 Okay, thank you everyone. I think it's sharp three o'clock in Oslo and I would like to welcome you all to this session, which is actually defined as the non-session and the non-health. It's probably also not directly education, which was just before us, but we have some very interesting speakers and topics for this session. Actually four different interesting uses of the DHS2 platform in sort of non-traditional domains and areas. We are very happy to have Jessica Herrera from Plan International. She is a Digital Development Officer on Youth Employment. She will open for us and later we will hear from Monica Sigrist from Frontline AIDS and Uwe Vasse from GIZ, as well as Georgina Hill from Pamur Jaleo project. So if you are ready, Jessica Herrera, please get us started. You can share your screen, I hope. Okay, I'm going to start sharing one second. Okay, can you see my screen? No, it's perfect. Yes. Okay, perfect. Okay, well good morning, good afternoon and good evening. I know we're coming from all parts of the world. I'm really happy to be here. As Nud introduced me, I'm Jessica Herrera. I'm part of Plan International in the Youth Employment Solutions Team and I'm happy to talk for a few minutes about how we're using DHS2, the tracker app for youth economic empowerment programs. So first of all, to start just a little bit of who we are, Plan International is an international humanitarian child center organization based in 72 countries worldwide. We're divided into donor countries and program countries. Then specifically for youth economic empowerment, our goal is to transition one million marginalized and vulnerable young people, especially young women, to decent work by 2020. And then we aim to do this by complimenting our programs through digital ecosystem. And this is how we call in Plan DHS2, we call it Yes Me, the Youth Employment Solutions Monitoring and Evaluation System. This is how it comes together, complimenting programs through different digital products. We have, for example, Yes Academy, which is an e-learning platform, and we have TESA, which is a chatbot that connects young people to economic opportunities. So through Yes Me is that we're planning on tracking and wrapping everything together. I'm going to show you a video that takes like a minute or two so you can see how the digital ecosystem works together. Let me know if this song comes through. Through Plan International, she learned that girls and boys should have equal chances to pursue their own goals, that she could work for an employer or become an employer herself. But Alma couldn't attend classes in the city. She needed another option. Plan International's Yes Digital Ecosystem offered her one. It provides courses for young people like Alma, which have been developed by experts who understand the country, the market, the opportunities, and what works and what doesn't. So they can learn what, when, and where they want. After completing her course, Alma was ready for the world of work. Plan International helped her find a place at a local company thanks to strong partnerships with the private sector. Alma was lucky, as her placement led to a permanent job. By monitoring Alma's progress every step of the way, we're gathering data to enhance and maximize the impact of the programs we offer. With one billion young people entering the labor market in the next decade, we need evidence-based, scalable, and effective employment solutions now. Plan International's digital platform provides these solutions. We are working across Africa, Asia, and the Americas so that young people like Alma gain the skills they need to succeed in the world of work. But we can't do it alone. We need more and better partnerships to scale up our programs and create decent job opportunities for everyone. Alma was able to realize her ambitions and live the life she imagined. Every young person deserves that chance. Together we can make it happen. So this is how the digital ecosystem comes together. We plan to be monitoring and evaluating the programs that we create from the beginning all the way till the end to make sure that young people are transitioning to work, and then we can keep on scaling up our programs. Sorry, it's starting again. So for the Yes Me implementation, Yes Me, specifically DHIS, too, in plan, we have implemented across three regions in 10 different countries, and we have implemented also in seven different languages. So we've been able to contextualize specifically to each country program, making sure that all the way to the sessions that are being implemented, the different interventions have been included in Yes Me so that each youth employment or entrepreneurship practitioner can be tracking the progress of each beneficiary that enters the program from the beginning that the young person starts a program with Plan International all the way till the program exit, and we've been implementing different strategies so that we can also track this beneficiary's journey even after Plan International. So we can assess the impact of our programs all the way to five years after the intervention. To give you a little snapshot on how the tracker program looks for us in one of the projects, we have the beneficiary registration, and then here's where we collect all the specific data in terms of personal details. If the person's over 18, then we don't need to be necessarily tracking guardian details. Then we collect a baseline to make sure that we can assess what the situation of the young person is at the time, and then by the project exit we can assess if there was any change in the behavior, in the situation, in the conditions. Then we go through an enrollment process in which we register this beneficiary in either an employment or entrepreneurship track, and then also we have different activity details, different sessions, different interventions. These are just some examples such as internship, apprenticeship, all the different trainings that are being handled, mentoring opportunities. Recently we've added also a COVID track to make sure that we can track also the cash advance that we're giving to these entrepreneurs. So through these session details, we're able to track what young people are staying on the program and which ones are dropping out, and that way we can track each step of the transition to employment. Then we have the project exit, and then we have the follow-up, and our aim is to be following up up to five years to tracking this individual beneficiary. Specifically, the data from USME, we look at it in two different perspectives. We look at individual level and the program level. For the individual level, we like to understand the situation of the beneficiary, identifying patterns, trying to reduce barriers in terms of getting employment, which is in the end the aim of the program. Trying to see if in different stages of the employment or entrepreneurship program, young people are dropping out. This is something we can avoid in our program, and also trying to match the skills of young people to the job. In terms of program overall, we aim to achieve more decent work opportunities, maximizing the impact, increasing the quality. We're able to assess if our indicators are showing that we're transitioning the most amount of people from registration all the way to program exit. We're able to transition them to decent work opportunities, and also with the evidence base that we're able to obtain from USME to facilitate scaling up through partnerships and through more funding opportunities. Just to highlight some specific challenges, the data security and youth safeguarding. Since we do collect a lot of sensitive data, we give waivers, either to the guardian or to the young person itself. Then we're able to limit as much as possible through use of roles in DHIS to make sure that the people that have access to the data, it's very limited and just specifically necessary. COVID-19 has created additional limitations on how we collect data, because usually we collect the data in interventions, in trainings, in physical interactions with these beneficiaries, but COVID-19 has put that limitation for us. There's been different strategies either through phone calls or we're in the process of prototyping a chatbot through Facebook to see if we can collect this data in other ways. We customize per country, which is a challenge in terms of time and resources having to translate and then just be able to contextualize each program to make sure that we're tracking the right areas. Lastly, youth are very mobile, it's a challenge to be able to monitor these young people after they exit the program, because they tend to move a lot. In terms of last, to close with a few of the successes, yesterday has been implemented in 10 countries in three regions. We have over 5,000 practitioners using it across the federation, being able to collect data and analyze it through the program. It's been implemented in seven languages and we have over 21,000 beneficiaries enrolled in YesME in the last five years. Then I think this closes my session. Thank you so much for the time. If you have any questions, I'm happy to answer them. Thank you. Let's maybe keep questions and ask people to post their questions to the community of practice web forum, which I posted a link to in the chat. I'll post it again now. We'll do questions at the end, but I just want all the presenters to have a chance. Please let's proceed to the next presenter, which is Monica Sigrist, Senior Advisor for Human Rights Data Systems at Frontline AIDS. Please, Monica, go ahead. Thanks. Let me just share my screen as well. All right. Is that looking good from your end? Yes. Great. Okay. So good afternoon, everyone, from Brighton in the United Kingdom. Bonjour à tous les francophones. Merci. My name is Monica Sigrist and I'm a Senior Advisor Human Rights Data Systems at Frontline AIDS, and I will be talking to you for the next 10 minutes about Frontline, how Frontline AIDS is using DHIS to monitor and respond to human rights abuses and violations using rights evidence action or React for short. So just to tell you a bit about who we are. So we're an international NGO working on the frontline of the world's response to HIV and AIDS for about 27 years now, working with marginalized people who are denied HIV prevention and treatment simply because of who they are and where they live. So we work with communities in more than 40 countries taking local, national, and global action on HIV health and human rights. So together with partners on the frontline, we work to break down the social, political, and legal barriers that marginalized people face. So we were seeing increasing stigma and discrimination and criminalization of people living with HIV and other marginalized populations in many places. And in response, we developed rights evidence action. So React, what I'll be saying for short, which is a community-based human rights monitoring and response system. So what React does is that it enables civil society organizations to document data about human rights violations experienced by individuals in the communities. So it provides and refers these individuals to services, whether legal or health or other public services, and then uses this data to inform quality human rights based HIV programming, as well as policy and advocacy at national, regional, and global levels. And then this work is supported on the information management side by DHIS2 using a tracker program. So this schematic illustrates in a nutshell the React program a little bit. So I'm going to talk you through this diagram. On the response side, this is illustrated by the green arrows. So this is all about a reactor, which is a person we've trained on the React methodology, meeting with a client to take down their notes and listen to their testimony and then provide or refer them to services or human rights program or an emergency response fund. And then the pink arrows illustrate the monitoring aspect, which is about documenting this information in an information management system, which is DHIS2 for us, which allows for the monitoring and analyzing of human rights data to inform programming, influence decision makers, evidence for advocacy, resource human rights programs. So React as a system has been used by frontline aid since 2014, but it was only in December 2019 when we moved React data entry into the DHIS2 platform. So we have about, I guess, 10 months of data now, or React within DHIS2. So just to get a bit DHIS2-y on this, the React data collection tool is based on a generic template, which is customized for each country implementing React based on things like the national human rights context and the population groups that the program is working with and the types of programming, whether it's a service delivery program or an advocacy program. And then from the frontline aids perspective, we also want to review the data collected at a global level across the countries implementing React. So in order to do this, the first thing we realized is that we needed to create a single program, so a single tracker program as analytic functions cannot compare data between programs. So we built one tracker program and then used program rules and org unit groups to hide things so that end user only sees the questions in the form that are relevant to them. The management of React information has been devised in accordance with the general data protection regulation of the EU. So we limit as much as possible the need to document personal information and use things such as unique identification codes to track clients in the system. So this is different from the auto-generated ones that DHIS2 can do for you because it's based on individual characteristics of the person to make it more easily retrievable like if the client forgets their code. However, we still wanted it to be system-generated in a sense to minimize data entry error. So I'll just show you a very quick video. There's no sound, so don't worry if you don't hear anything about how that works. Pay attention to this field which says, well, this is the Portuguese version. Just how it populates based on questions like what is the initial of your first name, what is the initial of your last name, which region of Mozambique are you from, date of birth and so on. And then it generates this code which we then used to track the individual. So almost identical to an auto-generated one, but slightly different as well. Then case information. This is an example one, it's not a real case, so don't worry. Just for demonstration purposes where the actual details, the testimony is documented about what the client has experienced. And then this is a repeatable program stage which means that each client has a record and every time they return to a reactor, the reactor will add cases to that kind of record. So over time, you have a collection of incidents, of human right incidents, a single individual has experienced and maybe you can relate it to changes in the human rights context or laws or policies and see how that changes, which is a great feature of Tracker, so longitudinal data. Then moving on to the analytics side, it's very important to us that data documented by reactors in DHIS2 is used by themselves as well as civil society organizations to inform quality human rights based HIV programming and to use that data as evidence for policy and advocacy. So to help in this, we developed these reactive dashboards as a starting point for reactors to start thinking about what they want to analyze. Just wanted to highlight the mapping functionality in particular because we did something a little bit different with this. We wanted to highlight plot spot areas within a country where we're seeing a high concentration of human rights abuses and violations. However, for safety and confidentiality reasons, we don't want to pinpoint areas on a map but rather just sort of show it at a higher district or province level. This functionality was not available at the time in terms of linking an organization unit value type data element to the maps app. So this is actually a custom map solution that we built with support from VAO systems, but it's working very nicely as you can see. I'm just going to play again a short video clip just to show you what sort of standard react dashboard looks like on the analytics side. So as you can see, we use a mixture of quantitative tables and infographics and we track things such as the profile of the client, the types of perpetrators, the types of incidents, and then what services were provided or referred. And this of course can be further interrogated by partners and identify links between these two different various different elements. So also to talk about some of the challenges, data safety and security is always a concern with users in the system in terms of it's understandable because of the sensitive nature of human rights related information. However, this is usually more a perception of security as a challenge rather than our actual experience. So users are worried about it but as I have demonstrated, we have built in some data confidentiality features such as the use of unique identification codes to minimize documenting personal information. We make use of informed consent forms as well if any personal information is going to be documented user roles to limit what different users can see. We also make use of various THIs2 features such as two-factor authentication, obviously things like session timeouts top with that. And usually once partners think about this in relation to what they were initially using, so paper-based methods or other tools like Excel, we normally want them over by the end of the training in terms of safety and security. Managing complexity is a big one because we use program rules and organization unit groups to customize a base template for different organizations in different countries. We have hundreds of program rules to manage now and every new country that comes on board and we customize things for them, we have to make sure that it doesn't have any impact on the data collection forms of the previous countries and users that are using it. So just something that's ongoing. Obviously in this context, can't have a presentation without talking about COVID-19. So in relation to COVID-19, we were no longer able to deliver our face-to-face React trainings on the React methodology to partners. Obviously we saw a reduction in program activities as well which given that we just only launched in December 2019, we were a bit worried about how partners would be able to continue programming activities. And then lastly around languages. So we do work in some obscure countries perhaps such as in Ukraine and in Georgia and the interface languages did not exist yet or DHIs too. Successes. So we're currently implementing React in eight countries. We're using DHIs too and with six more in the pipeline, this information has been implementation sorry has been staggered so they didn't all join in December 2019. In fact, the last country was Uganda which was only last month. I think so we've got that happening. It is also encouraging for us to see that partners are managing to actively use React in DHIs even in the context of COVID-19. So we've got about a thousand clients in cases documented which is great because we've seen that COVID has exacerbated a lot of human rights situations. So it's something that partners can still use. Let's document this. We've also been working a lot with UIO and the language, the translation database and have made significant contributions to the Ukrainian interface language. So if any of you are working in Ukraine, a lot of that is front line aids. The language then we've also translated React in DHIs too to six database languages. This is a bit easier because obviously you can control this. So it's allowing for data collection in all these languages which is great as well. Just to close off, I want to give one example to show how human rights data collected using React has been turned into evidence. So this is an example from the Middle East and North Africa region. We supported an organization called Menarosa to train focal points in the countries that they work in on React to document the experience of gender-based violence of women living with HIV and then React was used to identify and drive responses and to raise visibility of the issue and influence decision makers. So if you want to read more about this and if you Google Menarosa and silent stories, it'll be the first thing that comes up if you're interested to see what that looks like. Here is a quote from one of our React users and it just illustrates how React is a tool to arm activists and human right defenders to continue to make the necessary advocacy noises and arm themselves with Evident which is now the panacea for any advocacy and development initiative. And yeah, that's all from me. Thanks for listening. Thank you so much, Monica. Very interesting two presentations we've seen so far. Some similarities and a lot of innovation as well even in terms of language. So thanks. I'll hand right over to Uwe who is working on health insurance and actually universal health coverage. So it's sort of health but it's the financial bit. So Uwe, the floor is yours. Please stop sharing, Monica. And Uwe, start sharing. Yeah, okay. Can you see my screen? Yes, good. Yeah, thank you Knut. Thanks for having us. As you mentioned, we are working in health insurance. So non health is not really very correct. You don't get rid of this. Let me start by introducing the team. Actually, this was planned as a shared presentation. But since we are offline for technical reason, I just do it as the only one. And actually, I am the one who has done the least work on this. So the people you see on the slides right now, Yugita Saurav from Hisp India and my direct colleague Saurav from GIZ. They have done most of the work of it and all the credits go to them. They are in the community of practice. Knut has shared the link already. So if you have questions during the presentation, they will be ready to answer and they will be the competent ones. What is open image? We call it open image with an E. Although you might want to spell it open image, but we have voted we want to call it open image because in Kiswayli, you would also read it open image, of course. It's a software for managing health insurance schemes, but also other health financing schemes like voucher systems or capitation systems. And it's an open source product. It's a global good that is in the catalog from digital square listed as a global good for health insurance operations. And the aim is, of course, to contribute to the improvement of the universal health coverage worldwide. We have several live up and running productive implementations. Most of them in Africa. Tanzania started when it was migrated to Nepal, where it is running the national health insurance scheme now. We have a few pilots coming up. This is changing a lot. So I'm not even very sure whether this list is up to date. We have a pilot coming up in Djibouti. They are working on this for the health insurance there, Zandibar for health insurance scheme and also in Gambia there for financial transactions. And then we have country assessments in a number of countries. And we will have a new catalytic fund starting this year that will give us the opportunity to also support certain implementations. If an organization decides to go for open MS, we could have a bit of budget to support that process. And you just have to approach us. Okay, that is open MS, the software itself. I'm slowly bridging over to DHIS2 now because those are our main workflows and business processes that we are supporting. Enrollment, then the claiming process, claim entry process, verification of insurance status when the patient seeks service in the hospital and then the claims management where the hospital sends a claim to the insurer and the insurer is doing the review and adjudication of the claims. So the final stage reporting and monitoring is a module that we decided to build on DHIS2. We didn't want to do our own software developments just in the sense of the open HIE software architecture. You might have heard of open HIE. I'm not going to explain it here. If you don't know it, please Google it. And if you work in health, this is a very important architectural framework. From the beginning, we said we want to integrate into that. We want to be part of it. And we set up projects to have open MS talk to like BAMNI, open MRS, and also DHIS2. So yeah, basically, when you want to report on insurance data from open MS, you can export them to DHIS2. There was a dashboard that was created like on beneficiary reporting, how many people are insured, what's the coverage in certain regions that we have about 25 indicators, claims, the number of claims, amount of money that was claimed, that's about 50 indicators and then a few indicators on operations and like the processing times and the insurance systems, how long does it take for a claim to get rejected or paid. Basically, it's an installation of open MS in the organization. We have objects from that database in open MS that we push through fire interfaces. Fire is a standard internationally renowned on specific data exchange formats. And through those standard interfaces, this DHIS2 application is able to pull data on a nightly basis, for example, into tracker program entities. And then the analytics can be done over here on the DHIS2 side. Normally, this installation would not be in the national implementation that you use for HMIS. Normally, that would be within an insurance organization on the same server infrastructure as you would have open MS. Technically, in the tracker, of course, we are using data elements there. And for us, it was important to have the technical names specifically mapped to fire resources. So if there is claims response as a resource and fire and the attribute there is called process note, what we in open MS would call claim status. So here we are compatible to fire. And if you want to use the dashboards with another insurance management system, a lot of insurance companies worldwide have their homegrown systems, then you could, let's say, that way you have pretty good chances to use the dashboard because of the standards. Technology framework for the adapter, that thing that is pulling data from open MS and pushing it into DHIS2, that's a piece of software built on Java. And basically, it is like doing the data exchange. You can schedule it in a corn drop, like every 24 hours normally you would do that at night. And it will also do the metadata sink, for example, the health facilities and the location before pulling in new data. Of course, if you have different definitions of health facilities in the source system than you have in the reporting system, then the whole thing will not work. So you have to do that first. Let me give you a few links. Of course, you can download the presentation on the sketch page for this session, and then you can click on it. This is a link to the page that explains to you how to access the demo instance, which is online right now. Then we have a wiki page just summarizing most of the resources and the documentation in our open MS wiki. You can download the dashboard configurations for import into DHIS2 from GitHub repository and also the adapter. The adapter is a bit not yet final, so please be careful with that, not yet for productive use. Outlook for the next phase or the next coming month. There's a rollout project starting for the dashboard in Nepal now. It will also be Hisp India now taking the developments and really verifying it in the field. At the same time, we are looking at the dashboard closely to see whether and how to adapt it for Tanzania. Then a question into the room, like especially at Knud, who is experienced with the W8s old packages. Of course, we want to make this available for as a global good, just like open MS. The question would be that we would need some guidance on how to package this further so it can maybe eventually become part of the official DHIS2 content packages that could be distributed to other insurances as well. I think that the normal partner page, some of them are throwing money at us, so we should mention them with the Swiss Development Cooperation and the German Ministry of Development Cooperation mainly. That was it. Thank you for your interest. Please feel free to ask your questions to my colleagues. Thank you very much. That's really interesting and just to actually respond to your request for packaging. We would very much like to work with you on how this can be standardized and offered as a resource. Yes, we started with WHO and WHO is the main focus for developing content packages, but we really do want to do this as a more general process, also certainly outside of health. Even in education, we also want to offer packages. So, yes, let's continue that discussion on how to make all of this great work available more broadly. Also, very impressed by your simultaneous AI French translation. That's very nice. Maybe not if you're a native speaker, then you might find it ridiculous. Yeah, well, but at least it looks impressive to me, not a native speaker. Again, ask for people to pose questions in the community of practice. We might also have a bit of time at the end, but let's move on now to the last presentation, which will be by Georgina Harris-Hill, who is a co-founder of Pomogealeo in Tanzania. So, Uwe, please stop sharing your screen and Georgina can start sharing. Thank you. Let me just, one second, let me just try and get it up. Can you see it? We can. Yes, no. Yes. It's not. Okay, so my name is Georgina. I am the founder of Pomogealeo UK and I'm the director at Pomogealeo Tanzania. And I'm just going to be talking today about the use of the HIS2 in a social welfare setting about the system, the Tanzanian child services system, which is a data capture and case management system for childcare institutions, or more generally known as orphanages. So, Pomogealeo is a small charity based in Tanga, Tanzania, and our main work is around transforming care for orphaned and vulnerable children. We work to create alternative care solutions, so both preventative, so to prevent children from falling out of their family, alternative family-based care solutions, such as kinship care and foster care, and then also working to get children in institutional forms of care, such as orphanages, back into family-based care. Another one of the big areas of work that we focus on is developing tools and programs to ensure accountability towards children who are not living in family-based settings. Just to expand upon the problem that we've gone about solving, more than 8,000 children live in children's homes within Tanzania, about 8 million children worldwide do. According to Lumos and a number of the other large NGOs that monitored this issue, approximately 80% of the children residing in orphanage care or childcare institutions are not in fact orphans, contrary to popular belief. So there's a real knowledge gap about why they are there, how they got there, and who they are, and for too long it's been assumed, and therefore policy and programming has not been aligned and programming has been missing the needs of these children. Up until development of the solution, the government was not collecting any form of digital data and reports were manually written, and only including things like name, age, and gender of the child. Tanzania, like many other countries, majority of the orphanages or childcare institutions in the country are privately run by small charitable organizations, and in turn what we find is there's very low compliance with the laws, contrary to the fact that Tanzania has fantastic laws governing this issue in the law of the child at 2009. And I think also more importantly to highlight is that children residing in childcare institutions are at higher risk of all forms of abuse. There is a lot of focus recently as particularly in most countries are starting to become aware and talking about the risks of orphanage trafficking and importantly also to mention is that the UN General Assembly in 2019, it was the first time that all member states officially recognized the damage and the harm that childcare institutions caused for children and made an official commitment to transition away from institutional forms of care and start to invest more in family-based care. But the second end of the problem is we really don't know, and we still don't know globally, what are the issues that the children are facing? Why are they there and how can we better serve their needs? So why do we need a data solution? Children who reside, as I said before, in childcare institutions, we don't really know much about them particularly in Tanzania and I can say that that is the case for a lot of the rest of East Africa and data informs programming. So without the right data we don't know which kind of problems we need to be solving to ensure that these children can be transitioned back into the family. And I can give an example of that. When we started looking at the data that we collected through the use of the TCSS system, we started to realize that the major reason that children under the age of one were entering into orphanage care was maternal death. So we were able to look at different age demographics and different triggers that were causing them to enter and through that we were able to work on developing a program that addressed that problem at family level and this year in our region we've had, so in our district we've had no child under one enter the care system because they've been able to be helped through alternative programming. The other reason for a data solution is that there's lots of great laws, policy, and creations of this children's rights framework, but data allows us to translate these into measurable indicators and reduce corruption that is very evident in the system and increase levels of accountability. Our journey, as I said before, we were a very small charity and we started off with a piece of paper and a pen and we walked around and individually interviewed all the children in our district who were residing in a child care institution. We then transitioned that into a Microsoft access database and with that we went to the ministry. When we arrived they said great, we were able to produce some really shocking figures and highlight issues that for a long time had been assumed but never known and many of these issues excitingly were solvable but now we had the day to prove it but then came up the challenge that Microsoft access really wasn't going to work if this program was to be scaled in any way and that's where DHIS2 came in. In Tanzania as many of you may know it's already being used to monitor health outcomes, there's a lot of trust and acceptance in the model so we looked at creating working with a developer in Zanzibar to create an Android app and web tracker system. What does it do? So at the beginning of the TCS system we have a aggregate data collection where we capture all the information of why a child is entering into care and we get that really great ability to analyze the data of what is where these children are coming from and what the cause of entry. We're able to then use follow-up interviews so capture the children as they are residing in these homes. We created different follow-up timeline of events so we can start to track things like family visiting, education and health. As part of the case management system we added the ability to create exit strategies and each exit strategy now comes with an action plan that's required which is really important for increasing accountability and ensuring more compliance with the legal frameworks. We're also able as part of this case management timeline to if a case in exit strategy fails we can show that it fails and then create a new one so it really gives us that history of a child's experience whilst they're in the care system and this is really important because children often spend many years in orphanages and staff turn over meant that historically this data and this information about the child themselves was being lost and not only for a case planning and to be able to help the children in the way that is child-centered is this data important but also children have the right to know their story and their history and so actually through this we're able to keep a track and really great knowledge about where children come from and why they're there. Another feature that we added in was the ability to create red flags so things such as a child running away or if a child's case hasn't been had any updates to it for six months. In the care system as well particularly in Tanzania that this was an issue children were being left in orphanages for years at a time and no updates were being made so by doing this and creating the bespoke dashboards to each layer of social welfare they're able to increase the accountability structures and if a red flag goes onto the system we're able to create a way that certain tiers of social workers have to follow up on these issues so that creating accountability structures for children is so important and lastly we worked on the referral mechanism so within that we can refer to other stakeholders who need to be involved in the case planning for children so for example if the child is looking to be going into kinship care with a grandma and the grandma needs access to poverty reduction services we're able to within the system generate these referrals in a way that is allowing increased connectivity and increased accountability and just broadening that circle and bringing in other NGO stakeholders but previously hadn't actually explored providing services to children within institutions as I said at the beginning many often assumed that they're there because they have no family and so through this data we're able to actually bring in a wider network of people and through the referral mechanism allow them to see that these are actually children that need their services to the successes so far we've captured all the children within the region into the database we've hosted a training for social welfare officers on how to use the system and given out tablets for them to go out into the field and start tracking in real time children's planning cases and also as they enter into the children's home we have connected with the ministry of social welfare who are monitoring the project as well as a case study and they are really excited we've got really great feedback as well from them about how it is working and the big thing that we're really excited about is we're seeing change in practice we're seeing less children enter more children going into families and this is where we are really a big advocate for database solutions to this problem we're also seeing such as more children now are being known to the ministry level that need to be adopted or fostered that data previously was not able to be exchanged so easily and therefore children were being left in situations that are not ideal for their development and so through data we're able to create that communication pathways to really start to change practice and see a huge improvement in the way that case management occurs as for children was hiding in child care institutions future plans so through the use of the data we were able to identify two key areas that were really in non-compliance with the law one of them was that children were being illegally and irregularly referred into the care system and so addressing issues like orphanage trafficking we were able to design key interventions and trainings to rectify that issue and the other one being that over 90% of children did not have an established exit strategy and so by the end of 2020 our goal is that all children will have an exit strategy created and that is able to be monitored by the various levels of government to see the number of strategies created and what they are so that we can start planning for those children and we still have some of the social workers in rural areas that we would like to train as well on in using the tablets and providing them with a tablet and we hope to be able to do that by the end of the year and we're really excited about the potential of rolling this out nationwide as far as we're aware we there is no other system nobody else using DHIS to to monitor children in orphanage care or child care institutions and we really believe that although this is not an area that has got a huge amount of global attention it is so important because these children really need to be seen and I need to be heard thank you for listening to me I welcome any questions and I just wanted to reiterate the point that through the use of DHIS too we're really able to amplify the voices of children that were previously ignored we now know their issues better we're serving them better and we're changing practice through the use of this system so thank you very much and I welcome any questions thank you so much Georgina that's very inspiring certainly for people who work on the technical side to see to see that it's actually the data is actually really useful for for for this and unfortunately we don't have very much time I know I know there are two sessions coming up in just five minutes one on server management very technical and for everyone else there's about 14 different additional interesting use cases that will be presented in the so-called use case bizarre but I think I think we've seen some very very nice presentations today I hope this is not just of inspiration but it can lead to some further discussion in the community and and cross fertilization within but maybe we can take one or two questions if you want to put it in the chat I see a lot of applause in the chat or of course continue in the community practice any burning questions before for any of the presenters before we wrap up maybe people are just too overwhelmed there was one question that has been answered I see on the community practice well I do hope you will take this opportunity to to forge new relationships and you've seen interesting ways of using the platform it's also interesting to hear that people had issues with cross program analytics which which we are actually putting as a high priority for future releases but but it seems like all all of you have been able to do quite a lot with what's already there so thank you very much to the presenters Jessica, Uwe, Georgina and Monika and I'm very grateful we'll post this session also as a YouTube video on the YouTube channel thanks everyone and see you in the next sessions