 Okay, everyone. I see participants are coming into the plenary session. We have a very, very, very packed plenary and very popular, hopefully. We are now talking about, we'll be talking about for the next hour actually, some more hours actually in parallel sessions, the topic of the conference, the signing for data use. We have been working on data use for our DHS2 for some years. It's very high up on our strategy. However, we also this year are focusing more on how can we enable the design for data use, the incentivize data use. So that will be the topic for this one-hour plenary. I'm very, very happy to announce our our WHO colleague to open this plenary on designing for data use, Dr. Somnath Chatterjee. He is director of deputy of data, department of data and analytics, and he has served in WHO for over 20 years, working on measurement analysis and surveys. So he will be very, very good to start off this one-hour session, going into depth into designing for data use. So over to you, Somnath. Yeah, thanks very much, Kristen, and welcome everybody. My apologies that I cannot turn my video on, but so you'll miss seeing my beautiful face. But nonetheless, to get right on to what we're going to talk about now is really, I mean, you know, while I direct the department of data and analytics here at WHO, of course, you know, data is not for the sake of data. Ultimately, we want the data, no matter how it is generated, to actually be used to deliver the impact we want on population health. So so I think that really is going to be a focus today to talk about how to use data to measure impact and look at the profile of country health status. Can I have the next slide, please? So the art division of data analytics and delivery for impact really is created, you know, during WHO's transformation to have this relentless focus on results, obviously in collaboration with all of you, our countries, our partners in supporting the entire data ecosystem right from generation to use and to ensure that the data we generate is timely, reliable, and actionable so that it can inform the actions we take to deliver the impact to the people around the world. Can I have the next slide, please? So what have we done this far? We have just produced, like many of you would have seen, you know, the technical package for data and health information systems in countries focusing with its own surveys and surveillance systems, counting populations in terms of registration and vital statistics, optimizing the data that comes from health services, that is health facilities, whether it's the health facility assessments or routine health information systems, which is really our focus today, and then make sure that countries actually have national review plans to enable the use of this data to deliver impact. We have just released our first assessment of the status of the capacity of data and health information systems in countries. We also have released our most recent version of our annual report, the World Health Statistics, that sort of tracks the progress towards health and health related SDGs and other indicators around the world. We have also created a modern end-to-end data repository, so we are creating a data hub to actually service this entire ecosystem right from data generation in countries to sort of its storage, its documentation, analysis, dissemination, and use across all our regions and countries. Can I have the next slide, please? So here you see sort of a snapshot of, you know, what do we know about the status of health data systems and capacity. And as you see, in almost every single one of these areas, there are gaps. So I think the purpose of this exercise today, I think, is to see how can routine health information systems supported through platforms like the DHIs too, working in countries, actually fill some of these critical data gaps that we have. Because of course, you know, as the saying goes, what we don't measure, we don't manage, what we don't manage, we don't change. Can I have the next slide, please? So essentially, I mean, countries really lack a significant capacity in all these areas to monitor their health system performance. And as you can see here, whether it is to do with surveys, whether it's CRBS, whether it's health services data, or even looking at their own progress and performance or enabling its use, there remain significant data gaps. Can I have the next slide, please? So our effort here is really addressing data gaps through capacity building, aligning our resources in countries, improving the access to this data as public goods, and make it easy for this data to be findable, accessible, usable, and support a data exchange through a standard reporting and collection platform such that we truly believe in the axiom of not leaving anybody behind and providing appropriately disaggregated data to target action. And of course, all this in engagement with civil society and of course, all stakeholders at the end of the day. And what we need to do also is to increase the ownership and sustainability of data systems and of course, make ourselves more accountable so that whatever services are being delivered are more appropriate and responsive to the needs of the people we serve. Can I have the next slide, please? So what have we been doing with regard to routine health information systems component of data that comes from health facilities? WHO working with partners like the University of Oslo has been setting along with its technical programs, the normative standards and guidance. We have been working very closely with the University of Oslo in developing the DHRs to WHO digital packages, running regional and country capacity strengthening exercises and piloting and scaling up use cases to generate the right evidence such that we can actually provide these data related public health goods that can drive action. Can I have the next slide, please? So as all of you probably know, the University of Oslo and his network is a WHO collaborating center for health information system strengthening and since 2018. And we focus our collaboration with the development of DHRs to as the digital tool to enable country implementation, building capacity on standards, quality and analysis and actually supporting countries in doing operational research and best and informing best practices such that we improve standards, promote country ownership of their own data systems. Can I have the next slide, please? So this has been as we just heard going on for a while. You know, our role from WHO is to develop these standards and guidance while the University of Oslo and the his network actually produces the DHRs to configuration design and use and supports its implementation in countries and supports countries in the sort of use of the not just the platform, but actually the use of the data across a range of different health areas. Have the next slide, please. So the idea really is for us to work together to develop this integrated approach and the toolkit for routine health information systems right from standards and measurements to integrated analysis and providing programmatic guidance through these digital automated packages for facility data using the DHRs to platform. Have the next slide, please. I don't need to go into the details of this, but as you know, well, the DHRs to metadata packages that WHO has developed in partnership are using many, many places around the world. There are many countries that use this either as their national health management information system, or there are many countries that pick parts of these standard packages, including most recently for COVID-19. And of course, all this also in many countries supported through an Android app. Next slide, please. So our ultimate goal, as I said, is to really use data to drive the strengthening of data systems. So encourage countries to look at their data quality, make it accessible, look at the visualization of this data, assess their own situation, support the use of technology, and ultimately connecting the country data with the globally agreed health targets. And of course, as all of us know, there is an opportunity now with COVID-19 for us to actually ride this wave to strengthen data systems everywhere. Have the next slide. So as I mentioned to you, we are building the world health data platform and our data hub. So there is this single portal of entry now to WHO's data systems and its data assets, where also we present all our flagship reports and tell our data-related stories. Have the next slide. So we also have a dashboard where we show progress towards what we call our triple billion targets to deliver a measurable impact. Have the next slide, please. And as I said, we produce our world health statistics on an annual basis. Get to the next slide. And there is also a weekly data entry platform that we have developed for COVID. Have the next slide. That's the last, that's the end of the slides. Yeah. So I think in conclusion, what I really want to state is, you know, our partnership with the University of Oslo and all of you as part of the DHS2 community is really to see how we can work together to actually create the seamless data flow from countries, whether it is at the district or some other subnational level or the national level, up to a global sort of reporting platform like WHO says that we reduce reporting burden on countries and work together to actually facilitate the timely generation and use and dissemination of this data. Thank you very much. Thank you, Somnat. This was very, very, very interesting presentation. And Elaine, you will then introduce Jörn for the next session, I guess. Yep. So for the next coming slides, we've got Professor Jörn Bra from the University of Oslo who's been here since, I guess, the first stages within DHS2. And Jörn will introduce really as to why we need to start looking at this concept of designing for data use. So over to you, Jörn. Yeah, hi. Hi, everybody. Okay. So yeah, we can take a slide on that end. So I will give a brief overview of the motivation for why we have this designing for data use initiative. And it's to a larger extent based on work being carried out on this subject and in countries in East Africa and Indonesia. And where we have tried to put up an approach for improving the data use in the district and facility levels in particular, and also how to improve the DHS2 platform and its usability to improve data use. So if you look at the general approach we have followed, we have started with assessing the situation and suggest improvements. So we identify cases for routine data use, study practices, and we identify shortcomings. And we work with users to get with them to suggest improvements. So the participation and the participant design tradition is a very, very important part of this. And if you look at the general findings from these different countries is that all countries have routine districts and facility level data use and evaluation meetings. So they are using data. So we can say that one, I mean, the use of data, maybe data from DHS is maybe better than expected, but we also see that how actually the DHS2 is adapted to data use at a local level is maybe not as good as expected, because dashboards tended to be generally configured and not really focusing on what are the needs for local level data use. I mean, denominated data target population, et cetera, are not easily available in the DHS for the facility cashments areas. And many therefore use Excel and the functionalities of Excel instead of the database to put it that way. And for that maybe it's easier to include the data that you're missing like a cashment population for facilities, et cetera. So these are the topics we have been addressed. And you see that if you look at what functionalities on the data output side in the DHS that are most used, you see that it's the pivot table that is used for downloading to Excel. And of course to use data, whether it is in Excel or wherever, it's fine. But our point here is that in many cases better to use a database for producing the different analytics than having to even type in again things in Excel as is done by several, even long many are downloading next slide please. So when we approached the district health system, the facilities, et cetera, we have a social system perspective, we call it and we try to engage users in a participatory design approach. And by looking at all the different areas of data use in a district and at the facility level, and we see that actually there are many, many situations where data is handled and used. So in order to then work with the users to identify some key areas, we come up with some suggestions for improvement. And if we look at the next slide, we see that we started with some low hanging fruits. Because what we see is that all countries have this routine data meetings or routine meetings where data is discussed and potentially used at district level and at facility level. And in Rwanda, which is this particular case, we see that at the hospitals and the health centers, there are data validations each month. And there are staff meetings discussing the quality of the performance every month. And at districts, they get all the facilities together, representatives from all the facilities together and have meetings every month. And what we were then finding out together with the participants was that there were many improvements that could be done when it comes to the DHS and analytics and dashboards, etc. So that is one way to focus on designing for data use and to engage users in the participatory approach. And what we saw is like we saw in more or less everywhere that the main problem is this catchment area target population for facilities. And when you want to have, say, a district comparative dashboard looking at the performance and coverage indicators in the different facilities, that's not really possible because boundaries for the catchment areas are difficult to to set and you don't have population denominator data beyond the district in the DHS in this case. So that is the main problem that we need to address. And yes, next slide please. So in the case of Rwanda, then we have established what we call a data use project where we have, for example, many, many different approaches to to have a dialogue and conversation around how to improve DHS2 for data use and how to improve data use more generally. And we have an WhatsApp group where all the all the district health information managers are members and with the lively, lively discussions in three languages. And that just one example of how, how we can get through with various, various conversations and identify requirements and work on improvements. So many of the things that people wanted to improve was to be able to add colors, text, fix legend formats, etc. in the DHS. On the one hand, all that's kind of output issues. And also, how can we get more standardized reporting so we don't have to start from scratch every every month for the monthly report and more flexibility in actually reusing analytics. So many, many of these issues are then discussed with also with the core team developers. And some will have to be solved at the local level. So some requirements will be at the level of generic app development and some on custom app development. That's where we are actually experimenting a little now with the Rwanda project. And we are working together with what we call the design lab at the University of Oslo. Next slide please. So if we take the more principle analytical perspective on how to develop, how to involve local users in global development, we see that they're in the case of DHS2 because what is, I mean, actually part of the core DHS2, which is developed coordinated by the University of Oslo, that is say generic features that can be adapted to any context. But in order to come through with the local requirements, we have seen that in order for say the project in Rwanda to come through with the features that are not really good enough today in the generic core software, to go through this global development and engage with the roadmap process to get it on the timeline and get it developed. I mean, then we're talking about one year from you come with your requirement to actually get through with some concrete development. So that is too slow for what we call participatory design and more agile development of local applications. So this is where we then say that we need to add this custom app development approach as part of the general process of developing the DHS2. And that is not new, but maybe to improve that one is something that we should and are working on. And that this is not new at all. For example, the dashboards you see in DHS2 today was first developed as a kind of a hack in India. And through specification of that requirements from there, it was actually taken in as a generic app in the DHS2. And a recent development in Sri Lanka, for example, we saw that in Sri Lanka last year during the initial COVID-19 work, they developed a custom feature, which actually was how to trace, I mean, how to visualize contact tracing as a network so that you could follow the cases and the contacts. And that was very popular in Rwanda. And so that app development in Sri Lanka, that feature was then in collaboration with the core team, DHS2 core team, developed as a generic feature and is now used in many countries. For example, in Rwanda. You have two minutes or actually one minute, so you need to wrap up otherwise the rest of the guys cannot talk. Sorry. You have one more slide? Yes, I think so. And then you finish. Okay. And this is just a summary of challenges and specific requirements that we have identified. And many of them are linked to the problem of local target populations and denominator data. And that will be discussed actually in the session in half an hour. So we can rather come back to it at that point then. And another problem we have seen is that dashboards that everybody makes their own dashboard is not really the best approach. They can do that. But in addition to that, we must have a way to distribute standardized best practices dashboard. Yeah. Thanks for that. Okay. Bye-bye. Thank you, Jørn. And then Elaine will have a little bit of a conceptual introduction to our project. Yeah. Thank you very much, Jørn. And really what I'm just going to overview here is what do we want to achieve. And Jørn has covered quite a bit of this in terms of kind of starting on, you know, what we've done before. We're really looking at local needs situation and looking at local action. But we're looking at from the whole spectrum of information systems, design, development, implementation and use. And the aim being to improve the use of routine and practice. But sharing also some of those innovations that Jørn has said across the different networks and across the different countries and informing the future design and development of DHIS2 globally, whilst also addressing the local situation. And it's about also further strengthening our network of action. So therefore, really, when we're talking about this concept, it's not new, but we're just looking at enhancing and developing data use in practice. And in terms of enhancing, I mean, you'll have heard quite a lot about DHIS2 and its roots right from the opening address around its activist foundation. You have heard of all of the stories around kind of countries and regions looking at local relevance and how that has had an amazing impact globally and sharing our lessons and experiences across countries. It's very much field based, but also evidence informed. So this is where our kind of history of action research comes in. And it's done within the framework of system strengthening and capacity development. So we're looking at and you'll see in the examples that are going to come up some of those broader systems issues that are addressed within our development and use of the data. And as you know, we've got an extensive network within countries and kind of globally. And we are looking at enhancing and developing capacity within that, but also expanding. But I think interestingly, we're looking at also developing across sectors. And you will see in the slides are coming up of how we're actually managing to do this within the education sector. But there's other examples also of looking at it, say, for example, in food security and the agricultural sectors and others. And also we're looking at innovations and looking at as Jörn has said in the slide of making sure that the process is it's meeting the needs, the direct needs on the ground, whilst also over the longer term looking at how we can share those. So this concept of designing for data use is really about overall holistic approach to design. It's going the last mile to local level use of data in practice. And it's going from the whole stage of analysis to being able to collect the data, process it, analyze it, present it, interpret it, and use it. So what I'm going to do here is rather than kind of speaking continuous conceptually around it, we're going to share, you know, different aspects of designing for data use. I'm going to go through a couple of examples of the developing the capacity in the design part of it. And then I'm going to hand over to our colleague from Uganda to give some examples of innovation and intersectoral use. So these these examples I'm taking from our kind of our academies and our training. So the contributors are listed there. There's many people working on these training material at local level, at regional level, and also our academies. And it really is to highlight, just give you a few examples of fundamentally if you don't start looking at it from the kind of design from the kind of maintenance from the implementation, we end up with no data or no access to data, which fundamentally ends up with no use. So for example, by highlighting implications of poor configuration and developing skills to configure correctly, we find that we will show that in configuration, this impacts not alone the users in terms of collecting the correct items so they can actually generate the data outputs they want. But it also will look at improved data quality, and that will lead to improved use. And also it'll just make it much easier to administer the complete system. So we highlight issues from kind of configuring how that will impact our data use. We also for another example would be in looking at setting up the forms. And this is particularly, it's a particular issue when we're looking at kind of various forms from kind of paper systems, feeding into electronic systems, and dealing with legacy systems. And it's about developing capacity to define, identify and implement kind of good form design whilst dealing with the reality of striving for the best practice or good practice principles, but dealing with the existing situation around the work practices there. It's about issues around disaggregation, having that so that we can actually look at issues around kind of gender, age, disability. It's about avoiding duplicate variables within forms, across forms, across programs. And so something as simple as designing your data entry form is approached from the aspect of, you know, how does this improve our support information use. And the last example is something that's often overlooked is around kind of both the maintenance and the governance of the system. So general maintenance around, you know, kind of upgrades to DHIS or to your system or your server. And we've seen in the opening plenaries of how, you know, we're advancing with the kind of analytics, advancing with the kind of functionality within DHIS too. But we need to make sure that we're supporting the general maintenance and those upgrades within country. We look at issues around organizational units, configuration, and the impact that that has on how you can use the data. And as Jorn mentioned, the next session is going to look at kind of denominator data, and we'll see how something like organizational unit configuration can impact that. Another issue is around who has access to the data, sharing the data, at what level you share the data, because we want to make sure data is used at all level and the right people have the right data and access to that. That relates to, as I said, the sharing of the data, and particularly as we're expanding the data ecosystem between various ministries, various NGOs, the implications of sharing data in terms of the ability to use it. And obviously, this is fundamentally based on data integrity and data quality and the need for data quality checks. So I've just run through an example of the two kind of illustrated concept of the, when we're saying designing for data use, that it goes right back to the assessments, but also in terms of developments, design, and implementation. But I'm going to hand over to my colleague, Dr. Prosper, who is leading our Uganda, his team, to show you really where we have that cross-sectoral and the innovations that really are, I think, pushing the boat out for us to go the last mile. So over to you, Prosper. Thank you very much, Elaine, and the previous speakers for the introduction. Yeah, good morning, and good afternoon to all our participants. Thank you for joining us. So we're going to share a few of the innovations and some of the workarounds that we have done to promote data use from the DHIS2. If you can go to the next slide. Yeah, so what we see is DHIS2 has really done a great job in terms of getting data into the system, that is the data capture, both aggregate and individual level with all the mobile and other devices that we can be able to put data into the system. So for Uganda, we looked at access as one of the ways to be able to promote data use, and this is what we have across all countries. Of course, having the data and people are not able to access it becomes quite challenging to use. So one of the initiatives that we saw at the beginning, we used at the beginning of the DHIS implementation right in 2012, was initiative started by UNICEF Uganda in trying to promote zero rating what you what we call accessing DHIS2 at zero bundles, but this is prepaid. So UNICEF was able to work out with some of the networks to zero rate or white twist the DHIS2 URL, which enabled many users to be able to use their dongles, phones, and be able to access data. And this over time has really promoted data entry, but most importantly, the use, so that the district, national are able to get to the DHIS2 at zero cost, where the cost is covered centrally. So we saw this over time. And again, when we had the COVID surveillance, partners also came in and tried to zero rate. And again, also that improved quite a lot in terms of access. So this is an initiative that can be initiated by partners, but more importantly, if governments or ministries can come in and be able to work with telecom companies to offer this kind of a complex service to the community, it will lead to access and improve the data use. Then again, also with support of UNICEF, we with the introduction of DHIS2 SMS reporting, SMS notifications for appointments in trucker, feedback, surveillance notifications, the different user groups. We saw coming up with again, a pre-paid short code that the health now uses for most of the reporting and most of the notifications, TB, HIV, and also for surveillance, most important when we run our analytics and we're able to hit the threshold to compare the thresholds, we can send notifications. So this again is an SMS that has supported reporting right from the lower communities, communities, workers, districts to the reports to DHIS2 and also for the trucker implementations get this notification at no cost to the beneficiary. Terms of feedback again for the surveillance also has really supported data use in this surveillance. Then at the beginning, also of our introduction of DHIS2 for education in Uganda, and after looking at all the challenges we've had in health in terms of access again, we looked at an initiative to be able to have a pre-paid shared connectivity in the district headquarters. Originally it was planned to be used for the district health education teams, but as we moved on in the implementation and with the lack of connectivity at most of the districts before this being shared across the different departments, even in some areas including health, coming up to share this kind of pre-paid wireless connectivity. As you can see in the corner here, you will see that that's a wire mesh, I mean a wire mesh internet connectivity that we can be able to use, and the team down there usually visualizing their data in the education sector and again also across the health. So these are some of the initiatives that have promoted access and in the long run improved data use. Next slide. So again, when you are looking at data use again, you try to see that at least DHIS2 can provide a one stop center for all the data. So as we've been implementing aggregate reporting for most of the programs, there's been a lot of need for granular data collection and with the use of the tracker in the DHIS2, we saw this data avenue integrated already within the DHIS2 to be able to bring on board granular data for analysis. A picture you see in there is one of the oldest and maybe first tracker implementation in HIV can see all and the mobillas. This is where we started with HIV tracking of pregnant women through birth and the postnatal of the children. So this allows us to be able to integrate this tracker data with the DHIS2 and we've been able to do this using an in-house data input with that that most of the countries actually have taken up. It's a generic app that you can be able to get from the app store and install and this has allowed us to be able to easily integrate tracker aggregate data with the national aggregate data so that the data can also be analyzed in one place. So you'll see where we've been able to implement TB case surveillance, we've been able to also integrate easily this tracker data with the national DHIS2. We've also done this for the lab during COVID, integrating the lab results with the DHIS2. We've done this for OpenMRS, HIV, Uganda, again include this app which is a generic app that I encourage users to be able to get on and use to automatically I will get data and send it to the DHIS2. We've also seen this really really important especially as many patterners, many users want to bring the data and so implementation of the tracker has also helped data use. Next slide. Again we've seen a lot of demand to have visuals that can be able to inform decision making at one stop. DHIS2 has been great in terms of analytics but when it comes to presentation we see that different users, different people require different ways or styles of data presentation and again time-wise and training-wise you find the top management leadership may not want dive deep into the pivot tables and analytics to be able to support to do analysis. So we've been provided and developed a generic tool, the smart display, people with teams upset shared over the week how they've used this smart display in COVID surveillance. So we've brought the smart display app that allows us to be able to project data on smart screens as you can see in the picture. This is the command center for COVID and you can have the items of the dashboard running in a slide mode and as the meetings are going on as people pass by the command center they are able to to visualize their data and this we've been able to take it even to the public places as you can see this is an education dashboard that is being displayed in a public ministry of education that you know as people wait they can be able to see statistics about their data, their districts and all that. And again to further also improve use which may not really sound like this is real use but it's also to promote the use of the data within the system. For example we have been supporting COVID surveillance and their trouble passes we've come up with an app that can allow even and allow us to be able to generate a travel pass that can be scanned QR code as it travels us through different stations. As we have also come to the vaccination we've also been able to develop a vaccination certificate, electronic certificate that can be used to travel across the country. So real time data use is one data that we have seen that can be able to promote data use. We did this in the measles and rubbera campaign, the ministers, the different players being able to see the data real time coming from the district on a smart display really promoted the data use. Next slide and last yeah so again we looked at also promoting data use and even the other innovation that we have around for promoting data use. We have the cross sector data analysis and sharing that we have tried to start now for education and health. And this has helped a lot to be able to bring on board the education part of the education minutes of education in terms of improving data use. So what you see here is the campaign I was talking about and how this cross sector work was that immunization for children happens in schools and for school children. So once you have data from education, inform immunization in the in the health in terms of your denominators, in terms of your immunization posts, this promotes data use across the sector. The other piece that we have been able to integrate has been the COVID surveillance using the school surveillance and last also for the vaccination, as you can see here the circle point is looking at the teachers. So the teachers data is coming from education but who is immunized is vaccinating, it can be it's from health. So integrating these two systems and looking at this data has also promoted data use. Thank you very much and thank you Erin. Okay that's thank you very much. Will I go on to the next presenters there Kristen? Yes please, yes please. Thank you so much Prosper, this was exactly what we wanted to showcase innovative instruments and design for designing for data use. And I should say they can cross sectorally with the education and the kind of health sector being an example there. Okay this is a really packed plenary as Kristen had said at the beginning. So for the last few minutes I just wanted to give the floor over to Paul Bondage and Jennifer Shivers who will look at the open HIE sub-community on data use and just provide us with an overview of what they're doing. Elaine we don't see the slides anymore. Yep I'm just putting sorry I just have to share. Good and it's been the next slide. Oh sorry I was to give a plug for the upcoming sessions that we have as you mentioned there there was DHIS2 design lab and working and building on that there will be a session following that today at three and then as Jiren said use of data facility level solving the denominator problem that session will follow today at two immediately after this. Okay so sorry I am over to you Paul and Jennifer. And I think there's someone not muted I tried to find out but I'm trying to unmute Moise Malendale but it's unmuting so okay over Paul. Well hello everyone it's nice to see so many familiar faces it's been a long time since I've spoken with many of you but it's good to have an opportunity to talk about this new community that we have established over the course of this past year in collaboration with multiple philanthropies including PEPFAR the Global Fund and the Gates Foundation. If you could flip to the next slide it's been really it's been really nice to hear about all of the different examples of data use but I'd like to also include another form of data use which is at the direct point of care delivery. Clinicians like myself are often making decisions around specific things that need to be done for patients and we can see this really clearly with the problem of HIV viral suppression and HIV treatment continuity. Oftentimes when we're taking care of patients with chronic diseases information needs at the point of service delivery are more important than ever and we recognize that in order to truly achieve viral suppression we need to find innovative ways to support the point of care delivery such that we're improving people's long-term outcomes and what we've realized is that there are lots of innovations within the field around HIV treatment continuity. There's innovative uses of technology at the point of service delivery and above but oftentimes all of those experiences that are happening for many years in the field they're not necessarily organized in a way that can inform future best practices. There are not also not many consensus building opportunities around those best practices they don't necessarily occur organically so people are so busy working and taking care of patients and doing the best they can to support service delivery that they don't even necessarily realize that these innovations might have broad use and value to those in other environments and so we've established a community of practice to transform these real world uses of data experience is hopefully into agreed upon best practices by basically sharing them amongst each other and then supporting a synthesis of all of those field experiences into some recommendations as a community. So if you flip to the next slide if I could just briefly summarize you know there are all kinds of ways in which clinicians and health workers including community health care workers including people working in clinics and in hospitals they're all directly working with information when they're taking care of patients and that process of figuring out how to use data directly at the point of service delivery if you could flip to the next slide all of those examples are almost kind of like pieces in a puzzle the answers we believe are very much in the field. So if you flip to the next slide so the data use community in brief empowers these field practitioners to provide guidance and recommendations to all of the rest of us who are learning from their experiences. We're starting off with the concept of HIV treatment continuity but ultimately this data use community will support other really hard health delivery problems such as treatment continuity by bringing together implementer subject matter experts other key stakeholders to share all of these community best practices and we hope that over time as that knowledge sharing occurs we start to identify themes and that's what's already happening within the community and we also hope that all of these field practitioners can essentially influence those that are supporting care delivery such as aid agencies philanthropies and other stakeholders. So if you flip to the next slide the the community work that we're doing occurs at a few levels and so at the lowest level as I talked about there are literally hundreds if not thousands of innovators out all throughout the world who are developing ways in which they're taking care of patients with data and information and up to this point we have over 600 community members that represent many many countries and we have these monthly meetings where we've heard from at least 16 country examples of novel uses of data including systems that are based on DHIS2 but also other systems as well and in some cases bespoke systems that were developed to meet a very specific local need and so we've been building that community at the lowest level and we are in the process now of developing sharing and networking so if you go on to the the data use community web presence you'll see a lot of information from various implementers and you're starting to see some peer learning that's occurring between them but then ultimately at the top we want to design the future together as the field experience picks up a conventions that are over and over again relevant to context we want to identify those and to document those as a community and hopefully that would influence the way in which the world of philanthropy and countries themselves think about the uses of information and can maybe be hopefully positively influenced by it look to the next slide so as you can see there are a whole bunch of activities that we're doing as the data use community and it's everything from building out those best practices every month we have a meeting and where different practitioners are sharing experiences around different parts of the continuity treatment spectrum we've developed something called a working model which describes the clinical touch points on which people interact with each other to provide care and we've described within each of those touch points a number of interventions that occur across many countries and so if you want to take a look at that working model you should come to our data use community but as you can see over the medium term and long term we're hoping that common tools common approaches start to emerge from that field experience so if you flip to the last slide if you're interested in learning more about the data use community we have an email address that you're welcome to send us a note to there's also a website ohai.org slash duck there's a place there where you can go and sign yourself up there's a mailing list that you'll be automatically registered for it gets very low volume like one or two emails a month and in that you can find out about community events and so if you're if you're working in a country and you're very interested in a problem like HIV treatment continuity and you want to see interesting presentations around the ways in which countries outside of yours are working practically at the point of service delivery and using information systems to improve treatment continuity I think you'll enjoy the presentations they've been really educational to all of us on this community and so I'm going to pause there if there are questions or comments but I think we're up against our time yeah now thank you very much Paul and as you say it's interesting to look at kind of data use at a different level so over to you Kristen I think it's it's we've only got about two three minutes left yeah so thank you so much for all the presentations this has been a very very packed session but we wanted to give you a little bit of the snapshot of what we have been doing the last few years but also involving our our different Paul and also some not from WHO our very long-term collaborative center and participation in in joint work and this designing for data use is actually we didn't have time to present it but it's actually one of our big project now at the UIO together with all the his groups where we actually address data use in practice all the way from what Jörn was talking about how to understand the actual use in practice and how can we support that actual use and how can we overcome hurdles in the platform to design for as Prosper have shown showcased innovative solutions in order to overcome and work around in order to support the data use so I think this which we were supposed to start to end a little bit before so people are time to go to the next sessions we have several sessions today that we are engaged in that is the denominator or the local use that's coming just now in one minute and after that there is a research session where as several of our PhD students actually talk about their research projects previous and current PhD students so welcome and of course there are many others I think mountainous also have a the the DHS to the silent lab session today so check it out and thank you for coming we have been a good crowd 147 or something so I think we ended here and we see each other in next session bye