🤖 AI Generated Summaries for each #DAC2025 session + Deep Dive Audio for Day 2

Resources - Ressources
1

In this dac2025 AI Summaries series we will provide you with:

  1. :headphone: Deep Dive Audio AI Summary for the entire conference day
  2. :memo: Summary for each session (ordered in the same sequence as in the agenda).

Please note that it’s possible that these AI generated summaries contain errors; therefore, this post has been made as a wiki so that necessary modifications can be made by other community members especially speakers.

Thank you, and enjoy! :grin::+1:

:placard: AI Generated summaries for #DAC2025 sessions Day 1
:placard: AI Generated summaries for #DAC2025 sessions Day 2 :left_arrow: (You’re here! :slight_smile: )
:placard: AI Generated summaries for #DAC2025 sessions Day 3
:placard: AI Generated summaries for #DAC2025 sessions Day 4

:headphone: Day 2 Deep Dive (AI Audio Summary):

NOTE: This AI audio is an experimental feature using Gemini, so this audio deep dive (including the voices) are AI-generated and there might be inaccuracies and audio glitches. This audio is not a comprehensive or objective view of a topic, but simply a reflection of the YT videos and other material from the conference. We simply hope that you enjoy the audio overview of the whole day and that it sparks your curiosity!

Plenary Sessions:

CoP Challenge: 🏆 Level Up Your DHIS2 Knowledge!

CoP Challenge: :trophy: Level Up Your DHIS2 Knowledge!

The "CoP Challenge" was a **dynamic and interactive competition** 🎮 held at the DHIS2 Annual Conference 2025, from **08:30-09:00** on one of the conference days. **Hosted by**: Al-Gassim, the DHIS2 Community of Practice (CoP) Coordinator from Yemen. **The Challenge's Goals**: The session aimed to **boost participant engagement** ✨ and **facilitate knowledge sharing** 🤝. It also served to **familiarize users with the DHIS2 Community of Practice platform**. The challenge encouraged attendees to explore **innovation topics tagged with "DAC 2025"** and engage by replying with questions, insights, or comments. It also highlighted weekly "roundup posts" that summarized topics with headlines and questions. **Real-time Competition**: A **live leaderboard** 📊 updated in real-time, creating an exciting atmosphere for both in-person and online participants. The DHIS2 Community of Practice is a vast network, boasting **over 10,000 members from approximately 100 countries** 🌍. **And the Winner Is...**: The competition concluded with **Joseph Chingalo** @chingalo being announced as the winner. This interactive session successfully showcased the CoP's value as a platform for continuous learning, sharing, and networking beyond the conference itself.
Climate & Health Plenary: 🌍🌡️ Protecting Health in a Changing Climate with DHIS2

Climate & Health Plenary: :globe_showing_europe_africa::thermometer: Protecting Health in a Changing Climate with DHIS2

The "Climate and Health" plenary session at the DHIS2 Annual Conference 2025 provided a comprehensive overview of efforts to **leverage DHIS2 for climate-sensitive disease monitoring and prediction**. Led by **Professor Kristin Braa**, the session highlighted progress, challenges, and future directions for this critical and growing area.

Key Concepts & Building Blocks:

  • Climate Services for Health :light_bulb:: These are about providing climate data, information, and knowledge to support decision-making, based on scientific expertise and user needs. They aim to assist timely action and often require multidisciplinary and cross-sector collaboration, including with national meteorological offices.
  • DHIS2 as a Foundation :building_construction:: While the DHIS2 Climate App itself isn’t a “climate service,” it provides the essential building blocks (Climate App, Modeling App, CHAP Platform) to create such services.
  • Data Harmonization :link:: A crucial step involves aligning diverse climate and health data by period and organizational unit (like districts and facilities).
  • AI & Machine Learning for Prediction :brain:: The session emphasized using these technologies to anticipate health risks and establish early warning systems for climate-sensitive diseases like malaria and dengue. The CHAP (Climate Health Adaptation Platform) Modeling Platform is key, supporting the configuration, training, tuning, evaluation, and sharing of models for predicting climate-sensitive disease incidence. It’s designed to be a generic, reusable platform that can be tailored to local contexts.

Core Tools Showcased:

  • DHIS2 Climate App :sun_behind_rain_cloud:: Facilitates easy access and import of global climate and environmental data into DHIS2. It provides datasets for temperature, precipitation, humidity, heat stress, climate change, vegetation (NDVI, EVI), land cover, and elevation. It supports data import for weekly, monthly, and yearly periods, and offers multiple calendar support. Local data integration is also coming soon through ENACTS API.
  • DHIS2 Modeling App :bar_chart:: Acts as the frontend for the CHAP Platform, allowing users to select models, connect them with DHIS2 data (including climate data from the Climate App), and evaluate their performance. It supports various models (e.g., Chap Ears, Deep Learning) and allows for customization of covariates (e.g., population, rainfall, temperature, heat stress, elevation, intervention data).
  • CHAP Modeling Platform :robot:: The backend service that enables the automated learning of connections between climate and health data, leading to risk maps and predictions. It aims to cut duplicated efforts, give countries more ownership, and foster collaborative, open-source community development.

Real-World Use Cases & Country Experiences:

  • Togo Malaria Stratification :mosquito:: Integrated climate data into DHIS2 for planning seasonal malaria interventions (SMC). By analyzing rainfall patterns and historical malaria cases, DHIS2 helps identify districts eligible for SMC and the optimal start/end times of campaigns. This transitioned from manual to automated, real-time analysis.
  • Uganda & Ethiopia Climatic Suitability :world_map:: Utilized the DHIS2 Climate App to configure composite indicators of climatic suitability for malaria, based on precipitation, temperature, and humidity thresholds. This helps prioritize districts at risk and inform interventions. Ethiopia also incorporates elevation data for stratification.
  • Sri Lanka Air Quality & Health Risk :wind_face:: Pioneering work on correlating high-resolution PM2.5 data with respiratory diseases using epidemiological risk modeling, with plans for an early warning system.
  • Mozambique Climate Data Repository :cloud:: Development of a DHIS2-based centralized repository for the National Institute of Meteorology’s climate data, enhancing internal access and external sharing.
  • Mozambique CHAP Platform Piloting :chart_increasing:: Using CHAP to anticipate malaria outbreaks by predicting cases up to 3 months in advance and returning these forecasts to the existing iMISS/SIIM system for visualization and local action.

Challenges & Future Directions:

  • Addressing Fragmentation :puzzle_piece:: DHIS2 is seen as a key lever to reduce system fragmentation in health data digitalization, particularly highlighted in Mali with its 53 health applications.
  • Data Quality & Interoperability :globe_with_meridians:: Ensuring the quality of health data for early warning systems is crucial. The need for interoperable digital and data architectures that integrate climate and weather information systems was emphasized, often leveraging standards like FHIR.
  • Local Ownership & Capacity :seedling:: The project actively collaborates with HISP groups in 10 pilot countries to build local capacity and ensure that solutions are tailored to local contexts and needs.
  • Community & Collaboration :handshake:: The project promotes an iterative development approach where countries develop, tailor, evaluate, and innovate back to a global pool of reusable models. All pilot countries are meeting weekly for innovation sharing and capacity building.
  • Global Goods Guidebook :books:: PATH and WHO/WMO are updating the Global Goods Guidebook to support scalable climate and health digital solutions, providing a resource for policymakers and implementers on open-source digital tools.

This session underscored the critical role of DHIS2 in enabling countries to proactively address health challenges posed by climate change, moving from reactive responses to anticipatory, data-driven interventions.

Parallel Sessions:

DHIS2 Performance Monitoring: 🚀 Keeping Your System Healthy & High-Performing!

DHIS2 Performance Monitoring: :rocket: Keeping Your System Healthy & High-Performing!

This session at DAC2025 focused on the **critical importance of monitoring DHIS2 systems** 📊 to ensure their smooth operation and efficient performance. The goal is to provide insights for proactive management and troubleshooting.

Why Monitor DHIS2? :thinking:
Monitoring is essential to:

  • Understand the general daily health of the system.
  • Help with server provisioning, answering questions like “do I have enough CPUs allocated to my PostgreSQL server?”.
  • Project future resource requirements, such as disk usage growth.
  • Understand the impact of configuration changes, upgrades, or new programs.
  • Diagnose problems and detect suspicious activity when they arise.
  • Trigger alerts (e.g., via Email/SMS) from monitoring systems.

What to Monitor :chart_increasing:
Key areas to keep an eye on include:

  • System-level metrics: CPU, RAM, disk usage, disk performance (e.g., disk latency), and network. High disk latency, for instance, means the CPU is waiting longer to read data, indicating potential issues.
  • Application-level metrics:
    • PostgreSQL: Health of the connection pool, query length, and locks. Database size should also be monitored.
    • Reverse proxy: State of connections and throughput.
    • DHIS2 JVM (Tomcat): JVM performance (heap, garbage collection).
    • DHIS2 individual application endpoints: Performance of these endpoints.
  • Special DHIS2 Metrics API Endpoints:
    • Metadata integrity (total issue count, percentage, check duration).
    • Data summary (object counts for indicators, data elements, etc.; active users; data values and events updated; enrollments updated; system information).

Monitoring Tools Showcased :hammer_and_wrench:
Several tools are available, with emphasis on using the right tool to interpret what you are seeing:

  • Munin: Ships pre-installed with DHIS2 server tools and provides useful graphs for system metrics like disk latency and database size.
  • Glowroot: Excellent for tracing slow API requests and identifying performance bottlenecks in transactions.
  • Prometheus/Grafana: Popular for data collection and visualization. The DHIS2 Metrics API exposes a variety of metrics in the Prometheus text exposition format, making them easy to scrape. Automated Ansible-based tools can install and configure these.
  • DHIS2 Metrics API: Exposes out-of-the-box metrics like DHIS2 API activity, JVM status, database pool activity, EHC cache metrics, and CPU process activity, which must be enabled in the dhis2.conf file. It provides metrics grouped by URI (e.g., /analytics, /dashboards) including total requests, time spent, and maximum request time.

Challenges & Future Directions :light_bulb:

  • DHIS2 can be stressed by tens of millions of records and thousands of users, often exceeding initial developer expectations.
  • Data quality validation within DHIS2 is promoted before data reaches other platforms or models, to prevent issues like outliers.
  • While tools like Grafana are highly customizable, there’s a need for standard DHIS2 Grafana dashboards that can be directly installed to avoid duplication of effort.
  • Future work aims to expose more metrics and telemetry and focus on model tuning, evaluation, and combining models for predictive analytics.
  • The HISP groups are central to setting up infrastructure, connecting actors, and implementing solutions, ensuring data control and tailoring within countries.
DHIS2: Strengthening Health Systems in Francophone Africa! 🇫🇷🗣️

DHIS2: Strengthening Health Systems in Francophone Africa! :france::speaking_head:

Here's a visually engaging and easy-to-read summary for the "Lightning talks: Appropriation, intégration et optimisation: DHIS2 pour le renforcement des systèmes de santé" session! 🚀🌍💡 This lightning talk session, moderated by **Kofi Yadin**, showcased how DHIS2 is a **game-changer** for health system strengthening across Francophone African countries #connect:le-coin-des-francophones, tackling critical issues like data fragmentation and supply chain inefficiencies. --- #### **Mali**: **Fighting Fragmentation with DHIS2!** 🇲🇱🔗 * **The Big Problem**: Mali's health information system was suffering from severe **fragmentation**, with around **53 verified digital applications** (out of 58 surveyed) in use. These apps were often funded by various donors and programs, leading to **weak integration and interoperability**, compromised data quality, and potential biases in decision-making. * **DHIS2 to the Rescue**: DHIS2 has been adopted as Mali's **national platform for health data management since 2016**. It's seen as a **promising solution to limit this fragmentation**. DHIS2 covers the entire country, with data primarily entered at the community level (FOSA). * **Why Integration is Key**: The goal is to **improve data quality** (making it reliable and standardized), **optimize data sharing** for fluidity and security, **reduce the workload** on health workers, automate processes to minimize manual errors, and achieve a **holistic understanding** of national health data. * **Towards Sustainability**: Mali is working on solutions like mapping all software, creating a directory, and developing an interoperability guide. The country boasts a robust technical team with **around 40 DHIS2 administrators and two super-administrators**, demonstrating strong local capacity, though external support is still vital for advanced interoperability and system upgrades. * **Presented by**: Ismaël Dembélé, Country Director, HISP Mali. --- #### **Comoros**: **Integrated Supply Chain with DHIS2 & mSupply!** 🇰🇲📦 * **The Challenge**: Comoros aimed to **strengthen its health information system and supply chain**, moving from manual, paper-based processes to a more efficient, integrated digital system. * **The Integrated Solution (eSIGL)**: An **integrated DHIS2-mSupply solution** was implemented to manage health product flows in real-time. * **mSupply's Role**: Used at the **central office, regional warehouses, and hospitals** (totaling 12 sites). * **DHIS2's Role**: Deployed at **health centers and health posts** (totaling 81 sites). * **The Connection**: The two systems are **integrated via an API address**, allowing for real-time stock visibility and automatic reporting. * **Impact & Progress**: The project has enabled **daily reports and visibility of stockouts**. It has also reduced the manual burden on pharmacy agents. * **Key Challenges & Solutions**: * **Internet Coverage**: A major hurdle, especially in remote health posts. For areas without consistent internet, **monthly reports are used for data synchronization**. Health centers, however, benefit from **regular fiber optic internet connections** for daily updates. * Other challenges included delays in acquiring hardware and issues with national product lists. * **Next Steps**: Continued efforts to strengthen national capacity, integrate vaccination products and private pharmacies into the supply chain, and ensure ongoing system maintenance. * **Presented by**: Amine Ahmed Chamsi, Data Scientist and DHIS2 Administrator, Ministry of Health Comoros.

Congo: National Ownership for Polio Vaccination! :congo_brazzaville::syringe:

  • Highlight: The session also emphasized Congo’s success in leveraging national appropriation of DHIS2. This local ownership was a critical factor in the digitalization of their polio vaccination campaign, contributing significantly to its sustainability.
  • Presented by: Antoine Itoua Atipo, Director, DISER MOH Congo.
    • Please note: While the agenda highlights Congo’s success, specific details on its implementation were not extensively provided in the immediately available sources for this summary.

This session underscored the power of DHIS2 in adapting to diverse country contexts, from overcoming data fragmentation to optimizing critical health programs like supply chain and immunization, all driven by strong local ownership and integration efforts. :flexed_biceps:

Fostering Local Ownership for DHIS2 Sustainability✨💪

Fostering Local Ownership for DHIS2 Sustainability :sparkles::flexed_biceps:

This insightful session at the DHIS2 Annual Conference 2025 explored the **critical role of local ownership** in achieving **successful and sustainable DHIS2 implementations**. With over 300 in-person attendees from 68 countries, the conference emphasized themes of unity, solidarity, and collaboration amidst global health funding challenges.

The session featured experienced implementers and government officials sharing firsthand insights into success factors, challenges, and essential elements for building resilient health information systems.

Why Local Ownership Matters :thinking:
True success in health information systems depends on empowering local stakeholders. The goal is to sustain systems that are successful. This requires a shift from viewing DHIS2 as a donor project to a core national platform.

Key foundational principles for sustainability include:

  • Institutional Support :classical_building:
  • Funding :money_bag:
  • Legislation and Policies :scroll:
  • Capacity and Competence :brain:
  • Infrastructure :building_construction:
  • Data Use Culture :bar_chart:
  • Real-time data access :stopwatch:

Country Experiences & Insights :world_map:

  1. Ghana’s Journey :ghana:

    • Adoption: DHIS2 was introduced in Ghana over a decade ago (April 2012) and quickly adopted by the Ministry of Health and Ghana Health Service as the national HMIS. It’s now central to service delivery reporting, data quality, and decision-making.
    • Capacity Building: Ghana prioritized developing in-house DHIS2 expertise by training a core team of 10 advanced-level staff for remote support, along with a cascade of system administrators from national to regional (16 regions) and district (261 districts) levels. Senior managers were also trained to oversee and monitor DHIS2 activities.
    • Government Engagement: High-level government engagement was central to system adoption and trust. The Ministry of Health led the development of a national health information system strategy, positioning DHIS2 as the core national platform, not a donor project.
    • Success Factors: Strong government ownership and leadership, a clear governance framework, continuous local capacity building and training, stable infrastructure, and a data use culture.
    • Challenges: Retention of trained staff due to competition from NGOs and donor-funded projects, limited ICT skills at subnational levels, inconsistent funding for capacity building and infrastructure, and slow institutional adoption of SOPs.
    • Looking Ahead: Institutionalizing DHIS2 roles within the public sector HR structure, expanding digital literacy, formalizing mentorship programs, and collaborating with academia for innovation and research. The ultimate goal is a self-sustaining ecosystem of DHIS2 experts.

  2. Tanzania’s Progress :tanzania:

    • Transformation: Tanzania has moved from a paper-based data storage system (pre-2015) to a digital data warehouse, leveraging DHIS2 for web portals, scorecards, maps, and mobile use.
    • Governance: DHIS2 is integrated into the government structure, with financial and technical support from development partners, but the country is prepared to continue running the system even without external aid.
    • Key Initiatives: Connecting all health facilities with reliable internet (fiber optic), integrating DHIS2 into annual government planning and budgeting with a dedicated budget line, and fostering local innovations for data analysis and dissemination.
    • Future Focus: Capacity building in big data analysis and data science, ongoing DHIS2 maintenance and programming/system upgrading, developing electronic data quality and spot-check systems, and rolling out health facility community EMI and telemedicine nationwide. They also aim to enhance data repository, warehousing, and interoperability.

  3. West and Central Africa Perspective :globe_showing_europe_africa:

    • Six Critical Dimensions for Success & Sustainability:
      1. Capacity: A well-sized, multi-disciplinary team (public health, data science, IT, server management) that learns by doing.
      2. Approach to Innovation: A proper way to keep innovating, including participatory design.
      3. Governance & Leadership: Essential for successful implementation.
      4. Funding: Crucial, especially in times of funding cuts, to harness resources to strengthen existing systems.
      5. Data Use: Critical for proving value and driving sustainability.
      6. Community of Practice: For knowledge sharing and continuous improvement.

Panel Discussion: Challenges & Solutions :speech_balloon:

  • Emerging Threats: Funding cuts and fragmentation due to parallel systems developed by diverse interests or donors.
  • Staff Retention: Motivating staff by providing new challenges and career development paths, beyond repetitive data entry tasks. Institutionalizing DHIS2 roles within public sector human resource structures helps retention.
  • Financing: Governments are increasingly allocating funds for DHIS2 maintenance and HR costs. Ghana, for example, integrates funding into global fund grants for server space. Tanzania has a specific budget line for DHIS2 running costs.

This session underscored that prolonged success in DHIS2 hinges on robust local capacity, strong government commitment, and strategic integration efforts to overcome fragmentation and ensure data utility across health systems. :rocket::bar_chart: secure and sharable customizations add value to DHIS2 implementations.

DHIS2 Climate App: Protecting Health in a Changing Climate! 🛡️🌦️

DHIS2 Climate App: Protecting Health in a Changing Climate! :shield::sun_behind_rain_cloud:

This session, led by **Bjørn Sandvik (GIS Lead, DHIS2 for Climate & Health)**, **Omiel Patrick Okecho (HISP Uganda)**, and **Melaeke Serawit (HISP Ethiopia)**, focused on how the **DHIS2 Climate App** is a crucial tool for **Ministries of Health (MOHs)** to access and utilize climate data to mitigate the impacts of climate change and extreme weather on health outcomes. The ultimate goal is to enable health planners to **prepare faster, act smarter, and protect more people** from climate-sensitive diseases like malaria, cholera, or heat-related illnesses.

What are Climate Services & DHIS2’s Role? :thinking::light_bulb:

Climate services involve providing scientifically credible climate data, information, and knowledge to assist decision-making. They are designed to respond to user needs and require multi-disciplinary and cross-sector collaboration, often including socioeconomic variables and non-meteorological data like health data.

The DHIS2 Climate App is not a climate service itself, but it provides the building blocks for national teams to create targeted climate services. It’s a foundational step to easily get climate data into DHIS2 and harmonize it with health data. This approach aligns with DHIS2’s success in creating generic building blocks that can be adapted for various fields.

Key Features & Data Integration :globe_with_meridians::link:

The DHIS2 Climate App aims to give MOHs unprecedented access to climate data alongside health data within DHIS2.

  • Data Sources: The app supports various global and local climate/environmental data sources:
    • ERA5-Land (European Centre for Medium-Range Weather Forecasts): A “gridded” dataset, useful for temperature (9x9 km resolution).
    • CHIRPS (Climate Hazards Center): Offers rainfall data at 5 km resolution, providing better accuracy for precipitation.
    • NASA Data: Includes elevation (30m resolution), NDVI vegetation index (250m resolution), and land cover data (500m resolution).
    • ENACTS (Enhancing National Climate Services): A critical initiative for local data integration, working with National Meteorological and Hydrological Services (NMHS). It provides web interfaces and coming API integration for downloading gap-filled local climate data at 5 km resolution, requiring agreement with NMHS.
    • Other planned sources include air quality data (OpenAQ, AirQo) and custom data.
  • Harmonization: The Climate App aligns weather data with health data by period and organizational unit. For districts, it calculates the average of grid cells, and for facilities, it uses data from the surrounding grid cell.
  • New Functionality: The app has seen improvements like importing data for weekly, monthly, and yearly periods, multiple calendar support (Nepali and Ethiopian), and chart settings to make organization unit comparisons easier.
  • Local Data Importance: It’s emphasized that users are not restricted by the Climate App and can import any data they wish to align with health data or use in modeling tools, particularly encouraging local weather data from Met Offices.

Real-World Use Cases :world_map::woman_health_worker:

The session highlighted various country experiences demonstrating the application of the DHIS2 Climate App:

  • Uganda & Ethiopia: Climatic Suitability for Malaria :uganda::ethiopia:

    • Implemented a composite indicator for climatic suitability for malaria (CMM), based on thresholds for precipitation, temperature, and relative humidity. Districts are identified as “suitable” (at risk) if all three conditions are met.
    • This helps in identifying high-risk districts for targeted interventions and impact validation.
    • Ethiopia adapted Uganda’s suitability analysis, incorporating local context, including the crucial role of elevation data in malaria stratification, as mosquitoes may not breed effectively at higher altitudes.
    • This allows for much faster stratification, moving from years to months or even weeks, by keeping climate data updated in DHIS2.

  • Togo: Seasonal Malaria Chemoprevention (SMC) Planning :togo::syringe:

    • Togo integrated climate data into DHIS2 for planning seasonal malaria interventions.
    • Previously, this process was manual and outside DHIS2, relying on pulling malaria case data and using other tools.
    • The integrated solution allows for automatic identification of districts eligible for SMC campaigns based on rainfall peaks and case analysis, determining the number of treatment cycles needed per district.
    • It also helps determine the optimal start and end periods for the campaign in each district based on five years of malaria confinement case data (for children under five), optimizing timing and length to save money and improve efficiency.
    • This integration means climate and health data are now harmonized and available together in DHIS2, with data processing and analysis automated, operating on live (real-time) data.

  • Sri Lanka: Air Quality and Health Risk :sri_lanka::dashing_away:

    • Sri Lanka is working on a use case to correlate PM2.5 air quality data with different health risks, particularly respiratory diseases.
    • A key challenge is the limited number of weather stations, so they are developing high-resolution PM2.5 data (1x1 km) for the entire country.
    • The aim is to build epidemiological risk models, including lag periods between exposure and health response, and eventually develop an early warning system.
    • This project involves multiple partners and integrates rich health data from existing digital systems (like EIMM R, with 97% hospital coverage for ICD-coded diagnoses) with climate data in DHIS2.

  • Mozambique: Climate Data Repository :mozambique::package:

    • Mozambique’s National Institute of Meteorology (MET) is developing a DHIS2-based climate data repository to address inefficient data sharing between sectors.
    • This centralized repository aims to facilitate easy internal access and external sharing of climate data, moving from manual Excel file exchanges to automated processes using the DHIS2 Web API.
    • The Climate Data App is key to making this data “ready to use” for partners like the health sector.
    • The MET also dreams of having an improved public climate data portal and a mobile app for climate data.
    • The Climate Health Adaptation Platform (CHAP) is also being piloted in Mozambique to predict malaria outbreaks using climate variables.

This session underscored the transformative potential of integrating climate and health data within DHIS2 to move from reactive responses to proactive, data-driven interventions, ultimately strengthening health systems against the growing threats of climate change. :flexed_biceps::chart_increasing:

User Research for UX/UI Design: Building User-Centered DHIS2 Systems! 🚀💡

User Research for UX/UI Design: Building User-Centered DHIS2 Systems! :rocket::light_bulb:

This insightful session, led by **Marta Vila, Kim Frost, and Karoline Tufte Lien** from the HISP Centre Product Team, dove deep into the critical role of user research in designing effective and sustainable DHIS2 solutions for a global user base.

The Challenge: Reaching 1 Million+ Users Globally! :globe_showing_americas::straight_ruler:

Traditionally, feedback has come from implementers, which is useful but often misses crucial details. The session highlighted the immense challenge of gathering feedback from over 1 million DHIS2 users spread across 150+ implementations and 25+ HISP groups worldwide. These users vary from Ministry of Health managers to data clerks in remote facilities, making direct engagement difficult and costly.

Not identifying user experience issues early on can lead to:

  • Reduced adoption and engagement.
  • Training overload.
  • Higher support and maintenance costs.

The key distinction was made between:

  • Surface usability flaws: Obvious issues visible to anyone.
  • Subtle usability challenges: Small nuances that disrupt workflows or slow users down, often invisible to developers or implementers but deeply felt by end-users.

The Solution: The HISP UX Research Network :globe_with_meridians::handshake:

To overcome these challenges, the HISP Centre is building a global UX Research Network. This initiative leverages the collaborative nature of HISP groups and their deep connections to local health systems.

The network aims to:

  • Strengthen user-centered design within the DHIS2 ecosystem.
  • Ensure field end-user feedback contributes to continuous improvements.
  • Build capacity for HISP teams to conduct their own UX research activities.

This approach is significantly more scalable and sustainable than traditional field trips by core teams. It follows an iterative loop of Analyze (find the problem) → Design (solution, test design) → Build (develop, release).

Research in Action: Methodologies & Examples :microscope::woman_teacher:

The network trains “champions” from various HISP groups (e.g., 12 implementers/developers from 9 HISP groups were trained). They learn:

  • Generative methods: In-depth interviews to explore user needs, motivations, and workflows, focusing on active listening.
  • Evaluative methods: Usability tests using Figma prototypes to observe real user interactions and uncover design improvements.

A key project for the workshop was improving secondary data entry to make it easier to transfer data from paper forms to DHIS2, focusing on row-based data entry.

Case Study: Simprints’ Biometrics for eTracker in Ghana :ghana::hand_with_fingers_splayed:
Agata Kaczmarek from Simprints shared their human-centered design journey in integrating biometrics into DHIS2’s eTracker for Maternal and Child Health (MNCH) in Ghana.

  • Initial Hypothesis: Using caregiver biometrics (proxy) to identify children.
  • User Feedback Revelation: Proxy biometrics would not work. Users found it confusing, complex, and disruptive to their workflow.
  • The Pivot: Switched to a “one client, one record” approach, simplifying the workflow with clear, sequential text instructions instead of subjective icons.
  • Impact: User Acceptance Testing (UAT) showed:
    • 58.9% faster client identification.
    • 21.1% improved data accuracy.
    • 20% avoidance of duplication.
    • 80% user satisfaction.
    • Notably, face biometrics (58%) were perceived as easier and faster than fingerprint biometrics, despite being a novel concept initially.

The iterative process of testing and refining based on continuous user feedback, even for small details like capture area or auto-capture features, was crucial for success.

Next Steps & Resources :right_arrow::books:

The HISP UX Research Network will continue with:

  • Bi-monthly UX research meetups to build capacity and share experiences (e.g., prototyping with Figma).
  • A Roadmap focus for DHIS2 v43 on improving user experience for visualization, individual data analytics apps, and row-based data entry.
  • Introducing “Office Hours” for 1:1 support and feedback on HISP-specific UX work or personal projects.
  • Future in-person workshops to expand the network.

Available resources include study guides, note-taking sheets, the DHIS2 UI Library (for consistent web and mobile apps), and Figma Design Systems. The DHIS2 App Hub also serves as a platform to share and find extensions built by the community.

This session emphasized that true success in health information systems hinges on empowering local stakeholders, and user research is a powerful tool to achieve this by ensuring systems are designed around real user needs and workflows. :flexed_biceps:

Lightning Talks: Climate & Health Use Cases – Bridging Data for Action! ⚡️📊

Lightning Talks: Climate & Health Use Cases – Bridging Data for Action! :high_voltage::bar_chart:

This dynamic session at the DHIS2 Annual Conference 2025 showcased four impactful initiatives demonstrating how DHIS2 is being leveraged to address climate-sensitive health challenges. It highlighted efforts to integrate diverse data sources and build predictive capabilities for better health outcomes. ---

1. Global Goods for Climate-informed Health Data :globe_with_meridians::books:

  • The Vision: This presentation, by Matthew Keks, Timothy Wule, and Shona Camps, focused on the Digital Public Infrastructure for Climate and Health (DPI4CH). The aim is to support the WHO-WMO Joint Office on Climate and Health in operationalizing integrated climate and health information services.
  • Key Concept: It’s crucial to integrate digital health systems with climate systems to build interoperable digital and data architectures.
  • Challenges & Solutions: Traditional approaches often lead to fragmented ecosystems and “black box” digital systems that are hard to maintain. The SMART Guidelines approach helps create a proactive, standard-based ecosystem by defining essential data, workflows, and specifications.
  • Resources: A new Global Goods Guidebook for Climate and Health is being developed. This resource aims to help policymakers and implementers make informed decisions on open-source digital tools. It assesses existing digital tools based on criteria like global utility, community support, software maturity, equity, and climate-resilient design. DHIS2 is one of the newly approved global goods in this context.

2. Neotree-DHIS2 Link: Enhancing Data Accuracy in Malawi & Zimbabwe :baby::chart_increasing:

  • The Problem: Neotree, a charity operational in Malawi (5 facilities) and Zimbabwe (4 facilities), aims to eradicate preventable infant mortality and morbidity using a digital mobile app. A significant challenge is data transcription errors and under-reporting from paper-based clinical data collection in nurseries.
  • The Solution: The Neotree mobile app provides bedside patient-level data collection by healthcare workers, replacing paper admission forms and offering automatic digital data export. This data is then pushed to the Malawi HMIS through API.
  • Impact: Patient-level data collection significantly reduces transcription errors and the time/cost associated with paper-based processes. Automated aggregation also reduces errors from manual interpretation. The integration improves data coverage and accuracy, supporting health data reporting and decision-making. Neotree aims to integrate patient-level data collection with DHIS2 Tracker and other neonatal digital stakeholders.

3. Developing a Climate Data Repository in Mozambique :mozambique::droplet:

  • The Context: Mozambique’s National Institute of Meteorology (MET) is responsible for monitoring and disseminating national climate data. However, there was an inefficient data sharing gap between sectors due to reliance on manual procedures like exchanging Excel files.
  • The Solution: A centralized Climate Data Repository is being developed for MET, built on DHIS2. This repository aims to facilitate easy internal access and external sharing of climate data, automating information consumption.
  • Benefits:
    • Improved internal data accessibility through user control and permissions in DHIS2.
    • Enhanced external data sharing using DHIS2 Extensibility and API, automating data dissemination to partners.
    • Data ready to use by leveraging the DHIS2 Climate Data App for quick sharing of information.
  • Future Perspectives: MET envisions improved climate data portals and mobile apps for climate data based on this repository. The repository will serve as a primary source of local climate data for integration into forecast models on the CHAP platform.

4. Piloting the CHAP Platform in Mozambique :mosquito::telescope:

  • The Need: Recognizing the impact of climate change on malaria transmission, Mozambique’s malaria program sought an Early Warning System (EWS) to proactively identify patterns preceding outbreaks, including those related to climate variability. A key challenge was effectively integrating climate data into the EWS for accurate predictions.
  • The Platform: The Climate Health Adaptation Platform (CHAP), leveraging machine learning, was adopted to forecast climate-sensitive health outcomes like malaria.
  • Expected Outcomes:
    • Seamless integration of climate data for enhanced accuracy in outbreak predictions.
    • A standardized framework for developing and deploying EWS, streamlining system architecture and maintenance.
    • Inclusion of customized models for malaria and other climate-sensitive diseases.
    • Prediction of malaria outbreaks 3 months in advance.
    • Proactive interventions like vaccination campaigns and public health warnings before outbreaks occur.
  • Architecture: The DHIS2 CHAP Instance sends disease data and receives prediction data, facilitating integrated data analysis. The Mozambique malaria program seeks to extend CHAP to other areas like entomology and case management, using predictive models to generate climate-informed insights.
If You Dream It, You Can Do It: Innovations on Top of the DHIS2 Platform!💡🌐

If You Dream It, You Can Do It: Innovations on Top of the DHIS2 Platform! :light_bulb::globe_with_meridians:

This exciting session showcased incredible ways the DHIS2 community is extending the platform's core functionality to tackle diverse challenges and create powerful new tools. It highlighted how DHIS2's extensibility features empower innovators to build impactful solutions, turning ambitious ideas into reality. The session featured four key innovations, three of which were finalists in the app competition.

1. ICRC’s Prehosp Record Forms App :ambulance::clipboard:

  • What it is: A custom-built, offline-first mobile application designed to record quality real-time data for ambulance and pre-hospital care responses.
  • Why it’s innovative: It replaces inefficient paper forms, which often go undigitized and unused. The app provides a structured framework for clinical actions and observations for responders and enables managers to make data-driven decisions on service delivery and operations.
  • How it’s built: Developed on top of the DHIS2 Tracker application, it leverages Kotlin as the programming language and Jetpack Compose for its clean and reactive user interface. The DHIS2 Android SDK enables offline data storage and seamless data synchronization. It even includes a 3D body injury map using Scene View for interactive visualization.
  • Future: The app plans to be shared on GitHub after final testing and pilots.

2. AI Insights Application :robot::bar_chart:

  • What it is: An AI-powered application that allows users to interact with their DHIS2 data using natural language queries.
  • Why it’s innovative: It provides quick insights into aggregated data, indicators, event data, or tracker data without the need to build complex dashboards. This addresses the challenge of creating numerous dashboards and provides 24/7 access to insights. It can help investigate underperformance and understand root causes.
  • How it’s built: This open-source tool is designed to be highly flexible, capable of connecting with OpenAI’s large language models (LLMs) or locally hosted models like Oola. It’s available on the DHIS2 App Hub and supports further extension and community contributions.

3. DHIS2 Flexi Portal :globe_with_meridians::sparkles:

  • What it is: A deployment-ready and highly customizable public portal that provides secure access to DHIS2 data.
  • Why it’s innovative: It offers a no-code solution for creating public-facing dashboards, significantly reducing development time, human resource needs, and costs traditionally associated with building such portals. It allows users to control what data is visible to external partners and the public.
  • How it’s built: The web portal is developed using Next.js, while the manager application (for configuration within DHIS2) uses the DHIS2 platform and App Runtime. It supports all DHIS2 visualizations, theme customization, mobile-friendliness, and search engine optimization. Configurations can be exported and imported for reuse across different DHIS2 instances.
  • Current Status: It is currently being piloted in Tanzania and Somalia.

4. ArcGIS Connector App :world_map::chart_increasing:

  • What it is: An application that enables seamless integration between DHIS2 and Esri’s ArcGIS geospatial platform.
  • Why it’s innovative: It provides a no-code way to extend DHIS2 data capabilities for advanced geospatial analytics, visualization, and storytelling. It allows for real-time updates of DHIS2 data within ArcGIS. Users can combine DHIS2 data with over 10,000 layers from the Living Atlas and other global data sources.
  • How it’s built: The connector uses a custom data provider to decode and transform DHIS2 data for ArcGIS. It allows for powerful desktop and cloud analytics, including predictive analytics, feature extraction, and damage assessment using machine learning and AI.
  • Resources: The project’s GitHub repositories are publicly available for further exploration.

The session emphasized that DHIS2 is designed with extensibility in mind, offering various tools like custom apps, plugins, APIs (Datastore, Routes, SQL Views, Event Hooks), Android SDKs, and interoperability features (FHIR, Apache Camel) that enable developers and implementers to build diverse and impactful solutions. The DHIS2 App Hub and Developer Portal serve as central resources for finding, sharing, and documenting these innovations and tools.

This session truly highlighted how the DHIS2 community is continually pushing boundaries and doing what they dream to enhance health information systems globally! :flexed_biceps::globe_showing_europe_africa:

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