 Good morning. Good afternoon. Good evening, everyone. Welcome to the second webinar of the Tracker Use Academy, conducted by the Hisp Asia Hub. So in today's webinar, which we hope to do in like one to two hours, we'll focus on introducing you to the major features which are available in Tracker, the DHS2 Tracker, which covers both the web and the Android, and also to show you some new features that we are currently implementing in the latest versions of the DHS2. So this two hours webinar, we mainly try to focus on introducing these concepts by using a presentation. And towards the latter part, we will have a question and answer session where we will be able to take few of the questions that you have and probably go a bit deep into these features based on your questions. So if you have any questions about what we are presenting in the first one hour, please ask them in the chat so that we can take them up once the presentation is over. So I hope we can start. So the objectives of this webinar is to describe what DHS2 Tracker is and to understand how DHS2 Tracker can be modified based on your country's requirements or your organization's requirements and to describe examples of how DHS2 Tracker is used in different countries, so in different programs and to describe the features of the DHS2 Tracker. Now, first of all, what is DHS2 Tracker? So hope you have some idea about what DHS2 is used in the aggregate context as well as events probably. And if I assume all of you must have had some experience in DHS2 Tracker or have followed our Fundamentals Academy. So what DHS2 Tracker does is to allow for the collection and analysis of identifiable individual and longitudinal data. So this is how it differs from the DHS2 events concept that we mostly focus in our Fundamentals Academy. So here we are talking about identifiable individual and longitudinal data. This means we can create unique shared records that relate several different services to the unique record we are tracking. I know this description sounds a bit abstract, but if you can focus on what we are showing here in the screenshots, you can see that here we have a profile of a person named Brian Treffery. So what we are trying to do as a basic component in DHS2 Tracker is to register an individual. It could be an individual or it could be any entity. Why I say that is like commonly DHS2 Tracker we are using in our practical use cases to track people longitude. But it doesn't mean that we cannot use DHS2 Tracker to track, say for example, commodities like laboratory samples or say logistics, some equipment. So all these things for all these use cases we can use DHS2 Tracker. So when we register an individual or an entity, we can collect some properties of that individual at the point of registration. For example, as you can see here, when we are registering this person, we are capturing some properties or attributes of that person such as the age, gender, country of residence, et cetera. So this is what the tracker is capable of registering an entity or a commodity or a person. And then we can track them longitude and read across the time period. Say for example, if this person is registered in a health program, he may be having follow-up visits or like say laboratory visits. So at each of these visits, we can capture different fields such as some information attached to data elements across time. So this is what the DHS2 Tracker is capable of doing. So in this presentation, we will go through some of the examples of what we can do using the DHS2 Tracker features. The features unique to the DHS2 Tracker, we can schedule visits for various services and send them automated reminders based on these schedule visits. So these visits could be say pending clinic visits. So if you have a, if you run a clinic in our health program and if you want people to be sent reminders, it could be SMS reminders or email reminders. This is possible using DHS2 Tracker. And tracking missed and upcoming visits. So in our clinic, if we have a list of patients who have upcoming visit or like probably we have another group of people who have missed their visits, using the Tracker, we can track them. And we can also create reports displaying both individually identifiable and aggregated data. So you know very well DHS2 is really powerful in creating aggregate reports using Tracker. We can even expand it further by creating reports based on individual data. We can also support data quality and decision support during the data collection. If you're familiar with any health or non-health program, you know like that the point of data capture is the place where you can make most of the mistakes and it can really affect your data quality. So DHS2 Tracker is capable of applying some decision support mechanisms as well as things like validation rules at the point of data capture to enhance the data quality. And it can also send notification or alerts based on data within each individual event. So let me take for an example, we want to send a SMS reminder or SMS notifications once a COVID-19 vaccination has been completed. A vaccine event, say a first dose or second dose event was completed at the vaccination center. The person needs to get a SMS alert. This is possible using DHS2 Tracker. I assume you can all hear me because I'm seeing in chat there are some participants having issues. Could someone confirm that you can hear me? Yes, great, thank you. And the tracker is not at all about data capture. You can also analyze the data using the DHS2 Tracker. So I mean, there are different ways of doing that. So for example, all the data we collect for an individual level is automatically aggregated based on predefined parameters. So these predefined parameters we can configure when we are customizing the DHS2 Tracker. For example, if you register a set of people to a health facility or a vaccination center, and if you want to get aggregate dashboards, so you are familiar with what the aggregate analysis can do in DHS2, so the same things that we can do based on the tracker data. So once the data is captured at the health facility or the vaccination center, we are able to generate aggregate analysis such as dashboards which are available to the vaccination center or a higher level such as district or the province. So this will happen automatically once you configure the tracker. And both aggregate and individual data can be viewed and analyzed within the DHS2 using the built-in tools. So the built-in tools that we have include the dashboards, tables, charts, and maps. So this is something very similar to the analysis that we are doing in the aggregate component of DHS2. So it's just a matter of configuring the tracker to kind of build the aggregate analysis based on the individual data. And also you can export the data that is collected in the tracker to an analytic platform of your choice. So it could be a simple Excel export. And even we can create some advanced integrations in the DHS2 API which we are not too much focusing in this academy, but of course we will definitely show how to take data as an example. Data ownership. So data ownership is a major concern when it comes to the tracker or case-based data. So the ownership comes at different dimensions. One thing is the ownership of the data within the system as in like who can see the data, who can edit the data. So the DHS2 tracker contains some granular sharing settings that allows the administrators to define which organization levels, which organization groups, and which individual users or user groups can access specific kinds of data stored within a tracker group. So with that we can kind of restrict which set of users have access to which data and which organization units will be able to have access to the data. So by the ownership of the personally identifiable data is kind of preserved and the confidentiality is insured. And on a different dimension, the hosting of each DHS2 instance is handled by the owner organization. Say for example, the Ministry of Health of your country is the owner organization which will be hosting the DHS2 instance and they can define their own parameters for data storage in accordance with the local laws and privacy concerns as per the country requirements. And whether it's hosted locally within the Ministry of Health or YCT department's premises or in the cloud. No outside entity and I must mention including the DHS2 software developers can access the data unless that data is specifically granted by the owner of the database. So that's how it is worked. This is free and open. So software, but it has been designed in such a way that only you or your organization can access this data once configured properly. So now that I have mentioned some some overview of features and capabilities of DHS2 tracker, how are you going to customize it? The information and the workflows that are defined within the tracker are completely customizable. So DHS2 tracker is a kind of abstract concept and set of tools. And you have to configure it as per your country's organization's requirements. So this is what you are trying to master from this tracker course. So this course is specifically about the features of tracker and how to use the tracker. But we have another DHS2 online academy which is for the tracker configuration where we will be going into depths of understanding how to configure the tracker program based on your country's requirements. And to facilitate this, we have a number of standard digital packages which are also available as a starting point that can be freely modified based on local context. We understand that DHS2 tracker configuration would be a bit of a difficult task when you are new to DHS2. But now we have also seen that most of the countries are having a similar set of requirements. So for example, almost all the countries in the health domain, they have immunization packages, EPHIV, Manila programs. So all these programs tend to have a kind of a generic set of requirements and a generic set of data collection forms. So what the DHS2 team has done is to make a kind of concept called packages. It's kind of a bundle of configuration which you can download and install on your DHS2 system. So once you do that, you can get your DHS2 tracker programs, say for example, TV, up and running in no time. But the challenge is like if your country has some data collection forms which kind of deviate a bit from the standard package data collection forms, we have in the DHS2 standard package distributions, you might have to configure or edit them a bit. But of course, once you follow our DHS2 tracker configuration academy, or else you can even follow the documentation. This is not so much of a difficult task. You can definitely do it. So these packages are developed based on the inputs from the partner organizations, including WHO, CDC, UNICEF, GABI, et cetera. And the scale of DHS2 tracker. So something that we really have to be concerned about is whether these tracker programs are scalable. So as of now, DHS2 tracker is used in more than 75 countries and in the States. And these countries and organizations which are already using DHS2 aggregate, they can leverage their existing infrastructure to implement tracker programs without needing any additional software. So what I want to say is if you have a DHS2 tracker configured, sorry, DHS2 aggregate configured for your country and you are deciding that you should now try to implement DHS2 tracker, you won't be needing any additional software. But perhaps you might have to consider like what will be the resources, the hardware resources that you need to have in your hosting environment. So this is something that you will have to be concerned about because especially when you are trying to go for a national level tracker. But again, this is a kind of a stepwise process. So you can see based on your scale, you can even, you might have to scale up your hardware resources as well. But other than that, software-wise you won't need anything else. So the DHS2 tracker is in fact a collection of different co-apps and features. Now we have a set of applications for data collection. So these include for the web version, DHS2 capture app and the DHS2 tracker capture. For Android, we have the DHS2 Android capture, mainly for data collection. We have some data outputs applications or softwares, basically applications within the DHS2 co-software such as charts, tables, maps and dashboards. Now every release of DHS2 involves updates to these tools and we will also, in this presentation, we will talk about some new features that have been incorporated to these applications. So this is something that you will have to be concerned about, especially like if you are active on DHS2 community or if you are kind of focused about different updates that are sent out from DHS2, you will get to know what will be the latest features that will be included in the next release of DHS2. So depending on that, you can decide when your country needs to update for the next version to get the best out of the latest features which are included in the tracker applications of DHS2. So that is why being open source software and having open source community, you need to be a bit agile and check the updates of the latest features which will be released in time to come so that you can plan and advocate your ministry of health or the organizations when you can plan to update the latest version of the DHS2. So next we will try to go into the features which are available in each of these co-applications. So first we will discuss on the DHS2 capture applications and DHS2 tracker capture applications which are available in the web version of the DHS2. So DHS2 capture app, you must have definitely seen it is an application that has undergone several versions of development over the last, across the last few DHS2 version updates. So as of now, the capture application is able to register new track entity instances and enroll them into the programs. And also you can search track entity instances using the tracker capture. So if you are new to the DHS2 tracker concept, you can think of a track entity instance as a person. So basically we can register persons into tracker programs using the capture app. And also we can search persons using this application and also you can list and filter the people who are enrolled in tracker programs. So these are the main things that we can do using the DHS2 capture application. So in the next few slides, we will be demonstrating some screenshots and the functionalities which are possible in each of these applications. So the capture application is possible using the capture application. Traditionally we were able to create events and capture event-related data. So this you must be familiar if you have been using capture application. This was what the capture application was conventionally available, was possible to do. And now of course we have, other than this, we have integrated the tracker data capture. So you can capture data related to a tracker program. So as you can see here, we have the child program, which is available at this Yellowhorn Community Health Center. And there we can even capture some enrollment information that we capture when we register a person into this program. So this is possible in the capture application. And in addition, the application is able to generate pattern-based identification. So for example, if you can see here, we have the unique ID that the system has generated for this person. So now DHS-2 is able to, when we are configuring the DHS-2 tracker program, we can define the patterns. Say for example, as you can see here, we have in this example, 08-2021-DD1833. So here this is a kind of, this ID is following a generic format, which are delimited by the dashes. So this happens based on the configuration of the tracker program. So when we are configuring the DHS-2 tracker, we can define what is the pattern, a unique ID should follow. So once that happens, when every time a person tries to register a new track entity instance, the number is automatically generated. And this is possible using DHS-2. And in addition, the DHS-2 is able to identify the duplicates when a new person is being registered. Say for example, because especially in large scale trackers, there is a high chance that a certain person can be registered again in a different health facility or even in the same health facility by mistake. So to prevent that, we now have, this has been available in the last few versions as well, but in capture, it is possible to detect a duplicate registration at the point of the data. So next we will introduce you the application, the front-end application that DHS-2 has been conventionally using to register and track and record individual person's data. So this application is tracker capture. You may be familiar with it, but if you are not familiar, I will briefly mention what you can do using the DHS-2 tracker capture. So DHS-2 tracker capture is the principal application that has been available on DHS-2 to capture tracker related data. So using that application, you can register persons and you can capture the information for different events. So these events could be considered as follow-up visits in a clinic setting or a laboratory visit and the data that we capture for a laboratory request. So this can be anything. So all this information can be captured by using the tracker capture application of DHS-2. So as you can see here, what you are seeing here is called the track entity dashboard, or you can even think of this as a persons dashboard in the DHS-2 tracker. So here we can see what the person is enrolled to which program. It could be a child health program and it will also mention what are the other programs this person has registered to. Say for example, a person could be registered to COVID surveillance program, EB program, malaria program at the same time. Or even it will show what are the previous programs that person has enrolled to before. And in addition, we also have in the track entity dashboard component where we are capturing data. So as you can see here towards the left lower part, the tracker data entry widget is where we are capturing the data at the health facilities. And in addition, towards the right side you can see there is a particular widget to enter or edit the profile information which has been already captured at the registration and also to show the relationship. Relationship as in like what we mean by relationships in DHS-2 is like who are the other persons this person is related to. So this could I mean I don't mean it is like a family relationship kind of like sibling, no not like that. But like when we are capturing data in health programs it could be like in say for example if I take the COVID as an example, we can register a person for COVID surveillance or COVID follow up. And if we also have a few other programs say if we have a one program for contact tracing and what we can do is like if another person B is registered in the contact tracing program we can create a link between the person A being in this tracker program and the person B with the relationship called he has been in contact with. So this is something generic that we describe as relationship in DHS-2. So we will talk in depth about what these relationships are during our course. So in summary using the tracker capture we can review the targeted dashboard and we can review the program indicators as you can see here it could be the person's age which is automatically calculated based on the date of birth which is captured at the registration and today's date. So we can review the indicators and feedback we can manage all enrollments of that particular person we can manage relationships and we can even enter event data for tracking. So we will quickly go through a few of the features available in the tracker capture application. So one thing is we can compare repeatable events during data in. So if you are new to DHS-2 tracker you may be wondering what we mean by repeatable events. So let's focus on this example. So this example is from an antenatal care program. So in the antenatal care program in health services we have the first visit where we capture a series of information. So here we can see in the box number one the person has already attended the first antenatal care visit where we have captured a lot of information and after the first visit what we usually have is follow-up events. So in this follow-up events we can have actually many follow-up events during the course of a pregnancy. So in most of these events we are capturing the same information but this capture happens at various visits. We may capture some information in the third month, say six months likewise. But it's the same information it's just that we are tracking that information long it. So what can happen is like if the patient comes for the second follow-up visit it might be important for the healthcare worker to have a quick glance at what was happening in the previous follow-up visit. So this is possible in DHS to track a capture using this compare repeatable events where as you can see here now we are capturing the data for the antenatal care visit two where we have all these boxes and onto the left side we can see what were the information that were captured for the first visit. So always the health data enter the person who's doing the data entry he can compare the data as he's entering data to the data visit. So this can come really handy and to prevent some data quality data errors at the point of data capture. And of course DHS to tracker has advanced concept for sharing. So what we mean by sharing is using this concept in DHS to we can define which user sees what data, which user has access to which data. So this is a very useful feature to ensure the privacy and confidentiality of this case based data. So there are so many concepts in the sharing which is sharing concepts is a broad thing which I'm not going to go into too much of detail but I will just show you few screenshots of what is available and what you can do using the sharing concept in DHS too. So using the metadata and data sharing concept we can control who can see the registered individuals. So for example as you can see on the screenshot we can register a new person by default into the capture program in the capture application. That's the default functionality of the capture but like if we don't want a particular user or a particular group of users to register new persons but we just want them to weave the registered people we can do that. So if that's how it is how the tracker program is configured you will be able to see as in this screenshot below like when that person tries to register a new person he will be able to say he will be displayed a message saying you don't have access right. So this is not only applicable to registration you can also do it for the specific program stages. So what we mean by program stages is like say for example in the previous example we took about antenatal care the follow up visit. So we can decide we can define when we are configuring the DHS to whether a person will not be able to see any information at all related to the follow up event or he will only have weave access to the follow up information or he can actually enter information for the follow up stage. So this is all configurable in the HHS too. So as you can see here for this ANC registration this person is able to enter data that's why all these boxes are white and you can nice to see that he has entered data. And if the person is only having weave access this is how he will be able to see he will be able to see the data but all the data entry fields will be grayed out and you only will see the data but you can't enter or modify any data. So that's kind of the configuration we can achieve by data sharing in the HHS too. And in addition this can be even expanded so that even within the analysis application we can define who is able to see the data. This can come very handy in case we want only the facility people or people in healthcare institutes where the actual data capture happens for them to get a line list of persons but to prevent someone who is at the district or provincial or national level to generate a list of very sensitive patient personally identified information. So we can prevent it by configuring it in such a way that inside the analysis application who or which user group is able to see the granular level data. This is possible in the HHS too tracker. And of course you can always have a persistent top bar while entering data. So what I mean by persistent top bar is the bar here right at the top, the horizontal gray bar where you are seeing the first name, last name, birth, date and city. So why this becomes handy is like this information that we are displaying in this screenshot information or the attributes that we are capturing at the registration. But when we subsequently enter data at the health facilities related to the various stages like say for example a follow-up visit usually we don't tend to see the attributes that we captured at the registration. But just to clarify whether am I entering data to the correct person it's very useful to have this information displayed right at the top as you can see here. So this is possible in the HHS tracker and this is what we mean by having a persistent top bar which is configurable. And another very useful feature which is currently I feel underutilized is this concept called breaking the glass. This again is a functionality which has been available if I can recall correctly from the HHS to version 2.29 it has been there for couple of years now is a functionality again to ensure the privacy and confidentiality, security related issues. So what we mean by breaking the glass is typically the person who is having access the data entry user who is having access to his institute or to his vaccination center to his health facility may be required to have access to another patient who has been registered or been generally followed up in another health facility. So this is something that we might have to allow in our routine operations but then again this can have some privacy concerns in some setups where why this user from another health facility is having access to another to a person's information who is being followed up at a different health facility. So to avoid that you can configure the HHS to where if a data entry user tries to search a person registered outside of his organization unit but still wants to look up that person's information and probably into some information to that person we can prompt a screen like this where that data entry user will have to mention a reason why he is accessing that person's information. So it is locked into the HHS to we can even configure say for example we have some configurable options as mentioned here it could be open, audited protected or closed in the event of configuration as it closed he will not be able to actually open that record open if it is configured as open you can without entering any reason or anything you can look up that information and enter data but if it is audited or protected you will be prompted to enter the reason why you are searching a patient's information outside the scope of your organization unit. So these kind of features are already available in the HHS to and of course audited data values. This again is regarding the privacy and security so again I am emphasizing because this HHS to tracker always deals with case based information that is why we have all these features and that is again why we are demonstrating them in this webinar. So we can talk about the changes that happens to the attributes and the data elements. So attributes are the properties that we configure or enter when we are registering a person. Data elements are the information we capture in follow up visits. So whatever happens in the attributes and the data elements so it could be creating and entering a new data into the attributes or data elements so all these are locked as as audited information in the DHS to track. So this is what is shown in this screenshots. So if someone wants to go back and see who has done some editing or change who has changed the data of a particular person you can always go back and check and that is available as audit log and also you can shift between several data entry votes depending on the program requirements and user preferences. So this comes in handy because tracker is a kind of an abstract concept. It's very generic and when you try to implement the DHS to tracker you might have to be sensitive to the user requirements or the program requirements. So what we try to say is like the data entry screen of the DHS to tracker capture you have several views. So for example there's a view that comes by default is a longitudinal or timeline data entry where you have these boxes which are of different colors which you will have so many boxes if and one box put it into each of the with it we capture data right. So some people may like it but others will not like it they will like to have a kind of a row like row by row data entry or they might like a tabular user interface so most of these are supported in the DHS to tracker capture. So the typical scenario is you will have this timeline data entry and this is what you see by default in timeline data entry but you can change it to a different view based on the user's preference. So for example what you are seeing here is like again in the same timeline data entry but you are entering data for one person in just in one row so people may find this easy when they are entering data and this is definitely configurable in the tracker capture dash the fragmented dashboard itself so they can select this particular view and enter data if it is more visible to them than the default timeline data view that is available in the tracker capture and also if they prefer so this is again demonstrating how it how it is visualized when you have this configuration but if you want to have a tabular kind of user interface for tracker data entry this is also possible by enabling the tabular data and you enable the tabular data entry this is how the data capture interface will be visible and again new functionality which has been again around for last few versions of DHS to assign the events to a particular user and enabling a custom working list for that user so what I mean by assigning an event could be like say for example in the laboratory so if you are having a program a tracker program configured for the laboratory you might want to assign a particular lab sample to a lab user if you have five users you might want a lab request to one user another set to a different user so this is possible using the tracker capture using this assigned user function as seen on the screenshot number one and the number two and three are related to having custom working lists so for example if another person logs in and he wants to have it this is all related to the listing the front page so the front page listing we can configure it in such a way that you can have a custom working list with a different layout say like we may have a default layout where we may be displaying few of the attributes for the users but when you have a custom working list we can define what will be the attributes based on a filter criteria what are the track entities what will be displayed in my view so this is what I mean by custom working list and this is available in the DHAS to track and again the concept which I highlighted before about relationships so this relationship is is a concept where we can create a link between two track entity instances right so for example we have a person who is registered in the surveillance program and we have a different program for contact tracing and we find a person who is already registered in the contact tracing program and we want to create a link say he has been in contact with it is possible to create this link within the DHAS too so this can come in handy especially with the relationship analytics which is being developed right now which is still under development so and even like we will be introducing you to few DHAS to custom applications which have been developed by some of his organizations which are using this relationship analytics visualization so these could be achieved by creating the linkages between the track entity instances and this is possible by using the relationships functionality of DHAS too and so again now we are demonstrating here how a person can be enrolled to multiple programs so for example if the person is already enrolled in the case based surveillance has seen here and we want to enroll him to the contact registration follow up we can just do it by clicking on add new button so that way we will be I mean once that person is registered here we will be able to see that person the registered program as the other program I am not going into too much of details because this will be demonstrating during our course and of course we can display live indicators and program data values so what we mean by indicators you must be familiar with the aggregate indicators in the DHAS too but program indicators is a calculation that can happen real time while you are entering data so typical use case would be like especially when if you have your date of birth which is captured at the registration and you want to display dynamically once the data entry user is entering data the patient's age as of today it could be configured in DHAS too as a program indicator and we can display it in the indicators widget of the tracker capture or tracked entity dash right so these are kind of I mean it is dynamic and it will be displayed real time based on today's date and in addition we can schedule visits and track pair status so as you can see here we can see that this person is having has already had a vaccination event on September 13th and he has pending event which is scheduled on November 22nd and also inside the tracker capture we are able to visualize what are the pending events or scheduled events for vaccination so that way we can even see per person what are the future scheduled events and also like in a kind of a list view about all these scheduled events and tracking another cool feature which is available in DHAS too is to send reminders based on scheduled visits so this can happen say for example like we can configure the DHAS too in such a way like especially related to the program stage or event completion to send an alert then and there say for example once vaccination data is captured for the dose number one and when you click on the complete button we can trigger an email OSMS to be sent to the person's mobile so this is something very straightforward which is sent as a notification real time or else we can configure in such a way that at a given time of the day all the notifications will be sent as a bulk to the scheduled events this can come in handy especially to send reminders of upcoming events or vaccination or some health event to the clients this is possible using DHAS too and in addition there are some functionalities to enhance the data quality while capturing your data so as you can see in this screenshot and the gift image like when the person enters today's date and again today's date and select the type of the vaccine the batch number and the expiry dates are automatically calculated so this can come real handy especially to speed up the data reposes as well as to prevent the errors that could happen at the point of data entry these are all configurable in DHAS too and you can configure it the way you want and again we can show feedback so this feedback could be a warning or particularly an error so for example you can see in this screenshot at the bottom you can see here in this yellow color box it says the client has received their last dose please consider completing the stage and probe so sometimes like we find it very difficult to make the data entry user to click the complete button once they have entered all the data to inform or to officially agree that the data entry is complete but this is something that the data entry people usually miss so we can kind of have this prompt displayed where they have entered all the information like he has come to the data part of data entry screen to display a message like this and this again is configurable right so so far we have discussed features which are available in DHAS to capture and DHAS to tracker capture the web version of DHAS to now let us look at what are the functionalities which are available in the DHAS to Android so this part will be done by Saurabh so over to you Saurabh I will stop sharing Thank you Pamu for taking the first half Hello everyone thank you again for joining the webinar so I'll continue with the presentation for the next set of slides that we have hope I am audible to everyone so we'll talk about DHAS to Android to start with as we've seen with the web version the Android application works with all the three data models which are available in DHAS to that is the aggregate data model events model and the tracker data model both online and offline depending upon the internet availability there are some tailored user interfaces which are custom made for mobile data collection which the implementations can take benefit out of and more recently there have been advancements made in the Android app to support offline analytics within the track identity dashboard so that as the end user is reporting data he also gets some meaningful information out of the data that the user has been reporting for each patient so it's useful when using the Android app for collecting data for long-term care programs so as you see in the screenshots we you can assign various color schemes and I can store the programs and currently in the events data model you can always you can use simplified icon sets to capture your data for events so in case you want pictorial collection of data so you can associate color and an icon with your options in an option set and you will have interface which you see on the second screenshot so you have kind of a intuitive and pictorial data collection mechanism which also can be configured in case that is required as per the program needs all the configurations that have been done on the web are fully compatible with the Android application with some considerations so for the implementations who already have their web systems implemented and they do plan to reach out to the community now through the Android app they should ensure that they particularly test their configurations on the Android app before they start the rollout because there are some considerations which are required in terms of the program rules and the indicators when you make a switch to a hybrid mode of data collection between online and offline data collection so once you kind of test your configurations on the Android app and a few modifications might require might be required to do before you go to live data collection so the Android app will allow you to collect track data offline so if you're collecting data in absence of internet connection then there is a database which is available in the mobile device which keeps it which keeps the synchronized copy the last synchronized copy available on the web version and it is available to a user so anytime a user goes to the field before moving out to the field through the sync function a last available copy of the records on the web instance gets downloaded to the Android device so that if you're searching for patients in absence of internet you have access to that respective patient's data already stored in your mobile device so that you can access the patient make updates offline and then you can again synchronize your data in presence of internet connection so the updates could be pushed to the patients to whom you have interacted with today so these mechanisms help you to collect data offline and then synchronize with the data available on the web server then one of the most important features is to avoid duplicate beneficial registrations so the search and the adding new patients and searching new patients is part of an integrated search mechanism where before adding a new patient you start with entering the records or entering the information for a specific person and the system or the app would run a search for you already from the existing list of patients which are available in the app in case coincidence or coherence is found with an existing record the app will give you that the search result and tell you that a person with the same information is already available but in case you realize that this person is different then you can go ahead and register the new person and all the attributes which you had filled while doing the integrated search they are carried forward to the registration form automatically so you can do an integrated search and register function through the mobile app and as we saw on the web version there is a track identity dashboard for each individual person that you are tracking similar interface of mobile form factor of a track identity dashboard is already available where you can see the key details of the person and what all events or services a person or a patient has already taken and what new visits could be added or scheduled depending upon the program workflow in recent versions of the android application map views have been added as a new functionality set where when you are adding the coordinates for each patient you are registering these coordinates are then plotted on the map and you see these icons representing each patient so you can collect these spatial information in two ways one is through coordinates of each patient or you can also capture polygons so you can see the patients which are captured in a specific polygon or specific area and you can even see the pinpoint location of each patient where the person was registered so during the community outreach or you doing community programs you can capture the residential location of each patient and you can even analyze the data as per the location and more recently the google maps app has also been integrated so in case you are on the field and you want to know the estimated distance between your location and the beneficiaries location then you can always do search and the app will take you to google maps and it will give you an estimated distance between your present location and the beneficiaries location so these use cases these requirements were critically reported during the covid times when for example HIV patients the patients couldn't visit the health facility for the ART field pickup so these functionalities were quickly developed and added so that wherever in the implementations we were using android devices the health workers could reach each beneficiary and can make use of the integration with the google maps functionality to live use to see the distance between them and the beneficiaries residence the android app allows you to take pictures and store them against the data elements but you can also search or read QR codes and bar codes and you can use them as unique data points for beneficiaries or you can capture them as information for maintaining stocks for different batches with different use cases where you can use these QR codes and bar codes we kind of used these functionalities in registering patients through their existing master patient index card where they had a QR code with all their information so it was used to read patient information from existing health cards or national ID cards and even the use case also applies to various LMIS context where you can scan the batches or bar codes of each commodity and make a record of it so this particular feature can be used as a unique attribute to search or read data for a specific patient or a commodity in terms of the interface with different rendering types available so when you create a drop-down menu or in the HSO terminology what we call as an option set you can render the option set or a drop-down menu into different ways it could be horizontal radio buttons could be vertical radio buttons could be horizontal checkboxes or vertical checkboxes so there are multiple options available in which the options can be aligned there are some considerations here that you need to have a maximum number of options so that the interface doesn't get splattered when you are arranging them by horizontal vertically so you need to take things into consideration that your option set should not be a very long list of drop-down items so that it doesn't really kind of looks more less intuitive or less user friendly so these functionalities are available but the use depends upon the use case and the desired outcome which is required out of these functionalities then as we saw in the web working list we have a custom working list filters available in the Android application where you can filter your records by different dates by organics by user assignment by their completion status so there are multiple filters available by which you can create your working list so if on the Android application I want to see that next week to how many pregnant females I have to visit and do home ANC visits so you can put filters in terms of visits scheduled for ANC and you can put a date filter and it will give you a filtered list of beneficiaries or patients those you're supposed to visit and collect data and provide services so you can create custom working list in the Android application then as I mentioned before there are new developments being done to support local offline analytics in the TEA dashboard so you can have a look at key indicators either as single value items or you can see charts to see the evolution of data elements in form of bar charts, line charts and more particularly the use case is more suited to child growth where you're collecting parameters like weight and height and you can calculate these anthropometric measures like Z scores for all the variables weight, height and age and those could be used to plot the data on the local devices so you can always see the progression of child's age through the anthropometric measures but you can also plot the different variables for say NCT like blood sugar blood pressure so any value which you're capturing it could be plotted into different forms and it could be utilized for measuring the progress of the patient across the different important key indicators that you want to track for that specific person more and more features are being brought into make the device more handy for a health worker to analyze the patient's data and make useful decisions out of the data which is being captured then after android we come to the visualization tools as most of us who are familiar with DHIS2 are aware of the visualization modules which are available so we have a data visualizer which allows us to create different kinds of charts and the pivot table is now also available as a chart type within the data visualizer app then you have event visualizer and event reports which allow you to analyze data for different events and then we have the maps app which allows you to plot data specially both as thematic layers as heat maps and you can also use event clusters if you're collecting coordinate based information for events and environments so we would be covering in the academy the apps which are helpful to do analysis of tracker and events data so these sessions will be taken in detail so if you are planning to visualize tracker data then one is collecting individual information and using individual information for making decisions but of course when it comes to program level monitoring and evaluation we do need aggregated summaries of the tracker data so you can create program indicators which are basically your aggregations of the case based data which are collected and you can also create detailed line list reports where you can select pick and choose your variables from the event reports app and create your line list for the variables which you want to plot and generate a register for each specific program or a program stage then we have from the option sets or the drop down menus or the coded values that we collect through our data input screens we can very easily visualize the standard responses so for example the example which has been shown here is for COVID vaccination so there are different candidates available for COVID vaccines which are being produced by different manufacturers so if you want to see the consumption of different COVID vaccines by the manufacturers then you could very easily aggregate this data and put that data in form of charts and tables through creating these program indicators so the more codified data you collect the more easier it is to analyze that information by aggregating that information for consumption for making decisions so you can create indicators through both tracker and aggregate data so that is what we call integrated analytics where for example you want to create coverage indicators for COVID vaccination and you want to see the coverage of vaccination across health workers, across general population so your population data or your denominators come from the aggregate data model while your tracker data model will give you the sum of doses given by each respective person category so there you're using two different data models and you're combining that to build your indicators which can give you your rates and proportions and coverage indicators based on the requirements of the program so within the same report you can triangulate the data coming from tracker and you can pull in the data from the aggregate data sets and you can generate your outputs and use them in your analytics so for example if you see these the pivot table which is shown below so the people receiving first dose so age 35 to 34 this is coming from the tracker data model where we are combining the patients who were given the first dose and who belong to the age group between 35 to 54 and then we have the population estimates stored in a data set in terms of the eligible people under this age group who are eligible for getting vaccinated and then we are combining these to this program indicator and this data element to create an indicator to give you the value for those coverage amongst 35 to 54 years of age packet based on the eligible population so like this you can combine the information from different data models to do integrated analytics then from your raw data which are collecting you can apply different disaggregations depending upon the program you can create multiple disaggregations for age group and gender for example so you can create these flexible age bands through legend sets so you can either have an age band which kind of aggregates patients into information such as 0 to 4 5 to 14 15 to 24 and the same information can also be presented into a different age band 0 to 5 6 to 11, 12 to 17 so it depends upon the age brackets which you want to create you can create different age brackets and analyze the same information in different ways so this is the flexible disaggregations which are available which can be applied to the raw data which you are collecting then through the new event reports which was introduced from version 2.34 the support for enrollment analytics was also added earlier the event reports only used to show data for individual events but from 2.34 onwards you have enrollment analytics also added to the event reports where you can pull data from different program stages into a single event report for example we are creating a summary table here for COVID patients where from stage 1 we are capturing data for their underlying conditions from stage 3 lab is that we are collecting the type of test that we did type of sample that was taken and from stage 4 we are collecting the health outcome so from different stages we are selecting our data elements and we are combining them together into a consolidated line list so this these consolidated tables can now be created in event reports by selecting different data elements belonging to different stages then we spoke about the maps application so the maps application would allow you to plot data both as an aggregate layer that is a thematic layer to generate heat maps but you can also track your individual data by creating these location based clusters so when you are creating your program indicators for seeing the total cases or total people vaccinated then you can create these thematic layers and to see the data for the samples but in case you are capturing coordinates for each event or each enrollment then you can create these clusters which are basically a congregation of all the patients who share similar locations through the coordinates and then we create these clusters so these clusters would show you the total number of events which have happened in that specific location over which you can also add filters you can only see male events so you can do that and you can also create these combined clusters to see the proportion of cases by the specified type so if you are seeing by gender then it will give you a proportion distribution between the male and the female cases and if you want to see by any specific filter which involves option set or drop-down menu then those disaggregations could be plotted as clusters as well. So it could be whole clusters where you just see the total number and you can disaggregate or you can drill down to an individual patient or it could be donut-like clusters which give you a breakup between different drop-down options available so both the mechanisms are possible here to analyze the data for track of programs. Then of course as we saw yesterday in our webinar in many of the implementations the custom maps were put into use so for Nepal for the HIV use case we saw the biometric application is a custom map which is being used with the DHS to track the capture in Laos we saw the use of QR codes and generating vaccine certificates that was done as a custom map and similarly as we see here in Mathu we are using a custom map to generate the COVID vaccine certifications for the beneficiaries who have taken the vaccines. So in terms of the platform the DHS to platform and track capture are both extensible you can make use of the existing setup to build more apps and integrate those apps with the core data model so that your custom requirements can also be fulfilled along with the basic use case of the collection and management for any health or non health use case. So these are few examples where these custom maps were developed which were required to carry out more detailed analysis of COVID-19 data so the COVID-19 relationship is a custom web app which is available on the DHS to app hub the concept was to link the index case and the various forward contacts available and then creating such network diagrams to see that for one specific case ID what was the case type where the case was located and to how many people the case was connected to in terms of the contacts and there are algorithms which show you the different dimensions of closeness between business and the scores these are some custom applications which were developed by partners at Public Health Institute in Norway and even his Sri Lanka and his teams developed similar application for doing the COVID-19 relationship tracing where we could see each individual index case and to how many index case was this contact to how many contacts was this index case and you could even see the index case the details and you could go back to tracker capture and see the additional details of this respective index case so these functionalities are not part of the core as of now but depending upon the situation and the requirements and the criticality of certain use cases web apps are being developed more recently which work in interaction with the DHS to databases and moving forward these functionalities are always put on the roadmap to make them as core features so that within the default product these functionalities are available for people to utilize for different use cases now we come to the other side of things where we talk about more of continuous improvements that we are making to the DHS to framework the team at Oslo has set up a performance unit which basically works largely taking help from larger implementations to analyze different parameters on how the system is performing and how the system is behaving to larger datasets so the new tracker data importer has been optimized to kind of cater large sets of data import into the system the tracker search engine has been revamped there are a lot of improvements we've made to kind of which are basically at the backend level where the port has been written smartly the redundancies have been removed the query optimizations have been done with respect to the database the indexing patterns have been changed and the database locks and contention improvements have been made over time to ensure that in use cases such as COVID vaccinations or COVID surveillance or routine disease surveillance where you deal with lots and lots of cases the system response is as fast as quite by the end user to keep using the system in real time and not really use it as a secondary mode of data entry when he's kind of maintaining things on paper and then again doing the data entry at the end of the day so to avoid that double burden on the health workers continuous improvements are being made to improve the performance of the tracker then the API usage in the new tracker app which we'll just see on the next slides is being revamped to kind of save the entire events right now when we use track capture we see that each field that we fill it turns green that means each value is saved separately but in the new the new captured app which will include the tracker model we'll see that the entire event will be saved at once so that the frequent interactions with the database are kept as minimal as possible from version 2.34 these enhancements were rolled out for the community and this is just a diagram which shows the response times between the version 2.34.3 and 2.34.4 so the red bar that you see is the time taken the response time in these different functions that the system performs on users commands has been reduced significantly as compared to the 2.34.3 so these enhancements have been taken up from 2.34 and they are part of the latest releases for example 2.36 right now so it has been suggested for all organizations all countries planning large tracker implementations to stay close to the latest DHS2 version so that they can benefit out of the performance improvements that have been made out in the latest releases then we have started with planning the upcoming features in a much better way we are working with the team at Oslo we are organizing these feature prioritization workshops where each of us his groups work who continuously work with ministries of health in the partner organizations are giving our priorities to the developers at industry of Oslo and they are kind of building DHS2 roadmap which has a score for each prioritization each priority or each feature request that has come from different his groups and the higher the score the earlier the functionality would get implemented into the upcoming releases the team at Oslo is working on building schematic for DHS2 development in terms of the roadmap and the features which are covered in that specific release so it would be open to public very soon where they could see the different features which are planned in each release so that they could plan their implementations and their applications accordingly for those specific features that they are looking for a new event reports app is under development right now there are user experience managers and DHS2 experts at Oslo and representative from his groups who are working with the development team to design different wireframes and creating a functionality stack where the event reports app is kind of being revamped to give a more modern user experience and more similar look and feel as a visualizer app so that all the apps look on the same user interface the same UI and we are also trying to work on integrating cross program analytics right now when we do analysis of track the data it is restricted to one program so we can we can either see data for program or TV program but moving forward we would be able to see cross program analytics where I can see if the same patients are enrolled in the HIV program and the TV TV program so we can see data across programs then we have the event reports so this is the wireframe diagram of the new event reports app where you can see that you will be able to select the program dimensions from the left hand side and the main dimensions which you select for org unit and programs and you can see the time dimension in terms of what dates you want to utilize for your analysis then you will have a similar interface as you see in the new visualizer app where you can drag and drop the dimensions and you can select your input dimensions from the left hand side and you can see that you are looking towards the release of the new tracker web app so as Pamuk showed in the beginning that we do have a capture app now which is basically being utilized for event data collection but now that is being scaled over to tracker data collection as well so we have the main teams which are covered are the track identity centric dashboard which would be cross-programmed so we will have a person summary dashboard which will have information, key information for that person across programs so if I am enrolled in HIV, TB and diabetes programs for example then all the key parameters which are covered in each program for me would be shown to the clinician or to the end user so that they could see an overall picture of my enrollments in the system in different programs. The duplicate record handling is being improved, we are also working on use cases where batch entry is required where same set of information is to be added for different patients so that use case is also being taken into account this is more for the education use case that we have recently been working with where you have similar data to be reported for multiple students so we require a batch entry so that use case is also being taken into account for in the new tracker app that is being developed you can filter the organity by different programs the performance and the user experience are the key parameters which have been taken into account in developing the new app so these are some of the screenshots of the new app which is expected to be out for use from version 2.37 till next few releases both the apps would be available for consumption because it would take some time for the users to get transitioned to the new app so it would involve a lot of capacity building effort so keeping that in mind the both the apps would function but given the rich features which the new app will present to the end users and the program managers we kind of expect that we will see the transition from the old app to the new app in coming years so this is the version dashboard which gives you information for different programs where at all the information for this person has been captured along with the person's image if there are any notes which have been added in different programs such as key information such as allergies my paths history or anything which a clinician should know who has been interacting with the person for the first time then you see that in the notes section and any relationships which exist across programs which are listed here on the right-hand side then we have the enrollment dashboard for the program where you could see the different stages that have been created for this specific person and we now have a dedicated sidebar which will show you the feedback which is coming through the program rules which could be errors or warnings any feedback which have been set in the program rules indicators for BMI or any indicators which you create for monitoring the key parameters of each patient and the person profile so you can create different events for each program stage and these are now bundled together in the person dashboard so giving you a look at the latest program stages or latest visits for each program stage which have happened and total how many events have happened for lab monitoring how many overdue how many are scheduled and when was the last update made so this particular user interface will now be introduced in the new captured app for maintaining data for each person this would be the new person the person's enrollment dashboard with the data for stages and events the duplicates would be handled much better now so while you're registering a person into the program you'll see the details of that the potential duplicates which are there for that respect to person and you can also view the dashboard and the programs in which the person is already enrolled so that you can decide that whether this is already an existing person which you're trying to add so that you can stop there and review the person record which is already existing or you always have the option to save this as a new person and the enrollment in the program that you're going to do that so this would be how the duplicates would be handled in the new capture app so again on the top you'll see that this record would be a possible duplicate of another person when you will have functionalities to flag duplicate records and you'll see the flag over on the top and if you find out eventually that the person is not a duplicate you can always mark this person as unique so a lot of features which were missing from the old tracker capture app and the technology stack was old enough to not do any updates to the old tracker capture app hence a completely new version on the latest technology stack will be rolled out pretty soon so that the community can take advantage of the new functionalities and the new user interface then as I mentioned it will allow you to do nine listing data entry so in the traditional tracker capture app which we use right now we see most of our data entry mechanisms are from top to bottom but here you can also do left to right data entry depending upon how your program is designed and the number of data elements which are there so depending upon you can configure your view modes and you can enter data accordingly whichever mode convenient for the end user to enter the data for we have seen many large scale implementations in last couple of years to name a few the MR immunization campaign for measles and rubella that happened in Bangladesh where 400,000 sites and 35 million vaccinations happened where each child was resistered and vaccinated Shilanka core vaccination program was one of the national implementations where 60,000 doses or patients were resistered each day and 16 million people were tracked for their core vaccination Rwanda did a similar implementation for covid case of valence where 1.5 million people were resistered and the core vaccination was at a much larger scale where 100,000 people per day were getting resistered and these are the specific targets which the program has set so the stories for these implementations have been given on the DHS2 website the links are embedded here the presentation will be shared with you so you can review these stories and see how these implementations have been our testing areas to learn from these implementations on the performance enhancements which are required in DHS2 and what lessons we learned out of these implementations are now getting implemented in the new versions to enrich the functionalities of the software moving forward deduplication was an important piece which was missing in the old traditional tracker capture that we are currently using so process is already under place to kind of have a fuzzy search and matching mechanism to identify the duplicate records and have algorithms which could match the values across the combination of different attributes so name, age, sex, date of birth mobile number so a combination of these attributes can be matched to identify potential duplicates and a background job is being developed which would help you to give kind of a report that these are the potential duplicates that have been identified across the programs and how these duplicates can be merged so we could there would be two options available where we would suggest candidates for automatic merge and then you will have options to manually control the merging of identified duplicate records so these are some of the enhancements which are being planned over the next few releases so this was the last slide of the presentation if there are any questions please feel free to put them in the chat box you can also leave questions on the Academy Slack channel and the questions channel we could take up those questions across the Academy next week when we cover specific topics related to tracking use but if there are any questions right now we do have some time to take those questions and do further discussions if there are any queries or any feedback which needs to be shared so thank you for your patience I will have a look at the chat box if there are any questions no I don't see any questions right now do we have any questions okay so in case we do not have any questions now I think we have almost reached the end time of the webinar so again I would request you to put questions on the Academy Slack channel and we will be happy to answer them and once again thank you for attending the webinar today and we look forward to your participation we look forward to your participation in the Academy beginning Monday where we take you to the onboarding process and the introductory sessions on the tracking use training so we have one question on cohort analysis from Tracker yes so in program indicators now we have boundaries available where you can define your cohorts through the use of boundaries so you can define the patients that you are looking for for example if you are tracking your tuberculosis patients then you can create a cohort of the people who were registered during quarter one last year and what has been their outcome in the same quarter next year so you can create your boundaries when you are creating a program indicators and when you select your analysis time periods then it will give you the number of patients based on the boundaries that you have defined so the session on creating these program indicators is part of the Tracker Configuration Academy that is due in December so you are more than welcome to join that academy and this particular use case for cohort analysis is covered in a very detailed manner in the program indicator section in the Tracker configuration course okay so I don't see any more questions so I think we can end the webinar for the day and we look forward to meeting you guys on Monday when the academy starts so thank you very much for your time today and have a good day ahead