Testing and Validating Reports

Testing and Validating Reports

This guide provides a systematic approach to testing and validating reports before and after deployment.

Before deploying reports to production, thorough testing ensures they work correctly and produce accurate results. This guide outlines a three-phase testing strategy: unit testing of individual components (cohorts, indicators), integration testing of complete reports, and user acceptance testing with real users. Use the validation checklists to verify technical functionality, business accuracy, and user experience before going live, then follow the post-deployment monitoring practices to maintain report quality over time.

Testing Strategy

1. Unit Testing (Individual Components)

Cohort Queries:

  • Test with known patient sets

  • Verify parameter handling

  • Check edge cases (no results, large results)

  • Validate date range logic

Indicators:

  • Test calculations with known values

  • Verify parameter mapping

  • Check fraction calculations

  • Test with empty cohorts

2. Integration Testing (Complete Reports)

End-to-End Testing:

  • Run complete reports with test data

  • Verify all parameters work correctly

  • Test different output formats

  • Check performance with realistic data volumes

Cross-Validation:

  • Compare results with manual calculations

  • Check against other data sources

  • Verify with subject matter experts

  • Test with different user roles

3. User Acceptance Testing

Involve End Users:

  • Have actual users test the reports

  • Verify reports meet stated requirements

  • Check usability of parameters and outputs

  • Gather feedback on performance and functionality

Validation Checklist

Before Deployment

Technical Validation:

All parameters work correctly
Date ranges produce expected results
Location filtering works properly
Output formats render correctly
Performance is acceptable
Error handling works properly

Business Validation:

Results match manual calculations
Numbers align with known data sources
Reports answer intended questions
Output format meets user needs
Documentation is clear and complete

User Validation:

Users can run reports successfully
Parameter interface is intuitive
Results are interpretable
Performance meets user expectations

Post-Deployment Monitoring

Regular Checks:

  • Monitor report usage patterns

  • Check for error reports from users

  • Validate results periodically

  • Monitor system performance impact

Continuous Improvement:

  • Gather user feedback regularly

  • Update documentation based on questions

  • Optimize performance as needed

  • Add new features based on user needs