Dhis2 Data Entry

Steps

Step 1: Access the DHIS2 Demo Instance

Go to https://play.dhis2.org/ and log into the demo instance. Explore:

• Data Entry app: Where facility-level data is entered
• Dashboard app: Where visualizations live
• Data Visualizer: Build your own charts
• Maps: Geographic visualization of health data

Step 2: Understand the Data Model

Step 3: Enter Data

In the Data Entry app:

1. Select an Organisation Unit (pick a health facility)
2. Select a Data Set (e.g., "Disease Surveillance")
3. Select a Period (e.g., January 2026)
4. Enter values for 5+ data elements
5. Click "Complete" to submit

Step 4: Interpret a Dashboard

Open the "Disease Surveillance" dashboard. For each visualization, answer:

• What data elements are displayed?
• What time period is shown?
• What geographic level (national, regional, facility)?
• What trends do you see?
• Where is data missing, and why does that matter for AI?

Step 5: Export Data

Use the Data Visualizer to create a chart, then export as:

1. CSV (for spreadsheet analysis)
2. JSON (for programmatic use / AI pipelines)

Note the structure of the exported data — this is what AI models consume.

Artifacts

1. Data Entry Screenshot — Evidence of completed data entry for one facility/period
2. Dashboard Analysis — 1-page write-up interpreting 3 dashboard visualizations (what the data shows, what's missing, implications)
3. Exported Dataset — CSV or JSON export with brief description of contents and quality assessment

Assessment Criteria

Common Mistakes

• Entering data for the wrong period (check the period selector carefully)
• Confusing data elements with indicators (elements are raw, indicators are calculated)
• Ignoring "0" vs blank — zero means "none observed", blank means "not reported" — critical difference for AI
• Assuming dashboard data is complete — always check reporting rates

Related Skills

• fhir-resource-basics — How DHIS2 data maps to FHIR resources
• digitalize-paper-records — What happens before data reaches DHIS2
• ai-readiness-scorecard — DHIS2 usage is a key dimension of institutional AI readiness

References

• DHIS2 Documentation: https://docs.dhis2.org/
• DHIS2 Academy: https://www.dhis2.org/academy
• HISP Centre: https://www.mn.uio.no/ifi/english/research/networks/hisp/