the knowledge and the insights and the information from that to make predictions, to improve safety, to improve pharmacovigilance. So I did that for a little while. So again, very much into data and outcomes. And then briefly, there's too much about me. For the last 18 months or so, I ran an organization, which was the International Consortium for Healthcare Outcomes, which is a global organization coming out of Michael Porter's work at Harvard, helping establish global standards for measuring healthcare outcomes. So a little bit from a clinical background, but it's all been healthcare and all data. So, interestingly, in some ways, very different from other guests that we've had on here. But actually, in all the important ways, exactly like all the guests that we have on here, just sort of just sound highly accomplished and quite niche as well. But also, just very appropriate for this moment. So Nick, I'm going to hand this over to you. Go ahead. Ask Neil

Well, I think the first thing probably is to ask for sort of non-specialists out there, what exactly we mean by health outcomes and why it's so important to measure them, what they make better, you know, what measuring it makes better.

It's interesting that for many people who call themselves non-experts, they don't think about it. But anybody who anticipates at some point being a patient or someone they care for being a patient should pretty much be obsessed with health outcomes. In the UK, perhaps we have almost, dare I say, a complacency. Well, we have a quote to quote the Prime Minister, our NHS, not just the NHS anymore, it's our NHS. And somehow people think, well, that's everything, that's all right, because it must be good because it's our NHS. Well, as a case in point, what are the outcomes for the NHS? If you have a heart attack or if you have cancer, if your child needs some important treatment, what are the outcomes? So healthcare outcomes are attempts to answer that question. How well do we treat something? What was the result? What's the long-term result? How well do we compare with other organisations? And those comparisons may be within a country. Should I be treated in Birmingham, Cambridge, London, or international comparisons? So without healthcare outcomes, and again, maybe pertinent to the times that we live in, without healthcare outcomes, we are running in the dark. We are blind to what healthcare we're getting. And of course, if we don't know the healthcare outcomes that systems are delivering, we don't know whether they need improvement, where to improve them, or how to improve them.

So, I mean, I guess most people probably assume, and the only reason I think this is probably the case is that I probably assume it, but also when I've worked with customers for analysis, they often just assume that data exists, that it's out there, that someone's collecting it. Can you tell me what's the average increase in annual cost of grass-cutting services or something? And you think, well, actually, no one knows. No one collects that, right? The data does not collect itself. I was wondering, what would people be most surprised that we don't really have an insight into? I mean, is it the case that actually, when we recommend a particular treatment, particular course of drugs, or a particular surgical intervention or something, is it the case that actually most of the time, we've got a really good idea about what the kind of long-term impacts are? Or actually, is a lot of it just sort of common practice and intuition? I'm not sure

it's even the latter. It's definitely not the former, Nick. And it's very easy to do this. Next time you or someone listening to this sees a doctor, a physiotherapist, a dentist, a surgeon, just ask them, what will my outcome be if you treat me? How do your treatments compare with other doctors, stroke surgeons in this practice? And how good are you compared to the rest of the country? Be prepared for an embarrassing silence. Maybe don't ask if the person has a drill in their hand and is about to attack your teeth. There is a dearth of understanding and insight. As is often the case, there's a lot of data out there, but it's not collected. It's not interpreted. It's not understood. So small pockets, small, small pockets, the cardiothoracic surgeons in the UK, after fighting for literally decades to try and hide it and argued not to do it, now collect all their outcomes in a standard comparative way. And of course, they've now become the zealots for this, wondering why no one else does it. Because it's improved standards. It's improved quality. It's improved. It helps them make the case for proper investment. Today in the news, there's coverage, although it's obviously buried slightly by the virus, the pandemic of media coverage of the pandemic, but that actually, George's in South London, their cardiothoracic department was riven with problems that probably led to 40 or 50 excess deaths. So there's a real fear where outcomes are important without knowing that. Now that's the negative. Too often, and I'm guilty of it as well, talk of outcomes tend to turn to the negative. There's so much potential in understanding outcomes, which are good to increase confidence, to help people do the right thing, to help them get the right treatment. But in answer to your, another way of answering your question, in the UK, about, I can't remember how many, hundreds of millions, let's say at least hundreds of millions is spent treating asthma in this country, both in primary care and secondary care. No one has any outcome data for how those hundreds of millions are spent or the impact of them, where it works and where it doesn't work. And unfortunately, that's the same for the vast majority of healthcare, not just in the UK, but overseas. We know there's huge variation. We know there's huge waste. We know there's some great centres. Pretty much, we don't know where they are. And why is that? Is it going back to the example that you gave, Neil, that I remember when I was an economist and we used to make predictions all the time and more than most economists, my predictions were pretty much wrong. But something that we never did as a department really was to go back and check our predictions and report on those. And the reason why was because we all knew that they would be wrong. Now, is it the same case in health outcomes? Is this why clinicians are reluctant to do this, departments are reluctant to do this because it's better off if we just don't talk about that stuff, especially given the amount of money that's going into it? I think that's a really good point, Fraser. And I think maybe socially in the UK, you know, you can't criticise the NHS. You know, it's our NHS. It's a religion. It's heresy to say, actually, the NHS kills lots of people. It shouldn't. That's a fact. That's a fact because all healthcare systems do that. The difference is the really good ones work really diligently and hard to work out where they're where they could be better. There isn't a successful commercial organisation on the planet that couldn't, that wouldn't continually seek to improve to understand everything. I mean, take it away from the NHS, men, much of which much of which is good. We just don't know which bit of the NHS is really good. We don't we generally know the bits that are really bad because people start being found dead in the bed and drinking out of vases and their children die and then it becomes a crisis. But unfortunately, it has to be a crisis and that the hundreds of thousands of people who get suboptimal care who's, we don't know about that. We don't measure that. It's another example. And as a contrast, in the States, for example, as you know, huge amounts of care are paid for by employers, employers pay health insurance, and it's a huge amount and an ever increasing amount of the money that their actual costs of running an organisation if you're Walmart, Apple, Amazon, it's a big chunk of your costs. And these organisations know exactly to the pet to the scent, how much things cost, you know, Starbucks will know exactly how much they pay for paper cups, stirrers, the lids, and what they get for it. And they literally do not know what they get for the money they spend on healthcare. They spend it healthcare people get some treatment, but they don't know whether it's good or bad. So to your point, why do people not dig in? One, I think there's definitely a we'd rather not know, especially in perhaps social medicine systems where politically, it would be unpalatable, unpalatable. In other organisations and other setups, it's just such a big problem. And then there's vested interests in keeping things opaque. I think but maybe we'll come back to that. Peter,

and aside from the kind of social, but aside from the sort of social dynamics of prevent people from criticising the NHS and and, and the religion that you that you described, are there a lot of technical barriers or sort of on a on a tactical level for collecting data, because it occurs to me that I mean, it's something that we see quite a lot when we're advising customers around sort of doing intelligence or doing analysis that and data is often sort of created for one single use, used and then disposed, disposed of it sort of data is to record data in a way that is useful beyond its initial purpose is is costly. So, you know, you can see it all the time with businesses, sending emails and having conversations with each other, lots of information flying around, which, in aggregate, later on six months down the line would be enormously useful for the business in doing some retrospective analysis, but there's an additional cost would be incurred in at the time structuring it or, or applying structure after the fact. So you could then do some analysis with it. Is that does that

ring true in healthcare as well? It does very much. So the example I gave of asking a surgeon, for example, what are your rates of infection post during this process? Or if you're a prostate surgeon, you operate on prostate cancer, what's the rate of incontinence in patients that you've treated over the last five years, they won't know that information has been collected at some point, the patient has come back to a clinic, did you get an infection? Have you got incontinence that will be recorded, probably in paper. But it's literally data that's floating out there that no one, the perceived cost of doing something about it, is all the real cost of doing something about it, collecting that data in a standardized way across the NHS over time, is always too expensive now. But the long term, and maybe we'll get on to it, the long term costs of not doing that, no doubt are greater. But that, you know, as often as this case, that falls to someone else in the future down the line. And that's, that's a hidden cost. So I think you're right that those systematic issues are also prevalent. And I suspect that I suspect perhaps as well, there's like a bit

of a tendency to allow perfection to be the enemy of good in that everyone seeks a one big solution for everything in the NHS all at once, rather than saying, well, let's just do, right, let's just patient records at bedside, let's just digitize all of those at the point of collection, just one that one thing would collect enormous amount of data that otherwise languishes in paper file that nobody ever looks at ever again. Is that would you agree with that?

Yeah, very much, very much. And there's sort of big, big data, it's also in silos. So some of its paper, then some of it is electronic is in silos. And no one thought even though it's a national single healthcare system, to put to put in place systems that actually necessarily speak to each other, it's changing, but very, very slowly. When people have tried to collect the data that's out there, there's a chap called Samir Gray, who's been working at this for many years in the NHS now now retired and still working at it. And he, his work led to something called the Atlas of variation, which looked at not so much the variation in outcomes, because again, they're not collected, but the variation in practice. So the fact that, for example, with diabetes care, huge variation in the number in the way that different centres, different areas, different practices actually deliver the core, the 10 core things you're meant to do for every patient with diabetes. So you're right, lots of silos of data, some technical barriers, political barriers, perhaps social barriers, financial barriers, and also witness the current climate, there's always a there's always something new and urgent and important in the NHS, which unfortunately, stops capitalization, capitalizing rather on the superb data that would help inform not just changes here, but overseas. But as I say, these are international problems. So not just confined to the NHS, Nick,

yeah, I suppose. I mean, obviously, I come from a background as, as an economist, working in government. And so I mean, I tend to think about information as as really a tool for, you know, allocating resources effectively. And of course, you know, in a market, information has a really direct impact in that information will affect price. So you only need a few people to be informed. So you know, if I want to go and get a good bottle of wine, I can rely on the fact that, you know, and I don't know anything about wine, but I can rely on the fact that other people do know about wine to use price as a proxy for quality. And of course, as the price of certain kinds of wines go up, there's more of an incentive to produce those kinds of wines. And you don't really need to do anything to translate that information into into a better allocation of resources, you know, people buying better things and producing better things. Obviously, it's different in a market like, you know, in the UK for healthcare, by and large, which is, you know, government controlled. Even if I have information about what works, you know, there's not necessarily an incentive for me to operationalize that if I'm a provider. If I'm a consumer, I've got no real mechanism for, you know, for sort of acting on it. I mean, if I know one doctor is better than another, I can't somehow end up in a situation where they get paid more, you know, because I go to them anyway, I can just make their life worse, because they'll be more overworked. And so, you know, whereas I know, now I don't understand, really, I've got to be honest, I've looked at it, and I still don't really understand how the US healthcare system works. If it does, it seems like a huge mess of different organizations, all kind of, you know, insurers and, you know, and firms providing healthcare insurance for their customers, lots and lots of sort of principal agent problems. And, but is it different? I mean, is there more of an understanding in the US about the importance of information? What role? I mean, is there a big difference in the way that information plays a role in healthcare provision here versus in the

US? The short answer is no, unfortunately, and I'll give you maybe by way of example, in my last role, I was approached by the people who basically were in charge of allocating, spending, buying, buying, and then delivering all the healthcare for the state of, I won't say which state it was, the state of Connecticut, the state of Connecticut have a system, a statewide system for state employees and retirees. So that's basically, I think it's almost their budget is something like a third of the whole of England anyway. I mean, these states, as you know, are so huge. So this single, essentially a statewide insurance system bought and paid for all the care for their employees and their retirees, massive. They came to me to say, well, we want to basically make it a value based. We want to get better care. We want to understand what we're getting for our money. And then we want to be able to allocate in terms of where we get the best outcomes for the people being treated. We're going to start with just hip and knee replacements, you think relatively simple. And I said, well, what's it like now? How much do you pay now for these processes? And of course it's a big, big market. Lots of people can provide. And they said, we have about 10, 10 or 12 different organizations that will deliver these, these replacements. We pay between $18,000 and $84,000 for the same procedure. I went, pardon? I thought I'd misheard, you know, their accent or my English ears. They said, no, we pay between $18,000 and $84,000. This was for knee replacements. I said, oh, great. And what do you get for that, that difference in, that's a huge difference in cost. And they went, there was this awful silence. And I felt like I'd said something obscene. And, you know, they all looked at each other and they said, we don't know. That's the problem. They, the figure comes back to us from the insurance company, ultimately with all the add-ons, the hospital has this funny bill with all markups, there's opacity at every level. And they literally, and that, that mirrors in, in, as an example of the whole of the healthcare system in the States, vast amount of insurers pay the bills. They don't care particularly, unless they're a mutual, they've not got much interest in driving the cost down. In fact, maybe sometimes perverse interests, hospitals, of course, and anyone doing procedures get paid, the more they do, the more they get paid. So I've got a friend who's a radiologist, the more she does, the more she gets paid. So a whole load of perverse incentives, opacity. And as you say, Nick, unlike most markets, where there's a very clear link and the person buying ultimately has some indicator of quality, even if it's just by saying, well, everyone else is buying this wine and their thought must be good. There is no link between the ultimate payer, either the member of the public and any form of quality metrics. So when we get to what's the importance of healthcare outcomes, back to your first question, it's important for the individual. If you're having your knee replaced, your dad's having his heart bypass operation, there's huge variation in the outcomes. But then when you take that up to a country level and the states are probably the most extreme example, without clarity on outcomes for everybody in the loop, the provider, the payer, the patient, the insurer, you get in a situation where the money flows independently of the quality, and then you get perverse market forces driving costs up too often. Okay, so we're coming towards the end, but we've still got time for one or two more questions. Well, I don't think we haven't

so far really gone topical. We've got to go topical. So let's go topical. But well, I just have perhaps an even more general question, which is, I mean, again, thinking about health as a market, the interesting thing about healthcare, I think it fails almost every check of how you would expect to have, where you would expect to have sort of a well functioning, perfectly competitive market in that, you know, there's a lot of externalities, like, you know, people's transmission of disease, for example, that's an externality. There are natural monopolies, because actually providing kind of an integrated, I mean, people's healthcare needs are so varied that, you know, actually having a large organization providing them is probably more efficient. You have non homogeneity. So Neil's knee replacement is going to be a different product to my knee replacement. That's good, because we've got different knees. There is, you know, you're not even sure what you're getting when you're paying for something. And there are, you know, lots of legal entry barriers about, you know, you can't just, I can't just become a doctor. Now, even if I would be amazing at it, I can't just decide to do that. And so, you know, there's all kinds of, one of those issues is about information. Now, but if it's the question, if the issue, one of the key failures of sort of the health market, as it were, is to do with people's inability to use that information, I'm wondering, is there a limit to how useful it can be to give individuals? Who is it who needs the information? Do we want, do we want, can we rely on people to make the right decisions? I mean, people make terrible health decisions. How do we know they're not just going to go to the hospital, which has the snazziest logo rather than the one which actually ends up providing them the best service? Is that a someone else who needs this information? And how do we, how do we, what's the best way of using it?

Yeah, I think, so Nick, I think your point about was there a risk they'll just go to the place with the snazziest logos? That's what happens now. That's what happens now. I mean, I don't know if you heard or people listening heard the BBC report into Great Ormond Street at the weekend. So Great Ormond Street, couldn't have a better name. Peter Pan, the whole image, best hospital for children. Anybody who listened to that report would understand and know very clearly that going with the logo and the reputation is not the best way to do things. And I have friends who've worked in Great Ormond Street and have been telling me this for years, that there are major issues that need sorting out as with many hospitals. In America, people go to the place with the biggest logo, the name, the brand, that's because they've got nothing else to go on. So I used to, you know, get in a cab in the States and the taxi driver said, what are you doing? This is what, oh, can you tell me? He said, I've got to have my back done. Which is the best place to go to? Or they'd say, how do I know? I went to the place and it's the, you know, I don't know, the mass gen, it's meant to be the best, but how do they make it $80,000? So without any outcomes, let's go back to the theme of outcomes data. What do people judge on? And at the moment, we're in a desert. I think, of course, there's risks with data that's not helpful for people, but this is, there's a, what's the word I'm looking for? There's a shift in society to transparency and data and trusting people. It wasn't so long ago that people were told they couldn't choose their bank. They wouldn't understand interest rates. They couldn't look after their own portfolios. They couldn't choose this. They couldn't choose that. They couldn't book their own holiday. We needed intermediates. Healthcare now sits in splendid isolation where we're told, don't worry about the outcomes. We'll look after the data, trust us. And that's whether you trust the insurance company, you trust the NHS, trusting people. I'm not sure people are going to carry on trusting big governments with that. So I mean, it's a much longer answer to that question and a much broader topic discussion to have. But right now, people make decisions based on putting their finger in the air, asking the person they meet at the golf club or the brand logo of the hospital. I want to, in a little while, I want to come on, return to the current situation. But before we do, Peter, is there something you'd like to ask?

So in the UK, we have patient choice, I think it's called, which allows you to elect where you want to have your treatment. So if you're referred for a back operation, then you can look up on the NHS website where you can get your surgery and then elect to go for that. That's quite relatively recent. So is that, Neil, is that going in the right direction? Or is that a bit of a sticking plaster to use a terrible pun? I think it's absolutely the direction. And it's to Nick's

point, you don't need everyone to choose to change the market. And that works even in the NHS. So hospitals work on such thin margins that if there was good data, and people could see that actually, if I had my hip replaced at Cambridge, rather than Oxford, I've got a 30% less chance of getting an infection. I'm making those figures up. But there is huge variation between different centres. If even 5% or 10% of patients say, actually, I'm going to take, I'm going to drive 50 miles further to get my knee done, that would literally create financial challenges for the hospital that lost that proportion of their work. Now, some people think that's a bad thing. But I think being challenged when you're not delivering good care, whether you're infecting too many patients and driving change is a good thing. So choice is a good thing. But back to Nick's point, choice without information isn't choice, is it? It's a name and a logo on a website. Yeah, it's a guess. What we need is informed choice and outcomes, ultimately, who would choose if they could to go somewhere where they knew the treatment their child would get would be a worse outcome than somewhere else. So outcomes, you know, see, I'm banging the drum, and there's other things that are important. But market forces, even in a state system are powerful, if done in the right way. So I've got a couple of informal questions I want to ask Neil. But before I do that, Nick, yeah, let's talk a little bit about what's happening right now. I think you've got something

you want to say? Yeah. Well, we're on another podcast, we were talking about some of the some of the good things that might come out of, you know, the horrible situation we're in. From a health care provision data sort of perspective. What what has the COVID-19 situation highlighted about what we're perhaps good at or not good at? And what do you think it might spur? What would you like to see happen as a result that would, you know, perhaps,

there's the variance really, can I can I see if I can get Neil support for a scheme? Every time, every time I see not my GP, that my GP is great. But every time I go into as a sort of relative stranger to a hospital, for whatever reason, I all I want to know is, okay, you know, how, roughly, how long is this going to take? Right? Give me some probability distribution or me know something, you know, there's always I we just don't know, but you must have some idea. Is it going to be an hour? Or is it going to be five days? And then you know, what's the probability that it's this thing rather than other things. So you're you've got to do a blood test, because you're worried that there's some chance it might be something really bad. Well, a priori, what's the frequency of that thing in the general population? Now, I know that 99% of people aren't as au fait with using probabilities as I am. And that is completely right, that doctors use a different way of presenting information to most people. I would love to be able to sit some sort of exam to prove that I'm capable of correctly interpreting medical information, which would give me a card informed consumer card. I'm not sure you would pass it, Nick, but anyway. But I, you know, but someone could just be a card that would say, I'm an informed consumer. And you

know, what would happen, Nick, though, they that would be like holding a sort of cross up in front of a vampire and the doctors would run backwards screaming from you, because what it would actually reveal is that often, and again, this is the nature of it, the way they don't have the facts, they have a vague idea. And I think and again, you know, you mentioned Tristan at the top, our mutual friend, he probably have much better facts on this. But when they've tried to get the knowledge out of doctors about how they make diagnoses, and how they treat and how they advise, you can't get them because they're not based on doctors think they're based on, but it's more just gut feel, and intuition. And that's why in so many cases, and this sounds terrible as a doctor bashing doctors that AI is better at doing so many things. And now that the new work Google are doing around radiology interpretation of x rays show that actually machines are better at diagnosing breast disease from breast scans and doctors, because these things should be done with systems and measures and stats. And often they're done with medicines and art, it's an intuition. So one of the reasons they don't tell you isn't, in fact, it's not that they don't think you'll understand. I think they the worry is they don't have those figures themselves to tell you anyway. Just before we finish off a question I always ask to our guests. So just a brief one. Neil, if you weren't doing what you do do working in health data in a background as a doctor, etc. What would you do? What would be your career if you weren't doing this? I've sort of bit jealous of that guy who this last week said he was gonna be the nation's PE teacher and just plops the camera in front of Joe Wicks. I've never seen him. I mean, that's quite a good gig, isn't it? You pop a camera up and you jump around and your your brand value goes to 14 million. So that would that would be great. What would I do? Maybe you know what, maybe I'd go back to being a clinician, but I wouldn't work in a big hospital. I'd probably work on a small remote island somewhere and try and really work out whether I was making a difference and measure measure outcomes. Because clinical medicine is great and you can get, as we all know, you can get caught up in in data and outcomes and science. So the one-to-one, I'm the person, probably the short answer question, I'm the person who on the plane when they say is there a doctor, I'm the one who jumps up and says yes. Every other doctor hides behind their newspaper and goes oh my god. But I actually miss that one-to-one interaction with patients and about my only chance to do it is when some poor, typically a fat man's got his collar done up too tight and has drunk too much gin and it's just a matter of giving a glass of water and opening his shirt collar and you're

the hero and get pushed up into first class. Well but have you ever had to intubate someone with a

with a biro? No no I haven't but I do know, I do know the professor who who who claimed to to do that. There was this coat hanger, the oxygen tubing and the whiskey for the pneumothorax. So it's a that's a great story. And actually I'm the opposite of all those other doctors. I have no medical qualifications but I always jump up and say yes because I just know and even if it works out badly it will I'll still be the hero. I've you know did what I could. Yeah okay all right. You've got to leave those coughs in Fraser on the I know I do I don't. It's timely authenticity. It is isn't it? Okay so we're going to wrap up there. Thank you as always for listening to the Cognitive Engineering Podcast. I'm Fraser McGruer. We've been here with Peter Coghill and Nick Hare of Aleph Insights but a special thank you to Neil Bacon for being with us. So thank you very much Neil. Pleasure, thank you. And until next time, goodbye.