 Hello and a very warm welcome to everyone here and it proves to be it's going to be an interesting session here with stories from education sector in Uganda from looking at family planning in the Philippines and looking at the health sector in Tanzania. I'm going to hand over to the presenter shortly but a few just housekeeping rules I'm sure you're aware that the recording is taking place and so just highlighting the fact there. Also on the question and answers we're going to leave it to the end of the three presentations to do the questions but feel free to post them in the chat and then just to the presenters and Monica's up first I will just interrupt 12 minutes just to say you know that time is there and that you've got kind of three minutes to wrap up and each session here is get each presentation here is going to have 15 minutes because there's three sessions and hopefully that'll leave us with you know about 10 minutes at the end okay so Monica do you want me to share the screen or are you happy to share it? Thank you Elaine please go ahead and share the screen. Okay and this is just in terms of issues around interconnect connectivity so I'll just start it from the first slide there okay and over to you Monica. Thank you for not my video. Thank you very much Elaine and good afternoon good evening and good morning to you all my name is Monica Amoha and I'm presenting the DHS to data use cases in Uganda so my presentation basically will highlight the data use cases in Uganda but prior to that I will give a brief background of emits in Uganda and the strategies that we use to implement DHS to for emits. So just a background briefly emits in Uganda is centrally managed by the Ministry of Education and Sports at the headquarters and as you can see in the picture the ministry is responsible for printing and distribution of the annual statistical forms which are then filled by the schools and then the schools send them to the districts for approval and once these forms are approved they are relayed back to the ministry headquarters where data is entered, validated and analyzed and this has been done in a standalone access database system. Then the ministry goes ahead to produce the statistical year abstract books that are in hard copies and then they are shared with the districts as well as schools and also the education development partners and this whole process from data collection to production of these statistical year books takes around a period of around six to nine months so this whole time the districts and the schools lack evident based lack timely data for evidence decision making due to the delayed feedback in relaying the statistical year books. The districts also as you can see they are left out of the data management process because they only approve the field questionnaires and this process is annually done and it was last done in 2017 so between 2017 and now and to date we've had frequent data calls from the ministry to the districts to gather additional data to inform ongoing planning. Thank you. Next slide please. Next slide Eileen. Sorry. Sorry. Thank you. So what strategies did we employ in implementation of the DHS for education in Uganda? Our focus has largely been on the decentralized approach so we focused at the districts level where we revised the districts education management information system using the DHS to initially the Demis module is currently non functional and was not linked to the standalone system at the central level so the DHS to came in to support this since it's web best and could be able to link data from the district to the central level. We went ahead to empower the district teams to be able to use their data and manage their data at that level as well as the ministry of education team to be able to support the district implementations. Then we had various stakeholder engagements for buying and scale and important to note here is that we collaborated with Save the Children Uganda. We are collaborating with them an existing education development partner already working in the education sector. Several presentations were also made to the ministry technical working groups, the permanent secretary, the ministers, as well as the district leadership for buying and we are having continuous engagements with partners such as world food program, planning international UNICEF for continuous buying and scale up of DHS to for education beyond the four districts we are implementing in right now as well as continuous resource mobilization to scale that project to other districts. So we also had a capacity building for a multidisciplinary team at the district level unlike the health sector the district that unlike the health sector the education sector does not have designated data managers. So we've had we had to train the district education teams, the district planner, the ICT to be able to use this system as well as generate data for their own decision making and planning at that level. So we also brought in the district health data managers that have been using the DHS to in health for over 10 years to share their experience and stories on how the DHS to has supported them in health in management of health data. Then we also trained the ministry of education central level team to support the system as well as harmonize their central level data needs. So these were very various departments such as special needs, gender, statistics, and all these came together and harmonized their data needs and now we are having routine we are going to have more routine data collection vis-à-vis the annual statistical data that comes in once a year. Then lastly we went ahead and set up the districts we customized we set them up with computers, shared wireless internet, procured printers and storage cabinets as well as printed the data collection tools for them to be able to enter data into the customized DHS to next. So what are the data use cases through this we've been implementing the DHS to for education in Uganda since 2019 and over this time we've seen very interesting cases and use cases coming up from the districts as well as the central level. The first one is that data has been used for evidence decision making at district level as you can see from all these pictures is that we are having stories coming in from the districts telling us how they've used their data from the DHS to for education. So they've used the data for planning for budgeting that district level we have enrollment data that is entered into the system being used to inform allocation of computation grants to the various schools and then we also have the districts use this data for resource allocation based on the performance of the indicators in the system. So construction of classrooms, toilets, procurement of desks, allocation of teachers is all based on the performance of these KPIs and then as you can see in one of these under dashboards we have a scorecard here where we are having different this where we are having at districts be able to visualize performance at different schools or even the central level visualize performance at different districts. So this enables targeted monitoring and support supervision. This abstract here is from one of the districts telling us how they actually used the data to inform renovation of classrooms as well as construction of teacher houses. Next, then the second use case has been that this data has really informed implementation of health programs, especially at district level but of course this also translates to national level. The data from the system especially the enrollment data provided vital statistics for immunization targets. We had the Mezos-Rubera immunization campaign a nationwide campaign that took place in 2019 and the districts where we are implementing we are able to provide us with to provide vital statistics for immunization targets so that appropriate vaccines would be allocated to them. Then of course since the data is age-specific it gives learners who are eligible for HPV vaccination and so this also informed that immunization program as well as which learners are eligible in pre-primary schools for the deworming program. So this has really empowered the cross sector synergies between education and health and data sharing between the two sectors. Then of course as we all know we've been affected by the COVID pandemic also in Uganda we had a lockdown last year in March and all learners were sent back to school. So we went ahead to do a national data call as you can see from this dashboard. We collected data from all 140 districts across the country and this data was used to inform the COVID response to guide the ministry as well as the districts in distribution of self-study materials, the distribution of temperature guns and masks during school opening. The districts were also able to use the data for additional lobbying for additional partner resources and right now since we are going into the we are into the vaccination program for the COVID-19 we've updated the teacher information into the COVID e-registry and now this is going to also inform vaccination of teachers. So as you can see all this data is informing planning is informing decision making at all levels across the sector. This is an abstract from one of the districts also indicating that teacher information was extracted from the system and then the teachers were supported with food items such as maize, flour and beans during the lockdown. Next slide please Elaine. And then beyond now during beyond the COVID pandemic COVID response the schools now during the end of towards the end of the last year the schools were reopened and so we needed to do COVID school surveillance. So this prompted us now to start the COVID school surveillance using the DHIS 2 for education and this is in partnership with Save the Children and it's being piloted still in the four districts that we are implementing in with plans of scale up to the entire country because this is vital as it provides statistics relevant for the response. So just briefly at the school level learners and teachers are screened and then this data key data on temperature, running nose, sore throat, difficulty in breathing is recorded using short codes and then this data is entered in a toll-free SMS-based reporting system and then of course we have the real-time dashboards both at national and district level. So this data is linked also to the district health teams that are responding to COVID for follow-up and action in case it's out of the normal. For example if we have a school that has learners or teachers that have temperatures above 37 no difficulty in breathing they are followed up to see whether they were referred to a health facility or treated. Just to let you know just less than three minutes to go. Okay thank you so and then the other one the other use case has been improved data visualization and display at both districts and the national level so from the system we are able to generate very dynamic dashboards with key education indicators at the district they are able to print out and at a snapshot they're able to view their data then at the central level we've provided the central level ministry with smart screens and they are able to display this data and really guide them in decision making. Next slide and then also what we did within the DHI is to note everything not all the data is collected on the annual statistical form so we went ahead to integrate data from other existing systems such as population statistics from the Bureau of Statistics to help us calculate key indicators such as gross enrollment ratio net enrollment ratio then we also imported examination data from the national examination board for calculation of the performance index so all this now is visualized in one dashboard within the DHI is to and is able to be acted upon and lastly the DHI is to for education is helping us in the process of harmonization of the institutional inventory master list it's acting as a central repository for all registered and licensed institutions in the country so with this we are going to have continuous update and standardization of the master list based on the EMIS policy and of course we know that this master list is very vital for the ministry of finance in allocation of computation grants to institutions. Next slide so lastly I will end with a quote from one of our district planners Mr. Omal David who says because the political leadership look at their constituencies just a minute because the political leadership look at their constituencies but for us we look at service delivery versus performance indicators with DHI is to we are no longer arguing we just bring the data and the politicians will say okay let's put the school here the borehole there the toilet stances there so this shows that they are really empowered to use their data. Thank you very much. Sorry about that my phone went off to interrupt you but thank you very much. Thank you. Thank you. Sorry I don't know why my phone won't stop ringing. This is a very good example of how cross-sectional data use can work so thank you so much Monica. Absolutely we have fantastic fantastic examples there Monica I think Haydn an awful lot of hard work and as Kristen mentioned great cross-sectional examples there and there will be another session on education as well where we can follow up on questions so some of you you can post questions if you have for Monica in the chat now and we'll see if we can get them towards the end of the session but I'd like to now hand over to Adam and Phoebe if you could share your screen and again likewise I'll just time you from the 12 minutes and let you know at 12 minutes. Great thank you. Over to you Adam is starting and then he'll hand over to Phoebe. Great well welcome everyone to our presentation using DHIS2 to support learning in family planning. My name is Adam Preston and I'm a digital health advisor within the international development group at RTI. Next slide please. Phoebe okay great thank you. Just a little bit about RTI um oh I'm sorry I'm sorry go back I'm sorry Phoebe. I wanted just to quickly kind of go over our presentation today we're going to talk a little bit about who we are as RTI. I'm going to get into the project Reach Health it's a family planning project in the Philippines. I'm going to look at our Merla framework that we're basing a lot of our our work on that we'll be presenting today and then go through some specific examples of how we're doing that and how we're using DHIS2 within the project and then of course looking forward to our future plans to expand our use of DHIS2. So a little bit about RTI. We're the first tenant of Research Triangle Park which is one of the first U.S. research technology parks. We're founded in 1958 by three area universities state governments and local businesses to stem brain drain from the area. We're modeled after a technology park created by Stanford University that eventually evolved into Silicon Valley. All research activities are guided by our mission to improve the human condition. Health research is our largest and single field of study encompassing research that ranges from studies of the human genome and a development of new drug compounds to national surveys of health behaviors and the implementation of global health programs and that's where we're going to start today. Next slide. With that I'd like to introduce Febbi, Data Manager on Reach Health to share a little bit more about the project and how we're using DHIS2 to support learning and family planning. Febbi? Good morning, good afternoon and good evening to everyone. My name is Febbi Jevelin Dewayan. I am the Data Management Specialist for USAID's Reach Health project. RTI International in partnership with Johns Hopkins Center for Communications Program and Duke Global Health Innovation Center is implementing USAID's Reach Health project. Reach Health's project is a family planning maternal and neonatal health innovations and capacity building platforms project in the Philippines. Its goal is to reduce, I'm sorry it's not working, reduce unmet need for modern family planning, reduce rates of teenage pregnancy and newborn morbidity and mortality. It has three objectives. The number one is to strengthen healthy behaviors through social and behavioral change. Second is to expand quality, client-centered and respectful family planning and maternal child health care and services in underserved areas. And the third one is to institutionalize national, regional and local systems and capacities to manage, implement and sustain family planning and maternal child health programs in the Philippines. We have a total of 32 project sites composed of 18 provinces and 14 highly urbanized cities all over the Philippines. In order to improve the effectiveness of throughout the project, Reach Health utilizes the Merla approach. The Merla approach is the intentional application of results, focus, monitoring, evaluation and research to inform continuous learning and adaptive management for improving program effectiveness and policy decision making. So this cycle of monitoring and evaluation, operations research for continuous learning and adapting best practices is being completed and repeated on a regular basis. One of the ways the Merla approach has been implemented is through the conduct of post and reflex sessions to identify what's working and what needs adapting. Post and reflex sessions are meetings where data collected by the project are analyzed, interpreted and used as basis for decision making. So we have an internal as well as an external post and reflex session. Prior to using the HIS-2, the project has been using Excel and PowerPoint to process and visualize the data that is being collected. So we enter data in Excel at the province and city level and then this will be submitted via email and then it will be consolidated at the regional and national level and then we will create the visualization in Excel and PowerPoint and disseminate the information via email and meetings like post and reflex sessions. This process is actually tedious because the data management process is fragmented. We use different tools for data collection and then consolidation and analysis and visualization. With the use of the HIS-2, the time it took to process data has been considerably reduced and simultaneous access to data at all levels is now possible. So this is how we configured the HIS-2 for the project's data management teams. The first dataset that we have is the FHS-IS dataset. FHS-IS stands for Field Health Service Information System. This is the encoding tool for routine health facility data. Prior to the use of the HIS-2, the usual problem that we encounter are errors in data entry like negative numbers, having letters or symbols. In the HIS-2, it limits the entry of incorrect values and it also lessens the processing time since consolidation is already built in. We also have an event program called Activity Database. This is the repository for all project supported trainings and reportable activities in order for us to map the technical assistance that was provided to the facilities and health offices. And just recently, we also created another event program which is called Rapid Feedbacking for Facility Monitoring Data. This event program allows us to visualize the coverage and initial results of the monitoring, for example, we stuck out. From the data that we have entered in the different data entry and capture apps in the HIS-2, we created data dashboards for our post and reflect sessions. I will now be sharing with you one of the key examples on how we are using the HIS-2 for our post and reflect sessions. In February 2021, we have conducted a mid-project technical review which involves a series of activities. So it includes a lot of activities like survey to understand the expectations for the post and reflect session and then afterwards we had a pre-work session where we analyzed data and identified the learnings and number three is we had an action planning to identify adaptive solutions and dissemination of plants. The HIS-2 data dashboards was used in the pre-work sessions in order for us to analyze parent data implementation experience and core challenges. What we did is that during the actual conduct of post and reflect session, we divided the participants into several breakout rooms and then they have to discuss an indicator that was assigned to them. So in the discussion of the family planning current users and new acceptors indicator, we realized that the HIS-2 is very conducive for post and reflect session because it also allows fast modification of visuals to suit the needed analysis while the discussion is ongoing. So here are some examples of the learnings or technical discussions during the pre-work session for the technical review in Luzon. So as you can see, we talked about the major observations on the trend of the data of current users and new acceptors for family planning. We also talked about the major observations on the geographic differences of current users and new acceptors in family planning and we also talked about the reasons on the trends and geographic differences. Afterwards, we also talked about our learnings from the monitoring data and also our learnings from the implementation. After the pre-work session, we again gather for another post and reflect session which will then focus on identification of adaptive solutions based on the pre-work that we have conducted. So here, I will also show you some of the examples of the adaptive solutions that we have identified for the problems that we have enumerated during the analysis of the data. So for example, in lesson one, COVID-19 created new challenges to health-seeking behavior. We have identified that redesigning the USAPAN, it is an activity, a demand generation activity that directly links service delivery could be a very good adaptive solution. This was already completed by the team. And then second is to create videos and family planning methods to improve quality of family planning messaging and support of community health workers who can task shift. This one is already ongoing. Second one is another common problem that we have identified is that public and private service delivery points either individually or as part of the healthcare provider network cannot currently prioritize family planning service provision and recording and reporting. So the adaptive solution that was identified is to support the training and mobilization of community health workers in performing basic family planning tasks, following informed choice and volunteers and principals during normal conditions and in health emergencies. This is ongoing. We have already conducted a training of trainers for the community health workers. Next one is number of private family planning service delivery points remain low. So here are the adaptive solutions that was identified to conduct quarterly internal and external post and reflex session to identify areas of improvement. This one, I put it in ongoing, but we have already conducted it this June, internal post and reflection for family planning in hospitals. And the second and the third, we set a realistic target for private hospitals and we advocate the revision of the peers performance indicator reference sheet to require only three methods instead of five and focus on long acting reversible contraception for private hospitals. So in our latest version of email, this has already been updated. So I just presented you three sample lessons and the adaptive solutions that we have come up to for this presentation, but there are more. Thank you very much. Thank you very much, Bebi and Adam. Yes. Okay. Can I discuss the last slide? Thank you so much. Here is the learnings from the implementation of the HIS to itself. On configuring the system, we have to think with the end in mind how we build the data sets and program sets greatly affects what we can do or show in the analytics. So working with our technical advisors and program managers is very, very important. On capacity building, we have actually customized the training and user guide manual because we found out that using the actual data elements and indicators that the participants are dealing with at work facilitates the training process and makes it easier for the participants to understand the concepts being presented. And last but not the least is creation of a support group, create a platform where users and the HIS support team can reach one another for support. So for in the future, we will focus on enhancing the data dashboards to be used for post and reflect sessions to be conducted at the health facilities level. I hope you have garnered something from the presentation. Thank you so much for listening. Adam, is there anything? Yeah, thank you. We welcome all questions in the chat and feel free to reach out to us via email. And of course, we wanted to acknowledge USAID and our partners, Johns Hopkins Center for Communication Programs and Duke Global Health Innovation Center for making this work possible. So thank you. Thank you so much. Thank you very much. And February already has some comments posted up in the community of practice. So that's also another way of continuing the conversation. So really nice example of kind of pause and reflect, I think is applicable in all sectors. So I'd like for the last session just to hand over to Wilfrid who's going to present on Tanzania and focusing on the health sector. So Wilfrid over to you. And don't forget to keep posting your questions into the chat. Thank you Alain. Can you see my screen? Yes, that's great. Thanks Wilfrid. Yeah, good. So good morning, afternoon and evening and ground, wherever you are. My name is Wilfrid Signoni and I'm a DHS2 implementer from his Tanzania. I'll be sharing our story on data use in Tanzania, you know, looking at the challenges, opportunities presented himself in Tanzania and how we kind of address and a little bit about the plan which we have in terms of the future. So a little bit about history of, you know, DHS2 and the health prevention systems in Tanzania. DHS2 was our first adopted in Tanzania in 2011. 2014 we scale up nationwide to all the districts in the country. So in 2021 we have like worth of seven years worth of data, you know, from all the health facilities, public and private, different health programs have also been integrated within this national system so that we can have a holistic kind of view. Of course the data flow in Tanzania, you know, you know that health facilities are the most point where they, you know, kind of produce this information. So this information I produce mostly there at the facilities. Still at the facilities they have a huge registers, you know, books in different programs and they, you know, collect this information and aggregate these and then send them to either the higher administrative point where the DHS2 has been, you know, in Seoul at the district or some of the facilities also kind of have capability and our infrastructure where we have, you know, in Seoul is DHS2 for data collection. So we have kind of, you know, we started, you know, roll out DHS2 at the district level but we as years gone by we have scaled it at the health facilities so that this information can be captured at the health facilities. Now most of these, you know, data managers engage routinely in getting this information to DHS2. Once these information are, you know, into the DHS2 now either the regional managers, the health programs at different levels and even the national level are able to access this information immediately and also, you know, review this information before different stakeholders and parental impactors also get access to these information. We are talking about, you know, more than 100 million records, aggregate records here I'm talking about, you know, more than 2,000 users, you know, in the month you have more than millions, 3 million records, you know, being populated in the system so that they can be analyzed. So the challenge of availability of data is kind of diminishing and some other challenges are now propping up in terms, you know, of data quality and, of course, the information use and this is actually the topic which we are, I'll be kind of trying to present today. Now I've tried to kind of speak these overview of data using to the names of two areas. One I'll talk about challenges which we see kind of emanating due to the now the huge load of information which is available where we have now, you know, limited local routines that are used at the different levels in the government, in the country. You know, maybe too much emphasis has been put on the central level in terms of building capacity but at the sub-national level at the health facility we have a very low limited data use. Still people are clinging to the, you know, legacy systems which have been used to use, for example, Excel for the analysis instead of using this DHS2 web-based systems which we have and, of course, the low limited, you know, skills in using DHS2. For example, today we've seen a very good, a lot of, you know, data analytics tools within DHS2 where you can analyze your information but you find that in most of these national systems there's been low uptake of these particular advanced data analytics tools. So these are kind of the challenges which I'll be bringing up but also we see the opportunities which are coming up. There's a lot of innovations which are coming within the systems. For example, UNICEF, we call these UNICEF apps but they are apps which allows or facilitates data analysis and use, for example, BNA, bottleneck analysis, scorecard, etc. We see also there are kind of, you know, local innovation in terms of dissemination of information to different stakeholders and I will talk a little bit briefly about the HMAS portal which we have in Tanzania and, of course, looking also to the future in terms of how can we support predictive analysis and those kind of things. Okay, so seven years down the road after a full rollout of DHS2 and here's a snapshot of how that is used at the national system. This is kind of a snapshot. There's a pitch in DHS2 where you can, you know, see the level of use of these analytical features within your DHS2 system and this is something which I've kind of generated from our national system and as you can see there are different kind of reports but the most used report is called data set report. Now, for those who don't know, data set report is just a report which mimics the data entry collection form and usually data managed back in the days they were, you know, aggregating this information once they've aggregated manually this information. They take this information, they enter this information, this kind of report similar to the data collection tool and then send it to the upper level for analysis. So, seven years, you know, eight years, 10 years after the, you know, implementation of DHS2, we see that this kind of report is still the, you know, most used report in the national and it's used, you know, by far from the other particular analytical tools and this kind of begs the question of why, you know, low level of data use or low level of, you know, analytical skills at the low level where they kind of, you know, still have that legacy analysis skills or, you know, the demand only to, you know, use the data set report and then send it to the higher level instead of engaging with, you know, more analytical functions which are in DHS2 so that they can use this information in their particular, you know, local level. We also see that the second analytical tool there is the PivotTable and one we did kind of research, you know, one of the things which we noticed is that the PivotTable has been also quite being used extensively and not rather for, you know, local information use but, you know, just to pull all this information outside of DHS2, put them in Excel, you know, and then later on, you know, do their own analysis using the Excel instead of using the advanced tools within the DHS2. So this kind of brain brought in many questions, is it the capacity building for them to use these analytical tools within DHS2 or some of the DHS2 functions are not, you know, covering some of the local needs which are there but, you know, there are some many reasons which we got, you know, for example, people are kind of quite conversant with Excel so they decided to use that and use this Excel in their reports. Of course, some of the reasons are the ones they talk about, you know, the need, you know, to learn more about these analytical tools. So it brings that particular aspect that we still have a long way to go in terms of building capacity, exposing our national teams so that they can understand these features which we are actually building within DHS2 and, you know, use this information, use DHS2 to inform them during their particular meeting instead of relying with either legacy functionalities which they have or other tools. Now, these are the pictures which we got when we did a little bit of research in one of the health facilities. I mean, it shows one of the disease surveillance officers who have, you know, kind of designed some of the charts and then post them on their particular wall. Now, we found this quite interesting in terms that, you know, there's some level of information used at the lower level and this is at the facility level where they can use these information. The good part is all these information are coming from DHS2 but the local team there are very conversant, are more comfortable to extract this information, you know, and, you know, kind of draw them by pencil. I'm hoping you can see this pencil, they have a very nice case there where they hold these, they are kind of color pencils and etc. So this, you know, inform us more, you know, at the lower level. There is a demand of information used, however, the skills, we have limited skills and, you know, we need also to promote the use of DHS2 visualizations at the local level where they can actually use these charts. We have, you know, been shown examples of very advanced charts and if these particular charts visualization can be kind of scaled to the local level, then this, it will help match, first of all, our walls in our health facilities to not be clustered with all these, you know, pictures but, you know, people could also use some of the DHS2 to support them. And you just have four minutes left Wilfrid, okay? Okay, great. So moving forward, some of the, we understand there's no one single activity which is sufficient to achieve, you know, last improvement in data use. So the team has been working in several interventions for promoting information use culture at different levels. One is the BNA, bottleneck analysis. This is an evidence-based planning using bottleneck analysis. This identifies, you know, inequities, obstacles, effective health system performance, and also identify and document these route courses. On the right there we have, you know, different capacity building sessions which we have kind of been scaling. This particular app, this app was built within, by Histon Zania and Haste Uganda. There is also the app which is called Scorecard App. This is one of the famous app. A lot of people are using it, you know, it's used for planning decision making. This is something which we have done in Zania, implementing it, you know, supporting the analysis at the high level and also at the sub-national level. And some of the areas which we have worked on is, you know, with the BFBABRN star rating, where we kind of measure the performance of various healthcare facilities. We've also worked with Reproductive Maternal Newborn and Child Health Program, where we've communicated the status of these programs towards key global regional national indicators. We've worked also with the Nutrition and Authorization Hygiene team to support this particular implementation of this Scorecard. And of course, another intervention which we've worked on is HMIS National Portal, where we have extracted data, routine data from the national system, pushed them to the portal, each portal by district level. And, you know, all the stakeholders within the country and globally, they could actually watch, view these information and, you know, I see them. We kind of developed this from since 2017, and it's been kind of supporting dissemination of the ministry information from, you know, within to outside so other people can also see it, but also, you know, catalog communicate, you know, communicate the progress which we're having, but also increase transparency and innovation within stakeholders. So different interventions which we have also thought of in terms of supporting information used, one is the capacity building. We know that for that to be routine part of the decision making, people at all levels should have skills to analyze, interpret, synthesize, present and use this information. So the team has been working with building capacity at the country level, at all levels, with different skills, you know, we have started, we usually start at the national level and we're hoping that these efforts can be cascade to the lower level. We've also worked with health programs, you know, to kind of, you know, focus on identifying the skills in, you know, these indicating program indicators and etc. When we started the national scale, we focused more on data entry, you know, validation, but as the time has gone, we have now more focus on, you know, data quality information used and promote, you know, understanding what works and where does it work. We have also, we know that data users needs to know that they can trust the information on which they base their decision when the quality is low, demand for data decreases, that data informed decisions making does not occur. So as we expected, so we have been more or less also focused on improving, you know, conducting the regional data quality sessions where we have sit with the regions and districts, provide feedback to the lower levels on what the data quality issues and instead we have worked with the WHO and Ministry of Health to build a district that we call them a district data quality dashboard. We have also configured the WHO data quality app so that they can identify the outliers and these information are, you know, propagated back to these districts and then afterwards, you know, they, we hope that these particular sessions can strengthen the data use at the lower level. We have also been conducting research on information used to understand what works for whom, why and where. We are conducting this research with his network and other his groups, the knowledge generated from these, you know, research will be valuable locally and also within the community and we share these experiences and scale the interventions which are successful in one point to also in another area. Lastly, our future plans, I think it's high time we look about forward. We have been, you know, using this information to understand, you know, retrospectively but now we look about how we can use this information to do a predictive analysis, you know, using artificial intelligence and machine learning to improve the health service delivery within the Tanzania and this is an area where we are a little bit kind of interested and we are exploring now to see how we can use these AI and machine learning to improve the information used at the national level and also at the subnational level. Thank you. Great. Thank you very much, Wilfred. And before I go to the questions, we just got a few minutes for questions. I'd just like to reiterate something that came up in the chat. There is another an education session that will be, will take place on Wednesday, so you can ask further questions on the use of DHIS too in education in that session. There's also the Thursday plenary session where we'll be looking at the whole concept of designing per data use and we'll have sessions on Thursday after that looking specifically at the denominator issue. So you can also post, as we said, in the community of practice where there's been some ongoing discussions but I thought it was quite interesting just looking at the chat there is one around from JK Osborne saying, is there a difference really between the two ministries in health and education? Have you noticed any significant difference? So I was wondering if you'd like to respond to that. I presume Monica, you'd be in the best place to respond. Have you found a significant difference between dealing with the Ministry of Education and the Ministry of Health? Well, thank you very much for that question. I would say that, well, it's for government entities, it's more or less the same. There isn't a very big difference because you go through the bureaucracies to have the approvals and the buying. But then also the teams, there's a difference between the teams. For example, in health, they are more data driven and they've been using DHIS for a long time. So they are more receptive to new DHIS to innovations vis-a-vis in education where now this is a new innovation that we are trying to introduce here. Okay, thanks, and I'm sure you can continue that conversation on the community of practice. And the other question, and maybe this would be for Fabio or Adam or Wilfrid, is in relation to the e-learning or data use modules, what has your experience been with these modules at the national and district level? I guess, particularly with COVID moving into more e-learning mode. I don't know if Fabio or Wilfrid, you'd like to answer that? May I answer? Yes, Fabio, go ahead. We have actually conducted two trainings. The first training that we have conducted was an on-site training, in-person training. And then for the new staff that we have, since there's already a COVID-19 situation, we have also conducted an online training. So we use Zoom in order to conduct the webinar, and then we use Teams in order to monitor the outputs of the participants. So in Teams, we put everything there, the resources, the instructions on how they're going to do the exercises, as well as the references, like the customized PHIs to user guide manual. And we have also actually divided, for the second training, we divided the training into those who will be conducting the data entry, and then the second training will be more focused on analytics. I hope that answers the question. Wilfrid, do you want to add anything to that? Yeah, so there's quite a difference between physical and digital training. Yeah, we're all experienced at Wilfrid. I haven't read the difference between the online conference. Yeah, definitely. But I think with what we are experiencing right now, I mean, e-learning is something which would be more or less the way forward. And it's also easier to help the local teams where they can also train themselves within their local pace and do some kind of in-house capacity building. The important part is to make sure that you have build these modules as effective as possible, as my colleagues will say, put a lot of exercise so that they can train themselves and also retrain all the other stuff when they are in their kind of area of working. Yeah, thanks Wilfrid. I think it's something we're all experiencing then going online, is there's many opportunities and advantages to it, even though we might miss the face-to-face. So unfortunately, we've run out of time there. I just see some of the questions are coming up in the chat. These will get transferred over to the community of practice. And if you engage then with each of our presenters on the community of practice in the community of practice, but also throughout the week within the social gatherings and also the sessions I already mentioned that we'll continue to have this week. So before I just finish, I just want to say a very warm thank you to all of our presenters. Sorry I brushed you to decrease your kind of all the work you've done to such a short time space, but I think you all did very, very well. So looking forward to continuing the conversation with you all during the week. Thanks very much.