Pharma Market Access Insights - from Mtech Access

Engage NHS healthcare decision-makers with RWD

August 12, 2024 Mtech Access - Powered by Petauri Season 7 Episode 18

Discover how data visualisation dashboards can aid field teams in market access discussions with customers.

Healthcare leaders look to real-world data (RWD) to inform decisions. Field teams presenting decision-makers with RWD within a well-designed, easy-to-use visualisation can build a case for change, while positioning themselves as a trusted partner. Watch this 20-minute discussion between Iain Shield (Associate Director – Market Access) and Ben Spurr (Head of Partnerships) to discover how Connected Insights data visualisation dashboards can help your teams have strategic conversations with healthcare decision-makers. Iain also explains typical use cases for the dashboards for field teams, why data dashboards are useful for the NHS, and what sets Connected Insights dashboards apart.

Learn more about this showcase at: https://mtechaccess.co.uk/engage-nhs-with-rwd/

Learn more about real-world data visualisation at: https://mtechaccess.co.uk/digital-capabilities/real-world-data-market-access/

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- [Narrator] Welcome to this Mtech Access webinar.- Delighted to welcome you all here today. My name's Ben Spurr. I'm Head of Partnerships here at Mtech Access, and yeah, as I say, delighted to kind of be welcoming you to the webinar. I'll be focusing on engagement with NHS healthcare decision makers through real world evidence, and really, today, going to be joined by a great colleague in Iain, who will introduce himself in a moment, but really wanting to explore today, how audience expectations are really kind of driving that demand for kind of visualised data, and ultimately how we're starting to support our client base with really driving their impactful interactions with their own customers.- Perfect. Thank you, Ben. Thank you very much and good afternoon, everybody. My name's Iain Shield. I head up data dashboard activities here at Mtech Access, and looking forward to the next 20 minutes, maybe you're on your lunch, maybe I'm between you and lunch, just 20 minutes. Talk about real world data and the opportunities there. So what is the opportunity in this context with real world data? There's an awful lot of data in the NHS. You see it published on websites, you see it in the news. Those data can help inform your customers of how their health economy is performing, potentially spotting outliers, identifying trends, all sorts of use cases. We use those data to build visual, easy-to-use tools, dashboards that field teams can use to have conversations with your customers. That, of course, helps build a case for change and enables you to develop your partnership with your customers. If we think about it in just a little bit more context, you've probably heard of models as well as data dashboards. If a model illustrates the effect of a change, these types of data dashboards communicate the need for a change, things like how are we performing, where's the spend, what direction are we headed in, do we need to change, what do we need to change, helps you understand an area before going in. Ben, back to you. Does that help contextualise?- Yeah, thanks. So a good picture of the extent of the challenge perhaps, kind of let's put some kind of meat in the bones. What does that kind of start to ultimately look like? What types of tools do we have at our disposal?- Sure. Okay, thank you. Well, that segues nicely into this slide. So the dashboards that we create are visually appealing. They're simple to use, they're quick to navigate. I should say, we have built a platform that enables us to build these types of tools. You can see on the right hand side here, an iPad, on the left, a laptop, it could be a website. We've really got the tech nailed on this type of approach, and we can deploy them in all sorts of ways. If you think about it, though, from a sort of visuals point of view, and we'll mention this a lot today in the 20 minutes, we're able to make quicker decisions, interpret data better in visuals. If you think about a large number of Excel files or CSV files as a alternative, perhaps even data tables as a simple visual, guides you, it helps you, it draws your eye, it captures your attention. New perspectives come to light when data are reviewed in this way, and I think something that certainly, my attention has been drawn to is it drives an understanding of the customer situation, helps develop that common problem solving approach.- Yeah, agree, I think that, ultimately, customers are expecting organisations to bring that kind of value add and that information and insight about their own organisations. You mentioned there about the kind of the quickness and efficiency of delivering that message. And I think, I know we were discussing this the other day, kind of how important that is, kind of the average, I suppose, window for face-time opportunity is only six minutes in a face-to-face environment, and perhaps think recent kind of Veeva research shows that around about only 62% of accessible HCPs engage with three organisations or fewer. It really shows we have to be able to support our clients with jumping on those kind of moments that matter and making them as impactful as possible.- Yeah, absolutely, couldn't agree more, And I feel like it's worth talking about this just in a tiny bit more detail and bubbling up a few more stats to the surface. So this slide here, research by Robert Horn at Stanford University. A very similar stats to this across the internet if you're looking, but to summarise, visuals enable better understanding. Let's look at this first stat. 64% of participants made an immediate decision following a presentation that used an overview map, one of these little sort of tree diagrams you can see by the icon. 24% of meetings, sorry, 24% shorter meetings as a result of using visual language. And of course, these are believed to increase meeting effectiveness and efficiency. And this last start here, 21% increase in reaching consensus for groups using visual language compared to groups that didn't use visual language. Visuals enable better understanding. Visuals make meetings more effective and could shorten meeting time. It's more engaging and we are visual creatures, and let's make data that can be quite dry as interesting as possible using sort of visual techniques. An example of that is using health boundaries as an example here for a national view of variation. So you can see we've got different health boundaries displayed here. Our eyes are drawn to high-contrast areas, in each map and visual, you can quickly pick out sort of darkest areas. It's heat maps like this that can aid quick understanding of underlying data. And from a technical point of view, we can use or develop boundaries to aid understanding of the data in this way using heat maps or choropleth maps as as they're known. Does that help, Ben, add a bit more flesh to the bones around-- Yeah.- Data visuals?- Absolutely. Thanks, Iain. And I think, yeah, you've mentioned that it's evident already how we've kind of been talking about it, it's not just a cookie cutter approach of kind of developing a defined kind of deliverable or leave piece or interactive visual aid, et cetera. You kind of start to tell us a little bit more about that kind of flexibility of the tool and kind of how it is flexible to those kind of various and almost infinite use cases.- Yeah, yeah, sure. So to your point, I think how these types of tools can be used is difficult to lock down'cause they could be used in all sorts of ways, but if I can categorise, say, three ways that these types of tools are used, perhaps primarily the context is being used by field teams in a promotional context, often interleaved with other materials, perhaps value messaging where appropriate, perhaps with specific goals, collaboration opportunities, or promoting a specific initiative for mutual benefit. That's generally how these things are used, but there are, of course, other use cases, and a very obvious one is pre-core planning, understanding an area before you go in in a sort of business intelligence-type capacity, but also in non-promotional ways, by MSLs, for instance, medical science liaison roles. Those are the sort of primary use cases, really, if we can collectively bucket them in that way, but I don't want to kind of stop it there or pigeonhole it in that way. Think about your use case, let's work together, let's explore how this might work for your product, your team, and your therapy area. You're likely to have ideas about how these dashboards can be used. Let's explore that, let's explore that together with the experts in constructing these tools, testing them with our NHS associates, and deploying them in the way that suits you, but as far as your specific use case, let's talk about how that might work together and how we can use real world data to give your market access teams an advantage. So if we just think about that in just a bit more detail, like how could they be used by your teams, what could your team use the dashboard for, think about what value the data has for your customers, how it would fit with the narrative of your product. Would data support useful benchmarking as an example? Can it be used to explore which areas are outliers? Is longitudinal data following national policy or some other national driver? Can that data be used to support the value of your product? There are so many options here. It's trying to tease out a thread. Where might it work? How could we use it to benefit both your customers and the conversations that you're going to have? But what I would say is hold a mirror up sensitively, where are the opportunities for meaningful collaboration and where does the data substantiate a case for change?- A good word of a good word of caution there, Iain. Yeah, we've already alluded to this kind of, they're perhaps not a traditional, standard kind of deliverable or tool in the armoury. How are these different kind of, and how are they brought together?- Sure, okay, so how are they different? It's a fair question, and they are different, and perhaps let's talk about these types of tools that aren't the type types of tools that we develop. So we see around the place databases, they generate tables of data. We see tools that enable filtering and cutting of those data in certain ways. These are tools that enable you or your customers to search for data in response to, perhaps, a specific question they have. If you think about searching for a movie on Netflix or Prime, you spend a lot of time looking, you have to be online. In contrast to that, our dashboards are about a narrative. What we do is develop a storyboard. We develop that with you. That's to agree content and flow. The storyboard follows the narrative you want to communicate. We source suitable data for that that follows that narrative. The dashboard enables you to pick an area you're presenting within, and then it's populated with the relevant data. Your teams can learn the contents of the dashboard, that narrative and present that useful data to this predetermined story. The tools work offline and they feel like a presentation, not like a database. Does that help contextualise?- Yeah, yeah. I feel it does. I suppose putting my client hat on, again, having worked in partnership and delivered multiple projects, deliverables with clients, inevitably, we do work in an environment where there are complIaince or regulatory kind of challenges or internal processes that we inevitably have to navigate that can sometimes be a head scratcher, but it is something that we've been kind of exposed to where we've kind of delivered these, maybe kind of an overview of even just, I suppose the council and advice around some of the inevitable challenges or things that we need or critical success factors to overcome.- Sure, and it's fair. Working with data can bring its challenges and we're commonly exposed to these challenges and found suitable solutions, of course, and through experience in developing these types of tools, these are the common ones. So disparate data sets is a key one. You might want to review certain metrics together. They're reported by different groups in different ways. Data may be released at different cadences and have different latencies, and we're familiar with ways in which we can mitigate for this, different nations, in the UK, as an example, different nations may report different years or not have the data available, maybe published differently, organised differently. It can be very disparate between nations. Data can be reported at different levels, even with one nation if you're familiar within the NHS, of course, with practices, PCNs, sub-ICBs, ICBs, and so on and so forth. It can be presented quite differently. And this final point here, will the dashboard land well in conversations with the NHS? How do we mitigate? We have mitigated for each of these things, but let me just focus on a few of them. So this last one here, will the dashboard land well in conversations in the NHS? Well, testing the direction of the project, testing perhaps at a storyboard stage is a really useful thing to do, so we have an NHS Associate network and we could, for instance, and we do, test storyboards with our Associate network to ensure they will resonate, feedback from these types of sessions, incredibly valuable and it will ensure suitable data are used. Is the order right? Are the data points right? How might we use this feedback to change and evolve? How might the data change area by area? How do we use this feedback? So the feedback can potentially be incorporated into the tools or into the thinking as we develop, but feedback, if it isn't necessarily all of it could be used directly, it could also be used to prepare teams for likely questions. So the process of engaging with the NHS Associates in this project process, it can be really valuable on many levels. I just want to return to consolidating disparate data. Feedback on this type of approach is very, very positive. Different levels of data can be aggregated, just as an example, to display data in a more homogenous view. Data presented online as Excel or tables or CSV or PowerBI, we can pull all of those resources together and present it in a consistent view, and being able to do this makes it so much easier, makes it possible rather than not possible to review different data together or alongside each other. I feel like it's also probably worth mentioning how we use the relationships in the data to keep views relevant. So I know this is may maybe quite small on people's screens and the particular metrics are less important, but on the left hand side here, we have a national view, in this case example prevalence of disease X, I think we're looking at an ICB as being selected. You can see it's been chosen in a select list here. So this one's been highlighted, and we're looking at longitudinal data trend view as well as that metrics so we can see where it's headed. And underneath here, there's a sort of tabbed view where we're looking at the sort of tree structure of data from most granular on the right to most aggregated on the left. So practise PCN, sub-ICB, and ICB in this particular example. And here, if you like, the main flow is being set at an ICB level, but if I want to drill down further into the data, then I can pick a tab, that is like a overlay over the main flow, and you can see the detail in this particular case, PCNs are being displayed but filtered by the area that we've selected in the parent page. And I know this is kind of getting a bit technical, but there's a very good way of navigating between levels of data. You might be having different conversations with different types of stakeholders, and different levels of data may be more appropriate for different conversations you're having. This flexibility allows you to navigate around those data in the way that you might need so you can be flexible around the conversations that you're having.- Thanks, Iain.- So-- You've talked a lot clearly around different sets of data, and again, playing with the client hat on here, kind of where on Earth are we able to aggregate and to get all that kind of data and information from? I think kind of that sourcing is often a conundrum perhaps.- Sure, no problem at all. And the answer is, I suppose, very flexibly in all sorts of ways. So there's a lot of publicly available data and we've already mentioned that, so that is one clear source and it's available in all sorts of ways, and as I've been describing, we can consolidate that. Our clients may well have data, clients that we worked with in the past have real world evidence teams, maybe we can collaborate with those and actually receive data for these tools. It might be that we have a sort of collaborative hybrid approach. We may be able to source publicly available data. It may be that some is supplied. It might be that we don't have data yet, but in these contexts, we have relationships with third parties, data providers, and they have unique ability, really, to query data that is kind of behind the gate, and we can work with a third party, work out all the intricacies around access to those data and then we can receive that from the third party and wire it into a data dashboard like this and then provide it in that way. So I think there is no one size fits all, depends what data, what therapy area, what we're trying to achieve, accessibility of those data, do we need to go to an external to get behind sort of gated access to very granular data that can be aggregated to an appropriate level to include in a dashboard like this, so I suppose all of the above, Ben, is how we might approach that. Time's never on our side. I'm going to progress to what I think is the summary. Yeah, so let me just take a little bit of a step back. 20 minutes, it was intentional to keep it this short so that we don't bite in too much of your day and it's really just scraping the surface around this concept, this idea of using real world data. So my summary would be real world data, it presents a great opportunity to engage with NHS customers. Well developed dashboards resonate with NHS stakeholders. We develop these dashboards for field teams to leverage those data to facilitate conversations with customers. And the feedback is fantastic. So I would say speak to us, speak to us about your product, your therapy area, and how we may be able to leverage real world data to develop a solution for you. These are working, they're out there, feedback is fantastic. Let's make a start. If you have a seed of an idea, you want to explore it more, come and talk to us. Back to you, Ben.- Thanks, Iain, that's been a really kind of good overview there. So yeah, kind of reiterating kind of Iain's open invitation there, if this has seeded an idea, an approach, obviously, unfortunately we have perhaps run out of time for taking kind of live questions, whether it's even just further questions or seeding an idea that may be worth just exploring and scratching the surface of, please don't hesitate to contact us. I know on perhaps on the next slide, just a level of, I know you're already perhaps engaging with us, but any kind of contact details, please do invite you to complete the survey, and again, any questions or queries, if you wish to kind of place them there, we'll of course be able to pick them up, and I suppose finally, thank you very much for joining us today. Thanks for your time.- Cheers, Ben. Thank you all.