Electronic doctors and your health

16 July 2019

Interview with 

Peter Cowley, Angel investor; Ari Ercole, Cambridge University

AI

Artificial intelligence

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Around the world, more people are living into old age, which is putting increasing pressure on health services and patients are struggling to get appointments. In poorer countries, people might have to walk 20 miles just to get a clinic. The answer, we’re increasingly being told, including by Matt Hancock the UK’s Health Minister, lies in technology, including “electronic doctors” that use AI - artificial intelligence - to make diagnoses. So is this a realistic prospect? With us to discuss this are tech entrepreneur Peter Cowley and intensive care consultant and specialist in medical data science at Cambridge University, Ari Ercole. First up, Chris asked Peter, how do these "electronic doctors" work?

Chris - What’s actually behind these A.I. systems, how do they work?

Peter - Yes. Okay. So A.I., Artificial Intelligence, should not be confused with the intelligence that human beings have. The letters A.I. have been rather taken by the tech community and overused, something like 60 percent of all A.I. startups apparently in the UK are not using A.I. at all, they're using algorithms still. So what should be used is machine learning and deep learning and it’s all about taking data and deriving outputs from that. And a couple of examples certainly in the medical field: these chat bots which you can start to use now in the UK and other countries, where the computer system will be asking questions - not voiced at the moment, though may be when the smart speakers come online - but they’ll be asking questions with text to the point where it's trying to derive what the problem is then pass you on and signpost you back to a human GP or whatever and learning from that. That would be within a primary care setting and then in secondary care using machine learning of images, whether that's moles growing on your skin or some sort of scan, perhaps of the lung, and using that data from the past, from data from medical records and the data it's learning from communicating the interactive to give an output of some form.

Chris - But Ari, bringing you in, this is all about data. Do we have enough data in order to teach these things so they’re intelligent from the get go?

Ari - I think this is really the time for Data Science in Medicine. We've always generated a huge amount of data from health care from looking after patients, but in the past this has been unstructured, it's been on paper notes and actually from a clinicians point of view a lot of it was just sort of lost and you just wouldn't have access to it. Increasingly now the data is being represented in electronic health records and we're going to see those spreading over all of health care and actually now I think we have the reverse problem we have too much data that even the clinicians can't really appreciate and know what to do with properly.

Chris - Will this bear fruit though? Assuming that it plays out the way that Peter's outlining, are we actually going to see tractable, tangible medical benefit from systems like this or is this just hot air?

Ari - No, I think it will, but I think we need to be quite careful about exactly how we apply these sorts of technologies. So it may well be that in the future that we can replace doctors with computers, but we'll have to ask ourselves if that's really playing to the strengths of the technology. So computers are very good in that they never get sick, they don't get bored, they don't need lunch breaks and they can just do things repetitively in the same way every single time unlike human beings, but what human beings are very good at is dealing with uncertainty and being flexible about things. So it seems to me that we should be applying these technologies to do the drudgery, take away that work from clinicians and actually free them to make the best informed decisions, the best use of the data, make the data as salient as possible, but actually do the human part of the clinical practice.

Chris - Peter, most people don't want to deal with a machine though, they actually relish the human contact that comes with, say, a GP appointment.

Peter - That's absolutely true, when you've got that ability to do that, but bear in mind that a huge amount of the world has not got that access. If you take the Global South, the developing world, I don't know what the number of primary care GPs per head is but I should think it's 100 x less and they may be a very long distance away, so don't just assume that we're sitting in this sort of nice - we're all sitting here in Cambridge in this nice bubble and that it's not possible - but if you take the developed world: yes, many people would want to be in front of a human being when they're discussing something. But you know I'm obviously a bit older, as you can tell, the millennials are more and more wanting to be able to communicate in a way that's quick, convenient so you don't have to travel, you don’t have to wait around, you don’t have to book something when you can't do it, and get some sort of diagnosis or beginnings of a diagnosis what's going wrong. These systems will not send you a prescription, yet, for a drug, they will refer you on if necessary, or more likely say “don't worry about it - don't be so cyberchondriac”, as they say.

Chris - Comfortable with that Ari? Would you be comfortable as an active practising doctor to have patients being seen by these sorts of systems? Is this safe?

Ari - I think at the moment we're probably not quite at that point, in terms of actually making real decisions, I think the actual decision making is probably still firmly within the grasp of the clinician, but that doesn't mean that there aren't massive opportunities from these kinds of technologies to assist the clinicians and actually improve availability of healthcare in that way instead.

Chris - One of the criticisms though, Peter maybe you can answer this, is this whole question about data security, because on the one hand we're saying these systems are driven by data but that depends on people being willing to share their data and if people don't trust data holders, and we've had a lot of examples of this going wrong in recent years and people are becoming very data aware now, it could stumble at the first hurdle. 

Peter - Yeah, there's two initial issues there: one with explicit and implicit use of data. If you actually sign something off at least you've got a choice, but there is data out that's probably being implicitly used without your choice. And then there's a level of anonymisation: if you've got a very rare disease in a particular location then difficult to make anonymised, but if you're a general member of the population anonymisation’s easy. But in the end it comes down to trust, personally, and you know I'm pretty... a technophile here, I think the data will lead to better outcomes in time, I think. And I know there'll be doctors listening to this. There are misdiagnoses going on, and if that could be reduced in time, which I believe it can be, we might be looking 10 or 20 years out, it will be beneficial to the population. So it all depends on one's view. In the end, we've had this conversation many times Chris over the last four years, if you don't like being tracked don't switch on a smartphone, you know, don't use tech.

Chris - Last question Ari in 15 seconds, who gets sued?

Ari - That's a very good question and we don't really know, at the end of the day at the moment it's still me.

Chris - You take responsibility of the whole of Addenbrookes hospital?

Ari - I'm afraid I do yes.

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