 All right, so we'll start with the HIV track of the conference. So I will just briefly about how we plan to get this session started. So first of all, we'll present the HIV case surveillance WHO package to a small presentation on what guidelines are globally available for countries to adopt. Because since you'll gather here from most of the countries, it's important to understand what the countries are actually doing with their national HIV programs using DHS too. So we'll show what's available globally, but the focus would be on how countries have adapted their DHS to practice for HIV and ART care. So followed by my presentations, we'll take few questions if they're there, or else we'll move to the country presentations. We have four countries presenting Cambodia, Indonesia, Bangladesh. They are here, so they'll present. We'll have the national program of HIV from Nepal, joining online, doing a presentation on their national HIV tracker. All right, so for this small presentation, we'll try to introduce the HIV case surveillance tracker, the DHS to metadata package that has been built in collaboration with WHO headquarters in Geneva and the DHS. Through this package development, a lot of guidance is also being taken from the countries to use HIV trackers in countries. And what has been tried to do is to design a minimum data set that the country could use to track HIV patients for case of violence. Of course, when we look at the trackers that the countries use, they're much more extensive. But the idea here is to give a minimum baseline to work with and the country can then adopt the package as per their needs and requirements. Next slide, please. Okay, so the workflow that has been used for designing the HIV case surveillance package, the WHO case, is for the people who are already identified with HIV. So we're taking care of the ART care. So the person is already diagnosed with HIV and the person gets enrolled into the system. And since they're tracking that respective person, we're collecting some personal information, some unique IDs and some information on the ART site or health center where the person will get enrolled for further treatment and follow-ups. Once the person gets enrolled, an initial case report is filed where we try to get the minimum details. When was the patient diagnosed with HIV? What was the age at diagnosis? Some information on the health center and the key population groups a person may belong to. Then once the initial stages, the enrollment and the non-repeatable stage for the one-time event is created, you move to the treatment visit, which is a repeatable event. That means you film it multiple times based on the number of times the patient visits the health center. So you mentioned the date of initiation of treatment, the eligibility for TQT and TB status, the enrollment details on the ART, the viral load details and the prescription of ART. And what was the taste of the last medication day in order to check the adherence of the patient on the ART treatment. Then we have the case follow-ups. So you may do follow-ups, the patient may come to the facility for their ARB refill or you could also do check-up follow-ups and phone or be able to do home visits. So depending upon the mechanisms of follow-up that the national program has in country, you could define that when was the follow-up, when the follow-up took place, what was the mode of follow-up and what was the outcome of that respective follow-up visit. So it could be a phone call, could be a home visit and could be a visit at the facility. So this is the minimum information that has come out of the clinical guidelines that is must have. You could try to track HIV cases in country for their respective treatments and looking at the co-morbidity for TB and HIV together. So since this is the minimum which is available, you can identify the repeatable steps and add more information to these program stages, to these events to have more extensive information on your patient management and patient care. Next slide please. So the idea behind developing these packages was to give the countries a baseline to work with basically. So a country who wants to move from aggregate reporting of HIV to case-based reporting, they do not need to start on scratch. We have a reference available now. So that initial design is already a part of the package which is open for customization and adaptation as per the national program needs. So the package itself can be adapted. So you have two broad ideas which were taken into account. One was surveillance and one was case management. So for surveillance, the idea was to have a documented entry for initial diagnosis of HIV infection as and when the person was identified. And then track the care that was given to the patient over time for the taking of the disease. So you see there in terms of the basic design, you have the clinical surveillance and you have the TPT sections defined. So you get a readyment program which is defined as per the WHO clinical guidance for the minimum data set for HIV care. That could be further extended to include all the additional information that a country intends to capture to manage their HIV cases in the country. Next slide please. So we both are some key features of the package. So of course since we are tracking individuals, it's very important that we maintain the uniqueness of the data. So therefore, the package comes pre-configured with four kinds of identifiers and the country can choose which of the identifiers to use and they can even add their own identifier if there is a separate identifier available, which helps them basically to identify unique cases. So you have the national ID. So if you have the implementation of a national ID in your country, then you can use the national identifier. Health facility code. Now we see that in the health facilities there are ART registers where they also generate a patient code. So that could also be added here. You have program ID. So if a person is enrolled in multiple programs and is given program specific IDs also, then that could also be used in identification of the patient. Then we have the NHIS ID. Many countries have started supporting the HIV positive patients through their health and benefit scheme for insurance. So you can even use NHIS ID as one of the identifiers of the specification. So these are the ones which have been already pre-configured based on understanding that they have received from the countries who are using trackers for HIV. But these are customizable. You could add any more identifiers that you think have more coverage in your country and will help you in terms of uniquely identifying patients. So basically through this package, you're creating a longitudinal tracking of the HIV positive case where you are noting down the patient's access to the antiretrovirals and the preventive treatment that is supposed to take for tuberculosis. So these are the three events, the initial stages I spoke about. You have the initial case report where basically you'll capture basic details when the patient was diagnosed, when the treatment was initiated and some basic information. And then you do a surveillance as and when you reach out to the patient or the patient comes into custody. What's the reason for visit? Has the treatment started or not? And when the treatment was started? And if the patient is eligible for TB preventive treatment, if yes, then we have the questions for the TB prevention treatment section. So you can define when the patient qualified for what's eligible for TB preventive treatment, when it was initiated, what was the regimen given and on what date it is supposed to have completed. And if there is a need to restart the treatment again. Next slide please. Then you have these follow-up visits where for any reason if the person wants to visit the particular health center or the health center wants to reach out to that specific beneficiary or the HIV positive patient, then they could create a follow-up visit and report the information by the follow-up call was made, what was the follow-up method and what was the outcome. Then you can also see here, there are details which are supposed to be added for the treatment status. At least follow-up you update that whether the patient is on coronary artery or not on ART. One was the last viral locus test done if it was less than 1000 ml copies. And for how long the patient has been retained on ART and what's the last day to be ART when the patient was on ART. So these details, some of these are automatically calculated through program rules and logics that have been added based on the BAS data I entered and the latest given which is created. So these logics can also be modified depending upon the country requirements. Then coming to the analytics part of it, there are six predefined dashboards which are part of the package. So they already come pre-designed which have all the charts and indicators, all the indicators conflict with the respective investigations. So as soon as the country starts to report data, these dashboards get automatically populated. Again, these dashboards are configurable. So if you want to make any local changes, all of your people do that. So we're looking at case reports and demographics. ART linkage and retention, viral load, anti-prevention treatment, epidemic status, and health FESD dashboard for cohort management. So each of these dashboards comes with a fixed set of indicators and based on the category, the indicators have been defined and already arranged on a dashboard. In terms of the key population markers, if you see, while filing the initial case report, it can identify the key population for the patient. And sometimes you see that a patient may belong to more than one category. It may be MSM or maybe a person injecting themselves with drugs. So you could identify the key population markers where the patient belongs to and do multiple selections. And of course these can be added for country context. Many times we see that the country is more interested to have one single risk group for their analytics and they don't prefer having multiple disaggregation of the risk groups. But depending upon the country indicators plus the donor indicator reporting, you can modify the key population markers as well. So here are some details where you can get more, much more detail and broader information for this respective package. So you have a link here which has the demonstration instance. You could access the link using, you can access the instance using the below credentials. You know, the metadata files are available on the DHSDROP website. And the documentation on how this package has been designed, what considerations were taken while designing of this package are given on the docs.dhsdROP. So any additional information which is required for the HRD case surveillance package can be accessed forever. So that was the end of my presentation. Before we move on to the country presentations, if there are any specific questions, concerns or yes. Thank you John and I guess a wonderful presentation. Just from my understanding, a couple of things you explained. One in relation to the time of enrollment and then also after the detailed component comes in. I'm not sure what that label was. So you're collecting information on the health center at enrollment as well as at the time of detail and say enrollment sort of thing. So is there a separate segment in terms of the detail of type of health center that goes across those two levels of enrollment and then initiation of treatment. Number one. Secondly, this last slide and that's usually a time that's more of a public health side rather than the information. But classifying let's say a female sex worker or an MSM, while they're also injection drug users as well. So does the system have a protocol of possibly labeling a certain person across multiple populations as well? Is there a possibility in the system? Because that of course then has implications for the containment of the epidemic side of it. So I'm more towards the public health side in relation to that. And thirdly, I guess when they're receiving treatment for HIV plus active treatment for HIV antiretroviral and then preventive treatment for people's roses. So the system which is recording this information would have their sort of parallel streams of working. So there will be treatment and prevention, TB treatment centers, plus HIV centennial sites. So in the system there, does it have a common health facility which has the EPT as well as the HIV treatment thing just to understand the architecture. So those three things. Yes, so answer your first question. So basically, yeah, so you have an enrolling health center with a patient enrolled for the first time. But there are chances that the patients migrate quite often. So you may have what the patient might end up at another health facility. That's our scope of the unique identification of the client that even if a patient makes a follow-up visit to any other health center, then you're supposed to search for that patient and add records against it. So if the service delivery health facility is different from what the enrollment is. So you need to make a documentation of both so that you don't lose track of the records. And of course, you maintain quantity of care for that description. So therefore, if you need more extensive information, then also you can capture those health facilities accordingly. Coming back to your question on the decision on the key population markers. Right now these are just normal data inputs, which the ARD counselor defines based on the assessment that he or she has carried out for that perspective patient. But the system has the capability where you can set up assessment questions. So if a question, if you want to ask questions on the frequency of sexual intercourse is use of injectables and all that, then you could just keep on checking that. So based on the algorithm that the country uses for defining key population group types, then the system can assign the key population group based on the combination of parameters, because one parameter might have a higher level in the algorithm that if it's out of three then, but one carries more weightage than two carries more weightage than three. So based on the selections, you can then assign the KP type from the data assessment. So for the prep assessment that we've done in one of the countries, there they've used algorithm that they ask questions on drug use section and because it's used upon acceptance. And then they define that what could be the potential KP type based on the algorithm. So in this package, it's all manual input. But if you want to implement that in a country, then you can modify and replace this section with assessment questionnaire and then let the system assign based on the responses. Yeah. And the question on the... Yeah. So basically the idea here is to track comorbidities. So based on the experience that the countries have, if they're tracking HIV patients, they also have a subset of information to be kept for TB patients as well. That may be entered by the same HIV center, or if they have mechanisms in the country where the same person can access both the TB and the HIV programs, or you have a separate program altogether for tracking TB, HIV, comorbid cases. So that architecture and design happens based on the discussions on how the country actually functions in terms of parallel programs. So if there is a... can be a mechanism where the TB person can access the HIV records, they can make an update there directly, or the HIV person is doing the entire data and for TB also. Or we have a separate program where you're tracking HIV, TB, comorbid patients. So then you can design your systems. The same person could be enrolled into multiple programs. So I think these considerations are done when enough discussions are done with these international programs, how they operate with each other, and what kind of data sharing they agree upon. So based on that, you could think of the final design architecture for setting up the case events. Okay. Do we have any more questions? So fine. So we can move on to our first country presentation from Cambodia. So like the team member from Cambodia will be presenting to please come on stage. Good afternoon, everyone. My name is Dala. I'm from the National Center of HIV Cambodia. I'm a live IT technician. Today I'm very honest to present the progress of what we have done with the AS2 project called MPI, or Master of Patients Index. Yeah, please. Next slide. This is, I just introduced what we have been doing for our project. We have a Master of Patients Index. At NCHARP Cambodia, we have currently, we have five databases separately. You see, we have for NPD, a National Prevention Database. This one is exceptional. Just let this have been implementing the same in the AS2 version. So it is not a problem. It's not that hard. We have another four separate databases that is a live IT database and offline database. We have BISM, VCT, AOT, and lab. And all the databases, we aggregate all together to the MPI. Yeah, so we got the AS2 that cover all these projects to identify the index of cases. Next slide please. Yeah, this is what we have. Actually, I have highlighted three main points. First, the data I am calling, as I mentioned earlier. NPD is the AS2. So the same AS2 with our project MPI. So we can link together by just seeing the night every night. And other four databases is a live IT database. So we get a backup of the site and upload to the AS2. This switch maybe I would like to detail a little bit. For example, we have separate database and also have a 71 AOT site in Cambodia and separately offline. They are not linking together. So what we are doing, we make up send a raw file with encrypted and upload it to the AS2 and aggregate together. And then the other step, we also have done the direct data entry. It means that before we input the data offline in the old version, we did it best. And now we are developing a direct data entry using DH2. We also have finished this database. And now we are in pilot team for the AOT just in progress, but in a good progress. And at the point we have trained our local team for building capacity. We have been done successfully to cost one online during the COVID-19. And another one we are training at place by UCFH team and also supported by HITS. Next slide please. Yes. While we are aggregate all the database we have form 4 and another one will be in live. The 4 databases also have each framework. All together when we aggregate, we also have to aggregate all the indicators to the project. So this is what we have been collecting for the indicator. So we have totally 49 indicators. And then I will show one indicator for example in the next slide. Yes, by example this is one indicator among the 49 indicators. The indicator of the percentage of the new people live with HIV who have initiated on AOT on the same day. Each one indicator we separated by the filter option. For example, we can filter it by same day one to one day or better than one day. Or we can filter it by problem or by side AOT side, by safe, by KP or by AOT. This is one indicator we can filter it by this option. Yes. Next slide please. Yes. This is the use test that we are managed in our project. Normally we have been created 12 user tests but we highlight for a user that we are normal use, mostly use. For example, we have best, we have data analyzer, data entry and demand user is supervisor. And we have, in this present we have the actor, the user, the line, the line is full access and limit access. For example, you see the guy, for the guest, we can represent through the hair panel or someone who would like to see the report. We can request to our national center for the supervisor that for example I want to check the report or the last board in a province or report related to the KP. So the supervisor, we create a user for the guest for them both from the local fund or from the WHO, they want to get the report or any other side so we can create a user. So the client can see the report, limit it what they are requested. Yes. Next slide please. And it is just a simple screenshot that we have been done for the direct data entry using the AS2. This is just a short for the custom app for AOT, almost the app for our, we are using is custom app. For custom data entry app for AOT, we have to support for visibility workflow to repair the paper form and also to register the report before AOT. Yes, this is the form that we have been done. There are short things like this. Yes, also the custom data entry to support AOT workflow to enroll with the client in AOT to support drag project care and follow up with it. And then another point is transfer before the AID is transferred from a clinic to another clinic across AOT. Currently we have only for public clinic and in future we are also thinking about the private sector, transfer to private sector. Next slide. This is for dashboard. This is the dashboard that we have been developing. We have almost dashboard for AOT and visibility. And also the report, also the custom report app to generate a structured report. This is all the support. Next slide. I would like to summary the activity in the next quarter. And the main point that we are planning doing, we have to continue building capacity building for our BND team that are management officers. We need all the H2 framework before we have been successfully, two main course successfully, but we still need to make our skills solid and stronger. Number two is we are going to complete the testing of implementing dashboard indicator. We have not yet finished in this point and we have to complete. We have, we are going to pilot the identity on AOT and enroll at 7th sign in January. We have been piloting but AOT, we are going to pilot in January. And we also need to create a step down training to our data anti-club, to our professional manager, and also for the counselor to understand the H2 framework. The number six is we are going to scale up the pilot for data entry from at least 30%. This is the main challenge that I just summary. The building capacity is always in the main point. Building our capacity that we have become stronger and we can continue working on the H2. And another one is the lab that I mentioned earlier, the lab is cum-led. So we are going to aggregate the lab into our BSU and also the offline data entry. Also, it's our challenge of the, you know, the offline app. Currently we have three custom apps, AOT, VG and reported, but the custom app is not working with the offline mode. So it is also the big challenge. In Cambodia, there are some province, some sites very long distance, they cannot have the smoothly internet access. Or sometimes the internet disconnects for one month, for example. So we cannot work with the AS2. Yeah, that is the big challenge. Yes, thank you. If you have any questions, please write up. Thank you very much. Interesting topic. So I want to question what you saw the architecture before assuming for the data entry like the architecture to the AS2. The question is simple. That's the data is the real time where the input is direct to the AS2. Or you have the time for maybe one hour to hour for the updating the data. That's the question for the update data. Updating data in the AS2. Yeah. So for paper and then for the update of solicitation, the analytic. Yeah, that's the real time or not because we help them. Yes, thank you for your question. For the data entry, we are using directly direct data entries. You can say that not a real time. We just have one hour or one day sometimes or three days for data entry and put the data through the system. Currently, we have two people working. One is a doctor or a counselor that working with the patient. They fill the information through the paper and another data entry club have the paper to input through the system. That's why the data will be direct through the AS2. But not the same time when we interview with the patient and input the data entry when the patient comes. It's not the time. But the data entry going through the system. You mean the real time is like this. Yeah. So it is answer to your question, right? Yeah. Thank you very much. Thank you very much for the questions. So now we have a Bangladesh Kaleem online who will be sharing the HIV experience from Bangladesh. Good afternoon. I am I am from Bangladesh. Are you listening to me? Hello. Hello. Hello. Hello. Are you listening to me? Yes. You are clear. Okay. Okay. I am sure my visualization. Are you seeing my skin? Yeah. We are seeing the screen. Okay. Thank you. Thank you so much. I am a we're just getting receiving some echo. I'm hearing you. Aladdin, you're not playing it back to yourself, are you at all? Sorry. Sorry. You haven't got any, you haven't got your speakers on at the moment, have you? In my side. In my side. I am hearing you. In my side. Bear with us just a minute, hang on. I wasn't going to work for a while. Sorry? I think you are logging in from in two systems. Log out from one system and then it will be perfect. Yes, online participant can hear. But two voices are coming. Okay. Hi, everyone. I'm from Indonesia. I'm part of the research team in Indonesia. And it's another for me to present you about our use case experience or best practice using the exercise tool for the district level, HIV program integration, especially in the Pasar Bali, Indonesia. It's like this. Right. So for the outline today, I would share about the background current state, the implementation, the usage, and also the key results that we are going to share. Okay. So Bali or the Pasar is one of the city in Indonesia. It's maybe you guys always heard about Bali. It's one of the eastern part of Indonesia. And in the area, there are needs to validate and monitor the HIV program in the district of Pasar. And for the national level, the data has been collected through an app called HIPH information system or SIHA in Indonesia. And they built their own systems. But this app met stakeholders in the regional level or in the district level, hard to or difficult to access the visualization, and the analytics sort of things. Since the access to those information system or SIHA information systems can only be accessed by the HIV program officers. So for the stakeholders who are going to see or get the analytics or know more about the data and monitoring the program, validating the program itself, it's really difficult for them to access. And for that case, the stakeholders has high dependency to the program officer. While on the program officer has so many programs ongoing, so they cannot provide analytics as easy as possible to the stakeholders. Another thing, program officer lack of capacity in providing the analytics to the stakeholders. And also for now, there is no special HIS in the primary healthcare facilities. So it's really challenging for them to collect all the data in one single system. So and also the data also being collected using the PCT or voluntary consulting testing and healthcare workers initiative on consulting testing. And it means that they do have the data in hand, but no tools available to help them to provide the stakeholders, the analytics or to monitor and validate the program. Next, please. Yeah. So if you can see the graphics right here in the office, they use the Excel spreadsheet to generate the graphics. So it's take a lot of time to provide the stakeholders, maybe you, the colleagues here already experienced the same thing that a program officer in the healthcare facilities are not able to provide easy to access visualization. So and also the data are fragmented between the systems. Some of them are paper-based. Some of them are already in the system, but they cannot get the information holistically to the stakeholders. While on the other hand, of course, as I mentioned before, stakeholders always need to access information quickly. Since they want to discuss with the governor, for example, they want to discuss with the mayor or the ministry of health. And also from the data collected so far, the more key population identified from the data that was collected. Next, please. So we started the planning organization using this method different work, planning, organizing, acting and controlling. For the first phase, we assess the health information system in DEMPASAR and also determining the requirements in the area. And also we discussed with the district health office and also healthcare facilities, all we call PUSCASMAS for the primary healthcare facility. Next, please. And for the organizing phase, we start to do the procurement. We start the internal discussion for the technical teams. And then for the next phase, we start the collection for the data forms for visualization needs. After we get the needs and requirements, we, of course, we create the data elements, categories and sortings to start use and import and validate the data. Next, please. So when the actuating phase, the first one we made the data visualization based on the data source from the programmer. We create a number of data visualization and that supports based on the requirements provided by the program team. And the second one, we conducted the internal discussion with the staff's program regarding the needs of the indicators. So we sort of map the indicators and the needs. And also the last one, we use the dashboard to disseminate and we train the staff levels to use the dashboard. Next, please. For the controlling phase, initially, yeah, of course, we are not get the, we don't get the real-time data updating yet. Since we still use the aggregate data and it's updated on a monthly basis every 15th in every month. But for the monitoring and evaluation, we used to provide the stakeholders that every, we used to provide the stakeholders about the progress of the ongoing data collection in a weekly basis. So for the implementation, this is the aggregate data that focusing on the key population we identified. So maybe Surab last, the previous presentation mentioned about key population. In Indonesia, we have this around key population including the transgender customers, sex workers, TV, pregnant women and transgender to be connected to each other and provide the visualization to the stakeholders. Yeah, so this one is the visualization for the pregnant women, especially as the key population, because the stakeholders need to meet the minimum surface standard of each regional Indonesia that they need to integrate every program to HIV, for example, pregnant MNH maternal and neonatal program to HIV-AIDS. So next one, please. And also the TB tuberculosis program also need to see the integration between the HIV program that they are implementing in the area. What are the connections between TB and HIV and the data itself? Next, please. It's the same thing with sex workers and men have sex with men's population as well and transgenders and IDU tested for HIV. Next, please. So what I want to mention is that in Indonesia, the key population, for example, let's say transgenders, they also have customers. So this one is really evolving. The data is increasing year by year that they need to identify about the increase of the HIV cases for the people with transgenders, sex customers and also sex worker customers. Not only the sex workers, but also the transgenders customers. So here is the usage of the visualization in the dashboard. As you can see here, it's around 211 and 217 for each during the, I mean for the latest one, the November 2022. Next, please. So we conducted also the capacity building for the stakeholders and staff levels to see and how to use and how to access the visualization and later on the next, please. One of the stakeholders said that with the HIs too, now anyone who handles a program within the Pasar City can also answer how many HIV cases in the city and also its connection to the key populations. So it's not only accessed by the HIV program officer but also accessed by anyone who handles the program. Next, please. So for the next strategy, I guess the first one is that we want to integrate the other program like nutrition program and also utilize and improvements, data quality improvements and sharing also best practice how we use these systems and integrate the HIV programs. And also as we know that we do have now the HIV package from WHO, so that will be the next step that we are going to reach. And also, of course, since this is still in the aggregate level data, of course, the next step will be in the individual data. But I know the challenge is, of course, the systems itself because on the national level, they have their own systems. So the HIs too here, it just helps for giving you an example how the stakeholders in the regional level can use that to support their day-to-day monitoring and validation of the program. Next, please. Yeah, for the key results. So this dashboard actually about the integration of HIV program already integrated with what they call DRAC or DEMPATSAR health response information when all the health systems together in one DHIS too as a data warehouse. But for the specific TV use case, we integrated this program with pregnant women TV and other key populations. And now as the results, currently the stakeholders at the provincial health levels or city levels can access the visualization and make the decision or create the recommendation as well as monitoring or validating the programs that they already implemented in such area in the DEMPATSAR body. And now, yeah, I think that's all for me. Oh, good. I already explained all of the things. Thank you, Sirat. Thank you. Your presentation is pretty useful. But I just like to know more about, can you come back to the slide? You said that the family meal, can you come back to the slide? You said, yeah. Yeah, thank you. As we can see, that's most of the users, they are using the visualization to look at the data. And I just would like to know more in the September, you see, in August, the number of users, they are pretty high. And then going to the September, we see that the view of the user is down. So what happened in September then? Yeah, thank you so much. So actually for these two months, it's actually one of the time frame that we implemented this DHS to the team. So we conducted the training. Of course, they can create all more a few of the visualization and last part and the time. And that's why the next one maybe is slightly down to, oh my God, slightly down to around 100, or less than 100. But of course, with those information, we got that, why is it decreased? So we conducted, again, like capacity building or we follow up the stakeholders and the program officer that here's the tools that you always can use or you always can access. So this is also the main point that we need to ensure in our every program implementation in Indonesia that the importance of following up of the program or the implementation that we have. That's it. Thank you for your questions. Any more questions? All right. Thank you. So we will go ahead with another online presentation from a colleague in Nepal, Dr. Keshav, who will be presenting about DHS to track using Nepal plus some HIG drug resistance research that I've been using DHS to our national health. Hello. Are you listening to me? Yes. Okay. Should I start? Yes. Yes. Go ahead. Okay. Hello, everyone. I'm Keshav Deova and I'm working as a senior strategic information specialist at National Center for AIDS and STD control, which is especially my work is related to global funded programs. And today I'm presenting about the use of DHS to track our international HIV program and how we are using the DHS to tracker for research and survey purposes. Is my screen sharing sort of? Yes, Keshav. We can see your screen. Okay. So I'll repeat this. This is my presentation outline. So I'll describe about how we build a DHS to tracker based information system. We don't see a full screen. It's coming into the preview mode. Can you please make that change? Okay. Did you move this one? Now, can you see the screen? Yeah. Perfect. Please go ahead. Okay. So, and I'll describe about the features of our developed system that is DHS to tracker, mobile health and biomedical system. And we'll appreciate about our implementation experience at the national level and our lesson lot and our ongoing efforts to strengthen information system of national HIV program. So why we build this DHS to tracker information system is that like once individual infected with the HIV, see or he has to enroll in treatment for whole life. So recording up treatment details and analyzing reporting its outcome using paper based registers is not feasible. Let's say like someone is on treatment for like more than 10, 15 years. And if we, you know, try to monitor those, the patient progress or on treatment, it's almost impossible using paper based registers. The second issue is like about, you know, if someone is on treatment for whole life, their movement is obvious from one district to another district or from one province to another province. So that if there is no electronic system, then it's difficult to track, you know, their movement and this might result in, you know, the reporting of same individuals from multiple sides that result in overestimation of ARD coverage or double reporting of same patient or client to the system. So another important thing is like we invest a lot of resources, you know, to improve the life of the patient or client so that they can be, you know, improve their retention in treatment. So by using paper based registers or aggregated data, we don't know in real time what interventions or programs are working or what's not, you know, or not possible to know if we want to intervene, if someone is not retaining on treatment, if someone is experiencing also like at the national level, what are the reasons for the treatment failure. So it's impossible to, you know, to use the data by using paper based registers or the availability of aggregated monthly reporting system. So also another important thing is like usually we get, you know, from Nestle and Samas the monthly reporting about like how many of the patient are on treatment, just, you know, to analyze that detail, it takes a lot of time, you know, to prepare report manually and submit the aggregated monthly data to the system. So it's really difficult if you really want to intervene to reduce loss to follow up or missing status of the client. So all these, you know, challenges are really important is related to paper based register or, you know, monthly aggregated data reporting system. So to, you know, address these challenges, we develop the concept and what we plan is to, you know, develop the information system based on DSS tracker and to improve the retention, integrate the mobile health within the tracker and they also link the biometric system within tracker and generate monthly report within the DSS to national SMIS on a monthly basis. So this was the concept node to really implement this we collaborated with the HIST India and we developed the system and roll out at the national level. So these are the features of the developed system. And firstly we, with this, with the close support from HIST India we, you know, developed third party SMS gateway and linked with the DSS for sending SMSS and we also, you know, developed the script to identify the patient and type of messages to be sent to them and the frequency of SMSS to be sent to their mobile phone. And another important thing was like we also, you know, integrated the biometric system within the DSS tracker so that they can, you know, interact or interoperable within these two systems, they can interact with each other and share the recorded data. So these are the steps and all the, you know, code are available in the Github. If you want to know more about it, you can access and the link is provided here. And this is the features of the developed system in the left side. It's a, you know, the DSS tracker where the users can have to log in and the record the details of the client if someone is coming to the health facility for the HIV testing or if someone diagnosed with the HIV positive or receiving HIV treatment services the users use SIV AIDS.gov.np and they log in all the required information and also the Zava-based application develop for the biometric and the same login is used in this app and, you know, the collect the biometric information of the client. So these both systems are interacting with each other and can also share the information. So the, as I mentioned earlier, the biometric system we use is to help us to identify existing patient and also help us to access the patient dashboard in DSS to tracker. And it also helps to add, you know, a new patient into the system and link that information, patient data details into DSS tracker capture. And it's also help us to, you know, refer the patients if someone is coming, patient coming from HIV testing sites to ARD sites and the, these biometric system also helps to use to, you know, record the client code and identify that patient's record, recorded in another site. And similarly, this is the, you know, in DSS to tracker features. What we do is we can register and enroll the patient in the HIV program and we have like different program stages. Here I have shown the program stages of HIV testing and counseling, if someone is positive and enrolled in the treatment, then what are to fill in in the ARD follow-up. If someone is like pregnant, then the SI positive mother is pregnant, then we can also add their pregnancy details if someone is like the HIV mother delivered baby. We also add about their details if someone is dead and we also record their discontinuation of follow-up details. And this system also help us to refer clients between STC to ARD and ARD to ARD for follow-up visits. And it also help us to send, you know, the electronic records between the sites and between one districts to another. So mobile health can be used, you know, to schedule the text messages reminders to the mobile phone client for specific purposes to improve the retention in HIV treatment. And we send two types of messages. One is appointment reminders for pill pickup or viral load testing. And second one is about general awareness messages about positive prevention, importance of regular health checkup and all the developed text messages are in Nepali. So after like developing this system and we implemented, first what we did is we identified the big ARD sites in the capital city and piloted these in three SIB treatment centers and we also developed user manuals in Nepali and English to guide health workers to use the system. And we also, you know, invested the required necessary infrastructure, servers, biometric device and to, you know, to securely save the data. And then we had like a central team at the NCHC and the partners with technical backup from East India to support the sites. And we also provided, you know, to roll out the develop system in all its advertisement sites by one site coaching and we also provided several trainings and the resources allocated from the government and the other partners, technical partners, global fund, FHIR, self-care foundations, they also allocated resources for training and roll out of the system. And immediately after the roll out of the system and we got, you know, feedback from the sites about, sorry, how to remove this one, about like, especially about complaining about the double-recording system because they also have to record data in the paper-based registers and also in the Azure Tracker and some of the remote hilly and mountainous areas, they also have like, you know, poor internet supplies or slow internet speed. And when we rolled out a system in 2016-17, there were already lots of, thousands of, you know, PLSIB already on the treatment. So the health workers need to, you know, get all used back-dated data online. So it takes around, you know, 50 to 60 minutes to enter back-dated data. This was also issues from the health worker side. And incomplete information were there in the paper-based registers. So there was nothing to add in the registers. And there was, in the beginning, we also faced issues of Nepali date to the AD date in the system. Later, this issue was addressed and regarding mobile health, some of the PLSIB denied, you know, providing mobile numbers due to fear about disclosure of their HIV status because they face the stigma and discriminations from the society. And some of the PLSIB complained about the frequency of the text messages delivered to the system. We also updated this one. We reduced the frequency of delivery of messages. The interesting thing was we thought like a few of the clients would, you know, not allow us to take their biometric system. But till then, we haven't received any, like, you know, complaint from the sides like the certain or any individual client refused to provide biometric fingerprint. They actually accepted it after briefing the proposed and the processes. So regarding, we also faced some issues, not enough time to enter data into the systems. So health workers working at this treatment centers are also overburdened due to other responsibilities. And another big challenge was we trained one health workers and there was like high turnover of staff at the site. So we need to immediately implement another training activities. And to address these data recurring issues, we also hired data recorders for the period of one or two months so that all the backdated data can be entered into the system. So after like few months of rollout, we were so excited to, you know, get all the details complete and accurate timely reported data to the system so that we can generate all the, you know, monitor the progress of key indicators. But immediately, you know, after like few months of rollout, we faced like very slow progress in data recording in tracker. And when we call site to query about slow processing system, most of the health workers even don't remember wiggling for tracker capture. That was like really frustrating. And in summary, like not all site excited and happy to use DSS to tracker. Not much excited as us working at the center, you know, especially those officials working at the center of province were so excited, but not at the site. So what we then we try to talk with them and then we why they are not excited. They were not excited to enter data. The reason was like, because we never care to answer their main questions during rollout of system. That is why do they use this new information system and provide additional time considering their workload. So we never care to answer these questions during trainings. So during rollout, we focused on our advantages only at the federal level, such as use of individual level data to monitor treatment outcomes at the federal level. There are the regime and info to help us to provide information for procurement generate real time information about PLSI in the country, but we never care why should they use this information system. And then we started immediately organized several trainings and then we motivated sites. We started to focus on answering key questions like, there are like different reasons why site must use this information system which will provide resources to convince health workers sites that information system was developed to reduce their workload and support their day-to-day operation of services. So we also prioritize data use plans as sites. And we also help them to inform them like sites can generate monthly report with one click and upload it to the national system so that they don't have to prepare report in SMIC format manually. We save their time with aggregated indicators and individual level data patient for response. And we also developed site-level dance board. And we, for example, to show the list of clients who need attention based on the parameters of retention and treatment, adapting to dispensing practices, biological separations and all-time field pickup they can easily identify those clients. So we have also implemented several capacity development activities. And we developed YouTube videos how they can develop monthly report and upload it to the national SMIS. And we also developed, you know, these how can they monitor the different indicators for early warning indicators. If someone needs client is already return on the treatment or not. If someone is not, how do they identify the individual details? And these are the few pictures that of our capacity development activities we implemented in all provinces of Nepal. So what happened is like we developed that, you know, the system in HIV testing and treatment sites. But there are lots of other activities happening in the country of the prevention, HIV care and support. So we just getting data of these three components. But big of activities related to prevention were missed out from this tracker. And then we developed a plan to integrate form for whole HIV care continuum. And we worked with all the partners. Those who are working in this field and develop the forms in this tracker and rolled out in all districts and all services managed by NGOs. Hello. Someone is speaking. Okay. So please go ahead. Okay. You will have to wrap up in two to three minutes please. Okay. So these are the advantages. And we get, you know, real time data at the different levels. Currently we are like generating monthly reports from the tracker to the national system. And from dashboard alerts, health workers, HIV treatment centers or sites, you know, they can easily identify wound, you know, client to focus on to improve their root condition, identify the patient with unsuppressed viral load, which requires their attention and supports overall optimization of patient care. So this was our experience. And I've like provided the link here of our user manual, our YouTube channel. So considering the time limitations, I'm not going to go into our like how we are using these DSRs to tracker in, you know, planning and implementing HIV drug resistance after like developing DSRs to tracker inform system. We use this tracker for, you know, conducting HIV drug resistance at national level. This is just, I'll summarize in one minute. This, you know, explain about how this tracker help us to develop sampling frame and also in the randomly selecting sampling technique for the study populations. And maybe I can present this in like another platform, but I'll share this slide with SORA and you can access these slides. This is really, really important how we can use DSRs to tracker based information system to conduct any research at the health facility for survey or sentient surveillance. It greatly reduce the time and cost specific to development of sampling frame, sampling techniques and data collection. For example, our lesson learned or operas use can be replicated in other survey research at the health facility such as WSU recommended point for valence service when anti-biotic use in hospital CDC. But I'll present this in details in other forums. That's it from my side. Thank you. Thank you, Keshav for insightful presentation. Any questions for the Nevaldin? Thank you first of all for the presentation. Presentation is very interesting, especially on the fingerprint scanner. And my question would be on Nevaldin because we're also interested in that. The question is were there any resistance from, I don't know, from the government or from other ministry or other partners or even clients on the using or keeping the fingerprints and what was your response? Thank you for the question. So due to timely limitations, what happened is like missed the acknowledgement. We developed this system with the leadership of HMIS. Our HMIS director is there. Anil sir is there. He is like supporting us throughout the process. And we also received the support from the another NCHC government authority. They also supported us and they own the whole process till the like development of, you know, the user manuals to establishment of the shopper at the government sites. So that part we didn't receive much resistance. Another part is like we work closely with all the partners, like those who are working in the field of HIV from the beginning, like from AIDS Healthcare Foundation says if it's a 360 save the children and also close to work with the key populations. So we didn't receive much resistance, specifically related to, you know, entering data bag, you know, backdated data into the system because of, you know, lots of work responsibilities of health workers working at the site. But we solved that by hiring the data recorders for short period of time. That was resistance and another challenge is about you know, geography. We have like huge remote hilly and mountainous areas where we still we don't have like, you know, good internet facilities there that also, you know, to get all the complete data from those sites. So those were the big challenges and another one is like the main challenges for we get for all health programs, you know, the height on our rate. You have to frequently train them and the new health workers. Not from like the macro level, the issues like not accepting the whole ownership of the process. We didn't get that one because we involve all the key stakeholders from the beginning. I think in the presentation, we highlighted that for collecting the biometrics. The people did not give much assistance. They were okay to share. And then the decision to implement biometrics was made in discussion with the ministry and the HMIS team. So that's why we took implement here. Any more questions before we start controlling the session? Okay. So we have two questions from the online chat. One is for the Indonesia team. How many are the centers are there in Indonesia? So if you could answer that question. How many are the centers are there in Indonesia? How many are the centers are there in Indonesia? How many are the centers are there in Indonesia? I don't know. I'm not sure about that. Are there any antiretroviral therapy? It's, yeah. So, okay. So ART center in Indonesia, it's attached to the healthcare, I mean hospitals. It's like around more than 3,000 hospitals. Okay. So I think the OCA, the second question was, how does the OCA work in Cambodia? So at present, I think the OCA app is not in use in Cambodia at present. So I think that's the answer. That's OCA app. Usually it's for designed in Laos, which is basically used for the desktop version, which collects offline data capture for aggregate and events. For the tracker, we haven't designed anything yet because there is also challenges about how do we link the tracker institute or the person. If your person is registered in one particular place, how does it get synchronized, the security issues and all the things. So that's why we haven't really touched that one yet. So we are focusing only on making the direct data entry, the online version first, and see by the time how best we can try to enable internet access to the ART site. Because ART site is located in main centers, which is basically either a provincial hospital or a high level ART hospitals are not located in the health centers. So I guess like for offline data entry should not be focused on. We should like actually make sure how can they get internet, especially when there is patient based data stored locally. My friend about the biometric that the HHS can take biometric type of data. Sorry? Biometric, say the making finger. So biometrics data like I know like we can, but like let me find the relevant person who is actually hiding his face. Biometrics data in the HHS. The question was, can we use, can we collect biometrics data in the HHS? Yeah, well, so we right now, there's no kind of integrated way to do it. We are talking a lot to other potential partners like Simprints and others, and we might find a way to integrate. I know the Simprints team have done successful integration with the HHS team and we are exploring a collaboration with them, but there is no sort of existing native integration for this in the HHS to as we speak now. So any questions online? It's all the question done. The coffee is there so we can for break. Yeah, so thank you. I hope the session was insightful. So the presentations are uploaded on the website. They will be available to you and the online participants also. We can proceed to the break at the end, so thank you.