 Alright, so I guess we'll start with the most awaited word of the day. So the word of the day is a word that we have mentioned during the session. So it's probably towards the, like once you are done at least half of the day. We'll be mentioning the word of the day and the word of the day is what you have to mention under the attendance for that given day. So let me start with the word of the day and the word of the day is Covishield. So this Covishield is a vaccine that is widely used in most countries in the south and southeast Asia. So most of you must be familiar with this vaccine brand. It's a COVID vaccine. So what you have to do is you have to type in this word exactly the same. So don't, I mean, like you have to use all caps because the word of the day is case sensitive. So just type in this word Covishield in the input box under the attendance for Day 1. And then just complete. So please make sure after typing this, you also have to click on submit. Just saving is not enough. You have to submit it. Then only your attendance will be counted. We will also mention this word in the chat and the Slack. So our final session for the day is about tracker terminology and tracker data model. Now this is a kind of a theoretical session that we'll be doing in this entire training program. Like, so this is, this tends to be boring when it is theoretical but can't help it because you need this theory about how tracker is constructed, how tracker is designed so that you can start customizing it. But what I will try to do is to make it as interactive as possible. So you are always, you can feel free to ask questions in the chat. I will, I will keep my chat open so that I'll be able to comment and also like, I tend to ask some questions also during the session so please feel free to unmute yourself and answer. So let's try to keep this as interactive as possible. So the learning objectives for this session is to understand what a tracker data model is and how it is related to the DHS to tracker. And to define the common terms used within the DHS to tracker data model to describe the general flow of information used within the DHS to tracker data model. And to understand how the components of the DHS to tracker data model links together. So these are the objectives that we are trying to cover in this session. Right, so what is tracker data model. Now basically tracker or DHS to data model in general is the fixed part of DHS to that you cannot change. So basically it's like, like, just imagine of a building where you are kind of renting out some stores or shops right so the building structure, you cannot change it although like you can think of having different types of shops. You can have grocery shops you may have electronic shops, you can have different types of shops, but the thing is this building structure remains the same. So similarly, in the DHS to the data model is something that you can't change it, but what you can do DHS to being so generic is that you can adopt the DHS to data model and try to build on and customize the DHS to to suit your workflow. That's what you should try to do. And this includes the required structures and objects that define how we can set up metadata and store our data. So probably you have an idea about what is metadata and what is data. Right, so if I ask, wow, what do you mean by metadata anyone. You can please unmute yourself and answer. What are the differences I mean what do you understand what's the difference between metadata and data. I'm seeing an answer in the chat by Amit. It's data about data. Yes, that's correct. So but like if you don't still understand what we mean by data about data is metadata is kind of the structure. Or the, you can repeat, you can kind of refer to it as a schema based on we can input data. So for example, DHS to the data elements organization units indicators programs and the are the metadata of DHS to, but we can customize it in a way so that we can collect patient information or is in aggregate model information related to our clinic visits. So all the all these are particular data that we are collecting which has to be based on the metadata we have designed. So, as the designers or as the implementers of DHS to in a country organizational setting, what we do is we will be setting up the metadata. And our data entry users, they'll be entering the data into the system. So that's the kind of difference between metadata and data in a very simple, simple way. Okay. So, Now, when it comes to tracker. Now, mind you, I'm kind of referring to this entire presentation and the concepts that that will be discussing here with the assumption that you are familiar with the aggregated probably the events of DHS to a, there are certain metadata concepts that we are using in tracker data model. And based on that, we can structure the tracker data. So what we have highlighted here are some concepts that we'll be using in the tracker data model, which we can divide into two broad categories. The first section or first broad category includes the concepts that we use to identify what we are tracking. Okay, so for example, we have three terms called track entity, track entity attributes and track entity instance. So these refer to what we are tracking. So in simple terms, what do we mean by track. So that means like we kind of register something, and we keep on following up that personal commodity. Right. So that's what we mean by tracking. So, whatever related to what we track, who we track is what we include in this first section as track entity, track entity attributes and track entity instances. In the next section, we have some concepts, which describes the information we are collecting about the concept we are tracking. So let's take for an example, we have a person, right. So for the person or patient, whatever the properties right related to that person or patient is included in the first section. And in the second section, it's kind of collecting, I mean it includes the information about what we are collecting about that patient. So for example, we have a patient named Joan, and this, the patient Joan is undergoing some malaria treatment or TB treatment. And like what he receives in the hospital, what type of medicine, what samples, what tests were done, that information is what we are collecting under this second section. Okay, that's the kind of example that we can use to distinguish between broadly between these two sections. So let's go into more detail about each of these metadata objects. So, first of all, let's start with the first category which includes track entity attributes, track entities and track entity instances. Let's start with the second one, right, the track entity. So basically what we mean by track entity. Here it is a type of concept that is being tracked. It's a very abstract or very generic concept. So basically it means what we are tracking generically. It could be a person, a case, a laboratory sample, a village, hospital, I mean a health institute, whatever, right, it's based on our imagination, and based on our, the use case that we are using the DHS24, we can think of what we are going to track. Okay, so probably like, most of the, in most of the use cases, so like probably when you think of DHS24 tracker, you may always think of tracking patients, right, you may think of like we are using DHS24 tracker to register patients, and then we'll be able to collect some information in different health programs. So that's a kind of common use case, but the DHS24 data model supports to track any concept. So for example, we can use DHS24 tracker to track a commodity, such as like a lab sample. Okay, or else like if we want to track a case, even for that we can use DHS24. So it's a very generic thing. So what we mean by track entities, what is being tracked. And then what do we mean by the first concept that is mentioned here, tracked entity attributes. So tracked entity attributes, what it means are the properties of what we are tracking. Okay, so for example, if we have a tracked entity called person, then what are the inherent properties of that person. So for example, a person may have a unique national identity in your country, you may or you may not have. So if you have a kind of a national identity, you can use it as an attribute or as its property, or probably things that do not change and which it's kind of part of that person. So for example, the gender, the name, date of birth, phone number. So these kind of tend to be permanent or semi permanent, which doesn't usually change, and it tends to be a part of that person or kind of a property of that person. So these are the stuff that we mean by the track entity attributes or attributes of the track entity. And what do we mean by track entity instance. So basically tracked entity instance refers to a single track entity that has been registered in the system. So what is the difference between a track entity which we have mentioned before and this new term tracked entity instance. Entity is a very abstract concept, meaning it is very generic. It could be a, I mean like so for example, track entity type or track entity could be a person. So a single instance of this person is what we refer to as track entity instance. So for example, we have a track entity called person and a single person whose name is John will be a track entity instance. So under the track entity type person, we will be having so many track entity instances that we are registering in the same in the system. So for example, we will have a track entity instance called John. We will have a track entity instance called Peter will have a track entity instance called and so that way we can keep on adding persons and each of these individuals are referred to as track entity instances. Is that clear any questions up to this point because I mean we really need to get these concepts clear so that you can do wonders with the HSU track. So any questions up to this point about track entity type or track entity attributes or track entity instances. I hope not. Let's move forward. Next, let us look at some tracker program related terminologies. Now, I know like some of you may find it a bit confusing when I'm going through these definitions, but don't be scared towards the latter part of this presentations we will have some pictorial descriptions about each of this terminology and how they are linked together. And we will also do another example so that it will be very much clear to you. Right. So now we have mentioned we have some thing called track entity which has its own track entity attributes right so we have kind of safer example. Let's take example of a person. So if we have this track entity instance called John in a country a right in this country in the health department of that country they may be conducting multiple programs health programs. So for each of these programs now basically what we mean by a program is like it has its own workflow. Right so for example you love you all may be familiar if you are from the health domain, you may have antenatal clinic program right or else you may have nutrition programs you may have malaria program. So, each of these health programs, I'm not talking about DHS to I'm talking in your health system you may having you may be having this health program and they may be having their own workflows. Right. So for example, if you take a TV control program in the first encounter you will be registering a person, then they'll be follow up visits where you may be taking samples, right. And then finally once that patient is identified as cure, you will have a final outcome, and then you may not organize to continue monitoring that person. So, for example, when we are so similarly when we are applying that when we are trying to kind of use DHS to match the information flow of your health program, we use the DHS to track. Okay, so they are if you consider the health program, I mean if we have a TV monitoring health program in DHS to there are few terminologies that come with that health program. Okay, so three common terminologies that come with that are the incident date enrollment date and the concept of enrollment. So let's start with the last one, the enrollment. Okay, so what do we mean by enrollment. We have the track entity or who has its own track entity attributes. So for example, the track entity instance would be the person John. And on the other side, we have something called TV control program or is with our example here for which surveillance program. Right. So this program is something which will which I will come come come back to it a bit later. The program is a kind of a work flow that we create in our tracker in DHS to write. So we have the program and we have the person the track entity and the linkage between the program and the track entity is called the enrollment. So basically, when we have a track entity instance, we have to enroll that track entities to a program in DHS to write. So the process of taking a track entity and registering them into a program is called enrollment. I hope that is clear. But we will come back to it with few examples. And when you are doing this enrollment of a track entity into a DHS to program, this happens in a particular date. Right. So this date is referred to as enrollment date. So basically the date the entity is enrolled into the program is called the enrollment date. For example, the date of the COVID-19 patient visits the clinic and receives their initial diagnosis or assessment could be used as the enrollment date. That's the first encounter of that person with the health program. And then we also have another concept called incident date. So the incident date is the date which triggers the first event. For example, in the COVID scenario, it could be the date of onset of COVID-19 symptoms. So let me ask a question, an open question from all of you. I mean, what is the difference? Why do we need to have two different dates for enrollment date and incident date? Would this be same or these basically refer to two different concepts? What's the difference between the incident date and enrollment date? You can even explain with an example. Any of you? Okay. I'm seeing an answer from Amit. Everyone agrees. He mentions it in the chat. He says incident can be, yes, Ibrahim, you want to answer? The incident, the date, they're the same. The incident, the date of the sickness starts, then the onset is that the symptoms that appearing in the body. Yeah, exactly. So it's like this. So for example, as I mentioned to you, now let's take this example of COVID-19 surveillance program, right? So in the COVID-19 surveillance program, the surveillance program is run by the health ministry or like your health sector. So they get to know that you have this person, Joan, who has some COVID related issue. They don't know whether he's COVID positive or not. Only when that Joan, the person, Joan visits the health facility and presents him to the health sector. So that is where the interaction or the first encounter between the person, the track entity, Joan and the health program COVID surveillance program happens. So that's when we usually enroll Joan to the COVID surveillance program. So that is where we have the enrollment date. But why Joan has to come and present himself to the health is because he believes that he has COVID related symptoms or probably he may have even got a test done. And he knows that he's positive. So basically what triggered his visit was he being presented with some symptoms that may probably be due to COVID. So basically what we mean by incident date is in this case, in this example, it could be that the date he first got to know of his COVID related symptoms. Okay, so that is the kind of basic difference between the, between the incident date and enrollment date. And mind you, Fracker is very generic. So you don't actually have to use both these data in each of these health programs. Sometimes you may not be able to have a clear, clearly different incident date. But we will come back to this different use cases later. But I just wanted to mention you what are these two dates and at conceptual level, what are the differences? Okay, let's move on. Right. So what we can do is we can now log into the instance. So I will do it for you. You don't actually have to do it now. I will log into our demo instance and try to explain to you these concepts in a real, real life scenario using our COVID surveillance program. Now I'm in our demo instance, which is links.india.org slash demo one. So what I will try to do is the default program that we are using to track to capture tracker related information is called the default app is tracker capture application. So I'm going to click and open tracker capture. And here you have the law of PDR as the country. Right. And in that one, we can select different level two and level three units. And finally, I will select a health institute, CHW, Mahasot, which is there in the level four. And once I do that, here, I'll be able to see the different health programs that's out of mention to you in this initial presentation. Right. So we have the COVID-19 vaccination registry, case based surveillance and contact registration and follow up. So these are three different programs. So what do we mean by a program? So basically programming includes a workflow of information we want to capture in the DHIS to track. Right. So it's a very overarching thing. It's a workflow. So inside the program, you have it in such a structured way where how it can kind of match to your own use case. So I'll come back to the components within a program a bit later. But here what I want to demonstrate to you is the connection between the track entity and the program. Right. So what we do is like from here, I can select this second one called case based surveillance. That's a program. Right. So I have the Oak unit and now I'm going to register a person into this case based surveillance program. Right. So I click on this register button. And here it is asking some information. So it here we are seeing the enrollment. Right. So as I mentioned to you before, it mentions here the case registration date, which is the default enrollment date. So I can keep the date as today, which is 25th or even I can enter a previous day. Say for example, yesterday, 24th of October. And under the profile, we have different attributes. Right. These are the properties of the person that we have to capture when we are doing the enrollment or initial registration. Not all of them are mandatory, but you can even make them mandatory is asking for a point on the map. Right. So for example, if you know the person's location, we can click on this button here and in the map we can mention we can capture that. Right. But if you don't know that we can leave it blank and we can put a case ID like this. First name I will put test person and the surname I will put last name, the date of birth and probably mention that date of birth like this and age will be captured and the gender. Right. For matters. So I'm because this is just for the demonstration purpose I'm not going to complete all of them. But finally, after doing all these things you can click save and continue. So this is the point at which we register attract entity instance name test first name into the system. And at the same time, we are doing something else, which is enrolling this person test first name into case based surveillance program. Let me repeat myself. So here what we are doing is registering attract entity instance and enrolling that person to the case based surveillance program. So we are doing two steps at one go. In this initial step. Right. I have to click on save and continue and that's when this process will be completed. I'm sharing and going back to my presentation. Any questions up to this point. If not, I will proceed. And probably we can take few more examples was in rights. I have already mentioned to you what a program is, but the, but the definition is like, it's a sequence of events that an entity can go through the frame. Basically this frame can be a disease surveillance program, which will include clinical examination specimen tracking lab results and case investigation. For example, this COVID-19 surveillance program will include a diagnosis and clinical examination specimen tracking lab results and case investigation. And then what attributes are required when an entity joins the program. Basically program as I mentioned to you is a overarching thing where you have a frame or series of events attract entity instance can go through and also it also includes specific attributes which are required when the track entity joins the program. Okay. So, there is another concept called track entity attributes and program attributes which are kind of a very a bit advanced concept which I will not mention here, but probably towards the latter part of this tracker program or the tracker academy will be able to discuss more about it. Right. So basically that's where that's why we have mentioned attributes are also part of the program when the track entity instances joining the program. Okay. Is that clear. Let's see some examples then it'll be more clear to you. Are there any questions on chat. So inside the program, we have a few more concepts. Right. The first one is called program stage. So what do we mean by program stage. So forgetting about the definition. If you just look at the name programs stage. So that itself mean like this has something to do with part of the program. Right. So the definition is a tracker program basically can have multiple program stages. So inside the program I mentioned to you program is the information will workflow or the frame. So if we can divide this entire information workflow or the frame into multiple components. Right. So that's why tracker program can have multiple program stages. Right. So it is not compulsory for a tracker program to have more than one program stages, but it needs to have at least one program stage. So basically program stage defines what data should be collected during a specific type of event within the program. The keyword here is during a specific type of event. So if you go back to the reference to the program we mentioned within a program. I mean let's take this disease awareness program. It will include clinical examinations specimen tracking laparous and case investigation. Right. Each of these four concepts are different types of events within one big program. So what we mean by a stage is one if one type of event within the program. So here if we apply this concept to the to the use case laparous stage will collect information about results event. So inside this disease surveillance program you can have different stages. For example, clinical examination maybe one stage specimen tracking maybe another stage and lab results as well as case investigations can also be different stages. So inside the COVID-19 surveillance program as per this example we can have four different stages. But mind you there are no hard and fast rules as to how you define your program. I mean it's up to you and your program manages to design how good our tracker concepts to be matched with your program. So for example, even though we see there are four different stages that we can break this entire program into you might feel though we don't need for we can do it with three. You can argue based on your own rationalization. So that's that's totally up to you. But as conceptual level. This is what we mean by program stages. Any questions? Yes, I mean you're asking will we call all the components as frame or each component a different frame. Right. So here, I mean, as per this definition, right, we refer to the, I mean what we mean by the frame is the entire program, but then like within the frame you can have subframes right so that you have this broad frame called program. And it can be further divided into stages. Right. And inside the stages. We have different different events. So I will, I will, I mean, I think I'll be able to explain this more clearly to you. We have a diagram that is coming up in next few slides. So with that I will, I will get back to your question. So just remember, we are talking about one big thing called program, which can be further subdivided. And so as for now, I will get back to your question. Next we have a concept called event. So what do we mean by event event is something I mean within the program stages, the program stages consist of one or more events. So I mentioned to you in the previous slide about something called program stage. Right. So the program stage is a very generic thing. Say for example, laboratory result or laboratory sample is one program, one program stage. And inside that one you can have multiple events. Right. So why you can have multiple events is because say for example specimen collection stage, you may collect multiple specimens. You might collect a blood sample for food blood count, then you might collect a blood sample for like say, yeah, what else you can collect a blood sample for a particular antibody testing you may even collect urine sample you can for this COVID surveillance you might take a nasal swap. Right. For PCR testing. So likewise you can have multiple encounters for each of these stages and we refer to them as events. So basically event is one instance of a program stage. So you have this program, you have the program stage and one instance within the program stage is known as an event. Right. So another concept I have to mention this, you can have one event within a program or you may have multiple events within the program. So based on that, we define the program stage, sorry, let me correct myself, you can have one event within a program stage or you may have multiple events within the program stage. So based on that, if we can further categorize program stages as repeatable program stages or non repeatable program stages. So if your program stage, say for example, in this COVID scenario, the registration stage, if it is only once we are registering that patient person and we collect some basic information related to the registration if we do it only once. There will be only one encounter for that program stage. So we may refer to that program stages as a non repeatable. Whereas specimen collection, if you are collecting multiple specimen in multiple encounters, then you may refer to this program stages as repeatable. Right. Is that clear. Any questions. Right, so let's quickly go back to our tracker program and try to understand this program program stages and events a bit more. So, you may remember that I click what I did was in my previous demonstration, I registered a new person into the COVID surveillance program, and I entered the attributes, right the profile information and finally I clicked on save and continue. And when I do that, this is where I land this UI or the screen that we that I am right now is is referred to as entity dashboard. So we will get back to it in more detail when we are doing when we are introducing you to the tracker capture application. But just know that this is a track entity dashboard which has so many widgets, but what I will only focus in this example is the screen, right where we can collect the information. Right. So, okay, having some caching related issue. Are there any questions up to this point. Here we go. Okay. If we focus on this timeline data entry we will explain to you all these components in our later presentations. But here you will see this box the yellow color one is called stage one, clinical examination and diagnosis. So basically, within our workflow we have created a separate stage to collect information related to clinical examination and diagnosis. Right. So here you have all this information, right. Basically, these are data elements that we are collecting the information grouped under this program stage. Right. And other than that, we can have multiple program stages, as I mentioned you before. So this you see is the clinical examination and diagnosis and to create more program stages and capture more information. For this patient, we can click on this plus button. And when we do that, you will see that it only allows me to create capture information for the next three program stages, it not it does not let me capture data for the stage one again. Why, because that's how we have defined for data to be collected only once for the stage one. So that way the stage one becomes non repeatable. It would have appeared here, but it does not. But let me just select this stage two and click save and see what happens. So the stage two is about laboratory requests. Right. And here it does some information like say for example reason. I can select something and the type of. So let me do a serum. Then the type of test. I will just select serology and I click on complete. So let's see what happens if I want to add an add an event again. It still shows me the stage two here, meaning for stage two for that for this person, I can create multiple instances for this stage. Meaning stage two is repeatable because lab brick obtaining lab requests, you may you may be able to repeat it for multiple times for different type of program, different type of specimens, as well as different types of tests. That's why it is multiple, whereas this clinical examination and the, the, the history and the diagnosis that part, we are collecting some information, which we don't want to collect over and over again as per this customization. But for your instance, if you feel like you have some information that you may need, you may be needing to collect over and over again, you can make this repeatable. Is that clear. So I just wanted to highlight you from this demonstration. The differences between different stages and the concept of repeatable and non repeatable. I hope this is clear. Let me go back. This is something which you already know the data elements options and options sets. Right. So, if you are coming from aggregate background in DHS to if you have followed the aggregate related to academies and if you have practice, he has to aggregate in your routine work. You may be already familiar that we have something called data elements to which we can attach options and options. The only difference here in this tracker domain is that when we are creating a data element domain type has to be. So what we mean by data elements is the data points that that are collected within a program stage. Right. So for example, we have this program stage called lab test result. And inside that the data points for the different fields the variables we are capturing under that stage is known as data elements. When you are defining a data element for the tracker has to be in the domain type tracker, not aggregate and options sets and options are kind of a, I mean, these are two concepts which goes together. So option set is a predefined related list of values for each of the data elements. So each data element can only be assigned one option set. Please remember that one data element you can only assign one option set. And options are the individual options or individual labels or values that you can create within an option set. This is this you can think of in a multiple choice question the individual options you have a question, what we mean by options within options set. Right. So what we can actually do is be so for example let's take. I mean the very example that we saw just a while ago. The specimen type could be a data element, right, which can include multiple specific. So what we are going to do is we will create something called an option set as specimen type in that we can have multiple options. So for example, serum is a pharyngeal, right, would be different options within that option sets of specimen type. So this specimen type option set, we can attach it to and data element to a data element. And that's how all these are integrated. So this is this is again a very abstract thing. Let me go. I mean, like, take one example then it's a then kind of explain to you this entire work. Any questions, seeing some questions. Okay. Any questions about antenatal care. Right. And then defining data element. Okay, so I mean, in antenatal care. So it's like this. Now, within antenatal care we can have broader. So, okay, let's do like this. Let's discuss further about this and so we can take this antenatal care as an example. And let's discuss how we can create the tracker program. So this is the next slide and then let's take this example and so probably you'll be able to talk about how you envision this antenatal care program. And let's try to build a tracker on top of this use case. We do like that. And then Paul defining data element types is done in configuration so users do not have to think about this. Yes, exactly. The data element types and even designing the tracker program is done in configuration so the end users do not have to worry at all about this. But why I'm referring to this I mean why we are having this lecture this component within the trucker use Academy is for you to give an idea about the building blocks of trucker. So really, if you are an implementer, or if you are a person who uses data, and not a person who configures your DHS to instance you don't have to worry about configuring these things. But if you are going to teach tracker to end user as a implementer, then you will have to be thorough about these different building blocks of trucker. Right, so sorry, let's explain, and we use standard terminology. And we use standard terminology data element. I'm not entirely sure about what you mean by can we use standard terminology data element, you can be more specific. All right. So like snow mid city. Okay, you mean like, if you want to collect a particular code, right. For a data element. Yes, that is possible but then again you what you have to define is you will have to have option sets configured in such a way that the particular term that you want to capture as the final variable, right that you will have to define as option sets prior and then attach it to a data. That's how you are doing. Yes, correct. Right, so this we have already done. So let's look at the flow summary of the entire thing that we have mentioned so far. Right. So we have this as mentioned is in this first box we have something called track entity, right, and which has its own attributes. And what we do is we are enrolling that track entity into programs. So example of program could be maternal health, childcare program, HIV program, and baby surveillance program. Right. So we do something called enrollment. The program. Right. And then this track entity could be enrolled only once or many times. Right. Just mind you because the thing is like, for example, if we consider about, say, infectious disease. You might be enrolled, say even COVID-19, right, COVID-19 surveillance, you might be enrolled once into the COVID-19 and then you may get cured. But you can get a recurrence of COVID-19 you can get infected again with COVID-19 then you will have to re enroll that person with a different enrollment to the program so you can have one or multiple enrollments to the program in a lifetime of a track entity. And within the program you have something called program stages. So for example, you can have maternal health. Right. I mean like in each of these programs like for ANC. So if you take the maternal health program, you can have antenatal care delivery postnatal care as different program stages. So this again is about what you mentioned, Amit. So within the maternal health program, you may have different program stages. So some program stages, we might be able to collect some information about antenatal care. Right. So that you can have, you can, you know, like include all these data elements inside ANC or antenatal care program stage. Right. And then you have a delivery program stage. And you have a postnatal care program stage. Right. And collect the information inside that. So going back to Amit's example, you can have a repeatable ANC program where you are program stage where you are collecting the same data elements multiple times. But then again somebody else might argue within the antenatal care, we might have, we might configure it differently where we capture only the data elements which are only collected once. Right. As a non-repeatable stage and then you will, you may have a follow up stage where you are collecting repeatable information. Right. So you have different ways of arguing. And similarly you can do same with other programs like HIV, where you have HIV testing, counseling, ARPS, different program stages. We have any questions? Right. So this is in summary what happens when you are configuring EHIS to tracker. Right. So this is the tracker data model. So let's quickly go through the model. I will start with track entity. So for example, if we have a track entity called person, the person can have different attributes. For example, he can have first name, last name, and a sex. Right. And this track entity can be enrolled into one or more programs. So as per this, we can, if we have a program called COVID-19 surveillance, we can enroll this person to the COVID-19 surveillance program. Right. So that's the first section in the tracker data model. The next is about the program and the building blocks within the program. So for example, we have the COVID-19 surveillance program, which can have multiple program stages. So for example, we can have a program stage called clinical examination, lab request, lab result, and the outcome. Right. So an instance of this program stage is referred to as an event. So basically that is an encounter of this person with this program stage. So these program stages could be repeatable or non-repeated. So as per this example, clinical examination is something which is not repeatable. Okay. And then you might also have lab request where you may take request multiple times. Right. And for those, you might have multiple lab results. So these are repeatable. And then you can have something called outcome, which is again a non-repeatable because the outcome only comes to one for that enrolled. So for each of these program stages, you have a range of data elements that you can incorporate. So if we take, for example, the laboratory request program stage, it can have multiple data elements. So one data element could be lab test reason, another data element could be type of test, and the other could be type of the specimen. So some of these data elements will have raw value. Say, for example, if it is configured as a zero positive integer data type. Say, for example, now let's take this lab test reason. It could be of data element type text. So we don't need to attach any, unless you want to categorize it, we will not attach an option set. For example, type of test, you may have a predefined list of responses, which you can incorporate to option set, right, which can further be elaborated or included as options. So you might have the type of test as, the options you can have for type of test could be serology, PCR, NAAT, likewise. And then this option set, we can bind to the data element that we are doing when we are configured. Is that clear? So this is kind of the overview or summary of the tracker data model. So are there any questions? These are a few examples that we can take when we are like applying the tracker. So for example, we can apply to pregnant women through ANC delivery and postnatal care. We can think of child through a full set of immunization services, right, whereas patients receiving the antiretroviral treatment therapy, and then TB patient diagnosis and receiving TB treatment, disease surveillance, malaria case investigation, etc. So these are the examples. Right. Are there any questions? We are a little bit over time, so probably like if you want to leave, if you have other commitments, you may leave now. But if you need to ask questions, I can elaborate it further with a few examples. Saurabh, before we wind up and then go for the Q&A session, do we have any announcements to make? No specific announcements, just everyone please mark your attendance. And Parmarth, if you can just guide them to the feedback section on model so that they can add the feedback for the day. That's important for us to plan the next day and of course the future academy. So these two points. Yes. Let me share my screen again. Right. So, right, so going back to Voodal for the day one. Right. We won't all of you to mark your attendance because attendance is compulsory to be marked. So I hope you have done it and we have this section called feedback. So go to feedback and click on feedback day one. Right. So this is where you can give feedback. You just have to select an option for most of the questions asked. And then for some of them you can give some text. And then click on send. This is a simple Google for Google form you have so it's quite straightforward. And please mark your feedback. Yeah, the attendance word you have to type under the, so let me share my screen again. I'm not sure whether it will allow me to mark it because I must have already done it during the demonstration so this is where you have to click attendance. Right. And go to day one attendance. I have already done it so that you have an option here to unfortunately I'm not able to show it. You have to click here, the attempt one and then there you will find the input box where you can type in the comic shield, and then click submit. Not able to show it because I already demonstrated it once. So those of you who want to be like, now we can have a Q&A session like if you want me to further elaborate on the tracker data model with examples I can do that. For us we can wind up for the day. And the learning manager, okay already answered it's on model. Right. Those of you who want me to further elaborate on the tracker data model, I can do it here with this example. Are there any questions, please feel free to unmute yourself and ask. Yes, Arif. The question might be at first. Is it possible to hide or close the program stage based on the predefined logic. For example, if a woman only visit for ANC, but is it for others being ANC 2, 3 or 4. Sorry, Arif, could you please repeat? It was not clear. Is it possible to open or close program stages? Your question is, is it possible to open or close program stages? Right. Yes, based on some location. Right. So if you can just mention like, okay, now we have several ways of doing that, not really like opening or close. So what you want to do is like, so basically like, is it for people who have so if you can kind of explain a scenario then that would be kind of easy for me. Now for example, a woman visited place for ANC 1, 2, but he did not visit for others ANC 2, 3 or 4, but they already have come already apart. So in this scenario, it is possible to close one is to keep system, any possibility to close the 2, 3, 4 for this particular woman. He did not already stay, already passed the 40, 40 weeks. So he did not and data interoperator cannot enter the ANC 2, 3 or 4. If I have a program stage, ANC 1, 2, 3 and 4. The only visit if a woman visit for only ANC 1, but she did not visit for 2, 3 or 4. So if a data interoperator mistakenly entered for this woman for ANC visit 2, 3 or 4. But this particular woman is not those, those women, women who visit only the ANC 1. So in this condition, it is possible to automatically close ANC 2, 3, 4 stages for this particular woman. Alright, interesting. Yeah, so, so I am understanding like you have some requests. So let's make it more generic. It's just that so we have this program stages configured where you want a track entity instance to go through all the four program stages. But what you want to do is not to let the register for a given program stage and only let them enter data into one or two program stages based on a criteria, something like that. Is that so? I hope so. Sorry, my name was not able to understand. I cannot hear properly. Alright, okay, so I'll be like, sorry, probably I was I mean like, sort of did you get the question correct. Okay, let me like mention so one thing is we will be discussing about different controls we have around creating, you know, like the workflows, but, but only issue is we might not go into depth because this is not the trigger configuration academy, but we have several ways of doing that. So for example, one thing is the sharing settings based on which we can, you know, like, but I don't think for your example, this is applicable. The sharing settings is like if you want to limit the visibility or access to a program stage for a given user, we can use program settings. But in your case, you want to create a new event based on a given criteria on a different program stage. So I think this is like, this is a bit of a tricky scenario because like in a generic way to create a program stage on this. So it's a kind of a program rule where to create a program stage. So this may be a bit of a tricky thing, which is not directly supported but probably I can have a chat with you in detail to see the exact requirement. So this is something which has to be done through a program rule, as I feel but again, I'm not sure whether your requirement will be fulfilled because it's about creating a program rule on a particular program stage. So let me get back to you on this. Probably I can have a chat with you about what your exact requirements. So whatever you have anything to add on this. No, I think if you can send us a small description on Slack, then maybe we could help him better. And I think it has to do with the closing program stage data into your hiding program stages if that particular stage is no longer applicable. So, for example, if, if the female has visited in her third trimester for the first time for antenatal care, then all those stages are not applicable for her right like the first visit or the second third, maybe the third trimester she's taking her first ever ANC interaction. So in that case, can we hide or close or not allow data entry for the stages which are defined as per the workflow. So maybe we could do something with the program rules or such but then, if I can give a small description to us on Slack then we can help him better. Are there any more questions. Okay, if not, we can conclude the session. Please make sure that you mark your attendance and give feedback for today's session. If there are any questions, please type them in Slack, so that we can, you know, help you out today or in during the academy. Thank you. Thank you so much. Right. So, looks like there are no more questions. So, if you have any queries on Slack or else we will close the live session for today, hoping to see you all at the same time as today, tomorrow, which is 12 noon in the standard time. Have a great day.