Analytics for the Public Sector with Tableau and InterWorks

Transcript
So good morning. Thank you so much everybody for joining us this morning for the webinar, which is Analytics for the Public Sector with Tableau and InterWorks and a special guest speaker. So just before we get started, we've got a lot to go through, hence why we're starting bang on eleven o'clock. Just a little bit of housekeeping that I wanted to run through with you. So today's webinar is being recorded. So we've got a number of registrants who I believe will be joining as we go through. If you've missed anything or if there are additional people that you would like to share this with, we are sending out a recording via email for everybody who has registered for today's session. So just so to make you aware also, the webinar, you will be remaining on mute for the entire duration. If you do have a question and we have time at the end of the session for a Q&A, you can either pop those questions in the chat panel or there is a Q&A facility also where we will be answering questions live as we go. What we also wanted to share with you is we've got a number of other events coming up that focus purely on analytics within the NHS and public sector. So do head over to InterWorks.com/events. New events are constantly being put in the diary and we are happy to share them with you. So to introduce today's session, we are delighted to be joined by Victoria Cornelius, who is the Senior Lead for Analytics Engagement with NHS England. Victoria is going to be walking us through how they formed a public and private sector matrix team to take their population health dashboards to the next level and the positive outcomes that this has led to for them. We've also got Jonathan Hawkins on the call, who is the Tableau Public Sector Sales Engineer. Jonathan is very kindly joining us to share the work that Tableau has been doing in support of the analytics for the public sector, including embedded analytics. And finally, we have our own Rowan Bradnam, who is the Public Sector Lead here at InterWorks. Rowan's going to be showcasing some of the possible work that can be done in the Curator solution that InterWorks has designed and he's going to be demonstrating what that would look like with some very familiar data to all of you. That's the CQC data as well. Is that showing okay? That's wonderful, hopefully you can see that now. Great, so yeah let me just do a little intro first of our Care Quality Analytics. It's going to be in PowerPoint for just a few seconds and then I'll be jumping across to the actual demo itself. So this is our platform that we've set up called Care Quality Analytics. And it's based on CQC data, which is the Care Quality Commission. And it's just a little showcase of what Tableau can do with this data and the insight that can be brought out when we bring this together. So let's have a look at that journey. You've already met me at the beginning. So I'll skip through that. We've only got ten minutes, I'm going to try to be as quick as I can. So the Care Quality Commission, they're an organization that regulates health and social care in England. They've got their own websites and you can find out lots of information. A lot of people are regulated by the CQC. And I imagine a lot of the audience know a lot about that anyway. But just for those who don't, think like Ofsted for schools, it's the same sort of thing. It's a regulator. They regulate all sorts of services. This demo covers all of these different services. We'll probably hone in on care homes a little bit more than anything else but really the product looks at all of it. So within this you might be interested as someone who's being rated or reviewed to know how you're doing because if I was going to send a loved one to a care home, for example, or if I was interested in a particular dentist or something, I'd want to know the quality of that service. So that's one of the values that this regulatory body CQC adds. However, when we go into their websites, you're really looking at things one at a time. So this, for example, is the dental practice and you can see some information, but it's really one at a time and there's no real way to compare or contrast or benchmark or any of that sort of thing. The data is all there, it's available via an API, but there's no real tool to really look at this and you'd take a long time and you'd have to remember a lot of stuff and it's just not a good way to consume that data or get into that analytics. They do go into detailed reports. But again, that's one at a time. So how do I know how others are doing? Where do I feel comfortable in my journey, my research to send loved ones? How are the other providers in my area doing? How's my brand doing in the market and so on. And what we've tried to do is make this particular product as flexible as possible. And you'll see that as we go through from all levels of management from care home, individual care home managers, for example, all the way right up to national and regional supervisors and different markets and brand leaders and so on. Just to talk a little bit about what this is built on, the data itself is available via an API from the CQC themselves directly and we've been using AWS on top of that using MongoDB to call in the API and store that data. And then we've built it with Tableau, as you might imagine, we're a Salesforce company. And then we've brought that final step through into Curator, which is an InterWorks product, which is the portal that we'll look at. So let's jump in now and have a look at that demo and find the right screen. This is the one. So when we bring that up, we get a login that the data is behind. So I've got that in here. So we log in and it's a single pass-through. So once you've logged in, you don't have to re-log into Tableau or anything like that. We've got a home page here which we can look at to decide which part of our journey we want to go into and we can house lots of different things on this which is still a work in progress. We can have YouTube videos, tutorials, PDFs, other tools and analytics software but obviously we prefer Tableau because we find that they are the best with what we do. So let's jump into our first dashboard over here and you'll see a little tutorial pops up. I'm not going to take too much time to let you read through that, but it just gives you an idea of what's going on and how to understand the data and you can pull this out as you need for your own particular example. So let's close that and have a look at our first dashboard. I'm zoomed in quite far actually, I don't know why that is, let's go back out a little bit and maybe go in a little bit more here for this particular dashboard. So what we're looking at here is the number of beds within a particular region. So let's actually change that to number of locations, which is more specific to not just care homes, but to other sorts of data. And there's a whole lot of things we can do and change. But before I go in and toggle and mess around a bit, let's just have a look at what we're actually seeing. So at the top here, we're seeing some KPIs of which particular location, how many locations across the country are outstanding, good, requires improvement and inadequate. Above that, we have lots of options to change parameters around and do some filtering down to exactly what we want to look at. And then we get into the data itself. We're looking here at a bar chart, which shows us the national average going down here and then how each region is doing in terms of who's got more and less locations. And we've got a map here, which shows a little bit the size of the different colors which correspond up here. And we've got a timeline which shows us, you can see that a lot of the reviews slowed down during the lockdown, as you might imagine. It just wasn't safe to do that. And then they've picked up again over time and we can see how that's changed. So let's go and play around and let's see what we might look and find. So first of all, let's decide that maybe we're interested in just the inadequate ratings, those that need improvement. And we can see here who's got the most inadequate ratings across here and how that compares and contrasts to their overall ratings. We might not be interested in regions, maybe we're interested in going to a different granularity, maybe we're interested in CCGs for example. So we can see the number of CCGs. So we can see here there's some places that have quite a lot of inadequate ratings within them. Get a picture across the map. We might not want to look nationally, so let's take this down to just London for example and see, but we could take it down to a single brand or a particular local authority and we'll see within London where our particular challenge issues are. Maybe we want to zoom out a bit and look at those that require improvement rather than just inadequate and we can see how that's doing. We might also be interested in the percentage of locations instead. So instead of the raw number which is skewed by the different values, we can go down to the percentage and we can see here which of them have the highest percentage which require improvement or the higher percentage which are inadequate, so we can look at the highest percentage which are outstanding for example. So there's a lot we can do here. We can also change this for example to the average rating that these homes have, which is a metric that we need to explain a bit more but don't have the time here, or again, go back to the number of beds that we can see which are outstanding and who's providing more of those and where to go for that sort of thing. So this is really quite quick, sorry that we don't have more time to go into, but let's look at our next dashboard. So within this dashboard, as you can see, we could change the granularity of the particular places that we wanted to look at for the bar charts and for our map and so on. But if we look at our Locations Analysis, which is a separate dashboard, we can have a look at a more granular single location. It's going to look a little overwhelming to start off with, because we're looking at the whole nation. We actually look at the whole nation and where the outstanding homes are. We could look at this for all the locations. Again, it doesn't provide too much value just yet, because the map itself is pretty busy. We'd have to filter down in a moment. But again, we get those KPIs and we get an idea of how the ratings go and we can see here that actually these requires improvements have taken up a bigger and bigger chunk of the data. We can see these particular domains where things are stronger and weaker tend to be marked up and marked down. But let's go in and see some KPIs on the side as well. Let's go in and look at, for example, a particular brand. We work at InterWorks, one of our clients is Barchester Healthcare. So let's go and have a look at them and we can zoom in and see how they're doing in their overall picture. And we have 216 locations, a lot of them good, a few outstanding, no inadequate, which is quite good for them. Although the data, I do apologize, the data is a little bit old, between Christmas and my leave and the team and so on, we just haven't quite done the refresh, but the overall product in the end will have an automated refresh anyway. But we can zoom in and look at those that require improvement. We can see here how their reviews are doing. Their percentage reviews have gone up quite a lot, but we saw that that was a bit of a national trend. So maybe not too much to worry about with their total reviews. But they're a growing brand. And so that's quite normal. And you'd probably see that as well for good, you'd see those numbers going up just because the numbers are going up, although they have dipped a bit in the last year. So that's maybe something for them to look at and think about and we can see their particular domains where they're weak and where they're strong as well. If we go back to requires improvement, and if we maybe zone in on London again, because we were looking at that earlier, we can see maybe a London manager would be interested to see which particular homes he needs to work on. And actually they're not doing too badly in London, it's just 116 good and one requires improvement. So what we can do is we can go in and we can have a look at this particular home, see how their domains, their ratings by domains are doing, which we can see here, but we can actually go in and we can jump across to our single location dashboard and have a deep dive. So we've started right on the outside and then we've gone in and as we've honed in on our particular place of interest. Let's zoom out here a little bit, a bit more to see on this one. And what you can see here again is some KPI information at the top, how they've been doing over time. And then really interestingly, we can see what their current rating is in the domains. Behind that, we can also see the historic ratings and the ones before. We can see some key information about the particular organization and we can also see here their report, housed right here. We don't have to open a new tab in our browser or anything, although we can if I click here, which I won't do just yet. It's going to take me to a new tab in my browser and show me the particular, in fact, let me just do it quickly, show me the overview for this particular care home. In an instance, I can see that and then I can jump back. Or I can go in and have a look at the particular report in here, dive into exactly why is it, because I think that's a really useful point for the end of our journey, is to dive in to say, what exactly made this place require improvement? Where is it that it needs to get better? What were the comments and so on? So it's a really natural place to end. We can also go back so we can click here and say, oh well they used to be good back in 2017. So let's look at what was going on there, what's happened, what's changed and so on within that. And yeah, so that's really helpful. And then the last, oh, you can change this as well, you can go in. I won't go into this in too much detail, just given the time. We can go and have a look at a map and do a whole bunch of different things to look and find a different one if we need that support. Or we can also just click on here and find by searching and find a particular care home and look at their reports. Time doesn't help us today. So we'll just have to move on. The last dashboard just to look at very, very quickly is a comparison dashboard. So you can come in and filter down for exactly what you're wanting and pick out as many locations as you want, but we recommend up to about ten and then you can just see how they're doing in their ratings and across their domains and compare them to each other. You can save these as custom views as well within Tableau. Tableau provides the ability to do that, which is super helpful. And then you could just go in and check, every month, you and your competitors or you and the rest of your region, how are you doing and see what's changed and not changed and automatically refresh for that. So I think I have gone a tiny bit over my ten minutes, I do apologize, but yeah, I'm going to throw it back to you, Vicky. Wonderful, thank you so much Rowan. I'm really hoping Victoria you've been able to rejoin us and hopefully we can pass that back to you. Hi, I'm back on. Every time I try to do something it kicks me off. So I don't know where I got to but I'll jump straight into the work stream that led us to work with InterWorks and Tableau, is that okay? That's wonderful, thank you so much. Brilliant, no thank you and apologies for that. NHS and Zoom do not seem to like each other sometimes. So no, like I said, I don't know where we got to. I'll skip my brief intro and hopefully you heard that and we'll jump straight into Population and Person Insights, which is the program of work that led us to work more closely with InterWorks and Tableau. So hopefully you should see on my screen now, this is the workspace rather than my PowerPoint, thought I'd show you a little bit about the workspace which everybody can get access to, and I'll pop the link in the chat after I've stopped speaking. There's four main areas of this work stream, so data, dashboards, insights and knowledge, and I just wanted to give a brief intro into the data set. I think it's really important to get our heads around the data set that we had available and actually that the InterWorks colleagues and Tableau colleagues had to get their heads around really quickly to be able to help us with some of the dashboarding tools. So this data set is a person-level data set for everybody registered to a GP practice in England, so you're talking over sixty million rows of data. We've got really rich sociodemographic data in there, so ethnicity, age, gender, and really importantly the Index of Multiple Deprivation, geographic data, and also activity data in there, so outpatient attendance, bed days, etc. But when you're looking at a population health management agenda, looking with such a large cross-sectional but also longitudinal data set, it can become really daunting. So we decided nationally to adopt a national segmentation model. There's lots out there and it's basically categorizing your population into groups of similar healthcare need. We went for, after much consultation, we went for the Bridges to Health model and we work with a company called Outcomes Based Healthcare. But essentially that results in eight uber segments if you like, six of which are listed here, the other two are transient segments that you can pop in and out of, so maternity and the acutely ill. But essentially it assumes we all start healthy and well and then the other segments there you can see long-term condition disability, but also those end phases of life and segments with incurable cancer, organ failure and frailty and dementia, and each of those are underpinned by a list of over fifty sub-segments or conditions. Not all of them are conditions, hence why we like to refer to them as sub-segments, and you can see things in there like asthma, cystic fibrosis, depression, autism, etc. So that's the really complex data set, like I say not just cross-sectional but longitudinal that we had to play with, and before the relationship started with InterWorks and Tableau we did surface that as information in a dashboard. And some of the views you can see here and I'll come back to that later because that's the journey that we've been on with InterWorks and Tableau that I'd like to just bring to the floor a little bit more today. The other work streams within the program are the Insights work stream that I referred to, and this is where we work with program teams across health and care to surface some novel insights. I'm just picking out a couple here, so with the multiple long-term condition, looking at the development of multi-morbidities, gateway conditions, but also the impact of lifestyle intervention programs such as the diabetes prevention program on the development of those multi-morbidities. It's really insightful pieces. We've also got something in there called HealthSpan. I'll just click on that now hopefully it'll take us to that, and this is around not looking at just how long we're living for, but how long we're living in that healthy and well segment. And really insightful to me was we always live on a rhetoric that women live longer, but actually when you look at this insight, Insight One here around the health span in England for females was only 48.8 years, but actually for males it's 51.8 years. It's really some insightful pieces here and actionable insights that we're bringing to the surface through this data set and information. The last bit is the Knowledge piece, the how-to guides, and lots of useful resource links, and taking our user community on a journey to the next part of the population health management agenda, which is risk stratification, so how likely are you of attending A&E for example, and then the impactability stage, so there may be ten people who are likely to attend A&E on a Friday night in Leeds for example, but how many of those are impactable by an intervention? So it's the next pieces of the story, next pieces of the jigsaw for the population health management agenda. So that's the huge program of work that when we started working with InterWorks and Tableau they had to really get on board, get to understand really quickly which is as you can see no mean feat. The dashboard, as I said, we did have a dashboard initially and this is just one view that I just thought is worth sharing. You can't see it all here, it's just a screenshot, but I can assure you there's a lot of scrolling down to get your information. The feedback we had was I had to click on filters, screenshot that, get another filter, screenshot that, cut and paste to make any comparisons. The charts were just showing one-dimensional views of things, but it was a journey, it was really important to us to start to surface the data that we had and the richness, so a step-by-step journey to introduce the community to the data set that we had. And we gained lots of interest as you can imagine. Lots of people could see the uses of this data set and wanted to then immediately do more with it. We ran a hackathon event. I think that was probably the first thing we did with InterWorks and Tableau, and that was really critical to understand what visualizations were possible, but also what insights the community were wanting to draw from this rich data set. And this just goes to show this view, it's called a system view. People wanting to take a multitude of the views that existed, but they wanted a one-stop shop on a page. If I was to print this out for my directors, what could we see to get all of the insights on one page? And this took us on then leaps and bounds really, so that was a new, a better user journey of existing views. I think something else that came out of the hackathon was a novel insight that we couldn't find a way of visualizing before, and this is around flowing between those segments. So again, conditions, what are we likely to go to when we're existing in a certain segment or sub-segment? And we found a way of visualizing that and a way of bringing that to the community through the hackathon event, and it was a one-day hackathon virtual event, but we came out with these two views almost ready to productionize, which was absolutely fantastic. I think some other things that came out of our insight work, we've worked closely with InterWorks that then could bring into a productionized dashboard view, which is quite different from a standalone analysis piece of work as you can imagine, one of which being this which is one of my favorites, and it starts to triangulate three different measures, so cost, activity and prevalence. So the size of the bubble is the prevalence in your population of a certain condition, so say top right, incurable cancer, a relatively medium-sized bubble in your population, relatively medium-sized cohort in your population, but driving a lot of activity, a lot of cost. But then conversely something like asthma, a larger proportion of your population has asthma, but actually they're not driving that same activity or cost. I think what's really interesting here is you can start to drill down into some of those inequality, sociodemographic information, and you can really start to see how the conditions move across the page and the bubble sizes differ, especially with the aging population, etc. So it's a really interesting view that we managed to productionize in the dashboard with InterWorks development. Another one here that we also productionized was the risk of multiple long-term conditions, which I touched upon earlier, and it's about having a reference condition and what you're most likely to have alongside of that reference condition. And I'll touch on this again later because this is some work we've been doing more recently with InterWorks. We did surface that from our insight piece of work, but actually we're really working on improving the user journey around this really complex analysis here that we've got, and we've done some great work behind the scenes that are not in the live dashboard yet, but are soon ready to go once they've gone through testing. So that's been some really great work we've done recently. So I'll just touch on that actually, I'll just take you to that now before I move on. As you can see the view has changed here and it's just again really about providing a better user journey, a more understandable way of working their way through that complex data set and complex analysis that they can get ahold of here, and that's been some real great work we've done with them recently. And also multi-select. So before everything was single-select, and again people were having to take screenshots and compare them and try to aggregate data, and actually bringing in stuff like multi-select and things like that has really helped. Also the overlaying of instructions and clarity on those, and again just bringing to us the art of the possible and trying to make these small changes that make a big change and big impact for the user who is using these dashboards on a daily basis. And then again some relatively new piece of work, which again isn't in the live dashboard just yet, but is almost ready to go, is about bringing that risk stratification to that next stage of the population health management agenda. Again it's really complex analysis for people to get their heads around, but what we've found is with InterWorks showing us the art of the possible in Tableau of how we can present this information, how you can drill down through a user journey and start answering the questions that they're trying to ask of the data set, but also those multi-selects which really help work across pan-organization, pan-geography that we're starting to do, especially with the implementation of integrated care systems across the NHS sector. That's some of the work we've been doing on the actual dashboard itself. I thought it was important to touch on the ways of working that we've worked with InterWorks and Tableau. So I've talked about hackathon events which have been really innovative and working across the organization, but then with our immediate team we've done daily standups, show and tells, and what we've really found that we've really benefited from is the team suggesting alternatives, suggesting new ways. I think for us we don't know what's possible until sometimes we're shown it, so it's been really great that the team have really understood the data, really understood the end user needs and therefore could suggest some of these things to us. I think that was all I wanted to touch on in terms of that, but I did just want to touch quickly, if I can, more broadly on the importance of these public and private sector knitting together and the AnalystX community. So this is something that hopefully people are aware of, but again if not I can pop a link in the chat after I finish speaking. And this is where we've got a community of over 18,000 members working with over fifty strategic partners. It really is an example of private and public sectors knitting together, working together, and innovating and advancing. So we run huddle events through AnalystX and they're broadcast events to learn, share, ask, but we also through this Centre of Excellence here which was launched probably around October time last year, are running those more interactive events on a more regular basis across lots of different private sectors. So we're looking to run more hackathons as I say, but we've got escape room ideas, we've got online competitions. I think it's really important for us to be that pan-organization, pan-geography, showing the art of the possible and showcasing to the wider community all the tools and the platforms that are available. There's a weekly schedule of events which I hopefully just draw your attention to, so we've got something with Fitfile coming up around novel solutions for population insights and pathway optimization, but linked to this session here. Tableau we're offering Data Doctor sessions, so one-on-one you can submit your question that you're trying to get to grips with and you can get one-on-one consultation time. So I just wanted to draw the community to that, so what we're doing more broadly around the public and private knitting together. I will pause there in the interest of time, Vicky, and hopefully allow some time for the last speaker. Wonderful, Victoria, thank you so much. I'm delighted that you could rejoin us because that really was key and critical to today's webinar and really insightful, so thank you for doing that. I'm just going to now ask Jonathan Hawkins to join us. He is going to be walking through the work that Tableau has been doing supporting Tableau and embedded analytics for the public sector. So Jonathan, if you're happy to crack on, we can see your screen perfectly. Brilliant, so hopefully you can hear me too. Morning everybody. Great. Good morning everybody. I'm in the unenviable position of having to follow Rowan and Victoria there, so I'm going to take a few minutes focusing from a Tableau perspective, explaining how we think about things, what we're seeing across the public sector, and making you aware of perhaps some other resources or other sources of inspiration as my title alludes to, that can help you on your Tableau journey and bring that to life with another story about how another organization has used or is using still Tableau at this time. So my name is Jonathan. Yeah, my title, I'm a Public Sector Solution Engineer. What does that mean? I work with lots of organizations right across the public sector from healthcare through to central government across UK and Ireland, really helping them understand what data can do for them and how Tableau can help them on that journey. There we go, so taking a little bit of a step back and we've seen some amazing examples of how Tableau is being used and what are the types of visualizations, dashboards and products that can be made with Tableau earlier in this session. But I wanted to take this step back and give you an idea of where we've come from and what we're about. Our mission is to help people see and understand data. And if we focus on the data aspect of that mission statement, what that means is we have a platform and set of technologies that allows us to do things really flexibly and support lots of different types of data problems, not constrain you in any way, we would say, to drive lots of different types of outcomes. And we've seen some great examples earlier as I say in the session. But what that means is we can support lots of different people how they want to interact with data in the right way and we can help define that and we would say wherever that data is too. So technically, we can help bring that together and make a platform that can answer any problem. But I want to take actually the rest of this time to focus more on the people aspect of that mission statement because it's equally as important. We do absolutely focus on that as well and think about the data plan. You may have seen referenced elsewhere, the community of people, over two, two and a half million people that daily use Tableau, build their careers around it and give back to us as an organization and technology platform. So that's what we're about. Which means, and we'll find a way of getting some of these links to you because I'm going to walk through the top two, but the others if you want to link through to other stories about other organizations telling you how Tableau has driven value. And there's some really interesting and relevant content there about lots of different problems that affect us now, efficiencies, operational efficiencies, etc., etc., I'm sure will be top of mind for many people. We have really interesting user stories around that. And again, I'm going to focus on the top two links to begin with. And the first one is Tableau Public. So a really, I'm going to say, critically important place for inspiration to understand what Tableau and the community can achieve. One of the first places I go to start the week regularly throughout the week as well to see what is possible and what is possible in terms of the technology, how far people can take it, but also how Tableau can help support and tell stories. So it's a curated environment, I'm scrolling down the homepage at the moment, a curated environment we would describe as the YouTube of visualization. So it's free to use, free to publish up there, you get access to Tableau as a result, people gladly share what they're doing. There's organizations that promote the public-facing visualizations through Tableau Public as well. A really powerful resource. I think there's a healthcare section in here as well, so we can drill down on this particular piece by Mark. I'm sure there's some InterWorks content on here as well, just to give you a sense of not only what is possible, but how other people, how other organizations are thinking about visualization, thinking about using data and ultimately telling those stories. A really powerful resource to bear in mind. Let me go back here. The other one to focus on is, yeah, I talked about this flexible platform and the data piece of our mission statement. If I go back, a bit of an issue trying to click the link, there we go. I'm a bit fidgety. When this opens up, well actually that platform is extendable and there's a variety of different ways that we can do that. And again, just as an example of how we support that community and the community supports the use of the platform, the Tableau Exchange is a way of, yes Tableau, but other organizations being able to share ways of extending that platform. Be that preexisting dashboards that you can plug in and start using straight away through to additional extensions, think of them like widgets or additional objects that extend the functionality of dashboards that you can use right the way through to connectors to specific databases as well. So if you can't do it out of the box or you want a quick way of starting using Tableau, Tableau Exchange is a great place to bear in mind and think about how we can extend that platform. Yeah, this is a community of developers making that capability available as well. So my final couple of minutes, I'm just going to touch on one final story from Gloucestershire. Gloucestershire, I won't read exhaustively all of this slide, but they faced a challenge which I'm sure many of you will recognize around proliferation of Excel, lack of governance, lack of a common or shared understanding across the organization. So use of Tableau and actually the approach of using Tableau and Victoria alluded to that as well. I think what really makes this work is working with organizations like InterWorks to help define a pragmatic, agile and achievable way of using Tableau and data to achieve the outcomes in the business and impacts that you're looking at. So Gloucestershire were able to do that in an agile way, focusing on specific areas first, both in terms of a project, but also technically, so they were co-developing and building a warehouse at the same time. We don't need to wait for that to be finished and be perfect. We can work in an agile manner, picking up the data from where it is at the moment, switching that over to the data warehouse as that develops as well. As you can see, what we're able to deliver using Tableau, ten-times improvement on time to insight, massive, massive value there. Automation gains, increased quality decisions, and these are decisions being made right across the organization, at all levels within it, so clinicians, operational and executive users as well. So Tableau's got a way of being able to deliver insight to those different types of users and different cohorts of users, allowing them to make decisions and drive outcomes in the most effective way possible. Zooming down a little bit on their hub and again this is something that InterWorks can help deliver as well, but just give you a sense of what it looks like and dashboards similar to what Victoria walked through will be accessible through that hub. So that's me, that's a very quick overview and introduction to Tableau, the types of things we think about, how we think and how we're looking to help organizations and address the challenges in the public sector at the moment. I'd like to thank you for your time and that being said I'll hand back to Vicky and perhaps we'll pick up questions if there are any. Wonderful, thank you so much Jonathan and thank you so much to all of our speakers who have joined us today. We've got a wealth of knowledge on this call. So if there is anybody who has a question, as I said, if you would like to ask those via either the Q&A or the chat panel, please feel free to do so. We don't have any questions at the moment. So my assumption is that the speakers have done such a phenomenal job that everybody is ready to go away and create their own versions of these wonderful dashboards. We've had a couple of people asking about the links that you've seen. We will be getting those links sent out to you. That's all going to come via an email which will also carry a copy of the recording of this webinar. So yes, that's one of the questions we've just had through. Yes, we will be sharing these links out with you so that you'll have an opportunity to go through in your own time. I appreciate that we sped through this. We had an awful lot of content that we wanted to get through. And I appreciate that Zoom meetings have been everybody's world for the last couple of years. So we're trying to cut them down to about forty-five minutes. So that was me doing a little bit of filling. As it stands, we don't have any questions. Here we go. One question has come in. So we have a lot of community data. They were unable to use postcode for fear of patient security. So Rowan, I don't know if you want to chime in about data governance and how we've managed that level of anonymity within InterWorks. Yeah, I'm just trying to get my head around the question. So I think that within speaking about the population health, the PAPI stuff that we were looking at, basically a lot of data is rolled up so it doesn't get presented at that level of granularity at patient level. It gets rolled up and then the information governance is a little bit easier. There are some considerations about small number suppression, so like not showing particular details below like five people or that kind of thing, because then people can reverse engineer and try to figure things out. So that's another level of security that we apply. But generally, a lot of the population health is at quite a rolled-up level. So that gets around quite a lot of those problems in terms of the patient security. The other way, there's a lot of things you can do in Tableau around governance. So in fact, one of the new dashboards that we're building in population health is called a Waiting List dashboard and there's a bit more governance around that particular data and so what we needed to do is build in row-level security at a regional level, so people can't see the data from other regions that they're looking at. And so how we've done that or how we're doing that is that we are using, all NHS uses Okta. And so the Okta actually has the particular provider people come from and so that gets rolled up into the region that they're from. And so we can use the NHS applications platform to create user groups and connect those user groups to ones we've created on Tableau Server. And then within that, it then means that we can use row-level security as data filters within Tableau Server so people can only see the data that is there from that particular region. So there are ways and means and Tableau is a great tool to be able to solve a lot of those problems. In Greater Manchester, we use a lot of Snowflake and data governance around that to solve other more specific problems. So it's definitely something that we can talk to you a bit more, but given time and the amount of detail, I just suggest perhaps that we reach out to you, you reach out to us and we can maybe discuss that in a bit more detail to really look at the nuts and bolts of how to make that happen. But hopefully that's given you a little picture of the art of the possible within that. Wonderful, thank you so much, Rowan. Yes, I was literally just typing a note to Ann just to let her know that we'll contact her post this event just to follow up. We do have one additional question from Natalia. Could you please advise on a write-back extension for Tableau? I believe that's what she's asking. Yeah, so I'll pick that up. I think if I understand the question, it's perhaps around via the Exchange, there are write-back extensions that allow you to capture data in a dashboard and then write back to somewhere. Yeah, exactly, so I think I've seen that come through. There are some available, they are provided by those developers, so in some ways it's worth a conversation with the developers, but I'm happy to work through that with you. If we get your contact details, we can perhaps go into your use case in a way that, you know, what you're trying to do ultimately in a way that we perhaps can't on this call, and then we can see what the best option is for you. So I'm happy to do that if you want to pick up this conversation offline. Yeah just to add into that as well, in terms of information governance it gets a little bit complicated with the extensions because sometimes the data sits with the third-party providers and so that can be complicated in terms of data not being able to leave secure areas. So one other way to solve that problem is also through Curator which has some write-back stuff which you can host yourself so that gets around the information governance within that. So I've put a link in the chat there just to have a look at a particular demo that shows that off if you're interested and have a look. So again that's another way that we can go. So there's lots of options available to you really but maybe something for a longer conversation. Fab, thank you. Thank you so much once again. We are at time, so I'm going to call the end of the webinar. I would like to thank everybody very much for joining us this morning. We hope you found this beneficial. We will be getting a replay email across to you with the links that everybody has shared. Thank you again to Victoria, Jonathan and Rowan for leading us through today's webinar. And we hope to see you all in the future. Again, thank you so much for joining everybody.

In this webinar, Victoria Cornelius from NHS England, Jonathan Hawkins from Tableau and Rowan Bradnam from InterWorks presented analytics solutions for the public sector. Bradnam demonstrated InterWorks’ Care Quality Analytics platform built on CQC data, showcasing multi-level analysis from national oversight to individual care home performance using Tableau and Curator. Cornelius detailed NHS England’s Population and Person Insights program, explaining how the public-private partnership transformed their sixty-million-row person-level dataset through hackathons, improved user journeys and multi-select capabilities. She emphasized the AnalystX community’s role connecting 18,000 members across strategic partners. Hawkins highlighted Tableau’s mission supporting diverse data needs, showcasing Tableau Public and Exchange resources alongside Gloucestershire’s success achieving ten-times improvement in time-to-insight.

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