dashboard-design-for-trials

# Dashboard Design for Trials Design layout sketches for clinical trial data monitoring panels, displaying recruitment progress, AE incidence rates, and other key metrics. ## Features - Generate HTML layout sketches for clinical trial Dashboards - Support multiple chart types: progress bars, line charts, pie charts, bar charts, etc. - Customizable study protocol, site count, key metrics - Responsive design, adaptable to different screen sizes ## Usage ```bash python scripts/main.py [options] ``` ## Parameters | Parameter | Type | Default | Required | Description | |-----------|------|---------|----------|-------------| | `--study-id` | string | STUDY-001 | No | Study ID | | `--study-name` | string | Clinical Trial A | No | Study Name | | `--sites` | int | 10 | No | Number of sites | | `--target-enrollment` | int | 100 | No | Target enrollment count | | `--current-enrollment` | int | 45 | No | Current enrollment count | | `--ae-count` | int | 12 | No | Adverse event count | | `--output` | string | dashboard.html | No | Output HTML file path | ### Examples ```bash # Generate default Dashboard python scripts/main.py # Customize study parameters python scripts/main.py \ --study-id "PHASE-III-2024" \ --study-name "Phase III Clinical Trial of New Drug for Type 2 Diabetes" \ --sites 15 \ --target-enrollment 300 \ --current-enrollment 120 \ --ae-count 25 \ --output my_dashboard.html ``` ## Output Generates an HTML Dashboard containing the following modules: 1. **Study Overview Card** - Study ID, name, status 2. **Recruitment Progress** - Overall progress bar, site-by-site progress comparison 3. **Subject Distribution** - Gender, age distribution pie charts 4. **AE Monitoring** - Adverse event incidence rate, severity distribution 5. **Data Quality** - CRF completion rate, query count 6. **Timeline** - Study milestones, estimated completion date ## Dependencies - Python 3.7+ - No additional dependencies (pure standard library generates HTML/CSS/JS) ## Author Skill ID: 194 ## Risk Assessment | Risk Indicator | Assessment | Level | |----------------|------------|-------| | Code Execution | Python/R scripts executed locally | Medium | | Network Access | No external API calls | Low | | File System Access | Read input files, write output files | Medium | | Instruction Tampering | Standard prompt guidelines | Low | | Data Exposure | Output files saved to workspace | Low | ## Security Checklist - [ ] No hardcoded credentials or API keys - [ ] No unauthorized file system access (../) - [ ] Output does not expose sensitive information - [ ] Prompt injection protections in place - [ ] Input file paths validated (no ../ traversal) - [ ] Output directory restricted to workspace - [ ] Script execution in sandboxed environment - [ ] Error messages sanitized (no stack traces exposed) - [ ] Dependencies audited ## Prerequisites No additional Python packages required. ## Evaluation Criteria ### Success Metrics - [ ] Successfully executes main functionality - [ ] Output meets quality standards - [ ] Handles edge cases gracefully - [ ] Performance is acceptable ### Test Cases 1. **Basic Functionality**: Standard input → Expected output 2. **Edge Case**: Invalid input → Graceful error handling 3. **Performance**: Large dataset → Acceptable processing time ## Lifecycle Status - **Current Stage**: Draft - **Next Review Date**: 2026-03-06 - **Known Issues**: None - **Planned Improvements**: - Performance optimization - Additional feature support