How AI is Revolutionizing Medical Education with David Lay

Can AI transform the landscape of medical education? Join us as we bring you an enlightening discussion with David Lay, Assessment Manager at Queen Mary University of London, who unveils AI's transformative role in enhancing medical training.

David takes host Bill Banham through his fascinating journey from a History student to a leader in competency-based training, highlighting the challenges medical trainees face, particularly those under the UK's National Health Service. Explore how AI streamlines training processes and integrates with the General Medical Council's competency-based curriculum to revolutionize the medical education landscape and allow healthcare professionals more time to focus on patient care.

Personalized learning meets advanced technology in this thought-provoking episode. Discover how AI recognizes diverse learning styles and personality types to enhance training efficiency without compromising core educational goals. We dive into the automation of administrative tasks, providing more room for valuable feedback and professional development. David emphasizes the essential role of human oversight in AI-driven processes, particularly in the critical field of healthcare. By augmenting existing educational structures, AI not only aims to reduce training hours but also preserves the vital interpersonal skills necessary for patient care. Listen in for a glimpse into the future of medical training and the incredible potential of AI to elevate both education and patient care.

Chapters

• 0:03 Enhancing Medical Training With AI
• 12:59 Personalized Medical Training With AI

Transcript

Speaker 1: 0:03

Welcome to the HR Chat Show, one of the world's most downloaded and shared podcasts designed for HR pros, talent execs, tech enthusiasts and business leaders. For hundreds more episodes and what's new in the world of work, subscribe to the show, follow us on social media and visit hrgazettecom and visit HRGazettecom.

Speaker 2: 0:26

Welcome to another episode of the HR Chat Show. Hello, this is your host today, bill Bannam, and joining me on this episode is David Ley, assessment Manager over at Queen Mary University of London. David has nearly a decade of experience in medical education and competency-based training. At Queen Mary University, david leads strategic assessment initiatives and collaborates with academic departments to enhance assessment quality. At the Royal College of Paediatrics and Child Health, he pioneered an e-portfolio enhancement system ensuring alignment with the progress curriculum.

Speaker 2: 1:04

David is enthusiastic about the implementation of AI as a new way of enhancing competency-based training, believing it can significantly improve efficiency, accuracy and personalization in various educational processes. Committed to fostering strong client relationships and continuously improving service quality, david is known for his exceptional problem-solving skills, adaptability and deep understanding of user requirements, so one of David's latest projects focuses on how AI can significantly reduce training time with medical education, thereby freeing up more time for healthcare professionals to address service needs within the UK's National Health Service. By personalising learning experiences and automating admin tasks, says David, ai streamlines the training processes, improving those efficiencies, and this integration aims to enhance competency-based training while ensuring that medical professionals can dedicate more time to patient care. That sounds pretty good to me. Also, david is my mate, mike O'Flynn's friend. They lived together once. Regular listeners of the show will be familiar with all the disrupt events that I'm involved with, and Mike has spoken at a bunch of those, so there's another reason why we love David today.

Speaker 3: 2:24

David, welcome to the show hi Bill, thanks for having me. Uh, thanks for uh having me on and uh, yeah, thanks for outing me as a mate of Mike's, so usually keep that secret.

Speaker 2: 2:38

He's a. He's a fine individual. He really is. He certainly is. And um you got, you guys are housemates. I think is. Is that right?

Speaker 3: 2:47

Yeah, we went to university together, Anglia Ruskin University. Both studied history and ended up in very different careers from history. But yeah, we had a great time.

Speaker 2: 2:58

Okay, so you're a history buff, you're a history student and now you are doing something very, very different. Why don't you give us a bit of a background to your career before we get into the details of today's conversation?

Speaker 3: 3:10

Yeah, I suppose I studied history, took a couple of years out, worked in retail as a tech team member at Tesco's where I sold TVs and the like, which was great fun, and then ended up doing my master's degree in history alike, which was great fun and then ended up doing my master's degree in history.

Speaker 3: 3:27

So while whilst it's not medical and scientific in any way, it is very competency-based, so very much looking at different sources and bringing them together, and I suppose that's a through line into what I've been doing. But I ended up in admin, as a lot of people do, especially around that time. It was about 2012, 2013. And then I took a three-month job, moved down to London from Cambridge with my girlfriend who had no job in London, so I was on a three-month contract and I started working at the Royal College of Pediatrics and Child Health and that turned into eight years. Luckily, I got my contract extended and a number of promotions there and then went off to work in software for about four years delivering e-portfolios and training software, and now I've come back into academia, into assessment management. So a bit of a strange journey in many respects, but it's been interesting.

Speaker 2: 4:27

Thanks for listening to this episode of the HR Chat Podcast. If you enjoy the audio content we produce, you'll love our articles on the HR Gazette. Learn more at hrgazettecom. And now back to the show. So what are the current issuesid facing trainees in in medical training? And, by the way I'm going to preface this, I had to ask david to send me over a very long uh summary of it of the project, because this is not an area that I'm super familiar with. So, uh, why don't you give us the lowdown?

Speaker 3: 5:00

thanks, yeah, I will do. Um, so I think the issues facing medical trainees are very similar to the issues facing a lot of people, especially in education, and the main thing is time. So with medical education, especially from the postgraduate side, a lot of people will know the NHS is struggling at the moment with service need and time for doctors and nurses and anyone in that kind of medical profession to not only do their jobs but be trained well. And that encompasses a lot more people than you'd probably think, because you're not only looking at the people on the ground doing the training, but you've got to look at people who are delivering that training as well, and nine times out of ten they're consultants as well. So that takes their time away from it, like anybody who's been in education. So even from, say, secondary school onwards, there is usually a curriculum built and again, you as a student or a trainee won't often know what that curriculum is.

Speaker 3: 6:02

Within medical education you're kind of expected to. So, a few years ago, the General Medical Council, which is known as the GMC. A few years ago, the general medical council, which is known as the gmc. So if I start truncating everything and and uh, putting everything into to shorten terms, that's just a, an area of medical education you'll have to get used to, I'm afraid. Um, but within the gmc they they pushed out a new curriculum base which is a competency-based curriculum, which, instead of saying you need to do X number of hours or you need to have X number of things to equal Y, it's more that you do something on the ground and it links directly to a number of different learning outcomes.

Speaker 3: 6:43

So something that we're probably all very, very familiar with is COVID. That is a really good example of something that could be used, as you need to see X number of COVID cases to be competent at treating COVID. But as COVID has died down now, that's not a competency you might be able to achieve easily, depending on where you are in the world or where you are in the country, rather. So you build it as a competency, so you build it more generically and you say something along the lines of has a competency in a pandemic event. You probably go broader than that and then you build your experiences on the ground around that.

Speaker 3: 7:21

Obviously, that's quite an intricate thing to do if you're reading several pieces of documentation. So the method of training generally falls back on the old, tired method of X. Number of hours equals that you're competent and that really negates the differences and brilliant differences between different trainees and the way different people learn, and you know really how different people from different backgrounds interact with medical education as well. So I think they're the main areas. But you know, the big problem at the moment is everything you see on the news is absolutely true. There is a lack of time and a real problem in terms of service need and, unfortunately, that eats into training time quite a lot.

Speaker 4: 8:26

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Speaker 2: 8:39

Learn more at disrupthrco is different to the corporate world then, in that folks have traditionally had to have had x number of hours in the job to prove themselves, and by augmenting some of their roles with AI, we're saying that that no longer needs to be the case. How do we then measure the experience, the skills, the knowledge of medical practitioners if it's not with the traditional X number of hours to become a fully qualified doctor, for example?

Speaker 3: 9:21

Well, I wouldn't remove that completely, but I think, especially within this world of AI, what this gives us an opportunity to do is just be a bit more flexible in the way that we run these programs, so we don't have to rely on the X number of hours if we can give some more accurate data as well. So I've mentioned the NHS a few times, but specifically within that area. Within that area, you will find that people think of training as an extra thing to do, and especially if you're doing things online. So in my role when I was working for the software company, one of the things that we struggled with was to get people to understand the concept of going from a paper-based system to an online system or a digital system even more basic than online. And whilst you can change processes over, there'll be some processes that need to fundamentally change because of the way you're using them, and I think that's where we're getting to with AI now as well. So imagine that you, as a trainee or a user of a system, was doing something on the ground that you wanted your assessor to view. Now your assessor might just be a doctor that you've seen in the day, might be a nurse, somebody who's not really in your field, but they can judge you on how well you've done that case. So you can write your case up, press a button that will align to where you are within the curriculum. You can make that focused, you can make it quite broad and then you will get an assessor to view that. So how well you've done With a grading scale.

Speaker 3: 10:59

A Leica grading scale is really useful for this. So like one to six and then that's submitted and that grade is averaged against those areas of the curriculum. So if you've had one area against one specific, let's call it 1A of the curriculum, and you've had one area against one specific, let's call it 1a of the curriculum. And you've got a three. That becomes a three. If you've had a six and a four, it's averaged out against two, so it becomes three again. So you average out against it.

Speaker 3: 11:25

Now what I've described this as to other people is quantifying competencies, because you're simplifying down the process of learning so that you are just logging what you've done, being very easy to be assessed on and, more importantly than that, you as a trainee don't need to read through reams and reams and reams of documents. The AI will do it for you and that is like passing every assessment you do via the person who wrote that curriculum and knew its intended use. So, as you can imagine, medical education changes quite frequently. There's been a few changes in the curriculum since I've been around, even, but since 2018, it's all been on the fundamental model they're pushing at the moment and it is very flexible if it can be used correctly. So if you can pass that through an AI model that allows that flexibility, that will allow you to one standardize the process for everybody involved.

Speaker 3: 12:25

So you're not relying on individual trainees, you're standardizing it using the AI individual trainees, you're standardizing it using the AI, and it gives the person reviewing that trainee a little bit more data and feedback to go on as well, because I think that's a really key area. People rely very heavily on feedback and previously it's been very much. How many of these have you done? How many hours have you done? Do you feel like you're ready? And the feedback element is something that trainees have always come back and said we're lacking a decent, focused feedback element.

Speaker 5: 12:59

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Speaker 2: 13:45

Let's talk a bit more about this idea of competencies, but also I want to introduce the importance of personality types. Um, yeah, you, you, your, your project is all about personalizing learning experiences, um, and then automating admin tasks with the use of ai. Uh, okay, so we can get more granular with the competencies and then augment and assist and hopefully find efficiencies, et cetera, et cetera, et cetera. But where, where, the? Where the learning styles fit into that, where the personality types fit into that. It's not a, it's not a um, one size fit all. I'm, I'm guessing that there has to be a degree of this person is a visual learner or this person is an oral learner. Give us, give us your take on that yeah, so you're absolutely right.

Speaker 3: 14:35

I think that does hinder people at the moment. Um, certainly, in the role I'm in at the moment, I'm seeing a lot more requests for different types of examinations and learning to be given to medical students, which is great that we can accommodate that kind of thing and in terms of using something like this for that, I've seen a number of ways you could implement testing of very specific procedures. So you can test procedures using cameras and they can track all your movements and the AI can give feedback. But there's no reason, on a simpler level, you can't visually learn something. Feed the data into the AI portfolio that we're talking about via not necessarily typing it up, but actually just speaking about it.

Speaker 3: 15:28

You could record a two-way conversation. You could record a two-way conversation. You could visualize what you're doing in a graphic or even in numerous other ways. I think the key thing here is standardizing what it is that somebody should be learning via the competencies and then being flexible around those different areas of or different ways of learning. So you're you're not changing the goal posts depending on the, the different style of people learning. You're giving everyone an underlining, an underlying understanding. The AI is doing the heavy lifting in terms of those admin processes, but that that different type of learning can really be taken advantage of because the AI can understand it if the AI is programmed correctly.

Speaker 2: 16:19

I get that it's more black and white in the context that we're speaking about today within the sphere of medical services. You know it's not. We're not talking about a creative industry here, for example. So there are there are more uh, right and wrong answers, I, I guess. But, um, what? What are? Where do people fit in? Uh? What I mean by that is how do we ensure that people are involved at the right stages to make sure that they're auditing the? Uh, the AI, because you can't afford to get it wrong, can you Not, when you're talking about people's lives and people's health?

Speaker 3: 16:57

No, absolutely not. I think you raise a really good point there. So I would say the creativity of medical trainees and students is certainly there. It's not a creative industry in the sense that you're, um, you know, creating uh marketing materials or anything like that in a professional sphere. But you have to be very creatively minded to solve these issues and come up with uh treatments, and I think you can. You can really push that agenda using something like this.

Speaker 3: 17:26

But I want to be really clear on this the the ai tool at the moment that I, oh the process I've been looking at is augmenting the process that is already there. It wouldn't be replacing anything. I mean, the tiered system they have at the moment I think is really really, really works well, which is they have something called educational supervisors, which is similar to many industries. If you can imagine your boss in your work having a conversation with you and tracking how well you've done over the past six months using a company's framework or core values, this is a very similar thing. So what you're doing is really allowing that supervisor to view the information that you've gathered more effectively and it's standardized more effectively and it's standardized. So you're not relying heavily on if you've got a good supervisor. If you've got a bad supervisor you're not relying heavily on.

Speaker 3: 18:19

If you've misplaced where you think this case fits within a competency-based curricula, the the all the ai elements are there as suggestive elements and then it gives the people who are using it more time to sit down and discover that feedback approach which the GMC are really pushing.

Speaker 3: 18:41

Because, as you can imagine, as a medical trainee, one of the things you do lack is feedback, good quality time with somebody who can address not only the educational elements of the competency based curricula that we've been talking about, but free up some time for those professionalism talks and those engagement talks and all that bedside manner stuff that kind of gets forgotten a lot of the time in. You need x number of hours to do this because ultimately, being a doctor is a very people-facing profession. Especially in emergency medicine, medicine, general practice, pediatrics, just to name three off the top of my head You're going to be interacting with members of the public. So you want to preserve that ability and open and honest feedback element, but standardize the approach for training across the board and hopefully get to a point where you can reduce the hours of training so that people can be more efficient in training and you've got more time in service david, we are already coming towards the end of this particular interview.

Speaker 2: 19:43

Just a couple more questions for you before we do wrap up. Um, one thing that you wanted to make sure that we we mentioned in today's conversation is what makes this different. How is this different to others who are using AI? I feel like we have got a pretty good handle on it, but I'm going to challenge you in 60 seconds or less, david. Why is this so special? What makes it different? Go Well.

Speaker 3: 20:09

I actually think it's actually something that is similar to how AI has been used in the past. So I think the big jump in AI, as we all know, is the large language models and chat, gpt. Now a lot of people are looking at that for creative elements. So you know, write me a question, write me this cover letter, write me this and it will come up with things.

Speaker 3: 20:31

This is more like AI being used in the more classic sense of AI so early 90s, pushing forward and how it's still being used today, which is data analysis. The difference with this is the data analysis being used is inputs as language, so it contextualizes what you've put against the framework that's already there, so you're not asking it to reinvent the wheel or come up with something. You're saying I have done this, where does this fit within a framework I've given? And if you can imagine, that would be done with ones and zeros in the past, with kind of data analysis. This is doing a very similar thing, but with pros and with full paragraphs of data and then analyzing it against, say, a 50 60 page document and giving you some real insights into what you're supposed to be doing and how your work fits into that very good.

Speaker 2: 21:20

And just finally for today, david, how can folks connect with you and also learn more about all the cool things you're getting up to over at queen mary?

Speaker 3: 21:28

uh, yeah, so the best way to get me is probably on linkedin um david lay, uh lay dave, that just leads me to say thank you very much for being my guest.

Speaker 2: 21:37

Thank you very much for having me and listeners, as always.

Speaker 1: 21:39

Until next time, happy working thanks for listening to the hr chat show. If you enjoyed this episode, why not subscribe and listen to some of the hundreds of episodes published by HR Gazette and remember for what's new in the world of work? Subscribe to the show, follow us on social media and visit hrgazettecom.