What's the difference between V{enrollment_count} & V{tei_count}

Implementation - Implémentation
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Hello experts,

What’s the difference between V{enrollment_count} & V{tei_count} i was thinking it will be same for most of the cases?

Can somebody guide me of a scenario for program indicator or program rule where these two has a different meanings/values

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Hi @jthomas,

Let me explain it by example in hereunder:

Tracked Entity Instance (TEI) → a type of entity that can be tracked through the system. for example pregnant woman once she registered over the system we say a new TEI was created as a pregnant woman to be tracked over her pregnancy period at the system.
Enrollment – > One TEI could have one or multiple enrolments, for example, the pregnant woman (TEI) above could be enrolled for her first pregnancy and could come again and again for the following pregnancies (First pregnancy is the first enrolment, and second pregnancy is the second enrolment, and third pregnancy is the third enrolment, and so on…)
TEI and enrolments are managed by a program for example Mother-child health care program to manage the process of TEI creation and enrolment activities during the pregnancy period…

I hope this example is helpful to answer your question.

For more information, please don’t hesitate to DM me.

Best regards,

6 Likes
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Thanks alot @ayman.tuffaha Let me process and self-brainstorm a bit on this.

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Hi @ayman.tuffaha,

Could you please explain the meaning of this option in a tracker configuration page:
Only enroll once (per tracked entity instance lifetime)? This question occurred to me after seeing this post which has made clear for me the concept of multi enrollments.

Thanks

1 Like
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Hi @ferdinandmussavene ,

Thanks for your post, Yes my colleagues have previously explained the mentioned option, please visit the below URL links:

  1. Only enroll once (per tracked entity instance lifetime)

  2. Multiple enrollments in a tracker capture program

Best regards,

2 Likes
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Hi @ayman.tuffaha,

Does the following mean that each time a woman gets pregnant, she would have to be registered in the system? if yes, wouldn’t her name appear multiple times in the system?

I am eager to know how multiple enrolments work.

Thanks

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Hi @fernando ,

Thanks for your post.

No, a woman only needs to be registered in the system once. She will have a single tracked entity instance (TEI), ensuring that her profile is unique. at each time the same woman becomes pregnant, there is a search feature you can search by her tracked entity attribute i.e. her ID, name, and registration number, … and a new enrollment is created within her existing profile, with each enrollment representing the 9-month pregnancy period. This way, her name will appear only once in the system, but her pregnancy history will be tracked through multiple enrollments. each enrollment represents a completed pregnancy or completed enrollment (will be as a history of new coming pregnancy).

I hope this answers your question.

If you need more information, feel free to ask, and I can provide further explanation with a real example.

Kind regards,
Ayman

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Hi @ayman.tuffaha,

I would welcome a real example. Each time we fill information related to each pregnancy in a program stage we consider it a new enrollment? Another question has occurred to me? I make confusion when it comes to choosing either [V{enrollment_count} & V{tei_count}] to built program indicators. Would choosing either of them impact the PI result?

Thanks

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@fernando
Let’s explain in more simple way:
The TEI itself is just a person, who has unique ID with Name,. Surname etc

That person can be enrolled few times in the same or to the other programs. In flat language enrollment is just registration of the person in that particular program.

As an example let’s take HIV or TB program where we have a client, who can be registered once (TEI), and enrolled to the program and leave that program. Suppose that enrolled/registered client reached good suppression results and decided to leave program. But in few months/years found something wrong and come back to continue the treatment. When he come back he will be enrolled again, and it’s history can be found by the TEI, and his previous enrollments.

Hope I could provide explanation

Should you have any further questions feel free to ask

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Thanks, @Ulanbek for further explanation,

@fernando,
Each enrolment could have one or more stages and most likely stages have details of the health/medical status of the client/ patient in different cases i.e. first visit stage, follow-up visit stage, lab test stage, medicine stage, …etc.

Regarding V{enrollment_count} & V{tei_count} most probably the results will not be the same: V{enrollment_count} > = V{tei_count}

if you have any questions, please let us know.

Kind regards,
Ayman

1 Like
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Hi @ayman.tuffaha and @Ulanbek,

All the information you have provided regarding multiple enrollments is now clear to me. I don not know if I will be digressing from this topic, but I have a last question: from your expertise, how to determine which information to include in each program stage when creating a tracker program? e.g In HIV, TB, Pregnancy, Program, we might mix up data elements which should go in one stage into separate stages and get wrong output.

Thanks

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Thank you for your feedback. I’m glad the information on multiple enrollments was clear.

Regarding your question on determining which information to include in each program stage when creating a tracker program, here are some key considerations which helps also in the conceptual design process (Please use a proper naming convention for each data element to distinguish):

  1. Define Program Objectives: Clearly outline the objectives and outcomes you aim to achieve with the program. This will guide which data elements are necessary for each stage.
  2. Identify Key Milestones: Break down the program into distinct milestones or phases. For instance, in an HIV program, stages might include initial diagnosis, treatment initiation, and follow-up care. Ensure that data elements specific to each phase are grouped accordingly.
  3. Map Data Elements to Stages: Align each data element with the specific stage of the program where it is most relevant. Avoid mixing elements from different stages to maintain clarity and accuracy. For example, in a TB program, data on initial symptoms might belong to the diagnosis stage, while treatment adherence could be part of the follow-up stage.
  4. Consult Guidelines and Standards: Refer to any existing guidelines or best practices specific to the program area (HIV, TB, Pregnancy) to ensure consistency and completeness in stage definitions and data element allocation.
  5. Engage Stakeholders: Involve program experts and stakeholders in reviewing the stages and associated data elements. Their insights can help refine the stages and ensure that data elements are correctly assigned.
  6. Test and Validate: Implement the program stages in a test environment to validate that data elements are correctly assigned and that the output is accurate. Make adjustments as needed based on the results.

By carefully considering these factors, you can help ensure that data elements are appropriately included in each stage, leading to accurate and useful outputs.

If you have any more questions or need further clarification, feel free to ask!

Best regards,
Ayman