Episode 43 – What does AI mean for IA?

Debbie: Hello and welcome to Inflammatory, a podcast all about navigating life with inflammatory arthritis. I’m Debbie.

Katy: and I’m Katy

Debbie: How are you, Katy? How’s your son? Is he back at school now? Is he all better?

Katy: He went back to school on Thursday. So, I took him to the GP Wednesday morning last week you know, you get swollen glands in your neck. So, he’d got swollen glands, but then he’d got swollen lymph’s in his lymph nodes or whatever they’re called in your stomach were slightly swollen, which was what made, because he vomited on Monday night. So, then it just completely throws your week off. Cause my husband was away with work only for a night, so it’s nothing, but I then got plans in the office on the Wednesday. I’ve got 17 people coming into the office for an event, only a small event, but I was the one that had organized it. So, you feel quite responsible, but then obviously your children take priority. Luckily his granddad came round, my father-in-law Wednesday lunch, because my event was at the end of the day and I took him to the GP in the morning just to check. Because I don’t want to pass anything on to them. So, I wouldn’t want him to look after him and then get sick himself. So, it’s just always that juggle. But then by the weekend, he was back to himself. But you could tell, you can always tell can’t you when they’re ill.

Debbie: Of course, yeah.

Katy: But when he’d been sick, I didn’t think it was a sickness bug. So, I couldn’t work out what had made him sick, but apparently it was swollen lymph’s that then when you eat, they all move around and then it just, I don’t know. Apparently, it’s a thing that like kids and teenagers get. Never heard of it before. Like most kid things.

Debbie: I hadn’t heard of that before, but that sounds awful. I’m glad he’s all better now though. And yeah, back at school. Back at school.

Katy: Yes, back to normal, which is good.

Debbie: Yes, well, what we’re going to be discussing today, I think we briefly touched on it last week, is about artificial intelligence. I think we talked about it in the context of more social media last week. But actually, it is more involved in healthcare than I think that we know. just before we started recording, we googled when AI started. And I can’t believe it was in the 50s.

Katy: Yeah, it’s crazy. But it’s just more to do with technology advancements that have made it something. I don’t think I knew that much about it until late 2017, 18 through to 2020 was when it all started being more newsworthy, wasn’t it?

Debbie: Yes and think that’s when it was probably becoming more accessible to, I think, everyday people as well. Because I must admit, I didn’t know that it has been around for ages. And in my previous career, I was a statistician and so data was my life. And even now I love looking at data. I’m quite sad. But with healthcare though, what comes into your mind when you kind of think AI and healthcare?

Katy: Oh, it’s quite a tricky one because I think it is the classic, a robot doing an operation on you, which actually my friend had a robot doing an operation on her the other week and it was all fine. mean, and that’s not, I don’t know how that works, but it’s not fully artificial intelligence because it is an actual human controlling the robot. Because she had, I’ve forgotten, some minor organ or something removed. I can’t remember what. And it was just a keyhole robot removed it for her. But you’ve got a doctor controlling it. So, it’s quite different.

Debbie:  Yeah, it’s still that human side of it all still

Katy: Yes. Yeah. There’s still the human side.

Debbie: Yeah, I think it is there because I must have when I originally think of AI, I do think of I just have the vision of iRobot. It’s Hollywood side of it all. But that’s what I think of as well. But it isn’t that. it is. And I think this is where people, especially people like me, get slightly confused. And actually, what does it mean in health care? And we will actually be getting an expert on the podcast. This is just literally just us because we’re not medical professionals. We don’t really know how it’s fully embedded at the moment, but it is just looking at that data side and looking at the MRI scans, the blood tests and everything. But I think for a diagnosis, especially more in rheumatology, you do need that human doctor to really look at your joints and to really go through all of it because I think if there was a one test to show whether you had inflammatory arthritis, probably why not? But because rheumatology and inflammatory arthritis, you have so many joints as well that whether a robot could really, even if they were developed, could actually really test the joints to actually see the swelling and how bad it is as well. I don’t think they would be able to get that touch.

Katy: Yeah, I just don’t think, I mean, who knows what technology will bring in the next 50 years, it’s that also rheumatologists when they’re feeling your joints, they’re feeling for heat. I’m sure there’s heat sensors and things like that, I just don’t see that working as well. And actually having those conversations, because when you’re asked, I don’t know if you have this in your consultancy appointments, but when you’re asked to rate how you feel from zero to a hundred, you need that human interpretation of understanding that person and what that naught to 100 kind of actually is.

Debbie: Yeah, and I also think when you do that as well, you bring in as a human all the invisible symptoms as well, like the brain fog, the pain, because you can’t, even, no, no, you can’t, no. And so even then how a robot would ever understand pain, that’d be a really interesting one.

Katy: Yeah. You can’t see or feel pain from a doctor. They can’t feel it.

Debbie: So yeah, so I don’t think it can’t take into account all of that. And it is those invisible symptoms how you get that across to your consultant as well to really understand because I know we’re to be doing

Katy: Yeah. And fatigue, fatigue is such a huge symptom

Debbie: It really is.

Katy: that unless you know somebody’s face, you can’t like, my mum could always tell when I’m fatigued or I’m really over exhausted just by the way my face looks. I mean, I actually don’t expect, I don’t actually expect a consultant would be able to do that either because I don’t see them often enough, but you can still, for example, when I took my son to the GP. He said, he does look a bit pale. He doesn’t know my son, but he could sort of see that the colour had gone out of his face. So, he could tell there was something making him not feel great.

Debbie: But then I suppose one side of that would be we could just put makeup on. Sometimes people do feel that little bit better in themselves that actually if you then look probably better, do you then actually feel better? And I suppose even just going to the hospital, if you do look fine, they might not be able to see really what’s going on. I hardly ever wear makeup, so it doesn’t ever bother me.

Katy: Yeah. Pre-COVID days I’d quite often be dressed to go into the office so I’d be in the waiting room and I occasionally got asked if I was a consultant or worked in the hospital or like I was in the hospital to try and sell them something because I didn’t look like a patient.

Debbie: Really? Wow that’s interesting

Katy: I don’t know what a patient is supposed to look like. But I learnt from that and now I try and make sure if I go to an appointment I look as terrible as possible. I won’t wear makeup. I’ll look a bit bedraggled because then I feel like you look more like a patient.

Debbie: Wow, that’s interesting. Yeah, because I’ve…

Katy: So, I was always quite conscious of not looking too nice because then I think you can be misread just because you put some makeup on and obviously you then look better, which again, I completely agree.

Debbie:

Yeah. It just gives you that little boost when you need it really.

Katy: I think when I’ve put some makeup on, I look better. So, I feel a bit better. It’s a bit superficial, but it is, yeah. It’s like I’ve straightened my hair today. I feel way better.

Debbie: I’ve just ruffled mine, but it does. there have been studies on this though, that actually prove that because I generally only walk my dog and that’s how I ever get out of the house. I’m always generally in trackies because it’d be like, Oh, let’s just quickly go now. I don’t want to go and get changed And I’m at home. No one sees me, when I go out for a dog walk, I probably look homeless more than anything else, but it doesn’t bother me.

Katy: Well, at this time of year, well, I definitely look homeless on the school run. One of my friends last week, she thought she said I dressed like a fisherman because it was raining outside and I’d got green khaki trousers on that are a bit, they’re like a pleather type thing. Sorry, this is completely off topic. And then I got a rain jacket on, which unbeknown to me, it was exactly the same colour as my trousers. So, I looked like I was in my waders about to go fishing, apart from my Ugg boots that are going to get completely wrecked in the rain, which were really stupid. Anyway, moving on.

Debbie: Well, I suppose that is actually probably then a positive for having more AI because that takes away any judgment on how you look.

Katy: Does it though?

Debbie: Well think, how would it? I don’t know if it would, I don’t think it would judge you like that.

Katy: I know but it depends what data has gone in though, doesn’t it?

Debbie: That’s then the other thing is, again, as a statistician, whatever data you get out is only as good as the data that goes in. And I think this is where people have been getting quite concerned about all the data that maybe the NHS or other healthcare providers around the world are collating. What do they actually do with that? But I would want them, the one thing that I would love with the support of AI to do is to take away the trial and error of medications, we need those personalized medications treatments, because we have so many treatments now, but it does seem like, well, here’s a pathway, so we’ll try you on that, but we know it doesn’t work for everyone. And how do you then know that you’re the one that it does work or doesn’t work for? And that’s what we really need to take away from is that trial and error, because it is so frustrating.

Katy: I know it’s been talked about for quite a long time is personalized treatment. And actually, as you say, having AI look at the stats and the data of the type of people that certain treatments work for, then that might make us that little step closer and it might be already happening. don’t know if you know.

Debbie: Well, I am involved in, I think I’ve said before it’s called MapJag, but it’s also they look at JIA and rheumatoid arthritis and they do biopsies of the synovial fluid to try and get any biomarkers that goes along with, the blood test as well, It’s trying to get as much data out of us humans as possible to actually really see if there are any patterns, any biomarkers there to actually then say, no, this person wouldn’t work well on say that DMARD So we’ll put them straight away on a biologic. Something like that is what we need. And again, I think this also works into the theme of the month, my pace, not yours, because it’s not only just pacing yourself, but your medications work different paces as well, because we do get people saying, it worked fine for me near enough from day one.

Katy: Yeah.

Debbie: That’s great for you, but then it doesn’t work for everyone else from day one. And it can take that three months, I use 12 weeks for it to properly kick in. And I think that’s what is also a slight misconception out there because everyone goes, well, you’re now on medication, you’ll be fine.

Katy: Yeah, yeah, yeah, yeah.

Debbie: It can take time.

Katy: Yeah. And it’s, and it’s also, you sometimes need a bit of a dosage tweaking through that period from, from my experience on a lot of the DMARDS is you’d start on quite a low dose. They’ll see how your body takes it, whether it works. And then if needed, if the disease activity isn’t going down, they then increase the dosage very, very gradually. So, whilst it might take 12 weeks for that initial dose to take any form of effect. It then might take another 12 weeks for the next. So, it can sometimes, I think it can take as long as a year or more to know actually if something’s worked or not for you. a year in your life, I know it goes very fast now at my age, but a year in your life is such a long time. And for something not to work, then it’s so frustrating.

Debbie: Yeah. And then also during that year, you then don’t want to get any joint damage either. But then if you were then told that, no, this, we know that this one won’t work for you. We’ll put you on this one. And then it does work. It’ll be like, great. It’ll be better for the economy. People can hopefully, you know, still be working, still feel more human and not have that, that long-term damage. So, then you might not need operations. We need it just for life as well. And this is what, is the charity that we’re really trying to push is that we don’t want inflammatory arthritis. know IA and AI, they’ll get confusing. I’m just going to say what it is. We don’t want inflammatory arthritis to be that barrier because those treatments are already there.

Katy: Yeah. That’s what we want to see is like no barriers to people living with inflammatory arthritis and that we can all, do well.

Debbie:  Why not? And this is what we are going to be pushing for more as well. And if there’s any researchers out there looking at this, I know there are quite a few. Please get in touch, know, come on the podcast, explain what you’re doing as well. Because I think people are realizing that we need this information. And if there’s any other data that we can do any research studies that we can then be part of, please let us know because this is what really, really can change and impact a huge amount on people’s lives. Yeah. And I think the other thing is getting that diagnosis early And NASS the National Axial Spondyloarthritis Society is I’m always just so glad to say NASS That’s what they’re working on as well. And it was really clear when we had Rachel on the podcast that it took her 13 years to get that diagnosis. And even James, took a long time to get the diagnosis. We need those diagnostic tools to really be there to help support clinicians to get that diagnosis early. That is so, so key.

Katy: Yeah. And also, I guess once you’ve got the diagnosis based on your biomarkers that are plugged into whatever tool it is, having a better understanding of your future and what that disease progression might look like. Because as we know, our diseases are very different and no inflammatory arthritis diagnosis like the similarities, but there’s also so many differences. So it’s knowing how to support that person based on who they are, how they live their life, to help them have those better outcomes and hopefully not have to have like joint replacements and things like that later down the line or secondary diagnosis. It’s because we know a bit, I think it was James that said, you kind of collect them like Pokemon cards. Once you’ve got one, another one might follow.

Debbie: Yes, yeah, it is fully understanding that and again, any biomarkers as you say, anything to really pick that up, whether you’re more at risk of other comorbidities as well would be so, so important. But then I suppose not everyone might want to know that though. Would you? Yeah.

Katy: Yeah. That’s true. Yeah. You can sometimes know too much. I don’t know. It’s like, you want to know when you’re going to die? Because, know, essentially like life insurances trying to predict when someone’s likely to die to understand, it sounds awful, doesn’t it? To understand how much money they need to put in to make the payment out. I wouldn’t want to know that. I would rather just live my life as best I can.

Debbie: I do as well. And you know, considering my nan is over 100 now, I’m going to live forever. But then having any diagnosis, I think sometimes your mind does go into that it shows that you’re not immortal?

Katy: Yeah. For me, for example, I’d never before my diagnosis, I’d never really had any form of health problems. And it’s like in some work medical insurance policies, you can go and get like a health check once you’re over 40. One of my friends recently did that. And then it picked up loads of health problems. And so, I’m thinking, actually, I don’t think I’d ever want to do that because sometimes, I mean, it’s good. I don’t know. Sometimes it’s nice if you feel well, just to continue as is. I don’t know.

Debbie: I think that’s what I’ve always said to me is I always try to live in the moment. Again, because I’ve lived with IA for so long, I can’t ever remember a time when I’d never had it. And again, this goes into our theme as well is like when you have to cancel plans and everything. I don’t plan, I have to live in that moment because I never know whether tomorrow or even this afternoon am I going to be well, is something going to flare or not. So I really just do just try to live in that moment. Because it’s just trying to control the uncontrollable and the unpredictable. And I think this is again coming back.

Katy: And I don’t think any algorithm, I do not believe, I’d love someone to prove me wrong, maybe, maybe not, don’t know. I just don’t believe any algorithm can ever predict how someone’s, year is going to go based on an inflammatory arthritis diagnosis.

Debbie: Completely. Obviously, the way the AI works, it needs all that data. Whether there is enough data in the world ever to try to kind of predict those things, I don’t know. But then I think this is where it just comes back to, we are all human. And even if there are things that can then support healthcare,

Katy: Yeah. One thing I think it can probably do as well is more on the administrative side. They probably do use this in hospitals, I would presume, but like doctor’s notes, dictation and all that those simple administrative things that then give consultants more time back in their day. It’s not always just about the healthcare side. It’s also that giving time back so that consultants can actually focus on delivering the best for patients.

Debbie: Yeah, I was actually talking, it just that triggers something, I was talking to a consultant and because it was then it’s done by, it was an American AI when they said, obviously medical words anyway, it came up with something completely different. And it’s just like, what the hell was that? I never said that word, but obviously as it was more American with a different accent, it would have sounded very different. And that’s what it was. This is what I think you’re saying. And actually, it’s not and trying to then get all these medical terminologies. But then it also, think it could then show the consultants they need to put things in lay language more. Talk lay language best. It’s teaching you to talk lay language.

Katy: Yes! No, that’s a good point.

Debbie: That could be a positive out of it all. But yeah, I just think we are all human and never forget as well that you know your body better than anyone. And please do talk to your teams and try to advocate as much as you can. We’ve mentioned, Katy it’s hard for everyone to do that. And I think doctors could be even worse when they’re, when they’re then the patient as well. It’s just like role reversal. They find it hard and everyone does. It’s not an easy thing to do, but you know, you know your body and if it’s not right please do talk to your team.

Katy: Yeah. What do you, Debbie, what do you think is like the biggest positive and your biggest concern with AI in healthcare?

Debbie: My biggest positive would be to see if it can take away that trial and error in medication. think we have to have hope in it because it’s not going to go away. And if there’s anything that can really change and impact people’s lives, it will be that and just trying to get those biomarkers to get rid of that because otherwise, as I said before, it’s so frustrating. And my concern is probably to do with the data side. That it needs to be unbiased and it needs to be fully representative of everyone who lives with IA because everyone’s journey is different. This is what we keep saying on the podcast and what all our guests say is that their journeys are very different. There are some commonalities, but everybody’s journey with it is different. So yeah, so that’s kind of my concerns. What about you?

Katy: Think some of it, obviously, is treating the disease better and being more focused, but I do think there’s so much power in it giving consultants more time and more time to actually deliver the care that is needed for their patients and take away maybe some indecision, because it must be really hard. You’ve got a patient in front of you, what do you do with this patient? I don’t, I mean, I’m not a doctor. not like, just like, because there’s, there’s so many variables that they’re presented with but then the biggest concern is you hear so much around AI hallucinating. So, what happens if it hallucinates in healthcare? It’s very different to it. You ask any questions to help you pull together a presentation and it is spitting out a load of poor information, where’s the human checks that when it’s in healthcare, it’s actually giving the right information and it’s not hallucinating.

Debbie: No, I agree. please let us know what your positives or concerns are as well about AI because it’s not going to go away. It’s a bit like IA. I think we need to finish on some quick fire rounds though. I know we’ve done this before and it was really good fun.

Katy: Yep.

Debbie: If your inflammatory arthritis had a settings menu, what feature would you immediately turn off?

Katy: I’m trying to think of a settings menu.

Debbie: I suppose more like a symptom’s menu.

Katy: Yeah. okay. Symptoms menu fatigue.

Debbie: Yeah, I would, I would agree with that one. If your joints had a group chat, who causes the most drama?

Katy: My wrists.

Debbie: For me. It depends on what day, but at the moment I think my back and my wrists as well. Tech you love and tech that you absolutely don’t.

Katy: Yeah. I mean, I pretty much hate all tech. If anybody’s going to crush a system, it’s generally me. So, I’ll just say I hate it all.

Debbie: Hahaha! Okay, but you track all your things on your Strava, I’d say.

Katy: Yeah, so actually like I do love Strava actually, especially when we’re thinking about this month’s theme of My Place Not Yours. So Strava tracks how much exercise you’ve been doing. So today I got a notification from Strava saying last week you did a bit more than usual. want to consider resting more this week. So that’s quite useful.

Debbie: Actually, One word that describes your relationship with rest. We won’t repeat what Katy just said. She’s rubbish at it.

Katy: What? What? I’m rubbish at rest.

Debbie: I’ve got used to it and I actually sometimes think needed.

Katy: So that is, I would say it’s needed, but I sometimes ignore it.

Debbie: Oh, okay. We spoke last week about cancelling plans. Would you say cancelling plans feeling relief or guilt?

Katy: Sadly guilt

Debbie: Yeah, mine too, but I’m learning to have it more as relief. Yeah.

Katy: I’m trying to be a bit more on the relief side because sometimes, and I do actually quite often feel relief once I have cancelled.

Debbie: Pace today, slow, steady or stopped.

Katy: Steady.

Debbie: steady. I’d say steady, actually. And finish this sentence. My pace is…

Katy: Crazy.

Debbie: Ha ha!

Katy: or literally don’t

Debbie: That’s all. Don’t know. I was going to say my pace is mine. It’s what it’s what I do and I’m learning to not feel guilty, not apologize for anything.

Katy: I like that.

Debbie: So yeah, my pace is mine and I’m unique, you know, and I think everyone out there is unique as well. And just listen to your body and what and what is right for you. So yes, it’s been a great. Oh, gosh.

Katy: Got one for you Debbie. AI predictions, trust or side eye.

Debbie: at moment a probably side eye, but hopefully because

Katy: I agree, I don’t really trust it quite yet.

Debbie:  No, it’s too much I think in its learning stage and actually when we see more benefits and I think obviously what’s come across on the news as well that how people are using it for awful, awful things.

Katy: God, yeah. Yeah, that’s where,

Debbie: We need it to be properly trustworthy in order to trust it.

Katy: And it’s got so much, it could be absolutely incredibly amazing. It just needs to be used in the right way. Yes. Yeah.

Debbie: It could in the right hands as well. It’s been a great episode. Thank you, Katy, but please do rate and follow the podcast from wherever you get your podcasts from. Please do follow us on social media as well. We’re really trying to increase our Instagram followers. So please do like, share, comment again. All these algorithms, all these AI algorithms will help us get more reach. But, until next week, Katy, it’s goodbye.

Katy: Goodbye.

In this episode of Inflammatory!, Debbie and Katy dive into the growing role of artificial intelligence (AI) in healthcare and what it could mean for people living with inflammatory arthritis. They talk openly about the promise of AI, from helping personalise treatment to supporting earlier diagnosis, while also reflecting on the very real challenges of living with a long-term condition.

Alongside the tech talk, the conversation keeps coming back to what really matters: human connection. Debbie and Katy explore why empathy, understanding and being truly heard can’t be replaced by algorithms, no matter how advanced they become. They also touch on the everyday realities of chronic illness, including fatigue, invisible symptoms and the importance of learning to advocate for your own health.

The episode wraps up with a fun quickfire round, where the hosts share their honest thoughts on AI, data and the future of healthcare.

What we talk about:

• How AI has been around for decades and why it’s now becoming more visible in healthcare
• Why personalised medicine matters so much for inflammatory arthritis
• The life-changing impact of early diagnosis
• Why human care and compassion must stay at the heart of healthcare
• Fatigue and other invisible symptoms that are too often overlooked
• How AI could reduce trial-and-error when prescribing medications
• The importance of speaking up and advocating for yourself
• Why AI data needs to represent all patients, not just a few
• Living in the moment with a chronic condition
• How AI could give healthcare professionals more time to focus on patients

A thoughtful, honest conversation about balancing innovation with humanity and putting people first.

Sound Bites

• “You know your body better than anyone.”
• “We need to advocate for our health.”
• “AI predictions: trust or side-eye?”

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Disclaimer: Debbie and Katy are not medical professionals. They share personal experiences of living with IA to build connection and community. The podcast is for informational purposes only and is not intended to replace professional medical advice. We talk about our personal health journeys and the podcast is not intended to provide professional medical advice, diagnosis, or treatment. We are not medical professionals and in no way claim to be medically trained. The podcast does not take responsibility for any losses, damages, or liabilities that may arise from the use of the podcast. The podcast does not assume responsibility for the accuracy of third-party content.

For more information, head to https://inflammatoryarthritis.org/