 to start us off, right? And then I'll turn it over to Chippo from Zambia, who will speak to us a bit more. This session will be broke into two pieces. So we'll be here with a couple of presenters and then we'll have a small switch over and we'll do a couple of more presenters. The idea, the reason that we have a session like this is because we very much wanted to hear about real practical use cases of evolving programs in the field. Tracker itself as a data model in DHS2 was designed originally with a very kind of almost vertical thought process in mind for individual level data collection, where we know that at many levels of the systems in the countries that we support, they wouldn't be able to do a full-scale EMR, for example, at smaller level health facilities with community health workers, those kinds of things. But there often is a desire and funding and cadre of health workers for a single disease program, where there'll be somebody that comes in that has malaria funding and they want to do a malaria system, they wanna collect malaria data and they want to do it at the individual level longitudinal. And so that was kind of the birthplace of Tracker was to be able to do that, do that well. Somebody wants to do a single program, they want to do it longitudinally by patient, by individual item that's being followed. But we also know for many, many countries at this point, they have matured beyond that to where now they will have something like all of their primary healthcare that's being offered at a site with individual programs. They have a TV program, an HIV program, a malaria program, antinatal care program. And often the patient population might be all the same patient population from that catchment area, and they may be enrolled in two or three or four of those services. And so we, with the more recent release of capture that you saw Marcus share with us earlier today, we have a much more kind of individual centric tracker rather than program centric. The idea being that you're going to enroll a person and you might enroll them in one, two, three, four, five programs over their life. And in this way, this kind of individual level data capture in DHS2 does become something much more like a shared health record that is servicing the needs of your community at these smaller scale clinics amongst community health workers in village outreach programs, those kinds of things. Where still the EMR is not necessarily the appropriate solution, but running something like tracker on a mobile device or a tablet or through a simple web browser is something that can be accomplished. So we wanted to take a look in this session at some of the many different ways that countries are using tracker across various different programs and various different disease areas. We know there are countries, for example, like Rwanda that have done kind of a combination of many of these different things. You'll hear from the presenters about what their specific challenges have been and the ways that they're starting to use them. And we of course will have a community of practice link where you can hopefully engage in a conversation, ask questions, get responses from the presenters and from us here at the University of Oslo. So we invite that. We probably will have time for some live questions as well. So for those of you that are on the Zoom, if you want to put questions in chat, that's also possible. For those of you in the room, we'll try to open up for questions as well. So with that, I'm gonna turn time and the screen over Chippo to you if that works. Are you able to share your screen? Let me do that just now. Are you able to see my screen? Yes, we see it and we hear you well. Okay. Okay. Welcome everyone. My name is Chippo Chitambi. I am a Senior Strategic Information Officer at the Center for Infectious Disease Research in Zambia, short for, and it's called SIDAS. And I will be presenting on the Android implementation for vaccine management for the EPI OPT program, which is the expanded program on immunization optimization. The expanded program in immunization, which is the EPI, is among the many programs that is focused on making vaccines available to all the children in the world. So in Zambia, the EPI OPT has been supported and it has been supporting multiple immunization services across the country. This has brought together a lot of implementing partners. This is funded by GAVI and the World Health Organization. And SIDAS took part in this with the specific aim of improving program monitoring and data visibility and using the data for continuous improvement. However, the issue we've been having is that we use paper data collection and the use of paper data collection makes it very difficult to monitor the performance of the health facilities in remote areas. What we needed was a constant monitoring of how facilities are managing their vaccines and if they're having any issues. But with paper data collection, by the time the data is reaching the central head office, you'll find a problem has been in existence for three, four months and that wasn't enough time for people to give solutions to the problem. And so there was a need for essentialized electronic data system that would monitor the adherence to vaccine management standards in facilities. So the methodology of what we did was that we got an event capture program and we created it to collect data of all facilities. And what would happen is a team from Lusaka, which is the capital city of Zambia would go into all the facilities in the southern province of Zambia and we would collect all the responses to a checklist of vaccine management checklist. So this data is collected on the Android app. We use the Android app to implement this on tablets. This is because most of the health facilities we were collecting the data from in very remote areas. And we find that network connectivity is very poor or nonexistent there. And so the Android application made it very possible for us to go out there even when we're offline and just collect the data and then later synchronize it to the server. The server is hosted at the SIDER's HQ office. So the data is then extracted and we use that data now to monitor the vaccine management in the health facilities. So whenever there's any issue that has been flagged we would address it almost immediately. And to take this further we implemented data review meetings and we made sure that we held these meetings every quarter and all the issues that had been noticed in the past three months of the data collection were raised in the meetings and solutions had to be formulated right there in the meetings and every consequent review meeting, each district had to present on how the solutions have been implemented just so that we don't keep talking about the same problems over and over again. And so the results of this implementation has been that the vaccine management checklist has been used in 277 facilities in 13 districts of the southern province of Zambia and 270 facilities is quite a big number because it means that the number of children that have been impacted by this are quite high. Since November, 2019, when we started this program, when we started the implementation of DHIS-2 in this program, 5,010 mentoring visits have been recorded so far. So it means that five facilities have been visited 5,000 times and we collected that much data from all of them. The regular data review meetings have improved the analysis and the monitoring of facility vaccination practices which in turn have improved the immunization coverage rates in the southern province. And so from here, we just see that these are the number of mentoring visits that we've had so far and when we just started in quarter four of 2020 we had about 792 visits to facilities. It dropped off, every time it drops off in the quarters, this, the quarter one of the year is the rainy season in Zambia and a lot of areas are very, all the remote areas are inaccessible sometimes. So the number of facilities, we have access to drops in this time but then in quarter three, you see it goes up. That's because now it's the dry season and facilities are more accessible. And so we managed to go to all those that we failed to go in the last two quarters. And so the highest number of facilities we visited in a quarter, in quarter three of 2021 were almost a thousand visits and this was such a very, was a very big feat for us. So in conclusion, the DHIS 200 implementation has improved and eased the compilation of data on vaccine management in various facilities because this has just, it has streamlined how the data is collected and this has led to the ability to use the data to improve immunization rates due to the monitoring of facility adherence to the vaccine checklist. Yes. So this is it. Thank you very much. Great, thank you so much. And I think what we'll do, given the amount of time that we have for these two sessions is take some questions in between that can be kind of very specific and targeted. So feel free to think of questions now for Chibo. Do you, Chibo, can you turn on your camera? Maybe our audience here is looking up at your slides but it'd be great if they could see your face and maybe ask some questions. Let's see. Let me make sure I can pull this up on the screen. There we go. Can people see? Maybe. Zoom. Yes, we see you. Hello. So I had an initial question for you which was about the mentoring visits. Could you talk a little bit about what they do during these visits? Okay. All right. So the mentoring visit is a visit that is done by the central team from the province headquarters. And so it will be either a provincial nursing officer or a pharmacist, one of the pharmacists. So when they go into a facility, they have this long checklist of questions that they ask the facility people, either the nurse or the person in charge of the vaccine stock. And it's on a number of things. They stop management, trying to find out if the facility ever runs out of vaccine stock and what they do in event of that. There's also management of patients, of children, like trying to find out what happens when a child comes for vaccination just to see if they're following procedure. And then it's also on storage, trying to find out if there are any issues with let's say a fridge breaking down or some type of problem like that. So it's just trying to find out everything regarding vaccine management. So it's stock, vaccine stock, it's vaccine administration. It's just everything around that that they want to find out. They're trying to see if every month a facility is adhering to vaccine management standards, yeah. Okay, great, thank you. And was this a process that they were already doing before when it was just a paper-based system? Or was this a new process that was designed because of the implementation of the capturing individual data? So this was a process. So first of all, it was a process that was a bit new. It was being brought into practice and almost right around the same time, we were trying to find a way of implementing it, how best to implement it. So they started and it was paper and they had paper forms and they were going to the facilities with that. And then they would have to come back to a central place and enter that data. And then a few months later when we revised the systems and noticed it wasn't really working, then we implemented the DHIs to implementation of it and tried that. And so first of all, what we started was we started with just the computer, the web-based DHIs to version and they would still collect the paper and then bring it to a head office and then enter it from there. And then we noticed that also wasn't working. So that's when we tried out the Android application as well and it turned out it was the best fit for us. So it was kind of like a tiered implementation process. Great, thank you. Are there other questions? Yes. Thank you, Shibu, for your presentation. Just like we push it. I understand that this was done by the other countries that we might be. And then the Android bit to bring in change. For example, I didn't give you an opportunity to remind you that a certain facility you visited last month and tell you what to do before you can see the people that the facility you were working for and still have that challenge. So that system, remind you to do a follow up or in your next visit you will be able to see what you have seen before and you will be able to do more. So you may have trouble hearing so I'll try to repeat the question for you. So the question was with this switch from paper over to Android kind of what were the added benefits to doing so? Were there kind of built-in reminders to the people doing the mentoring letting them know that they needed to go or was there could you see the previous history that would enrich the ability to do this kind of follow up? What were the benefits? Okay, so we didn't put in any reminders. So it was the visits happen when funds are available and when it fits in the schedule of the person who's going out there. But yes, they are able to see the results of the last visit. And so when they go into a facility they can see what the answers were before. They can see what the, like let's say the stock levels of a certain vaccine they can see that last time this facility ran out of this vaccine or these quantities of vials. And they can now compare the responses from now and before. And then also, and that's on the part of the person who's doing the actual mentoring. And then from the head office point of view as well like the central office is that we can see trends. And so if it points to anything, let's say in the community, let's say a facility keeps running out of a certain vaccine we know there's something either the community is like the facility is underserved, the facility is not stocked enough according to the community. And this is something we need to present to the supply chain people and just make sure that they provide more or they allocate a larger amount of vaccine for that specific community. Yeah, so yes, on the interviewer part, the mentor part, it helps because they can see past results. And then from the central office as well, it helps because we can see trends which can help change a few policy items or a few allocation items. Thank you. Great, thank you. Any other questions? If not, then maybe I'll just ask one last one and then Eric if you can be ready. So one last question was for me about kind of reporting rates. Have you seen a difference in the reporting rates since moving to this digital system and maybe combined with that, are they still doing the paper and the digital or have they moved over to digital? Okay, so they've moved to digital completely so we don't have any paper, we don't use paper at all. The reporting rates have increased now because before let's say, take for instance, the first time we began, we were reporting on slightly above 200 facilities. And by the time we were getting to, let's say last quarter, we were reporting on 277 facilities. So the reporting rates have increased and the frequency as well has increased because there's less data loss and they kind of have more access to the data as well. So yeah, the reporting rates have really improved. Great. Okay, thank you so much, Chibo. I will give you a round of applause. And then please, Chibo, keep an eye on the link to the community of practice. There may be more questions that are added there and you'll have a chance to jump in and respond to those. But now we'll switch over to hearing from Eric. Can you hear us? Is your mic working? Yes, Mike, thank you. Can you hear me loud and clear? Yes, it sounds great. So I'll let you go ahead and you can share your screen and introduce yourself. Thank you very much. I hope you can see my screen. I'll try to make it much bigger. Yes, we can see your screen there and it's in presentation mode, looks great. And hopefully you can see my face as well. Man, let me look for your face. One moment. Well, I can see everyone. Good afternoon, team, and it's good to have you here. Yes, we see you now, great. Thank you, thank you, Mike. My name is Eric Munya Babazi. I work with his Buganda and I support a number of functions. And one of those functions is to do program monitoring for his Buganda, but also I support DHIS to implementation in a number of ways. With you this afternoon, I will try to summarize one of our implementations in country, which is the uptake of electronic TB and new process surveillance for our national TB and new process program at the Minister of Health. And naturally it's the Minister of Health is supposed to be making this presentation, but I haven't really managed to get the person responsible to show up, but I need to also take note that they have been key and have been participating in this process. All right, so a quick background. Really, this comes from our national strategic plan which specifies the importance of strengthening information management, including digital technology for the country. And this really specifies the participation of private sector in the reporting through DHIS too, as the, you know, mentions the ability for establishing e-health infrastructure for case-based surveillance and also the scale up of electronic logistic management information systems for TB and medicines. I had cheaper mentioning about drugs for COVID and then strengthening data used for planning at treatment units and also at district level. So in terms of policy and the framework for supporting this for the country, that's really sort of like established and it's in place. And so what was really missing was to have, you know, a real-time case-based surveillance system in place to support a lot of what has been established in these policy documents. And yeah, so in 2020 with funding from CDC and Baylor, Uganda, the ministry started this process of evolving the electronic TB case-based surveillance tool based on DHIS to track. And of course, the important aspects in this process is to get all stakeholders that are on board and having their input in terms of where to start from. And of course, Hisp Uganda being the key partner on DHIS to in-country were involved. And the team at Ministry of Health put in place a national team to support the rollout and capacity building and as well as putting in place a technical working group to provide, coordinate, provide and monitor the implementation. The need really for this case-based surveillance tool which we call the TBL, TBL is TBTibacrosis and liprocy was scaled from having, like I mentioned, a real-time inter-grown visual-level data collection system for reporting but also most importantly, track patients along the continent of care and this is specifically for TB. We know that we have a lot of HIV TB, but this is a program within the Ministry of Health or a department whose primary interest is in the disease called TB. So monitoring patients through the continent of care, looking at transfers, monitoring appointments and looking at contact tracing and then treatment outcomes was primarily one of the focus elements for having this tool in place. And of course, beta picatela response of the program in terms of addressing the challenges of reporting through data system. I also want to mention that prior to this, we were collecting aggregate data as a country and being able of course, pulling this data through the national aggregate HMIS, which is the Health Management Information System. So the other point has really, which key here was to have an efficient system for patient care management to improve surveillance, looking at TB at all levels of service delivery and wanted to of course improve program and resource management at community and health care level and also to improve clinical care for patients. So this brought us to a point where the HIS to, the community has also done quite a lot in terms of putting in place tools, resources so that we don't have to start from scratch. Yes, there are lots and lots of tools, but the key here was to start from the WHO here at the data toolkit. Which part of that involves or has the TB package that has a number of things? Of course there is the TB package for dashboards, for aggregate data and also for case surveillance and then drug resistance as a bit tracker. But we particularly wanted to have a proof of concept and then we used the TB case surveillance tracker package to do the first initial proof of concept for the team at MOH to really have an idea of what this would look like and how it would be formulated. So once we had the TB package approved then we went ahead and did an initial assessment to a certain of course needs of the readiness for facilities in terms of uptake and how they would use this. Initial of course, the discussions focused around starting with regional health centers here in Uganda, we call them regional referrals. And once we established that those main ones had the necessary infrastructure in place and that leads to some extent resources, then we're able to start the customization. So we worked with stakeholders to fine tune the user needs and the customization for four key programs. Of course there were meetings back and forth involving the different teams I mentioned above, both at national and also facility level. And then we went ahead and had the TB tracker customized based on our local reporting and TB tracking tools both at national and also at facility level. So after we were done with this, we went ahead and did an initial testing in seven health facilities that were both urban and very urban. The initial training and testing was to really certain again sort of prove that these facilities would be able to submit this daily because these surveillance tool is actually daily tool. As you see a patient and you get them and registered into a TB register, then transfer the patient through to the TB tracker. I need to mention that the country policy actually here is that we have both the manual and also the electronics. So we haven't really moved completely to the electronics side. So we did that initial testing to see how that would work and the results were quite interesting and promising. And then went ahead to do a national and regional training, 515 participants and then piloting in 97 health centers and then ultimately scaling up to 228 facilities to date. So very quickly, the tracker is the, perhaps one of the most successful in the, which we started, I think about nine months ago and reporting is quite improved. We're able to get data on all kinds of indicators. The system is hosted by the Minister of Health, which is one of the key pointers in terms of buying and ownership and then internet for facilities that reporting this data is provided by the implementing partners regionally. And then also partners that are supporting TB in these districts and facilities have also helped to provide devices for reporting in terms of laptops, Android and also rather Android supported devices. Then a key point on this was that we originally had some few parallel systems that were being implemented in different places, including TB, DR or disease drug resistant TB in some regional referrals. And then also some community systems like 99 dots and so many others that were being piloted. So we went ahead to do the migration of some of this data and also the integration of the TB tracker. For example, we have a system called Uganda EMR that is implemented based on open MRS and whose primary role earlier on was for HIV and also HIV TB. So the patients that come in, whose entry point is HIV, those ones are now able to seamlessly flow to the TB tracker using that integration. Yeah, about currently about 86% of all facilities that have been trained of the 240 are able to report on a daily. We had a couple of backlog in terms of TB case notifications and about 58% of that backlog from 2020 coming to the end of 2021 have been captured as of course, as they continue to report. And then of course trainings, national and regional continue to happen. And then what you see is a dashboard taken out of the reporting rate completeness in terms of dashboard. The teams are able to generate the monthly, actually weekly, monthly and quarterly, as well as annual progress reports at different levels. So some very quick success factors. The buying is, we've noticed that it's very key. The availability of technical assistance through the Minister of Health, Health Desk. And also his has been also very key. We've had to put in place weekly feedback meetings and updates through WhatsApp groups. We have 15 regions and the region has its own WhatsApp group that involves TA teams at the national level that continuously give and provide feedback. Availability of infrastructure, I already mentioned this for the facilities that have been trained. Internet, we've had to negotiate something called zero rating with service providers so that they add the URL for the system on a zero rated platform. Regional partners support training, support onsite mentorships, support visits and so on. We've had also, of course, the DHIS to flexibility to generate user friendly visualizations. These are very key. Then facility staff have been trained and then I already mentioned also the integration with some of the existing systems that are in the landscape. Some quick lessons learned. Active participation of stakeholders. This is key and very, very important. End user perspectives brought into the customization process. This was also very, very important as we didn't find a lot of back and forth. Data integration for reporting needs to minimize duplication. I mentioned some of the systems that already in, for example, dealing with smaller components of the TB program, things like DOT, things like VOT. You have this small system that is dealing with each of these in the community but having all of these in one place sort of helps. The linkages with localized facility EMRs has also been good. And then the leverage on the DHIS, the expertise in country is very, very key and working with different teams, facility and district level, including of course the district surveillance for co-persons, the biostaticians and the rest. Yeah, so that was my timer. So some few challenges we have found, for example, issues where of course, internet is a bit of a challenge and we have to resort to using Android devices like the phones and tablets. But in most cases, they will take long to push the data because there is no internet. Yes, we've set up the phones and the Android tablets, but sometimes because they need internet to push the data to the central server, that will take a bit of a time. Then dedicated data management staff in TB units, our, the structure and organization of health centers here is in such a way that you'll find A that the TB unit is merged with the HIV unit. And then most cases maybe even where they are separate, there are no trained staff to manage TB on a day to day basis. So sometimes that becomes an issue, limited funding to scale up. We currently have close to 2,300 health center threes and above, which should be treating TB. Those ones of those we've only gone in 224. So the scale up is still a bit limited partly because of funding and then of course data management skills. So we are working with all partners at different levels to support the scale up and specifically for procurement as well as engaging on staff capacity building, but also on continuous supports per vision and mentorships to mitigate some of these issues. I take note that my time already expired, but I want to thank you so much for your audience and over to you, Mike. Thank you, Eric. I know the microphone is not really facing the audience, so I hope you can hear the applause, but we'll see first if there are any questions. I have a few that I can get us started with, but if there are any early ones, yes, please. Thank you very much. Thank you for the use case. My question is probably coming back to some of the earlier slides when you talked about probably the use of paper tools. If I watch you very well, it seems like you are using paper and electronic tools. So I just wanted to find out to what extent are the workers managing all the issues as they are implementing and they don't think, I mean, are using the other over the other. Okay. Let me ask that one first before I forget, because I have to say it into here. So Eric, he's asking about, you had mentioned earlier in the presentation, about the paper tool and that the paper tool is existing side by side with the tracker-based tool. And so it was a question of kind of how does that work and is there a preference amongst the users for one or the other? Are they seeing benefits from the digital one or is it more of a burden? What do you have to say there? Thank you, Mike. Should I take this or I wait for any other? Go ahead with this one and then I can come back to you. All right. Thank you. Thank you once again. I didn't hear the name, but I appreciate that question. So like I mentioned, our policy in the country really is that primarily all systems in terms, in the health sector are paper-based. So any digitalization is supposed to be based on what is existing on the paper. So even as we continue to introduce some of these digital solutions, like in this particular case, the TB tracker, there is an established paper-based process that tracks reporting through the papers. So at the unit, for example, we'll have the unit register. And then of that register, we normally have they are called TB client cards. And these are the, these TB client cards are the ones for monitoring things like appointments, things like transfers and so on. But within the unit register, we will basically every month, no, every quarter, they will generate a quarterly summary report which is also manual, which is also manual. And there were normally earlier on without the DHIS too, those manual reports would actually be sent to the district and the district would have to make a summary for the district and send it to the ministry of health. But now with the DHIS too, they still have the process in place, but the quarterly aggregate summaries entered within the HMIS, which is the aggregate system. And then they are, the minister of health is able to get the quarterly reports electronically. But with the tracker, the idea is to get actual patients as and when they are being notified within the system. And so the process is still in such a way that you have the manual processes happening, but then after that someone has to punch in the individual patients in the TB tracker. I hope that is a bit clear. And the idea, of course, is that with time, they are able, once we are able to show that they can actually fully rely on the electronic TB tracker, then some of the manual tools could also be sort of eliminated. Oba, thank you. Thank you. Did you want to ask for your follow-up? Yeah, probably. Just a quick one. So I find a lot about the screening process of the TB patient, you know, presumptive TB appliance. Is that also kept, like we did in the despair of only those we have been notified? All right. So the question is about the screening. Is it presumptive as well or is it only the notified? What's included in the system? Thank you. Thank you very much. Quite an interesting question. Yeah, so for the screening process, of course, key to note that there are many entry points for before we actually notify. You have patients through different entry points and these patients are registered in a presumptive TB register. And out of that, then we have to get a lab confirmation. So what we agreed on at the national level here was to take only confirmed TB. So we are not actually picking patients from the presumptive TB, partly because a lot of those are going to be, you know, numbers that don't give us the exact case load. So the team at national level agreed to start with the confirmed TB. And these are the ones that ultimately end up in the unit TB register after they have a confirmed lab report. Thank you, Eric. I see a question that just came through in the chat about how you deal with data quality issues, the manual system versus tracker entries, at which point tracker is updated. You had mentioned, I'll add to the question, you had mentioned having a backlog of data that you're getting into the system. What is the process for that? And so maybe just some thoughts on data quality and going from paper into the digital. Thank you, Mike and thank you, Kalima for the question. It's quite actually interesting when you flip the question because for data quality, you really need the systems are checking each other. And this is how, for example, we are expecting to get from the 220 for health facilities, we're expecting to be getting daily patients updates or both notified appointments, transfers, and so on and treatment outcomes. So those were we're expecting to get those daily. What is interesting is that in the TB tracker, we actually created a replica of summary aggregates like you have seen on the dashboard. Now, those summary updates sort of they are helping, they help us to see what is actually happening within the facilities before the reporting period, which happens quarterly. So by the time we get a quarterly report in the national system or from the district, we kind of already know where to start with either by looking at the total aggregate numbers from the TB tracker on a monthly basis and compare with what they have submitted in the manuals in the manual summary tools at the district level. So that way we're able to follow up and where they are outliers. But of course, what we have seen is that naturally what will be in the quarterly reports that are sent to the district is likely going to be less partly because either of miscalculations or poor tallying. So what we get in the TB tracker is the benchmark of near accurate in terms of looking at patients because in the tracker you have the real person, you have an actual patient that you're following up through the quantum of care cascade. And when you look at the aggregate reports, you're not able to tell and tease out. For example, if someone in a district or a facilitator reported 200, 150 patients notified, you won't be able to know. So the tracker in a way is actually helping to validate a lot of data that has been reported in manual tools or even in other aggregate systems. So we do monthly data cleaning exercises to look at this. I mentioned earlier that we've been providing weekly feedback for individual events so that by the time we get a report either the month or a quarter, a lot of these issues have been sorted out. Ovan, thank you. Sir, maybe time for one more. Did you have a question? Thank you for the presentation. It's great to see the individual level tracker really is the basis of the report. There's two questions. One is that last point on data quality. What data quality issues do you see in aggregate data? Once you've got information on individual track and HIV, we see a big problem to the aggregate data model unless you've got tracking. And then secondly, how have you developed this in relation to some other seed programs? So how has TB, I love this in relation to HIV? Sometimes we're asked to have a TV tracker and HIV tracker and then an HIV TV tracker to make sure that you've got testing and TB testing and HIV and HIV testing and then TB. So maybe just those two question of data quality that shows the aggregate issue and then how you've developed it with some other seed programs. So Eric, the question that first, there are two parts. The first one is about if you're able to use this tracker individual data to better understand what's in the aggregate data. If you were seeing that there were parts of the aggregate data that maybe were not conveying the full picture or how maybe you use those two together when it comes to data quality. Are there some checks that you're able to perform with the individual data than prove on the aggregate side? And then the other, I'll save the other part of the question. If you wanna address that one, I'll bring up the other part. I make, did you say you bring up the other one after? Yeah, yeah, go ahead with that. And then I'll ask this. Okay. All right, thank you. Thank you very much. So like I mentioned, we still have two systems. We have the TB tracker, which is currently individual best and it's at the facility. And we also have the HMIS, which is also based on DHIS2 and it's aggregate. Now, what we have been doing, like I mentioned the tools, the manual process is already structured. We have a quarterly TB report, which is the report that ends up at the Minister of Health. At the facility, I mentioned the primary tools are the register and the TB client card, which are summarized and sent to the aggregate system, which is the DHIS2. So what we are currently doing is to, within the tracker, we have generated the quarterly summary report. We are able to pick the daily individual patient records and then automatically generate a quarterly report which can be compared to the actual quarterly report by the district or by the facility in the EHMIS. So at the end of the quarter, we have two reports which should essentially be the same. And with the idea is that with time, districts should actually stop sending or manually entering this data in the quarterly report and then pick the quarterly report from the TB tracker because there we are able to pick these patients' data and information directly. So that's currently what we are doing. But beyond, of course, beyond that, I mentioned that there are other processes which include data review meetings, which happen on a monthly and weekly basis for the individual patient's data. So that's currently what's happening. We have not yet started pushing the quarterly report generated from the tracker to the EHMIS, partly because of course, scale up is not yet fully complete. We are the completeness, the coverage of the facilities is still a bit low. It's 228. And that should be a much smaller percentage compared to the number of facilities we want to cover. Again, I mentioned that we've just been implementing this for the last nine months, but we are seeing some really very good progress on this. Could I get the second question, please? Yeah, just maybe to add to that, it's a really good question and it's one actually I think we're still learning more and more about as systems start to have both types of data. So we at least have some preliminary evidence that there are kind of systematically going to be differences between individual and aggregate. And for many different reasons, it depends a little bit on what the health programs are, but it can be something as simple as kind of the time periods that they're using when they're banding their reports, but it can also be much more serious things where you're trying to count the numbers of visits of a single individual. They're supposed to follow a specific program, but in the aggregate that gets lost. One person had 10 visits, one person had one visit, and they get lumped together and you assume they both had five, right? So you actually should expect some pretty significant differences at times between your individual and aggregate, and I think there's a lot more we can do to understand this. What are the strengths? What are the benefits? What can you learn by triangulating them? Which is again something, maybe we have a couple of additional presenters as well and we have more times for questions. So that concept of triangulating the data and being able to do some checks kind of both ways, I think it's still being worked on. We've got some work with both CDC, WHO, GAVI, a few others that are looking at how to do more sophisticated analysis this way. And I think there's a lot more there that we can learn. But I think maybe I'm going to hold on your other question because it's actually very relevant, I think for some of the other presenters as well, and we're going to give them some time to go. So Eric, thank you so much. Please stay on. And if questions pop up either in the chat or in the community of practice, you can feel free to jump in. But thank you so much, Eric. Thank you, Mike. Appreciate it. Great. And then Nanny, do we have you? Yes, Mike. Great. Thank you so much. Your microphone is working well. Do you want to go ahead and share your screen? Sure. Let me, let me try to share my screen. Great. Okay, we're seeing your slides. Okay. I'm trying to put now in presentation mode. I hope you can actually be able to see my presentation. Yes, we do. Thank you so much. Yeah. So I'll let you just go ahead and introduce yourself and yeah, thanks. Thanks so much, Mike. And thanks everyone for participating. I'm Nanny Rungu and I'm currently working as a senior marketing advisor responsible for research, monitoring and evaluation of the Malawi in power activity. And I'll actually be making a presentation titled the use of data from the data is to improve project performance, especially looking at the data for addressing girls and young women. And this is the Malawi in power experience. So I'm actually presenting on behalf of the Malawi in power activity and we are actually working together in the populating this abstract in the sum of the authors including Dr. Bonface Market, who is our chief of party, Linda Muumbo, who is also on the score and has actually contributed largely to this presentation and this paper. And then I also have Yonan Yondo who is also on this call. And we are, he's the senior technical officer for research and monitoring and evaluation under the Malawian Power Activity. And then Matthew Kankurungo, who is also the data and the HMIS manager for the activity. So our presentation will actually look at basically the introduction, where I actually gave a brief overview in terms of the project as well as the challenges that we initially had. And then we'll actually look into the methodology in terms of how we're able to maneuver around the challenge that was there. And then you'll actually also be able to share the results, what was actually achieved after we have actually employed the different methodologies. And then I'll end up with a conclusion as well as a recommendation. Now, a quick snapshot in terms of the project overview. So Malawian Power Activity is a paid for RVS. And for this project, we are actually supporting the government of Malawi, the government of Malawi's commitment to epidemic control by stopping transmissions as well as preventing new HIV infections, especially looking at recent goals and the human age between 10 years to 24. So in terms of our target audience for the project, we are only focusing on addressing goals and the human age 10 to 24. And we are focused in the two districts of the southern part of Malawi. And these are matching as well as the Zumba district. The project is actually being implemented in collaboration with the different partners. And these are local implementing partners with the family, the Health International 36, the FHIR 36, being the prime partner. And then we have got the Christian Health Association of Malawi, commonly known as CHAM, as one of the subpartners. And also the Pagachari Institute of Health and Development for Communication being the second partner that we are actually working with. So the project is part of the USAID dreams project, which is actually focusing on addressing goals and the young women. And the goal for the project basically is to of the Malawi Power Activities to actually support the transmission of HIV infections among the addressing goals and the young women as the idea indicated. Now, the project is actually providing SRH services, which are sexually reproductive services to addressing girls and young women in the two districts. And despite the project's collection, as well as the access to high quality HIV, as well as SRH data, platforms to actually periodically analyze this data to improve project performance were actually minimal. And therefore, there was a need for us to actually be able to use the data that we're actually analyzing as a project to help us to make informed decisions for the project at the same time to actually be able to make a mid-course adjustments where necessary. And also looking at the inadequate skills, especially among program staff, despite that, we have a robust monitoring and evaluation team, which is also managed in the conduct with data analysis. We also had a challenge whereby our program staff needed to actually be able to have a feel of the data. And we're actually looking at it that they can actually be able to do this analysis within the tractor, which is actually being housed under the DHS2 platform. Therefore, we also had a challenge to actually have a platform for us to be able to perform as which was actually minimal. And then in terms of the methodology, in March 2021, the project actually started in 2020. But then in March 2021, having looked at the challenges that I actually addressed in the previous slide, we actually initiated a total quality leadership as well as adaptability model, which is actually an FHI's model for reviewing program performance. And this actually reviews performance on a daily basis in making mid-course collection. And these were actually done through a platform that is called the situational meetings. So the situational meetings are actually a platform for us to actually be able to review data on a daily basis and then utilizing such a platform to actually make mid-course collections. And the model actually requires us to actually be able to set the data targets and also coming up with a data tracker updating and informing us on the achievements for the day as well as any other challenges that we actually encountered on a daily basis. And then through these data targets, we're actually able to use granular cycle of data to actually monitor performance to enable program improvement. And then we actually use the DHS to track a version 2.8, 33.8 to actually be able to capture as well as to analyze and also visualize our individual data on the three sexual reproductive health as well as HIV indicators, which will actually be discussed in the methodology. During these situational meetings, first we'll be able to identify challenges in AGIW service provision as well as prioritizing local solutions to improve project performance. We integrated the DHS2 tracker with a real-time interactive Power BI dashboard at community district as well as project level. First we'll actually be able to track project indicators with the required desegregations. Now, in terms of the results following this TQLA process, one thing that we have actually noted is that using the DHS2 tracker, we're actually able to systematically analyze and visualize granular cycle level data during the situational meetings, which actually lead to targeted program adjustments and it also contributed to an increase in the number of adjacent girls and the immune men that were reached with standardized evidence based sexually productive as well as HIV services from 13,608 as well for Q1 or for the year to actually a total of 56,000 as well for Q4 in FY20-21. Furthermore, out of those adjacent girls and the immune men that were reached with these SRH as well as HIV services, looking at specifically for adjacent girls and young women who access the HIV testing services through testing, our annual target was at 15,008 in the access HIV testing services as of end of, we're not only providing conventional testing to these adjacent girls and young women, but then we're also trying to make sure that for those adjacent girls and young women that were actually identified HIV positive, they should actually be initiated on treatment. And we actually saw an increase in as far as the number of HIV abuse offered the HIV testing services and those that were actually identified as new positives. Increasing from 11 in Q1, we're total of about 46 at the end of the year. And we actually also ensured that for those that are actually identified as new positives, we should actually try as much as possible to make sure that we are in line with the global campaign of 95, 95, 95, whereby for 95% of those that were actually identified as new positives, at least they should actually be initiated on treatment. Therefore, as a project, we actually registered 100% linkage rate and 99% linkage rate, whereby about 45 out of the 46 that were actually identified as new positives were all initiated on treatment as the end of the year. So this actually just shows the importance of how we are actually utilizing our data through the situation. Meetings for them for adjacent girls and young women to actually also be able to access linkage services. Out of the adjacent girls and young women who access SRH services and 10,460 adjacent girls and young women were actually access to HIV safety kits. So HIV safety testing was also part of the comprehensive package that the marine power activity is offering to adjacent girls and young women. In the out of the 10,460 HIV safety kits that were actually distributed about 10,253 adjacent girls and young women were able to actually access these safe test kits. And this achievement actually demonstrates about 90 that we're actually able to register in the reporting period. And the next slide that is actually displayed on the screen just actually shows the cascade in as far as the number of test kits that were actually distributed against how many adjacent girls and young women received these safe test kits. And out of the 10,253 adjacent girls and young women who access the safe test kits, 33 were actually screened reactive in the following the safe test. And out of the 33, 30 were actually identified as we're actually confirming the new positive. And all the 30 were actually initiated on treatment. In the conclusion, I actually want to mention the fact that the use of the DHHS2 tracker for systematic as well as periodic granular level data analysis through the structured platforms, such as the weekly situation meetings, that we're actually able to conduct as a project. One, we're actually able to optimize the use of data to actually improve the performance on key indicators, such as the overall reach with the NIH as well as HIV services. And also on indicators to look at the linkage to care for community interventions targeting adjacent girls and the young women. Finally, the process of utilizing data from the DHHS2 tracker helped us to actually be able to identify local solutions. In the end, we're actually able also to strengthen the capacity of the local implementing partners in usage of the data from the DHHS2 tracker. Let me end at that particular juncture and the problem will be hand over the mic to you, Mike, for further questions or comments or probably maybe if another presenter is to present at this moment. Otherwise, that's the end of my presentation. Thank you. Yes, thank you, Nana. So yes, thank you for that. And I think that with your conclusion slide, we're seeing kind of a theme of ways of using tracker data in order to inform monitoring in order to do periodic analysis in order to do follow-up and compare with aggregate data. There are a number of ways to use it kind of alongside other processes to strengthen them. So that's just a theme to point out. We would just mention also for Umbar, our next presenter, we had thought we were ending this session at four o'clock, but we actually will end at 3.45 because we're supposed to go take a big group photo with everybody. So I just wanted a time check there, but Umbar will leave at least 15 minutes for you. But just maybe if anybody has some questions right now for Nanny, anything you wanted to follow up from that slide. One question that we had held over from the previous presentation was about linkages to other programs. Previously, they were talking about TV and leprosy and screenings and notifications. And the question was about, are there efforts to take that data and try to compare it or utilize it alongside some of the other health programs, for example, HIV? So I think we could turn the question around here as well to ask if there are efforts on the HIV side. Are you, is there a parallel tracker system for TV or some other system for TV? Are there efforts to look and combine the data? Are they the same patients population? Just curious if there are any linkages there. Hi, Mike, was that mine? Can I pick up the question? Please, go ahead. Yes. Thank you. Thank you so much. Thanks, Michael. Yeah, thank you for that question. And the straight answer really is that, yes, there is. There is linkage and actually for HIV programming, one of the emphasis is that they need to look at the linkage between TV and HIV. So for example, in terms of screening, all HIV patients are also screened for TV and sometimes vice versa. So in terms of systems, I mentioned earlier that we have an EMR that is doing more or less the clacking of patients, HIV patients at the point of care. And this data that is collected through this EMR is compared to the data that is collected in the TB tracker in our particular case. And I mentioned also that we have done an integration between the two systems so that if a patient's entry point is the HIV clinic and this HIV patient is presumed to have TB and later confirmed to have TB, then that patient could actually exist in both systems but also the management of the patient is on both sides. It's both on the TB side and the HIV side. So this linkage is there, it is happening. For us, we've gone ahead to integrate both systems to be able to follow this patient through the quantum of care. Over. Great, thank you so much. And that's a trend I think that we will see more and more of we started seeing it happen in every country where they're introducing multiple kind of tracker programs that are related that they start to need to be able to have the same patient in both. But there's probably going to be much more opportunities as well on the data analysis side. So that'll be something that I hope to have more for us to talk about as more countries do it. But I think we'd better move on and let Anbar have time for the presentation. Anbar, can you hear us? Is your microphone working? Yes, hello, Mike and... Great, thank you so much. Are you able to share your screen with us? Yes. Great, we can see your screen. Yes, hello everyone. In fact, I'm from Mauritius, I'm Anbar from Mauritius. We have a great, I mean, DHIS2 unit here with several programs being integrated and also we are planning for other programs also being integrated into DHIS2. For the time being, we have Dr. Dina Singh, the DHIS2 focal person is not here with us for the time being. I'm presenting on his behalf and the behalf of the Ministry of Health hepatitis case-based surveillance into the DHIS2 tracker. I'll start by presenting a bit about Mauritius. Where is it actually? Because in fact, I've gone to different countries and most of them don't know about Mauritius. It is located on the south coast of Africania Madagascar and we have a very... In fact, it is a more tourist attraction. Tracker problem. Well, with... Dr. Dina, on the stage. I'm sorry. We have a population of 1.2 million, nine districts and now per capita income is around 8,700 US dollars with an economic growth rate of 3.8%. Our government health expenditure as a percentage of GDP is 3.2% and our health expenditure as a percentage of the total expenditure for the government of Mauritius is around 7%. We were, in fact, based on these indicators, we were driven to be a high income country by... Well, in fact, by 2020, but COVID-19 struck us and is, I mean, other social issues that are going around the world. We have remained our upper middle country and about the indicators of health system indicators with five regional hospitals, with five specialized hospitals. We have one public health institution for every 800 people. Life expectancy is 773.8%. In fact, mortality is low, 13.8% per thousand live births and we have a doctor population ratio of 29% per 10,000 population. In fact, our government is committed to provide universal and quality health services free of any user cost. Our health system is free here in Mauritius. Everyone benefiting from it and we don't have such outreach because everyone is connected to the regional hospitals. Well, why DHIS2? Because in fact, I have been in a training in the DHIS2 fundamentals course and we have ministry has thought DHIS2 to be a very good system for public health reporting. In fact, it is also endorsed by WHO. In 2018, we had the joint external evaluation report by the WHO mentioning that Mauritius needs to upgrade the system of electronic and real-time reporting. So it has recommended for Mauritius to have a robust IT reporting system for the health services and we have got DHIS2 to use DHIS2 for recording public health events. In fact, we have DHIS2 tracker, we have also DHIS2 data set, two different servers for recording statistics and for recording patient data. We have not only for hepatitis, but for COVID-19 vaccination, the expanded program of immunization of infants under five. We have a tracker for HIV and AIDS. We have a tracker for TB surveillance. Then from these programs, why I chose hepatitis C surveillance because it is in line with our SDG target 3.3 to end epidemics by 2030 and combat hepatitis. And we have also been in the verge of elimination of HIV with the Gilead services. We have had the medicines and all that. That's why we chose hepatitis C because in fact, this is a success story for Mauritius to have hepatitis C surveillance in DHIS2. And also, I believe there is no built-in package of HIV, which shows the versatility of the DHIS2 team in Mauritius. To create an interface by itself for each data components into DHIS2 and to show, well, the DHIS2 team in Mauritius is capable of implementing, to develop, to implement and to use the system proficiently. This is some screenshots for our Mauritius HMIS tracker into the DHIS2. The objectives for the DHIS2 to integrate hepatitis C surveillance need for a patient registry. The existing patient registry was on an Excel. And in fact, it was a bit difficult for us to capture all and to report timely for these cases. That's why the DHIS2 was used to collect individual data to initiate reporting for WHO. That's our main concern for using an electronic system for reporting through means of the different components in the DHIS2, the built-in charts, the built-in private tables and all that too. I mean, to be able to report to much standards of reporting and comply with our surveillance system. And of course, to improve the reporting rate. Using the traditional methods of data capture was, it was fragmented, there had been a lot of challenges. That's why the DHIS2 has enabled us to improve our reporting rate and also to be, to increase, I mean, the efficiency of the HCV screening in Mauritius. This is the team for hepatitis C surveillance. We have doctors, we have physicians, we have the nursing aids, all, I mean, all work together into the DHIS2 for data capture, for analysis for reporting. They report to the central level and the central level report to WHO and other stakeholders. They were, I mean, they are the primary persons who collect data who are on field to collect and to record at CV data on the DHIS2. This is a case-based form. This is the dashboard. Now it has, if you can see, slowly we have been working, we have been registering patients and the figures are volatile or changing the charts, the bar charts for registered by gender, registered HCV patients by gender, by age group, by district residents. I mean, these indicators, these charts were not, I mean, were not possible with the fragmented data capture technique, data capture methods, existing methods. Through the DHIS2, this has improved a lot for these indicators. And I believe if there will be requests for other indicators, it will be possible using the DHIS2. We have done a short analysis for our existing DHIS2 system for the tracker programs. The strengths are that we have a political commitment to use the DHIS2. It has taken up to a higher level to use DHIS2. Even the Minister of Health is aware, is aware of and strongly recommends the use of the DHIS2 in the different, in other programs. We have good internet connectivity, high internet, high network coverage to use the DHIS2 in remote, well, we don't have such remote places, but at the health facilities. In fact, in two days on Wednesday, we will be distributing tablets to periphery level for usage of the DHIS2. We have the support of the WHO, the University of Oslo, of course, and the HHSB Uganda for their continued help and support for the development for any issues raised. Our weakness on the other hand, that we don't have much funding. We don't have a dedicated funds in the Ministry of Health budget for the DHIS2. But still, we do have opportunities, opportunities for capacity building for decentralization of the DHIS2 and the integration with the coming eHealth project for the government. We need capacity building for program coordinators because when we will decentralize the DHIS2, program coordinators need to stand alone for the DHIS2 for manipulating, for using, for extending their knowledge into the DHIS2. If they want to create indicators, if they want to amend a bit of their registration form, they will not need the services of the central level of the DHIS2 national code team for that. They will be able to do by themselves. Well, the global fund. We would request the global fund to continue to give their support to Mauritius. And the challenges is still, well, challenges, it's not only for the DHIS2, it's for the health system as a whole that human resources because trained human staff, trained health staff, what they do, they get promoted, they get transferred and they go to a place where the DHIS2 is, I mean, is not operational. But however, in the long run, when if the DHIS2 will be integrated in the whole health system, even if staff are trained for a particular program, this knowledge, he will be able to transmit to the other health programs as well. The way forward is for a capacity building for the DHIS2 national team, which will include the data manager myself and the server administrator. We actually have a server administrator, but it's not, we still experience other issues. We still experience the dashboards being, being not loaded properly. We still, but with the capacity building, with the proper training, we will be able, I mean, be a master of the DHIS2, program coordinator. We need the, we need to integrate GIS and maps into the DHIS2 for visuals of integrators into maps, buffer zones to identify high-risk regions. We are establishing new programs into the DHIS2. The neonatal intensive care unit is in pipeline, cleft lip cleft palate is in pipeline, integrated disease surveillance and response has already been integrated as a data element, as an event data capture. But we will need to, to implement the case-based registration form of IDSO into the DHIS2, for which we are having the workshop in two days on Wednesday. Of course we need to strengthen our HIV case-based reporting in relation to, to HIV and integrating the whole public health system into it. Well, our ultimate goal for the ministry to build a data-driven culture for real-time reporting. And following that, we'll have evidence-based strategies towards elimination of viral hepatitis. This data-driven culture has, is not, is not dated, not dated for, for, I mean, for now it has been dated for long to build it to, to use ID, to use systems, to use electronic system for, for reporting for, I mean, because technology is, technology is everywhere around us. We need, we need to use that, we need to use that out to our maximum for our benefit. And we will, I will end my presentation with the final word of thanks to the University of Oslo for the development and sustaining the DHIS2 throughout. The DHISP Uganda for the continued technical support and consultancy services. Thanks to the WHO for their continuous provision for financial and technical support in terms of consultants, in terms of some finance to use the DHIS2 for workshops. Still the government of Mauritius and the the ministry of health for recognizing the DHIS2 as an adequate and promising tool for reporting. And of course the program coordinators, not only for hepatitis, but for other programs being integrated into the DHIS2 because without their their support, without their help, I mean, it will be the DHIS2 would not have been a success. Well, I mean, Mr. Tilak is here among us. A word of thanks for, for you also, for your support for your technical guidance for the DHIS2 to be a success. Thank you. Great. Thank you so much for sharing us the the hard work going on in Mauritius. Unfortunately, we don't have very much time. I do think you convinced us all to try to have the annual conference there this next year. It looks lovely. And we'll look forward to hearing more about the expansion of your tracker programs, but we will need to close this out. There's another activity. So we're saying thank you. Thank you, Anbar. Thank you to all of the presenters. We really appreciate it. And everyone, please do follow up on the community of practice. You can continue the conversation there. So thank you so much. Please go outside quickly.