🎧 Listen to the Episode
In this episode, Ursula and Christine are joined by Tara Cowling, Founder and President of Medlior Health Outcomes Research—a Canadian leader in real-world evidence (RWE), health technology assessment (HTA), and health outcomes research. Together, they explore how health data can be transformed into actionable insights that improve care, trust, and outcomes for patients.
Tara shares her journey from her early work with NICE in the UK to leading an independent research consultancy in Canada. She explains how better data access and health literacy can prevent missed diagnoses, improve early detection, and strengthen public confidence in healthcare systems.
From data privacy and interoperability to the promise of AI and next-generation patient registries, this conversation unpacks how collaboration between patients, researchers, and decision-makers can shape a smarter, more equitable future for healthcare.
Why you should listen
- Discover how data trust and transparency affect patient outcomes.
- Learn what “quality” means in real-world evidence and why transparency and reproducibility matter.
- Understand the role of health literacy and interpretation in how patient data is collected and used.
- Hear how AI and predictive analytics are redefining the future of healthcare data.
- Explore how long-term patient registries and real-world insights can drive policy change and better funding decisions.
Episode highlights
- [00:02:00] Meet Tara Cowling — Founder and President of Medlior Health Outcomes Research shares her journey into data and healthcare innovation.
- [00:07:15] When data goes wrong — real stories that show why accessible, linked data can save lives.
- [00:10:00] Mental health and data — Tara explains why mental health checkups should be as routine as dental visits.
- [00:12:30] Health literacy and trust — how communication and transparency build confidence in data use.
- [00:16:00] Defining quality data — what makes research reliable: transparency, reproducibility, and context.
- [00:21:00] The promise of AI and real-world evidence — how technology and patient data can drive personalized, equitable care.
- [00:22:30] Building the future — Tara’s vision through the Avita Health Foundation for long-term patient registries that shape better health systems.
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Tara Cowling
Founder and President of Medlior Health Outcomes Research ~ Leader in RWE, HTA and Health Outcomes Research
Tara founded Medlior Health Outcomes Research Ltd. in 2008 with a priority for providing value and insight to health outcomes research projects through robust methodology. Tara has over 20 years of health outcomes research experience in both public sector and industry. Prior roles include five years with Alberta Health Services as the Lead of Clinical Data Services and five years in HTA/Market Access for AstraZeneca UK, Wyeth UK, and IQVIA UK. In addition, Tara gained experience as a Research Fellow for Clinical Guidelines in Chronic Conditions at the National Institute for Health and Care Excellence (NICE) in London, UK.
Transcript
[00:00:00] Ursula: Welcome to Amplify Elevating Patient Voices, a podcast powered by patient voice partners, where real stories spark bold conversations. I’m Ursula Mann.
[00:00:12] Brent: And I’m Brent Korte. Together. [00:00:15] We’re talking with patients, caregivers, and the healthcare change makers who are listening and taking action
[00:00:21] Ursula: from personal journeys to policy shifts.
[00:00:24] Ursula: These are the voices shaping a healthcare system that listens.[00:00:30]
[00:00:33] Ursula: Christine, I’m so excited about today’s show and glad you’re co-hosting this with me. Today, we’re gonna be talking a lot about data. What comes to mind when you think of healthcare and data?
[00:00:42] Christine: I think sometimes we have too [00:00:45] much of the wrong data, but not enough of the one that we really could use. I’m not a huge data person myself, to be honest.
[00:00:51] Christine: It is not my forte, but I have to admit that when you see really good data that is meaningful to you, uh, it will resonate with [00:01:00] whoever you know, whether you’re right brain, left brain person, data oriented or not. It’ll speak to you.
[00:01:06] Ursula: That’s exactly why I wanted to have this conversation with you because data I know you sometimes tell me you really like the human side, which is one thing I really appreciate [00:01:15] about you.
[00:01:15] Ursula: I know if we had Barry on this, he says he’s a freak in the sheets, the data sheets, and he’d be all over the data, but I think it’s a really interesting perspective to recognize that it’s really complicated and what would make it really meaningful. So today we’re gonna [00:01:30] talk about data past. Data present and data future, and I’m excited to have Tara Cowing join us to talk about her experience in data, looking at what’s complicated and perhaps what would make it less complicated.
[00:01:44] Ursula: Christine, what do you [00:01:45] think? Should we get started? Anything else on data before we kick this off?
[00:01:48] Christine: Absolutely. I’m very excited to hear about what Tara has to say, even if I’m not one of those buried data driven person.
[00:01:56] Ursula: I know with your experience knowing everything you’ve [00:02:00] dealt with, you think strategically as to how to apply things.
[00:02:03] Ursula: And so as you and I work in patient engagement and with multi partners, we’re thinking of perhaps not numbers all the time, first and foremost, although there is a serious application [00:02:15] of what that means to the patient. As people are making decisions, do I want to do this or do I not want to do this? And whether or not they’re thinking that data is first and foremost in their mind to make that decision, I think sometimes it is.
[00:02:28] Ursula: Tara, thank you for joining us [00:02:30] today. We’re delighted. I’ve had the opportunity to spend some time with you over the last little while, and I always get a little bit more bedazzled by data. Every time we chat. I think your energy is contagious. Can you tell us a little bit about yourself?
[00:02:41] Tara: Absolutely. I am a data enthusiast [00:02:45] and I’ve had an interesting career path.
[00:02:48] Tara: I’m the founder of Medlior Health Combs Research, so we’re a Calgary headquartered independent research consultancy and going for about 17 years. It was a little bit of a journey to get [00:03:00] to Medlior, so I actually started my career in the UK working at Nice and then in market access roles for AstraZeneca, Wyeth, and I-Q-V-I-A before moving back to Canada.
[00:03:09] Tara: My joke, the wrong side of the country for the pharmaceutical industry. That was in the first job that I applied for, which was [00:03:15] at the Calgary Health Region. Now obviously a HS many moons ago in the data department. So I worked there for five years, got some exposure and understanding to the type of data that the health system routinely collects, and then I had an opportunity to do some sort of [00:03:30] freelance and consulting work, or discovered that commercial work really set my soul on fire, wanted the challenge, I wanted to be questioned, and I found it really rewarding to work on those sort.
[00:03:40] Tara: Types of projects because they were often multinational projects ’cause could see the global health [00:03:45] application. Then at the same time over the years, I’ve been able to take on other opportunities. So I’m also a board member for Bio Alberta and the co-founder of the Avita Health Foundation, which is a nonprofit advancing the use of real world [00:04:00] evidence through a next generation registry platform.
[00:04:03] Tara: I would also add that I am a fierce women in. STEM Advocate. We have a Med Year scholarship at the University of Calgary for women in stem, and I’m also a member of the Women’s President’s Organization and the [00:04:15] Healthcare Business Women’s Association as well.
[00:04:17] Ursula: Kara, thank you for sharing. That’s a lot of hats.
[00:04:20] Ursula: I imagine that’s very long hours. We’re gonna get to that a little bit later, but I wanna take a step back and think about the past a little bit, and when you first realized why data [00:04:30] mattered to you, you were curious about it, you wanted to have an application as to cause, so. Was there a moment or experience that made you first realize that this is really what gets you excited and you wanna dive more into to data and what’s happening?
[00:04:43] Tara: Yeah, definitely. I think it was my [00:04:45] time in the Calgary Health region where I hadn’t realized how much data is routinely collected through our health system interactions. Because when you think about it, of course it is. But actually it really is, there’s these really powerful data [00:05:00] sets for inpatient data, outpatient data that have data, drug data.
[00:05:03] Tara: There’s just a lot of information and there’s so much. Insights and research that you can derive from that data that I just thought, this is really interesting because in theory it’s [00:05:15] at our fingertips and the numbers of questions and applications that you could apply to that type of data, it’s endless and it was just really exciting for me to realize.
[00:05:24] Tara: I had no idea with the degrees in health sciences and previous roles in health [00:05:30] sciences, I had never really appreciated as a citizen and as a patient and as a researcher, that all of that data is in fact there and pretty much every health system in the world and the opportunities for using that data to get new insights was really exciting to me.[00:05:45]
[00:05:45] Christine: Can I ask for just a clarification here? What data point, like who is collecting this data? Oh, that’s such a
[00:05:53] Tara: good question. ’cause it’s not simple. So there are multiple data sets and there’s multiple data custodians. [00:06:00] So in theory. You as the patient are the owner of your own health data. So we have custodians, so people who are there to protect and guard your data.
[00:06:10] Tara: Publicly funded health system. So if you were talking about the states, no, your [00:06:15] insurance company owns that and you sign off to it like your bank. But from a universal healthcare perspective, is paid. Utilizing the health system collects that data and under the Health Information Act obviously has the capability to use that data to improve the health system [00:06:30] and improve the delivery of care.
[00:06:31] Tara: So the data is actually diverse. We have our inpatient EMR system, so your chart when you’re in inpatient, at the hospital when you’ve been admitted, but there’s also separate data sets that are there for emergency [00:06:45] department visits, specialist visits, the drug data, the lab data, and then totally separate to that.
[00:06:50] Tara: Is your primary care data. If you really wanna get crazy when you talk about health data, and I like to get crazy is dentist is has health [00:07:00] data, your optometrist has health data, your physio has health data, your chiropractor has health data. We just don’t necessarily house those all under the health system or the government body of.
[00:07:11] Tara: Data custodianship, but there is a huge amount of [00:07:15] data on you as an individual that is captured and housed by all of these different sectors. So one of the challenges, obviously, linking that type of data together because they are housed and managed separately, but there is a tremendous [00:07:30] amount of data from any type of interaction you have around your healthcare.
[00:07:34] Tara: Interesting.
[00:07:35] Ursula: Tara, you and I had chatted about, and I’d like you to share with our listeners exactly what happened, bringing this real to the patients. There was a public story that got [00:07:45] released about data gone wrong or testing gone wrong.
[00:07:48] Tara: You care what happened. For sure. Unfortunately, there’s countless cases, but a couple come to mind here in Alberta where patients unfortunately experienced delayed diagnosis and delayed treatment.
[00:07:59] Tara: And [00:08:00] sort of the thinking behind that is if the data had been more accessible, more linkable, more shared, would that have led to different results? So in some cases. The delayed diagnosis or the delay in treatment because of not getting the diagnosis as [00:08:15] early as possible, it leads to more severe consequences.
[00:08:18] Tara: So cancer is obviously the best example of this, right? Because if you do have a delay in diagnosis, inevitably you’re gonna. Progress in your cancer and then potentially treatment may or may not work. A [00:08:30] good example of this was Jocelyn Laidlaw. She’s a very well-known media person in Alberta, and she had a story where she had to advocate to get a screening, done, some screening and testing done.
[00:08:42] Tara: When they did do it, they found out that she had [00:08:45] stage three colorectal cancer, but she had to advocate, she had to push for that additional screening and testing. She was treated and she’s. Survived and is luckily in remission. There’s other stories as well that Greg Price is another. He had missed or delayed [00:09:00] diagnosis of testicular cancer and unfortunately he did not survive.
[00:09:03] Tara: So these are stories.
[00:09:05] Christine: It’s funny you should mention that, because I’m part of this other initiative and his sister created a short film about his experience. Yeah. And we watched [00:09:15] it together. Wow.
[00:09:16] Tara: And they’re really moving and it shows you it could happen to anybody, especially someone as well known and in the media as Jocelyn Laidlaw and her family’s made a huge donation to the Alberta Cancer Foundation.
[00:09:26] Tara: They’re very involved in the work of the Alberta Cancer Foundation, which is [00:09:30] fantastic to advocate for screening and early detection and treatment. But these situations can and do happen. I think that with the data and the access to data, there’s an opportunity, I think to manage screening diagnosis and [00:09:45] early treatment better through flags, through doing some, you know, predictive analytics.
[00:09:49] Tara: Understanding who’s at risk by, by on the imaging data. Even flagging when someone is high risk and should be screened maybe more frequently. So there’s just [00:10:00] opportunities when it comes to the data and how we’re leveraging it. Linking it between the ability for the specialist to be able to see the primary care doctor’s data and vice versa.
[00:10:09] Tara: If you think about the patient being the owner of that data, why are these barriers there? Because it’s doing a [00:10:15] disservice to the patient to not have their data visible across these different data silos. So there’s a lot of movement in that area.
[00:10:23] Christine: Now Tara, it makes sense when you’re talking and giving the example or cancer.
[00:10:27] Christine: I’m thinking maybe another dimension [00:10:30] would be like in mental health. Oh, absolutely. Where you don’t have those kind of markers, biomarkers, you don’t go for blood tests necessarily to get a diagnosis there. That could be an area where maybe the data is not helping [00:10:45] as much or not. Exist, and we talk a lot about caregivers and the importance of understanding caregivers and of course that would be missing outta the picture altogether.
[00:10:53] Christine: Absolutely,
[00:10:54] Tara: absolutely. Mental health, to me, you’ve nailed it, I think is we’ve got a better understanding I think [00:11:00] between that sort of mind body connection and certainly mental health. Is health, right? It shouldn’t be any less than physical health symptoms. And there’s a strong connection between the two of them.
[00:11:10] Tara: And so for me, I would like to see mental health dealt with dental checkups [00:11:15] twice a year. Go in and see your provider, get a checkup. How are you doing? And if you need more treatment or management, you can get that. But as a routine part of healthcare delivery, we should have that mental health checkup. Of course, that requires resources.
[00:11:29] Tara: There’s [00:11:30] tremendous wait lists in the province when it comes to mental health services. So it’ll, I think if there’s an opportunity to use data to at least flag high risk where more resources are.
[00:11:39] Christine: But when you think about it, even when you’re doing your physical with your gp, there might be an opportunity right [00:11:45] there, a quick questionnaire when you’re seeing the nurse before the gp.
[00:11:48] Tara: Yep. And even then. Why do you even have to see the gp, right? We’ve got our health data portal here in Alberta. It’s where everyone got their immunization records during COVID. Why can’t you know, through utilization of a health data portal [00:12:00] be sent? These types of screening questions like, how are you doing and how are you feeling?
[00:12:04] Tara: And then that could be flagged to your GP because we know there are so many resource constraints from the provider perspective, but we have technology that can really facilitate that more routine collection. [00:12:15] I’m not saying it’s as good as seeing someone face to face. ’cause someone can say, I’m fine. You can tell they’re not fine when you have that face-to-face interaction.
[00:12:22] Tara: But I think it’s such a digital world and especially with youth and adolescents where we know there’s a very high rate of mental health [00:12:30] issues. They’re very good on their digital health apps. I’d be surprised if we couldn’t glean from that particular age group some really good mental health data that could help inform their management and their treatment.
[00:12:40] Ursula: Tara, you’re really describing a lot leading with evidence, which I really [00:12:45] appreciate everything from what’s really important to how to measure it. You talked about data interoperability and that has some concerns there. You’re a female, you’re leading in a highly technical and data-driven space. Is there some other barriers outside of data interoperability [00:13:00] that you’ve encountered and some things that you’ve come across to help you push through those?
[00:13:05] Tara: I think the barriers with health data to a large extent boil down to privacy issues. Right? And it’s very understandable that those are concerns for the general [00:13:15] public. I think a lot of work can be done to improve health literacy of why a. Do you want your data to be used and you want diverse data?
[00:13:24] Tara: There’s underserved populations that don’t interact with the health system, and therefore we don’t actually pick up necessarily on all of [00:13:30] their data. So I think really building trust and transparency around how is the health data used? Why do you want it to be used? Why do you want your data to be included?
[00:13:39] Tara: Really feeding back to the public. This is what we found, right? We know oftentimes in research, you know [00:13:45] that feedback loop is missing. So if patients know that their data’s being used, but they have no idea what the results of that are, you’re not building trust and you’re certainly not building transparency.
[00:13:54] Tara: So I think there’s a lot of work that can be done as a health system looking for sustainability and [00:14:00] efficiency to really bring the public into. This is what our health system really looks like, but to make sure that there’s health literacy, that they understand it, that it’s meaningful. I think we do need to engage a lot more with the general public and patients rather than having a lot of these [00:14:15] discussions around data.
[00:14:15] Tara: Just being at the government level, the policy level, even the research level. Uh, I think there’s a lot more we can do to get that. Public engagement and demand, quite frankly that their data is used to improve the health system.
[00:14:29] Ursula: I really [00:14:30] appreciate you mentioning health literacy with regards to data. I’m very interested in when people are asked a question, how they’re interpreting it, and I think that really factors into health literacy.
[00:14:42] Ursula: I’ll give you an unrelated example. I’m [00:14:45] 16, I’m living in Italy and I’m staying with a family that has two girls and a boy, and I’m doing a school exchange with one of the girls. The son one day comes up to me and asks me, have you met my friends? And I said, no, I haven’t met your [00:15:00] friends. And the look on his face that ensued, the sadness, perplexed me.
[00:15:04] Ursula: I didn’t understand what I had said wrong, and he was really sad. And he asked me again, have you met my friends? And I said no. I found out later that evening from the girls what he was [00:15:15] trying to ask me and what he wanted to ask me is, will you come with me right now to meet my friends? And that’s a very different question.
[00:15:22] Ursula: And although that’s not data related, I’m very interested and curious is are we taking the time? Using the resources appropriately [00:15:30] to make sure that what we intend and what we want to understand from patients we’re asking in a way that they’re interpreting. And I think that’s a valuable piece to pause and make sure that we’re using neutral third parties.
[00:15:43] Ursula: People that are not as close to [00:15:45] the data and maybe the subject matter experts to ensure that we’re taking the time to understand it, it makes the data that much more valuable. Otherwise, we might have data that we don’t even understand isn’t as usable or really isn’t as reflective as it could be of the population.[00:16:00]
[00:16:00] Christine: Absolutely. Yes. If there’s one thing everybody should learn from these times is that, yeah, there needs to be that connection, those connecting the dots for people, because otherwise they can go down the rabbit hole of imagining that their data is [00:16:15] gonna be misused in all kinds of ways. We’re definitely living in a world where there’s a lot of conspiracy theories floating around.
[00:16:22] Christine: Right?
[00:16:23] Tara: Yeah. Exactly. I think patient privacy is just always gonna be top of mind, and there’s so many guardrails and there’s so much [00:16:30] protection of that data. But I think we’ve, at least in Canada, we’ve gotten to a point where, you know, by protecting the data so much. It’s actually now disadvantaging patients, like it’s reducing clinical trials coming to Canada because the timelines to get trials started and initiated, [00:16:45] because we have so much processes around health data, it can make it really challenging.
[00:16:49] Tara: So I think part of it’s gonna be finding a bit of a balance in 2025 of what does this look like and what should this look like? Privacy, of course not. If the [00:17:00] risks for not using the data outweigh the risks of using the data. And I think that’s where we are right now. And those sort of case studies exemplify that the risks of not using this data and connecting this data and really optimizing the data, it, [00:17:15] there’s gonna be, unfortunately, cases like this where there’s outcomes, there’s patient outcomes that we wouldn’t wanna see.
[00:17:21] Ursula: I think you hit on such important points, and I, this is why I do love talking data with you, ’cause exactly what you said is something I am a conversation and a presentation I’ll be [00:17:30] talking about next week. It’s building the trust with people as to where is the data going. You’ve, I’ve heard you say many times people are willing to share their data if they know what’s going.
[00:17:38] Ursula: To good uses and how it’s going to be used with transparency as well as closing the loop. I think you’re absolutely [00:17:45] right. If a person does participate in a clinical trial, and there are situations where people say no, what happened and where did those results go? And did they benefit personally, and was there a contribution to the greater goods, so to speak?
[00:17:57] Ursula: What happened to that as well? I think there’s lots of really [00:18:00] interesting things that are happening currently that we continue to look at and. I guess to think lastly of as we look at presently what’s happening with data, I know you’re passionate about quality, and you talked to me a lot about quality.
[00:18:13] Ursula: So what does quality [00:18:15] really mean to you? How would you give a late description of that to a person? When you’re thinking of data-driven insights, as you’re explaining that quality
[00:18:24] Tara: a hundred percent. I think in this. In this space with data-driven insights, using [00:18:30] health data to drive decision making, it boils down to classic science 1 0 1, transparency and reproducibility.
[00:18:38] Tara: If you are completely transparent, this was our data source. This is what we did with it. These are our results. [00:18:45] And somebody else could come along, repeat it, get the exact same result, that’s high quality. Right? So when we’re working with health system data, as I would believe most academic researchers are, you’re really looking at it from that perspective of is this transparent and [00:19:00] reproducible?
[00:19:01] Tara: The methods that I used, even if it’s not great, right? Even if the timelines in the budget did not allow you to do the pure golden method that you would’ve liked to have used, as long as you’re transparent and reproducible. People can interpret those results [00:19:15] appropriately. And that to me is quality. And I think oftentimes, unfortunately, we see a lack of transparency in methods.
[00:19:23] Tara: You don’t know how people came out with that result, especially if you think about the social media context, right? What you’re telling me this is a [00:19:30] thing, how do I know this is a thing? What did you do to get to that answer? So I think that sort of scientific. Process is very critical when it comes to we’re using this data.
[00:19:39] Tara: Real world evidence is based on real world data and real world means essay, right? It’s [00:19:45] messy, it’s not perfect, but it has many advantages over the controlled data. It is the real world. These are diverse populations. They may be populations with comorbidities and concomitant medications, and it’s messy.
[00:19:57] Tara: There’s a lot of confounding you can [00:20:00] control for a lot of that because you’ve got. Such large sample sizes, typically it can still give you a very meaningful result and it can really fill in the gaps of those clinical trials, but the quality issues are there. One of the things we’ve seen the FDA crack down on with a lot of the [00:20:15] US data sets is that they are commercially generated data sets and there is a lack of transparency around, they call it the data provenance, basically.
[00:20:23] Tara: Where did it come from? Canada has a huge advantage. Government data. It’s very transparent where it came [00:20:30] from and how it was collected. So as long as our methods of what we do with that data in order to get those insights and those results is there, we have extremely high quality world-class data here in Canada.
[00:20:42] Tara: That can actually inform healthcare decisions around the [00:20:45] world. There’s many advantages to Canadian data over other jurisdictions because we have high quality data source coming from the government health systems that are routinely capturing this data in a very standardized method. And so as long as the research [00:21:00] methods behind it are sound are, as I say, reproducible and transparent, those in cars can be trusted.
[00:21:07] Christine: Tara, if you don’t mind my asking, so how do you make sure that people. Don’t jump the gun and create or [00:21:15] see causality where there is no causality there. There may be a correlation between two events, but that doesn’t necessarily mean one causes the other. A hundred percent. Again, we’re seeing a lot of that in our environment these days.
[00:21:27] Christine: The truth is like nobody
[00:21:29] Tara: with a [00:21:30] scientific education would do that. Right. And with the health data we’re talking about, you really need to be an epidemiologist or biostatistician, like you really need to be qualified. This data is overwhelming, but when you get to the result, so you’ve published it or you’ve put it out there in the public domain, could some blogger come [00:21:45] by and go, this means that, right?
[00:21:46] Tara: And so that aspect of it is in my mind. It’s the reporting. It’s how you report it. Are you very clear about the limitations? Any types of caveats or considerations. So how we manage [00:22:00] that within our team is we always have clinical co-investigators. We have a study team, so it’s not just us as data scientists going, statistically speaking, we found this result.
[00:22:09] Tara: That’s nice. What does it mean? How do you interpret it? You need to have that [00:22:15] interpretation. And to be honest with you, not only coming from clinical advisors, which is very much the norm. But from your perspective, if we’re seeing certain results showing up, is it meaningful? Is it not meaningful from that kind of clinical and patient context?
[00:22:28] Tara: But I think that’s really [00:22:30] important. That is very clearly communicated because even to your point, just because something statistically significant doesn’t mean it’s clinically or even from a patient perspective, significant either way for good or for bad. So you do need to have that interpretation very clear.[00:22:45]
[00:22:45] Ursula: So I can hear the excitement in your voice and despite there being challenges with data and trouble there, world-class Canadian data, that’s an exciting situation to be in. As we think about the next era of patient engagement evidence. What are you really excited [00:23:00] about? What do you see coming down the pipeline?
[00:23:02] Tara: There’s no doubt it’s gonna be a lot around the AI opportunity, right? We have a huge amount of data to crunch, as it were. And we also have a huge amount of unstructured data, which means it’s free text, large language models, natural language [00:23:15] processing, even things like imaging data, right? Early cancer screening and diagnosis because you’re having ai.
[00:23:21] Tara: Potentially pick up on minuscule changes that for a human would be very hard to see, and predictive analytics, right? Being able to bring 7,000 variables together and go, [00:23:30] Hey, we are predicting something with some level of accuracy. So I think the AI opportunity is huge. I think that’s a whole other kettle of fish in terms of responsibility and trust and transparency.
[00:23:41] Tara: But I do think it’s a really big all. For us to get better [00:23:45] at predicting health outcomes and being able to change the course of those health outcomes through the different variables people have in their lives, right? The modifiable risk factors that we all have. So I think there’s a huge opportunity for getting into that data and really [00:24:00] delivering better, more personalized insights for individuals so they really understand for them as an individual what would be meaningful to change in their life or to add to their life to get better health outcomes for themselves.
[00:24:13] Tara: Opportunity is there.
[00:24:14] Ursula: So [00:24:15] I heard you say earlier, we need patients to own their own data, and that’s really important. We’re also in a situation with innovation coming down the pipeline, it’s difficult for decision makers to track long term what’s happening. What are some opportunities in that [00:24:30] realm?
[00:24:30] Tara: Yeah, definitely.
[00:24:31] Tara: But there’s some of the reasons why I was so excited to co-found the Avita Health Foundation because really what we do need is that long-term prospective data, but also capturing outcomes that aren’t routinely collected by the health system, but are really [00:24:45] meaningful. The quality of life outcomes, but even things like employment status, presenteeism, absenteeism, leaving education, a lot of the caregiver burden that we started talking about that could ideally be captured.
[00:24:56] Tara: So really what we need is more of a registry platform to be [00:25:00] able to standardize that data collection. Because if we had everyone with their own little personal health. They’d be collecting the same data differently. So having a nationalized standardized infrastructure to collect key outcome data across patient [00:25:15] populations where really very cost effectively, you could collect this data for 10, 20, 30, even a lifetime of years, and giving the access to the individual.
[00:25:25] Tara: Here’s your data, and what I think is most exciting and interesting is here’s [00:25:30] data of people like you, right? So if you’ve got a particular condition, how am I doing versus the average patient population, that is also my sex, my age, my ethnicity. You can really start doing some insights that can help.
[00:25:44] Tara: [00:25:45] Empower people to make better decisions for their health and even advocate for their health because they’ll understand, how am I doing relative to somebody else that sort of looks like me, relative to the aggregate group of patients
[00:25:56] Christine: out there. On the other side, I could imagine [00:26:00] that it could help our healthcare public, publicly funded healthcare system to make some potentially wiser decisions.
[00:26:08] Christine: I can give you an example. I mentioned to you that I work a lot in the kidney health space, and we often talk [00:26:15] about a lot of funding is put towards hemodialysis and not as much funding towards transplant. If you were to really capture all that data that you just mentioned, I am convinced. That it would seal the deal [00:26:30] with governments to help them understand that they really do need to put more funding behind the transplant versus the dialysis.
[00:26:37] Christine: It’s interesting because I had a conversation
[00:26:39] Tara: with a former health minister and we were talking about some of this data and just the fact that the, the [00:26:45] budgets are siloed. We think the data siloed, so are the budgets. You got a hospital budget, you got a drug budget, you got different budgets, and my challenge to him was, when you look at some of these.
[00:26:54] Tara: Data points we’re talking about, especially around things like employment, that’s the tax [00:27:00] space that goes into treasury. Treasury then fills down to all of these siloed budgets. So actually it does matter and it should be of interest to the government because it’s actually telling you how from a treasury perspective and your tax [00:27:15] base.
[00:27:15] Tara: How much could you move that needle if you could put those people back to work or have less time off work and things like that. So it’s quite meaningful to actually look at that. I think just historically it’s been very hard to quantify, but I think it’s not to say it can’t be done, [00:27:30] it’s patient generated.
[00:27:31] Tara: So there’s effort, there’s work to set up that infrastructure and that capability. But so that, that’s a challenge that I’m looking forward to taking on because I think there’s gonna be a lot of inequity in how dollars are spent. Capturing [00:27:45] that type of data to really inform those decisions. Now you got me totally jazzed up about data.
[00:27:50] Christine: Come on, it
[00:27:53] Ursula: happened. I’m seeing the light, Christine. I knew it would happen. I am telling you it’s [00:28:00] contagious conversation. I can see the excitement. Data, not excitement to data excitement. Tara, you have another convert here. So she’s seen the light on data, wisdom, data, excitement. What you’re describing, Tara, with the Avita Health Foundation is [00:28:15] verily fascinating.
[00:28:15] Ursula: It’s really a game changer. I, there’s not much that comes to my mind, certainly that I’ve ever seen or heard about, where a not-for-profit has a data registry for patients where patients and physicians and different partners can co-create what’s [00:28:30] important to measure. Track it long term. I heard you say.
[00:28:33] Ursula: As well report back to systems and decision makers as to what’s happening. That’s quite incredible and I can tell there’s more conversations we’re gonna be having on that. So I really look forward to that being around the corner [00:28:45] with the future. On a fun note, I know you love traveling, Tara. I’m a little curious, what’s the next trip, the Oven Q that you’re really excited about?
[00:28:53] Tara: I’ve got two coming up. One two. I know it’s contentious ’cause it’s obviously New York City. I have never been [00:29:00] there, so I’m very excited to see the Apple. The Blue Jays obviously just devastated New York. It’ll be
[00:29:05] Christine: shy. Time to go in there. As a Canadian I’ll Don’t wear your Blue Jays paraphernalia. I was gonna say, I’ll keep my blue jay spear pen vanilla at all.[00:29:15]
[00:29:15] Tara: Then, but I’m super excited and I get to see the Canadian Trade Commissioner in New York, so that’ll be a lot of fun to visit their office and learn more about Canada and New York. And then I’m going to the UK for Life Sciences Week, so I’ll be part of a delegation in London. It’s. [00:29:30] The Canada House, 100 year anniversary in Trafalgar Square.
[00:29:33] Tara: So there’ll be a big party to go to, which is exciting. And then I’ll be going over to Northern Ireland and Dublin for some meetings. And I have Irish ancestry, so I’m sure it’ll just be, my skin will be so happy under a [00:29:45] dark cloud and with all kinds of moisture will be great. And some Guinness.
[00:29:50] Ursula: That’s very exciting.
[00:29:52] Ursula: Best wishes for the future travels. That sounds very exciting. I know you’ll represent well with your Canadian flag, little, a maple [00:30:00] leaf that you give out to showcase the Canadian work. I wanna say a very big thank you for joining us today, sharing your excitement with data and some very interesting and prerogative ideas.
[00:30:09] Ursula: And Christine, what do you think? I feel your excitement has grown. What are you now gonna say about [00:30:15] data?
[00:30:15] Christine: I hope I have the opportunity to have a side conversation with Tara someplace because I’ve got a whole lot more questions for her.
[00:30:24] Ursula: Wonderful. That’s fantastic. To be continued on the data front. Look forward to hearing [00:30:30] more and making a difference in the ecosystem together.
[00:30:32] Ursula: Thank you, Tara. Thank you so much. Thanks for having me. Thanks. Bye.
[00:30:41] Ursula: Thanks for tuning in to Amplify a podcast powered [00:30:45] by Patient Voice partners. If today’s story moved, you share it, leave a review and help us amplify more voices.
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[00:31:24] Ursula: Until next time, stay connected. Your voice [00:31:30] matters.