DEFINING Underserved Communities in Healthcare | Ashish Rishi

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And I was like, my dad was never told that this study existed.
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He was never given the chance to even say yes or no.
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And I've never stopped wondering or asking if he'd been in it, would he have had a few more months?
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Would he have seen me graduate?
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And I can't answer that.
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That's if, buts, and maybes.
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But for me, what I can do from my perspective is make sure other families are at least asked.
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Because the exclusion I work on isn't people refusing research.
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It's people never being invited.
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Hi, I'm Caitlin,
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and I'm Clarinda.
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And this is Not Just Patients,
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a podcast where we break barriers to meaningful patient involvement in healthcare.
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Thank you so much for tuning in to this special episode of Not Just Patients.
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This episode marks the launch of our new series on underserved communities in healthcare, where we are aiming to reimagine healthcare as a more inclusive space by asking tough questions about who currently gets seen, heard, and designed for, and more importantly, who gets left out.
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If you are one of our regular listeners, you will notice that this episode has drum roll, please.
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video! Yes.
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Our new series on underserved communities in healthcare will be released with both audio and video, and we will be releasing more frequent episodes as well, as opposed to our regular monthly releases.
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This has been made possible by our amazing partners who have supported this series.
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We'd love to thank our conversation partner for this episode, which is Unwritten Health, who offer a patient experience data platform that can be used to generate evidence that your healthcare products work safely and equitably across the populations they serve.
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And joining us for this conversation today is Ashish Rishi, founder and CEO of Unwritten Health.
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And together we're going to be exploring what it means for communities to be underserved across the healthcare system.
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Thank you so much, Ashish, for joining us today.
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No, thank you for inviting me.
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I'm very excited.
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Wonderful.
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So our aim today is to really set the scene for this whole series.
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So with that in mind, the series is talking about underserved communities in healthcare.
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So the first question that we have for you is what makes a community underserved in healthcare?
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Right.
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I'm going to try and unpack this as simply as possible because it is such a big question.
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And we use some certain terms quite interchangeably, like underserved, underrepresented.
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Yeah.
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You know, and it sometimes can focus on ethnic minorities.
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And I think it is a broader discussion.
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So the way I'm very careful about where I put that word, sort of underserved.
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But for me, it describes the service, not the community.
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So I don't see it as a characteristic of the people.
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I think it's the track record of the system itself.
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So for me, a community is underserved when childcare consistently delivers less to them.
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So they get less access, less understanding, less evidence, less benefit.
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I'm sure you're aware we've done a lot of research on Written House and we have this report called frequency of inclusion.
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And it does show off literally in ordinary experiences.
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So it's not one big dramatic you are now in an underserved community.
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So in our survey, we we surveyed like over 1200 people from underrepresented communities.
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So I say underrepresented when they're not in the data.
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And 82% of our participants felt their health concerns were not taken seriously at all.
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82%, eight out of ten.
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Wow.
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And that's scary for me.
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And only 15% said that had never happened to them.
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So they 15% had positive experiences.
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One and a half people out of ten.
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I mean, that just scares me.
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So when I talk about underserved communities, it is those that are just not getting the right kind of access that maybe the more affluent or the uh middle class, sort of middle-aged population are getting, who are also, by definition, probably higher socioeconomic status and higher education status.
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There's so many different different things there that make up what I consider an underserved.
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Yeah.
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So I'd actually like to flip that question a little bit and and allow you to go a little deeper into what a well-served community would look like, for example.
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Are they a particular profile generally and what kind of access would they get comparatively?
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Yeah, that's an amazing question.
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Because we never really talk about it from we always talk about it from the underserved perspective, but what does served actually look like?
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So from my perspective, if I look at it just from a UK perspective or even European-wide um as well as US, where I consider the served community are, they are generally Caucasian, so indigenous to the country.
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Indigenous is a tricky word anyway.
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So let's just say people of European descent who are of higher education background or have access to more technology and are able to articulate what they want from their health care.
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And also that's where cultural barriers come in, you know.
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Like I I even though I'm in the UK, my family and how we we address healthcare is very different to how a white family, per se, an English family in the UK would see it.
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Um so a third person generally they are they get access to their healthcare quicker.
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So we could call it post-code, and they could be in more affluent areas.
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So you you know, you we could talk say London versus maybe urban areas of Birmingham, for example, wouldn't get the same kind of improvements.
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And it's all about funding and where that funding goes.
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And and in the UK specifically, so we have Manchester, who are devolved for NHS budgets, and then you've got London, which is essentially controlled by the government.
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Um, what we're seeing is from communities are getting different access to different kinds of treatments.
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Uh, for me, health equity or um tackling health equity or inequalities is every single person, or regardless of colour, creed, religion, postcode, has the same kind of access.
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Um, I don't know if I've answered your question, but credibly putting, it is it is that middle bar population and above, they get access to what they need from the NHS.
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I think that's a great question, Clarinda, because yeah, thinking about it the other side is actually really interesting, and basically everyone else you could consider underserved in some way or another.
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And I also love to sheet the way you kind of flip, not making the community necessarily the subject or certainly they're not the the problem.
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It's actually the system that's underserving them, which I think is a really sort of powerful way to look at it, because otherwise there's almost that onus or uh thought that they're kind of causing it, which is of course isn't the case.
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And the onus actually kind of stands on the the system itself and ensuring that you know, no matter where you come from, you can get equitable access to care.
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Absolutely.
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I totally agree with you on that one.
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It's uh it's it isn't sometimes down to social uh determinants of health sort of aspects.
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It's it's sometimes it's much broader than that, it's cultural, it's much deeper.
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Yeah.
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Yeah, that makes a lot of sense.
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Thanks for setting the scene really clearly and succinctly.
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I think that sets us up really well for this conversation and the rest in the series.
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Enough to understand your own story, your own journey, and your motivations for your work with Unwritten Hill.
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Yeah, definitely a very, very personal journey that has taken me to where I am now in my career.
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It really does start with my with my dad.
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So just for contact, I'm 47 years old now.
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My dad was 49 when he was diagnosed with prostate cancer.
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Um, and it was a a very terminal condition.
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And I bring in my age into it because it's I'm going through a very self-reflective period as I hold on.
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My dad was actually had cancer at this age.
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Um because it took it took the diagnosis itself took three years.
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So three years of him going to the doctor where he was dismissed again and again and again.
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And I remember it, and I was 16, 17 years old at that time.
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And he would come back.
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I won't repeat the kind of swear words he was using, but it was like, you know, he would repeat what the GP would say to us like, Well done, Mr.
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Rishi, you're losing weight.
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And my dad would get very irate by this because he was he worked losing weight, but he wasn't trying to lose weight, he couldn't digest his food, he was having a lot of pain.
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But then the GP would say, That's not that's not bone pain.
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You've just damaged your hip.
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Take the pain pillars, take paracetavoles, whatever it is.
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Every time he was sent home, and it took him to lose his temper in the GP and demand a referral to a hospital.
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And by that time, when he was referred to the hospital, he was diagnosed with terminal prostate cancer, and uh he'd given six six months live.
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And I remember it really well, but I didn't know what the issue was.
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They've discussed inequalities, equity, you know, all this racial bias, all this stuff that you see in medical gaslighting.
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None of that was knowledgeable to me.
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So I was 17 and I remember me and my mum were taken into that room.
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And my mum, English is her third language.
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So even though she's she's very highly educated and she's done very well for herself, it was still we were taken into a room, the consultant telling us like, and it very matrix, and I I just remember that tone because that tone is still like a trigger for me.
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And he was like, I'm sorry, Mr.
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Rishi has terminal cancer, he's got six months left to live.
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Here's a flyer, and we will get an appointment to you in the next few weeks to discuss next steps.
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And that was it.
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Um, me and my mum were like, Yeah, okay, you can leave now.
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So mum and I, yeah, we walked out of that room in a daze, confused, like, what the hell has just happened?
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We knew he wasn't well, but we didn't, we didn't think prostate cancer, we didn't think terminal, we were just like, whoa.
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And it was really hard.
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So my dad actually went on to live for another six years, and his last wish was to see me graduate from university.
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He used to joke that I was I was too ugly, so there's no point holding out for a wedding.
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[laughter]
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So he graduates a bit of food.
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Um graduation would have to do
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such an Indian thing.
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Yeah.
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And he he actually passed away in June 2002, and it was three months before I was supposed to walk across the graduation stage.
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Um, so he didn't quite see that, and that stayed with me my whole career, really.
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So I I then uh you know, every Indian wants their son to do or daughter even to be a doctor, and I was nowhere near intelligent enough to be that kind of individual.
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But I did want to stay in science, and I really wanted to understand is how can I fix this?
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So that's when I, after I graduated, I did a postgraduate in neuroscience.
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But at that point, you know, I just couldn't name it.
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So, and it came years later, and it was in my medcoms career.
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So I worked at some of the some of the bigger sort of um medcoms agencies down south in London, and that's where I started to understand clinical trials, inclusion-exclusion criteria, how studies are actually run.
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Um, and I was working on a prostate proposal for a prostate cancer product, and that's when I realized I was like, hold on, this is the global phase three study that I'm reading the data and the you know, the reader for.
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And the lead investigator was it was my dad's consultant.
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I used to go to all my dad's appointments, and I was like, my dad was never told that this study existed.
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It was never given the chance to either say yes or no.
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And I've never stopped wondering or asking if he'd been in it, would he have had a few more months?
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Would he have seen me graduate?
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Yeah.
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And I know, and I I can't answer that.
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That's if buts and maybes.
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But for me, what I can do from my perspective is make sure other families are at least asked, because that the exclusion I work on isn't people refusing research, it's people never being invited.
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So that's what I'm trying to try to change.
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And and those things have stayed with me and they drive everything I do.
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Yeah, and what I've learned really in the last 20, 25 years is my family story, sadly, isn't rare.
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It's not unique.
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And in that frequency of exclusion survey, people have told us they were never told they might be eligible for a clinical trial.
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So that exclusion is still happening decades on, and these experiences are everywhere, and yet they're almost not representative of the data.
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And so that experience is becoming universal and the record is empty, sadly.
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Yeah.
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So I'm just trying to kind of fix that.
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And that's why the company is now called Unwritten Health, a new one.
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And because the health experience of these communities, you know, they're largely unwritten.
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So our job is to write those stories at scale in a form that the system can't ignore.
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So uh yeah, that's that's my journey to why I'm here, sat here talking to you two.
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Thanks so much, Rashis, for sharing that.
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And yeah, sorry that had to happen to your family for you kind of follow this path and get here today.
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I think in the patient engagement space, it's often the story.
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But it it is a shame that that's kind of come from that tragedy there.
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And I think, you know, from what you were just describing from your story and the follow-up thoughts that you've had about that, is that in those situations, sometimes it's a decision has been made on behalf of someone without their involvement because of some sort of social determinant that or perception or assumption that's been made by whether it be a clinician or a researcher.
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And again, not always the case.
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There might have been some sort of legitimate reason and it's hard to know.
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But with that kind of evidence that you spoke about from the survey that's been done, there's clearly something, some undercurrent or something there that's meant that actually there is something that's stopping these communities from getting that equitable care, whether it's purposeful, whether it's unconscious bias, whether it's just years of I guess process and how things have always been done.
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But yeah, it's it's incredibly sort of hard-hitting and sad to hear about it.
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You know, encouraging for there's there's work being done in this space, and that's exactly why we're doing this podcast as well.
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No, I I appreciate that.
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And I think that's why I always frame it.
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I think the the process element that you mentioned is that's why I see it as an infrastructure issue.
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It's not, you know, we are good people, you know, people across the industry are good people.
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It's just an inability to to identify it and change it.
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And that's why, you know, and that's I see that as my my mission in in some way or other.
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Yeah, amazing.
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So you've spoken there actually about how being underserved can show up at different points in the healthcare system as well.
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So you mentioned at, you know, at point of care, but also from a research perspective.
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But I wonder if you could share kind of across the whole breadth of the healthcare system how actually being underserved happens and how it pulls through across kind of the patient experience and and lifeboat.
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Yeah.
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Um, so I've I've recently coined this term called inclusion debt.
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Let's start right at the beginning of that journey.
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You know, their job development, the identification of the compound, you know, who is it for?
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What is the unmet need?
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And if it's well, it all may cost, you know, revenue, f Yved.
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But if someone from the community or the community haven't been engaged at that stage, we're gonna basically compound now.
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Because at the first stage, a mistake has been made.
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Once they get to developing that clinical trial, once we go through phase one, phase two, phase three, we're building more and more issues.
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So there will be a payoff at some point.
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So for me, it looks in research, it looks like absence.
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So from our research, you know, more than a third of our respondents have never even heard clinical trials before they they met our survey.
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So I've actually been doing a lot of education with our community on equity engine.
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Is this what a clinical trial is, this is why it's important, and this is why you need to be involved.
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And I often bring up the pulse oxometer example from the pandemic when you know initial uh phases were of the pandemic, where a lot of black and south asian people in the UK were were were dying from from from the uh pandemic.
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And it was because the pulse oxometer that's used to measure lung function was under, I think it was over reading the data.
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So patients were sent home, then you're okay.
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And then they were puffed.
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But that was because that had never been tested on dark skin.
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So black and brown skin, and it didn't work.
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Um to the point to this day, so you go to the public loom, you know, when you put your hand under the soap dispenser, sometimes it doesn't come out when it's used because it's never the the UV doesn't work on dark skin.
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Always frustrated me.
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Um, and I've learned this over recent time.
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So, you know, dermatology products and so on.
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You know, I I have a uh a family friend who's from Nigeria and his tongue has eczema, and they need to get the eczema medication over from Nigeria because the ones in available in this country probably have never been tested on black skin, so they don't work.
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Um so research for me it is essentially absence.
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But and when the system does talk to people, I still think it fails.
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Um and I'm not sure why, and I'm finally diagnosed that.
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So in our research, 45%, so nearly like one in two, had been told about clinical trial, but they didn't fully understand it, what they were being told.
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So they just was like, Yeah, yeah, yeah.
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I I mean, I'm like that.
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When I don't have a clue what I'm talking about, I'd be like, yeah, yeah, yeah, and just walk off.
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But so communities are missing from the evidence base, which means treatments are developed and tested.
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Yeah, and people that are not like them.
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So we need to change that.
00:18:07.279 --> 00:18:18.799
But and then when I that's research, you know, you can then get into patient recruitment if you're just doing the same old patient recruitment tactics, you're pumping money into digital ads and so on.
00:18:18.799 --> 00:18:27.200
Whereas certain communities, I think I think this is broad now, will not cost the ads we see on a Facebook or a Instagram or whatever.
00:18:27.200 --> 00:18:30.640
So only someone really, really desperate is going to click on it.
00:18:30.640 --> 00:18:34.160
And they're I mean, the the experience there is awful.
00:18:34.160 --> 00:18:37.599
Sometimes they don't get callbacks and and all that sort of stuff.
00:18:37.599 --> 00:18:39.359
So yeah, it's it's not very good.
00:18:39.359 --> 00:18:43.759
But in policy, I see it as it's like invisibility.
00:18:43.759 --> 00:18:47.519
So like that policy runs on on data, right?
00:18:47.519 --> 00:18:54.720
But if there's un underrepresentation in the data and your community isn't in that data, your needs aren't in that decision.
00:18:54.720 --> 00:19:03.680
So the gap again compounds dismissed by the GP, absent from the trial, invisible on the data set that policy is built on.
00:19:03.680 --> 00:19:07.759
So again, we're we're building flaws upon flaws upon flaws.
00:19:07.759 --> 00:19:11.759
And if I look at say that point of care, it does look like dismissal.
00:19:11.759 --> 00:19:16.559
Even if you just use my dad's example, um I yeah, I'm a I'm a chunky boy.
00:19:16.559 --> 00:19:20.880
Um I you know, I go to the GP with any kind of ailment, the first thing they'll say is lose weight.
00:19:20.880 --> 00:19:22.640
And I'm like, what's I gotta do with?
00:19:22.640 --> 00:19:24.160
I don't know, I've got an itchy head.
00:19:24.160 --> 00:19:25.599
I've you know, whatever.
00:19:25.599 --> 00:19:33.680
Yeah, and 82% of our community that in our in our research, they have felt their concerns weren't taken seriously.
00:19:33.680 --> 00:19:36.880
That's a 12% of them, it happens all the time.
00:19:36.880 --> 00:19:45.839
You know, we can get into our women's health and endometriosis, how long it takes to get diagnosed and the pain that they're experiencing.
00:19:45.839 --> 00:19:49.759
So, yeah, it's just it's a lack of education.
00:19:49.759 --> 00:19:57.759
You know, we can go through the medical textbooks, they are used, they you know, the case studies are all from the white population.
00:19:57.759 --> 00:20:12.000
We can even look at the pain scale that is used in healthcare to this day, was tested on black women who were slaves in the 1800s, yeah, and we're still using those pain scales.
00:20:12.000 --> 00:20:24.880
So that's why you'll often hear horrible stories of black women who are having a crisis, the sickle cell crises, in pain, not getting access to the pain pillars because it's seen as drug-seeking behaviors.
00:20:24.880 --> 00:20:29.039
So there's so much miseducation out there, so much challenges.
00:20:29.039 --> 00:20:42.160
So that yeah, all of these things compound into just creating a very, I would even say, unsafe environment for for some communities who will just not access to healthcare, yeah, as they should.
00:20:42.559 --> 00:20:49.839
What strikes me about everything you said is the term underserved is is a shifting term.
00:20:49.839 --> 00:20:57.759
I mean, you can when you think about underserved communities, there are some profiles that might come to your mind, you know, like say racial, ethnic minorities.
00:20:57.759 --> 00:21:01.119
We have a list that we're covering in this series, for example, right?
00:21:01.119 --> 00:21:03.920
Those are the more obvious ones.
00:21:03.920 --> 00:21:29.759
But if I think about some recent examples, I've come across one very large clinical trial went to phase three, hit sites, and then was pulled and could like just pulled basically because it was targeting people aged 50 to 70 years and required them not to have comorbidities like diabetes and hypertension.
00:21:29.759 --> 00:21:38.240
I mean, essentially that is ageism because how can you design a trial like that?
00:21:38.240 --> 00:21:43.759
Uh, assuming, I mean, knowing that most of that population would have those comorbidities.
00:21:43.759 --> 00:21:59.759
And it just leads me to think about the amount of waste in research that is created, not just research, but in all of these, like policy making in at every stage by not including these populations for poor.
00:21:59.759 --> 00:22:01.440
These things are designed.
00:22:01.440 --> 00:22:08.799
Similarly, you were talking about trial recruitment tactics and using digital media.
00:22:08.799 --> 00:22:16.960
Beyond the choice of whether people appreciate the ads or not, do people have access to those digital media at all?
00:22:16.960 --> 00:22:25.759
And is that section of the population being completely eliminated if they don't have access to those digital tools?
00:22:25.759 --> 00:22:28.319
So that's an interesting question to ask, right?
00:22:28.319 --> 00:22:36.559
And I feel like it's it's such an such a shifting perspective as to who is who you are leaving out.
00:22:36.559 --> 00:22:42.559
And it's something that every healthcare decision maker should be asking, I feel, at every stage.
00:22:42.720 --> 00:22:43.039
Yeah.
00:22:43.039 --> 00:22:43.680
Yeah.
00:22:43.680 --> 00:22:51.359
What you've hit upon there, Clarence, there's something really, really important because it's the same exclusion and it's fucking again and again and again.
00:22:51.359 --> 00:22:55.039
And it actually led on to you talking about digital.
00:22:55.039 --> 00:22:57.039
I think it moves into AI.
00:22:57.039 --> 00:22:59.680
AI is being talked about so much right now.
00:22:59.680 --> 00:23:07.200
You know, it's been used in improving patient recruitment activities, improving drug discovery, improving so many things.
00:23:07.200 --> 00:23:11.440
But the data that it's all been built on is not representative.
00:23:11.440 --> 00:23:18.400
So what we're gonna do, we're gonna include more and more and more debt, as I call it, that inclusion debt, and it will keep building.
00:23:18.400 --> 00:23:23.200
And I think, you know, we run the risk of things getting worse rather than better.
00:23:23.200 --> 00:23:23.839
Yeah.
00:23:24.160 --> 00:23:25.119
Yeah, absolutely.
00:23:25.119 --> 00:23:42.319
Just I guess on that kind of same thread as well, I was thinking about how essentially at the moment healthcare is sort of improving like a great rate, it's innovating constantly, the science is moving, and actually there have been some major breakthroughs.
00:23:42.319 --> 00:24:02.559
But actually, if that, like as you say, is based on data from only certain populations, then that gap between I guess what we called well-served earlier and underserved communities is just going to get bigger and bigger and bigger because one community is being left behind while the other's sort of being shot out into space in a way.
00:24:02.559 --> 00:24:04.000
And you know, yeah.
00:24:04.000 --> 00:24:17.359
You do see that regularly in the newest breakthroughs and things, those diseases that matter more to those well-served communities, or they've been tested in those well-served communities, and some of them don't even work for those underserved communities.
00:24:17.359 --> 00:24:19.119
So that gap is getting bigger and bigger.
00:24:19.119 --> 00:24:31.119
And I know that even something like COVID, for example, was a really, really strong indicator as what was happening actually in in healthcare, and it highlighted those inequalities really strongly.
00:24:31.119 --> 00:24:32.480
Yeah, absolutely.
00:24:32.720 --> 00:24:33.039
Yeah.
00:24:33.039 --> 00:25:02.400
And I definitely see that in India, I mean, the gap is already extremely wide, and this would probably apply to a lot of other lower middle-income countries where the gap is huge between urban and rural areas, or between educated and non-educated people, because of the way the healthcare system works, uh, which is very much based on your capacity to understand your capacity to pay, all of those things.
00:25:02.400 --> 00:25:08.400
So it's already not a universal healthcare system, right?
00:25:08.400 --> 00:25:18.960
So it's very much true that that the more well-served communities continue to be well-served, the underserved communities are left behind.
00:25:19.279 --> 00:25:27.599
Yeah, and it's it's it's it's one of those, it's probably the hardest question right now in the w in in our space is how do we improve that?
00:25:27.599 --> 00:25:31.119
Because those the disparities are getting wider and wider and wider.
00:25:31.119 --> 00:25:32.559
Yeah, it's it's it's hard.
00:25:33.279 --> 00:25:51.119
So I have a bit of a a tricky question for you, Ashish, in the way it's in the way to phrase it, but you know, we've spoken a lot about the fact that there is this big gap between underserved communities and what I guess is the the optimal health that is available for those well-served communities.
00:25:51.119 --> 00:25:52.960
But why has that happened?
00:25:52.960 --> 00:25:55.200
Why are these communities underserved?
00:25:55.519 --> 00:25:56.720
It's a difficult question.
00:25:56.720 --> 00:25:58.720
Um, and I've been trying to diagnose it.
00:25:58.720 --> 00:26:05.599
So if I look at it from a UK perspective, so I'm I mentioned um the frequency of exclusion research that we do.
00:26:05.599 --> 00:26:12.640
So we surveyed 1200 people in the UK, all of them from underrepresented, underserved communities across the UK.
00:26:12.640 --> 00:26:20.960
And we asked them about their healthcare experiences, their relationship with clinical research, the barriers they face, and would they change their minds?
00:26:20.960 --> 00:26:25.839
And there were four findings that I think really define the issue, I think for me.
00:26:25.839 --> 00:26:32.559
Um the first was that that dismissal finding, you know, 82% of the community thought their healthcare concerns weren't taken seriously.
00:26:32.559 --> 00:26:35.599
And that's the root cause running under everything.
00:26:35.599 --> 00:26:41.200
You know, if you dismiss once, you dismiss twice, you dismissed three times, yeah, you will just ignore it.
00:26:41.200 --> 00:26:51.599
And I have I have close friends of the family and friends who who just are tired of that constant battle to get access to the healthcare they deserve.
00:26:51.599 --> 00:26:57.279
Um so technically, you know, begins with that healthcare, and healthcare has already failed these communities, I think.
00:26:57.279 --> 00:27:00.240
So that comes out pure from our research.
00:27:00.240 --> 00:27:10.400
The second I would talk about are a lot of the conversations are around attitude to healthcare and attitude to clinical trials.
00:27:10.400 --> 00:27:13.039
And I think it's actually the question is different.
00:27:13.039 --> 00:27:16.720
It's what are the barriers that are stopping people?
00:27:16.720 --> 00:27:20.079
So it's and for me, it's very structural.
00:27:20.079 --> 00:27:27.599
So, you know, the industry might have spent like a decade treating diversity as a trust problem, requiring like a communication solution.
00:27:27.599 --> 00:27:34.079
So, you know, we're gonna do during the pandemic, we're gonna black out our social media, we're gonna do more, better messaging.
00:27:34.079 --> 00:27:38.559
But down the line, the authenticity got lost.
00:27:38.559 --> 00:27:43.920
And so now it's just uh, I don't know, it's like a slogan, put it that way.
00:27:43.920 --> 00:27:48.480
So, you know, to this day I still get patient recruitment flies to look at.
00:27:48.480 --> 00:27:51.200
And I I I should last, but it's just hilarious.
00:27:51.200 --> 00:28:00.880
And I got one, I did it for a for a particular client on prostate cancer recently, and they wanted feedback on their recruitment materials and their patient belief steps and so on.
00:28:00.880 --> 00:28:18.960
But the branding was beautiful, you know, the study was beautiful, but the imagery they chose for um a prostate cancer study was a black man on a golf course wearing a polo t-shirt, looking set and healthy with his wife's laughing um or assumed wife.
00:28:18.960 --> 00:28:20.799
Um, but yeah, they were having fun.
00:28:20.799 --> 00:28:24.880
And I put it, we put it through our platform and you know, asked for feedback on it.
00:28:24.880 --> 00:28:28.000
And you know, it was it was literally savage.
00:28:28.000 --> 00:28:37.039
It's things like firstly, if I'm got prostate cancer, I'm not likely to be on the golf course, I'm not likely to look as as healthy as that.
00:28:37.039 --> 00:28:50.799
Um the language you are using is is borderline offensive because we're we're trying to synthesize how we talk to, say, the black population, but it's not written by people with that lived experience.
00:28:50.799 --> 00:28:54.559
So it's and some of it you can see is AI generated.
00:28:54.559 --> 00:29:00.960
So more culturally sensitive leaflets are part of it, but our data challenges that directly.
00:29:00.960 --> 00:29:08.400
So, and the two biggest barriers to take apart in research were simple, too many hospital or clinic visits.
00:29:08.400 --> 00:29:14.400
I've got a job, I've got three children to look after, some of us need two jobs.
00:29:14.400 --> 00:29:19.119
I can't take time out to go to all these hospital or clinic visits.
00:29:19.119 --> 00:29:25.279
And the second biggest result was clinical trials are simply not designed for people like us.
00:29:25.279 --> 00:29:26.880
That was the language they use.
00:29:26.880 --> 00:29:30.880
Trust became was actually, I think, third or fourth on the list.
00:29:30.880 --> 00:29:32.400
Yeah.
00:29:32.400 --> 00:29:45.759
So the sector has been trying to solve like the fourth least important, not least, fourth most important issue, but not the protocol design and not who is who is promoting the study.
00:29:45.759 --> 00:29:48.720
Um and these are huge issues.
00:29:48.720 --> 00:29:59.680
And and the third thing I we sort of was able to dissect from the data is this communication piece that I've sort of touched upon is it's failing at scale, and it's not where you would expect.
00:29:59.680 --> 00:30:09.440
So all the people told about a trial by a healthcare professional, the most confused group were not those of lower education, they were university graduates.
00:30:09.440 --> 00:30:12.480
68% of them didn't understand.
00:30:12.480 --> 00:30:20.240
And against 30% of people with GCSEs, which is like uh uh I don't even know how to internationally uh so uh uh yeah, high school diploma.
00:30:20.480 --> 00:30:20.880
Yeah.
00:30:21.200 --> 00:30:26.160
So for me, this isn't a literacy problem in communities, it's a jargon problem.
00:30:26.160 --> 00:30:30.400
We need to put the the issue on the industry.
00:30:30.400 --> 00:30:41.599
So, as one of our respondents put it, language barriers to make it hard to understand medical information, but I'm not talking about English, I'm talking about the words used on these flyers.
00:30:41.599 --> 00:30:43.359
So that's that's a real issue.
00:30:43.359 --> 00:30:56.960
And fourth study I've got written on my notes here is 83% said they'd be more likely to take part in a clinical trial if it was designed with their community in mind by people who understood their lives.
00:30:56.960 --> 00:30:58.720
And that was written by 45%.
00:30:58.720 --> 00:31:10.079
And these are lay people, so these aren't like patient experts or you know, us in the industry who are saying you need to speak to more than just one or two advisory boards.
00:31:10.079 --> 00:31:12.160
It needs to be bigger, there needs to be bigger data sets.
00:31:12.160 --> 00:31:13.920
The lay people are saying the same thing.
00:31:13.920 --> 00:31:17.359
So the willingness is there, it's the design that's missing.
00:31:17.359 --> 00:31:28.000
So under underneath all of that, I see it as structural, social, cultural factors and structurally, you know, research infrastructure built around a default participant.
00:31:28.000 --> 00:31:39.599
And that default participant is broadly white, male, employee, mobile with no caring responsibilities, because they are able to dedicate that time.
00:31:39.599 --> 00:31:42.400
And they're never fundamentally redesigned for anyone else.
00:31:42.400 --> 00:31:44.960
Socially, there's a clear income gradient.
00:31:44.960 --> 00:31:54.400
You know, participation runs from 85% in higher income households down to the low 60s of time, travel, caring responsibilities.
00:31:54.400 --> 00:31:56.240
They come up with more when you have less.
00:31:56.240 --> 00:32:02.880
Um, culturally, health decisions in many communities are made relational, like in terms of what the relation is.
00:32:02.880 --> 00:32:07.680
A researcher talking to one person is often talking to a whole family's decision.
00:32:07.920 --> 00:32:08.160
Yeah.
00:32:08.720 --> 00:32:26.079
And this actually led me to creating my previous company was I was on a site visit and I was in the US, and I remember the lead investigator of this site was I am not recruiting people of Hispanic population because it's a small clinic and they all are there to make the decision.
00:32:26.079 --> 00:32:27.200
And I don't have time for that.
00:32:27.200 --> 00:32:28.720
So I refuse to engage with them.
00:32:28.720 --> 00:32:30.480
But we all talk to our family.
00:32:30.480 --> 00:32:33.680
I think this isn't a South Asian thing, this isn't a Hispanic thing.
00:32:33.680 --> 00:32:34.480
We all will.
00:32:34.480 --> 00:32:41.839
Um, but yeah, so yeah, and one of my findings, I word it as my favorite finding, but I don't know if that's the right kind of language to use.
00:32:41.839 --> 00:32:43.759
And it's something that I call symmetry.
00:32:43.759 --> 00:32:54.079
So, you know, 50% of the people named too many hospital visits as a barrier, but then also the same number named a trusted community as a thing that would change their mind.
00:32:54.079 --> 00:32:59.039
The community has told them the solution is a large as large as the problem.
00:32:59.039 --> 00:33:04.240
So what's missing isn't evidence, it's that desire, it's will, and it's the right approach.
00:33:04.480 --> 00:33:04.880
Yeah.
00:33:05.039 --> 00:33:05.359
Yeah.
00:33:05.519 --> 00:33:05.680
Yeah.
00:33:06.000 --> 00:33:08.480
They're my my big takeaways, I think.
00:33:08.880 --> 00:33:11.920
That's yeah, that's a lot to chew on.
00:33:11.920 --> 00:33:23.599
I think uh what really stood out for me as a communications professional is the piece you spoke about regarding the communications imagery.
00:33:23.599 --> 00:33:31.119
Uh, I've been on that side where I've picked out the imagery, you could say, of a lot of campaigns.
00:33:31.119 --> 00:34:01.680
Uh, you know, and I think what's interesting is that somewhere along the line, um, companies in any space pretty much decided that oh, we need to have more diversity in our imagery, and that meant having a black face tick or having a colored person tick, but still pretty people, smiling people, happy people, people in shape.
00:34:01.680 --> 00:34:16.000
Essentially, I mean, I probably I'm guilty of that as well, because the truth is that patients in distress on imagery would make people uncomfortable.
00:34:16.000 --> 00:34:28.320
But that is probably the most realistic depiction, and that's something that would call out to another patient if they were to look at it and say, Oh, yeah, that looks like me.
00:34:28.320 --> 00:34:38.559
And I don't know if people are comfortable or ready to make that kind of leap to yeah, face it and say that this is what real life looks like.
00:34:38.559 --> 00:34:46.800
It's not all on a golf course, and you know, it's it it is it is hard to live with these kind of chronic conditions.
00:34:46.800 --> 00:34:51.039
So uh yeah, I think that that's that's like one big takeaway for me.
00:34:51.360 --> 00:34:53.920
Yeah, and that's something that I've always sort of worked upon.
00:34:53.920 --> 00:35:07.039
And so in my previous company, what we would do is so we used to create these materials and so on, and we would co-create it every time with that community, whoever the community is that we're working with, and we would create three examples.
00:35:07.039 --> 00:35:18.480
And that would work better, because we had that endorsement before we took anything to a client, because fundamentally the client client is gonna be looking at it from the lens of what's the information?
00:35:18.480 --> 00:35:21.920
Does it truly depict the disease or the condition?
00:35:22.159 --> 00:35:22.400
Yeah.
00:35:22.639 --> 00:35:35.440
But if we can go in and and bring in some of that community voice and just change the language up a little bit, you know, not in terms of uh trying to make it like like slang, but I would say trying to make it more the community member has said this.
00:35:35.440 --> 00:35:47.519
I've even had a battle once for a chemotherapy product where it was predominantly Middle Eastern Muslim women who were who were taking this.
00:35:47.519 --> 00:35:56.960
The battle I had was I I worked with an Imam and I was like, can you provide some kind of statement that we could put into our flyer that will give credibility to the study?
00:35:56.960 --> 00:36:04.159
Because there is no uh pork gelatin, there is no alcohol in it, and fundamentally what we're trying to do is improve their lives.
00:36:04.159 --> 00:36:14.960
And there was no sus, but I had issues with the with the the um sponsor and essentially saying we can't do that because it will alienate, I don't know, community X, Y, and Z.
00:36:14.960 --> 00:36:16.400
And I said, No, it wouldn't.
00:36:16.400 --> 00:36:23.599
It actually would show that you're thinking about the community, and maybe you could add more community voices in the future.
00:36:23.599 --> 00:36:25.679
Um yeah, I thought that through in the end.
00:36:25.679 --> 00:36:34.400
It was one of the proudest things I've ever done because just through that, I was able to our recruitment project finished like six months ahead of schedule in the end.
00:36:34.400 --> 00:36:41.360
So but all that was was just being authentic, and it's I think we maybe we sometimes make it bigger than it should be.
00:36:41.840 --> 00:36:49.599
Not to make a sort of crude comparison, because it's not the same, but it's almost like seeing uh a chocolate bar or something if it's vegetarian.
00:36:49.599 --> 00:36:53.599
I'm not a vegetarian, but that's not gonna put me off from eating a chocolate bar.
00:36:53.599 --> 00:36:56.400
It just means that more people can eat it.
00:36:56.400 --> 00:37:10.000
And yeah, that it's just it just feels strange to me that that would well, the worry there was that it would alienate, I guess, a well-served community rather than sort of being additive and saying actually we're being more inclusive.
00:37:10.000 --> 00:37:15.920
And honestly, you said so many things before, Ashish, that I could spend another hour talking to you about this.
00:37:15.920 --> 00:37:27.280
But I guess the one thing I want to want to pick up on, sort of following the same thread, is actually that, you know, our podcast, not just patients, is all about patient involvement in healthcare.
00:37:27.280 --> 00:37:42.800
And again, that is moving and improving their processes, there are initiatives in place to ensure that patients are involved in research protocols and involved in developing information and involved in HTA processes, etc.
00:37:42.800 --> 00:37:45.199
But again, that's just starting.
00:37:45.199 --> 00:37:48.559
And is that happening from a representative perspective?
00:37:48.559 --> 00:38:02.239
Or are the people who are involved in these conversations and who are educated and willing to engage with pharmaceuticals, engage with researchers, are they in the well-served community?
00:38:02.239 --> 00:38:05.119
I think the answer to that is the likelihood is yes.
00:38:05.119 --> 00:38:34.000
So again, it's saying, you know, in in order for patients to truly be involved and for it to actually represent the people who it serves, yes, you need patients in the room, but you need a diverse representation of those patients in the room as well, because every single individual is different, and therefore you need more people to represent those different like facets of different communities as well, to ensure that actually a solution does work for everyone.
00:38:34.000 --> 00:38:41.280
And to your point before, that there is data for everyone as well that you can show that this works for some people and not others.
00:38:41.280 --> 00:38:42.559
What can we do about it?
00:38:42.559 --> 00:38:44.159
Or this does work for everyone.
00:38:44.159 --> 00:38:44.800
Fantastic.
00:38:44.800 --> 00:38:47.199
Here you go, take this to all of your patients.
00:38:47.199 --> 00:38:54.559
It's it's all about representation and sort of that diverse and inclusion across the healthcare system.
00:38:54.960 --> 00:38:55.360
100%.
00:38:55.360 --> 00:39:06.159
I mean, you know, we've heard horror stories of heart failure drugs, you know, not being tested on women, but just seeing women as a smaller man and then adjusting the dose accordingly.
00:39:06.159 --> 00:39:10.719
And I don't want to name the product of the company, but essentially we know what happened.
00:39:10.719 --> 00:39:12.320
Essentially, that drug was pulled.
00:39:12.320 --> 00:39:14.079
People lost their lives, sadly.
00:39:14.079 --> 00:39:16.880
So yeah, it is it's a dangerous game.
00:39:16.880 --> 00:39:24.400
And it's it's about remembering that representation for the industry, the decision makers isn't just about skin colour, it is much broader.
00:39:24.400 --> 00:39:31.119
I think there's like on the diversity wheel, there's like 120 different factors that can that make someone diverse.
00:39:31.119 --> 00:39:36.559
Um, so there's a lot to think about in terms of who you engage, how you engage, or when to engage.
00:39:36.559 --> 00:39:46.880
And I think not not to make this about unwritten house, but essentially that is what we're trying to do is making sure that we can create that data more democratically.
00:39:47.119 --> 00:39:47.519
Yeah.
00:39:47.519 --> 00:39:50.159
And it's wonderful work that you're doing.
00:39:50.159 --> 00:40:01.360
We've heard about how the inequity plays out in terms of how people perceive it and the different points at which it plays out in the system.
00:40:01.360 --> 00:40:09.760
But what is the impact of inequity on both the communities and society?
00:40:10.159 --> 00:40:10.400
Yeah.
00:40:10.400 --> 00:40:22.719
So I think the impact really that I would put it down to, and there are so many different factors, but the one I want to sort of think about is when it comes to communities, it's avoidance, and we know what the consequence is of avoidance.
00:40:22.719 --> 00:40:37.360
So when 76% of the community has avoided or delayed delayed care in the past year, conditions that could have been managed early progress to series presentations, you know, that's that's just science.
00:40:37.360 --> 00:40:38.079
We know that.
00:40:38.079 --> 00:40:43.119
So then medication will go unreviewed, um, preventable admissions accumulate.
00:40:43.119 --> 00:40:47.519
So we know what kind of impact that has from an economics perspective of the country.
00:40:47.519 --> 00:40:53.519
Um and people manage things alone or leave on informal networks, you know, like Dr.
00:40:53.519 --> 00:40:56.800
Google, and we know how quickly that can be.
00:40:56.800 --> 00:41:03.440
So rather than return to that rather than return to a system, has essentially just let them down.
00:41:03.440 --> 00:41:12.880
And if we look at what these communities are living with, um, so we if I think about it from our data at the moment, is 63% of our respondents have a long-term condition of some kind.
00:41:12.880 --> 00:41:18.400
The most common were asthma, depression, pain, type 2 diabetes.
00:41:18.400 --> 00:41:21.440
So those conditions are quite invisible.
00:41:21.440 --> 00:41:24.000
You know, you don't know, you can't see it if someone has it.
00:41:24.000 --> 00:41:28.320
But they're also quite stigmatized once you do know you have it or someone knows you have it.
00:41:28.320 --> 00:41:33.360
And these are decisive the conditions most likely to be underdiagnosed, under-treated, dismissed.
00:41:33.360 --> 00:41:39.039
And I could actually I sort of even bring in endometriosis is is a prime example.
00:41:39.039 --> 00:41:40.960
It's such a big issue at the moment.
00:41:40.960 --> 00:41:46.320
And it has been for years, but I'm positive about where policy is going in the UK at the moment with that.
00:41:46.320 --> 00:41:47.599
And that's that's a good thing.
00:41:47.599 --> 00:41:53.599
Um, so in the communities like living with them, they're they're the same communities that excluded some clinical research.
00:41:53.599 --> 00:41:57.280
So it's the same finding, just expressed in different ways.
00:41:57.280 --> 00:41:59.199
Um, if I'll be honest with you.
00:41:59.199 --> 00:42:05.119
And I think there's a smaller issue here, not a smaller issue, so it's a it's a silent issue that no one's really talking about.
00:42:05.119 --> 00:42:07.920
And it is that data, it's the evidence in itself.
00:42:07.920 --> 00:42:13.599
So when treatments are tested on people, you know, that are not like me, I'm a type 2 diabetic.
00:42:13.599 --> 00:42:16.079
That medicine will work as well for me.
00:42:16.079 --> 00:42:28.400
And I I I sort of challenge it with my TP because I'm pretty like I I look after myself, but my HBA1C is not under control, and I don't get why it'd be because the medicine medicine doesn't work.
00:42:28.400 --> 00:42:33.519
So, you know, that I'm in this industry now, I'm going, oh my lord, is this medicine being tested on me?
00:42:33.519 --> 00:42:34.639
Is it any good?
00:42:34.639 --> 00:42:37.119
So you get into that really bad state.
00:42:37.119 --> 00:42:57.920
So yeah, and no, and one number that also stays with me when we talk about inequity in these communities, if I look at it from an England perspective, is we're in a east of England, which I I would say is more rural, um, has healthcare avoidance in 94% of our sample who were from east of England would avoid healthcare.
00:42:57.920 --> 00:43:04.719
But in London, it was 56%, and they're two very entirely different realities, and they're in one country.
00:43:04.719 --> 00:43:08.559
So that's why that one size sits all will never, ever, ever work.
00:43:08.559 --> 00:43:11.519
So it's looking at racial variations as well.
00:43:11.519 --> 00:43:14.639
And we're talking about a small country like England, UK.
00:43:14.639 --> 00:43:16.079
So there's so much.
00:43:16.079 --> 00:43:23.679
Imagine the size when you when you think about India, when you think about US and China, wherever it may be, um, yeah, there's a lot more to think about.
00:43:23.679 --> 00:43:28.639
But then when I think about society on the whole, I think everyone pays, everyone suffers.
00:43:28.639 --> 00:43:30.880
It doesn't matter who that person is.
00:43:30.880 --> 00:43:34.320
So economically, you know, that is expensive.
00:43:34.320 --> 00:43:39.920
Every person who delays like primary care and later arrives in like A and E and those readmissions.
00:43:39.920 --> 00:43:48.880
I think there's a there's a stat somewhere in off the top of my head, it's like 4.1 billion uh cost to the NHS for for these readmissions.
00:43:48.880 --> 00:43:52.719
And you know, that isn't a cost that we're declining to pay.
00:43:52.719 --> 00:43:54.880
It's just we as a country we're paying it.
00:43:54.880 --> 00:43:57.920
So that's where that inclusion that I keep talking about.
00:43:57.920 --> 00:43:59.760
We have to pay for it somehow.
00:43:59.760 --> 00:44:00.239
Mm.
00:44:00.239 --> 00:44:02.880
And science, I think there's an issue.
00:44:02.880 --> 00:44:04.719
It degrades the evidence for everyone.
00:44:04.719 --> 00:44:12.239
So the UK the underrepresented communities are they're large and they're they're a growing share of the population.
00:44:12.239 --> 00:44:17.039
So medicine that's built on data that excludes them is simply worse medicine.
00:44:17.039 --> 00:44:21.039
It's less generalizable, less safe, less effective.
00:44:21.039 --> 00:44:23.119
And commercially it's self-deceiving.
00:44:23.119 --> 00:44:28.000
So recruitment is one of the biggest costs and timeline drivers in drug development.
00:44:28.000 --> 00:44:30.159
But that cost, where does that go?
00:44:30.159 --> 00:44:31.599
Drugs that are extensive.
00:44:31.599 --> 00:44:32.960
It affects the economy.
00:44:32.960 --> 00:44:35.039
So it is that vicious cycle.
00:44:35.039 --> 00:44:40.320
And you know, looking at it from a civic duty perspective, it erodes that trust.
00:44:40.320 --> 00:44:43.119
And you know, trust is is infrastructure.
00:44:43.119 --> 00:44:47.519
So once communities learn the system isn't for them, they disengage from all of it.
00:44:47.519 --> 00:44:51.599
So with that screening, vaccination, research, prevention, whatever that looks like.
00:44:51.599 --> 00:44:53.679
Pandemic showed that at scale.
00:44:53.679 --> 00:44:56.800
It showed that it showed it on a daily basis.
00:44:56.800 --> 00:44:57.360
Yeah.
00:44:57.360 --> 00:45:07.199
So yeah, and I don't want to be too much of a downer, but I think these are these are all the different elements that are playing and making things worse when there is simple solutions.
00:45:07.199 --> 00:45:12.000
Engage with the community and include their voice.
00:45:12.000 --> 00:45:14.000
So don't make it a checkbox exercise.
00:45:14.000 --> 00:45:18.079
It's the same narrative that I'm sure you you guys will talk about on a daily basis.
00:45:18.079 --> 00:45:22.639
So and it actually will have an impact, but just you got across the process.
00:45:22.880 --> 00:45:25.599
And that leads, I think, really nicely on to the next question.
00:45:25.599 --> 00:45:29.760
Speaking about flipping the script and how we can sort of improve things.
00:45:29.760 --> 00:45:37.119
So you've just said there, like it's all about hearing those voices and making sure that they're included, involved, represented.
00:45:37.119 --> 00:45:40.320
But that's not happening as much as it should, I should say.
00:45:40.320 --> 00:45:47.519
So what should healthcare leaders do differently then to ensure that those voices are included and involved?
00:45:47.840 --> 00:45:57.440
Yeah, so I've got I've got three things that that come to me that I would not necessarily the most important, but for me, they're the ones that I still that are prequins.
00:45:57.440 --> 00:46:01.119
The one is is to treat those structural barriers that we're talking about.
00:46:01.119 --> 00:46:11.280
And so every new study protocol, you know, it should pass the past like a I don't know, we can call it a structural review, whatever that looks like before recruitment open.
00:46:11.280 --> 00:46:14.000
Can appointments happen outside of working hours?
00:46:14.000 --> 00:46:17.360
Can any element be done remotely or in a community setting?
00:46:17.360 --> 00:46:20.000
What's the true minimum number of in-person visits?
00:46:20.000 --> 00:46:22.719
Has anyone interrogated that information?
00:46:22.719 --> 00:46:27.760
Can remote participation being the deed for, you know, not an accommodation?
00:46:27.760 --> 00:46:31.360
So they they they few things we could interrogate it a lot more.
00:46:31.360 --> 00:46:37.920
And it's not just say the three of us in a room interrogating it, but it's it's bringing in some of the people with lived experience.
00:46:37.920 --> 00:46:41.199
Well, I'm assuming it's a random condition, you know.
00:46:41.199 --> 00:46:55.920
It could be a safety type two, it could be me, I could be there interrogating it as a patient, as a someone who has a job who is working in this space, but one person isn't enough, two people are not enough, an advisory board of 10 people for me is not enough.
00:46:55.920 --> 00:46:57.119
It needs to be bigger.
00:46:57.119 --> 00:47:00.880
And the second thing I would probably talk about is is funding.
00:47:00.880 --> 00:47:12.239
It's funding those community organizations and treating them as a not as a distribution channel, as a, I don't know, we're doing Facebook ads, we're doing community groups and we're doing this.
00:47:12.239 --> 00:47:14.000
No, it needs to be much broader than that.
00:47:14.000 --> 00:47:16.400
It needs to be like research infrastructure.
00:47:16.400 --> 00:47:27.119
So in our so, like, for example, in our trust data, that community organizations came top above GPs, the NHS, and pharmaceutical companies and universities that actually run the research.
00:47:27.119 --> 00:47:30.239
So a trusted community works is important.
00:47:30.239 --> 00:47:37.440
So build them into the infrastructure, fund them, support them, be present, be there.
00:47:37.440 --> 00:47:41.760
Um, and I think three for me is fix that language, uh, consent forms.
00:47:41.760 --> 00:47:45.599
You know, there should be a comprehension process, not about signature.
00:47:45.599 --> 00:47:47.599
We need to be measuring different things.
00:47:47.599 --> 00:47:54.079
And again, I go back to my university grads, you know, two-thirds of grads calls, pony clinical trial conversation.
00:47:54.079 --> 00:47:58.639
Problem is the capital research, plain language isn't a universal standard.
00:47:58.639 --> 00:48:02.000
So yeah, so it's having a special measure, or particularly webs.
00:48:02.000 --> 00:48:05.760
Yeah, I would say the other three big things for me to start with.
00:48:06.800 --> 00:48:07.199
Yeah.
00:48:07.440 --> 00:48:07.840
Yeah.
00:48:08.159 --> 00:48:08.559
Thanks, Ashish.
00:48:09.199 --> 00:48:11.440
I think that that sums it up really nicely.
00:48:11.440 --> 00:48:18.400
What would you say is one assumption about underserved communities that healthcare needers need to let go of?
00:48:18.800 --> 00:48:23.920
So to me, I think it's challenging the assumption that these communities are unwilling or the problem.
00:48:23.920 --> 00:48:25.199
They're not unwilling.
00:48:25.199 --> 00:48:31.920
The system is just inconvenient of everything, and it's never no one's ever measured why it's inconvenient.
00:48:31.920 --> 00:48:33.360
So it's time to start doing that.
00:48:33.360 --> 00:48:44.000
So and yeah, I think for me it's understanding that they're not unwilling, it's just ensuring that your study is more accessible to these different community needs, which sometimes are conflicting.
00:48:44.000 --> 00:48:48.800
Uh, we're in healthcare, we're ahead, we're about improving lives, and that should be a default, I think.
00:48:49.039 --> 00:49:02.960
Yeah, I think something that you said earlier strikes me, which is that if these communities have felt unseen and unheard for so long, they have disengaged essentially.
00:49:02.960 --> 00:49:12.800
They've pulled away because they feel like this does not work for them, it's not built for them, they are choosing to avoid healthcare, and that's also scary.
00:49:12.800 --> 00:49:21.840
The 90-something percent that you mentioned, I don't know what that what they're doing if they're not if they're avoiding healthcare, how are they addressing their medical concerns?
00:49:21.840 --> 00:49:33.280
But then when you have a crisis like a pandemic, I mean the pandemic was the epidemic, but it could be any kind of uh health scare, right?
00:49:33.280 --> 00:49:36.000
It could be um an epidemic.
00:49:36.000 --> 00:49:38.159
You need everyone to pull together.
00:49:38.159 --> 00:49:48.400
And then it's like the way that we talk about rare diseases, that rare diseases are rare individually, but when you put them together, they are a significant number.
00:49:48.400 --> 00:50:00.320
Similarly, these undeserved communities together are a significant account for a significant percentage of the population that won't be pulling together because you've never seen and heard them.
00:50:00.320 --> 00:50:11.920
And now when you want them to come together and be part of this solution that uh everybody needs, you expect them to play your game when you've never played theirs.
00:50:11.920 --> 00:50:16.639
And uh and that's that's such an interesting way to look at it.
00:50:16.639 --> 00:50:34.480
That how are we building systems that consistently exclude large segments of our populations and then you know, expecting them to be these model patients who adhere when we prescribe them things.
00:50:35.280 --> 00:50:38.159
I think you your framing there is spot on for me.
00:50:38.159 --> 00:50:41.519
I think it's why should we play their game if they're not playing our game?
00:50:41.519 --> 00:50:52.480
And it is that's where that sort of battle comes, and yeah, it's a big challenge, but I I do I really do believe getting that patient voice earlier is the solution.
00:50:52.480 --> 00:50:53.199
It really is.
00:50:53.199 --> 00:50:59.360
Even you know, there are some companies that go and review the services or how the GP surgery looks like.
00:50:59.360 --> 00:51:11.440
There's there's even small enhancements we could do there, and the sort of lies we put in, and yeah, and there are there are management consultancies there who are doing that, but again, they're basing it on what kind of data, who are they talking to?
00:51:11.440 --> 00:51:14.000
It's um it's not very transparent, yeah.
00:51:14.400 --> 00:51:14.880
Yeah.
00:51:14.880 --> 00:51:29.840
I think what struck me as well when you're speaking about the solutions that you're speaking about, that doesn't just improve accessibility to underserved communities, it improves accessibility for everyone.
00:51:29.840 --> 00:51:30.400
Yeah.
00:51:30.400 --> 00:51:33.840
And that's quite clear as well when you spoke about the university graduates.
00:51:33.840 --> 00:51:36.239
I know Clarinda and I have spoken about this a lot.
00:51:36.239 --> 00:51:41.840
We're both working in medcomms, we have science backgrounds, we're patient experts.
00:51:41.840 --> 00:51:46.480
I've been to a doctor's appointment and had no idea what would speak to me.
00:51:46.480 --> 00:51:52.320
And yeah, you know, I I sit on that sort of or more of the well-served side, honestly.
00:51:52.320 --> 00:52:01.519
And if I can't understand it, then how does anyone with without sort of my background and experience and expertise manage that situation?
00:52:01.920 --> 00:52:02.320
100%.
00:52:02.880 --> 00:52:06.960
It's just really clear to me that actually there are some things that you can do.
00:52:06.960 --> 00:52:19.679
Yes, it is to help underserved communities, but it's also to help everyone feel more comfortable, more informed, yeah, easier to access the the healthcare and and the research that we're talking about here.
00:52:20.079 --> 00:52:26.480
That's a very good point there, isn't that we are in this industry and we do this day every day and we're still struggling.
00:52:26.480 --> 00:52:28.880
So yeah, we can't expect everyone else to get it.
00:52:28.880 --> 00:52:29.920
Absolutely 100%.
00:52:30.559 --> 00:52:38.880
So this has been so interesting, Ashish, and I think it's really set up perfectly for the rest of this series on underserved communities and healthcare.
00:52:38.880 --> 00:52:46.000
So, what questions do you think we should keep asking throughout this series as we're talking to people from different communities?
00:52:46.320 --> 00:52:50.639
I think what you you did very well today is to keep asking why.
00:52:50.639 --> 00:52:59.679
And I think it's not the how, because the industry focuses on the how, it's why is in like this, you know, because that's how we challenge the status quo.
00:52:59.679 --> 00:53:03.440
So for me, your you guys are fantastic out in the why.
00:53:03.440 --> 00:53:08.719
Keep doing that and yet hold everyone to account as much as best as you can is hold everyone to account.
00:53:08.719 --> 00:53:10.400
Yeah, that's what I would love to see.
00:53:10.559 --> 00:53:11.360
We'll do our best.
00:53:13.199 --> 00:53:14.079
You guys are great.
00:53:14.079 --> 00:53:17.920
I think you guys are very good at this, and uh, yeah, just keep asking that why.
00:53:18.159 --> 00:53:19.119
Thank you, Ashish.
00:53:19.119 --> 00:53:26.639
And finally, what do you think a healthcare system designed around real lives, real people's lives would look like?
00:53:26.880 --> 00:53:37.199
Well, it would be the three of us not together obviously, that'd be weird, but buried to our CP appointments and understanding what on earth are they saying, that's a style.
00:53:37.199 --> 00:53:41.760
Because then I I know for a fact we would then trust whatever that doctor is saying.
00:53:41.760 --> 00:53:45.920
We would then go take that medication as they're saying rather than doing, you know, whatever.
00:53:45.920 --> 00:53:48.159
So I think that's a key thing.
00:53:48.159 --> 00:54:02.320
But also, I mean, if uh the ideal is everyone is getting access to the same treatments at the same time, and it's uh we know it works whether you're got brown skin, whether you've got white skin, whether you've got black skin, we know it works.
00:54:02.320 --> 00:54:06.320
That would be heaven, I think, or paradise, whatever that looks like.
00:54:06.320 --> 00:54:07.440
That would be my ideal.
00:54:07.760 --> 00:54:14.559
I think that's a a vision that we can all get behind and hopefully start start working towards in the near future as well.
00:54:14.559 --> 00:54:15.679
Absolutely.
00:54:15.920 --> 00:54:17.039
Thank you, Ashish.
00:54:17.039 --> 00:54:20.239
It's been really, really lovely having you here.
00:54:20.239 --> 00:54:21.280
And thank you.
00:54:21.280 --> 00:54:23.519
We're really excited about this series.
00:54:23.519 --> 00:54:29.920
We're excited to ask these tough questions, and thank you for being on board with our tough questions today.
00:54:29.920 --> 00:54:32.079
And you answered all of them really well.
00:54:32.079 --> 00:54:38.159
And I think that this has been a really rich and insightful conversation for us and for our listeners.
00:54:38.159 --> 00:54:39.920
So it's been lovely having you.
00:54:39.920 --> 00:54:40.880
Thank you.
00:54:41.280 --> 00:54:42.400
Thank you very much.
00:54:42.400 --> 00:54:43.760
I appreciate this.
00:54:44.400 --> 00:54:50.320
This has been not just patience with our guest, Ashish Rishi, and your hosts, Caitlin Rich and Clarinda Cerejo.
00:54:52.079 --> 00:54:57.440
Our thanks to our conversation partner, Unwritten Health, for making this episode possible.