AEB Tracking on DHIS2

Implementation - Implémentation HIV
1

Dear Community Members,
I hope this message finds you well. I’m reaching out to tap into the collective expertise and experience of this community regarding the development of an application for tracking Accidental Exposures to Blood (AEB) on the DHIS2 platform.
I am currently working on a project aimed at enhancing AEB surveillance and management within healthcare facilities. DHIS2 has been identified as the platform of choice due to its flexibility and scalability.
I am seeking insights, models, or experiences from those who have worked on similar projects or have expertise in this domain. Specifically, I’m interested in:

  1. Data model structures optimized for AEB tracking on DHIS2.
  2. Best practices in data collection, validation, and reporting for AEB incidents.
  3. Lessons learned and recommendations for successful implementation.

If you or your organization have developed models, implemented projects, or gained relevant experience in AEB tracking on DHIS2, I would greatly appreciate your insights. Whether it’s sharing your data model, offering advice, or pointing me towards helpful resources, any contribution would be immensely valuable.

Warm regards,

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Hi @elmoujarrade

Thank you for your post. Unfortunately, I wasn’t able to find information specifically for AEB. I’ll reshare your post and see if we get any insights.

Thanks!

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Dear @elmoujarrade,

from the HISP Center we have recently published the updated HIV toolkit based on the latest WHO Consolidated guidelines on person-centred HIV strategic information: strengthening routine data for impact

The HIV prevention component has several components that I can think could be very useful for your specific use case as:

  • HIV testing
  • PEP
  • STI
  • Hepatitis

The HIV Prevention tracker structure is mostly a flat structure with only one main repeatable stage to record activities for any type of prevention visit. This intentionally simplified structure allows for increased flexibility for local adaptation and customization. For example:

  • Sections can be easily translated in stages in case different user have to entered different information (as detailed previously the HIV Prevention service are very transversal and can have several actors involved on the distribution of the services)
  • Reduced amount of program rules and well identified by the section targeted
  • If a specific activity (prevention intervention, such as VMMC) is not relevant to your country’s package of HIV Prevention services offered, you can simply remove an entire sections without repercussions on the rest of the data model.

You can find more information on the HIV prevention toolkit here, the metadata download here and have a look to the dashboards and tracker program in our demo site.

Last thursday we had a webinar for the launch of the updated toolkit and here you can find recording

Please, don’t hesitate to contact us in case of any doubts/questions!

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