Clinical Decision Support Documents
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research: patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms).
Key Benefits
- Patient cohort analysis with biomarker stratification
- Treatment recommendation reports with GRADE evidence grading
- Statistical analysis (hazard ratios, survival curves, waterfall plots)
- Biomarker integration (genomic alterations, IHC, PD-L1)
- Regulatory compliance (HIPAA de-identification, ICH-GCP)
- Publication-ready LaTeX/PDF format (0.5in margins)
- AI-generated clinical decision flowcharts
Core Capabilities
- Document Types: Patient cohort analysis, treatment recommendation reports
- Biomarkers: Genomic alterations, gene expression, IHC markers, molecular subtypes
- Statistics: Hazard ratios, 95% CI, p-values, Kaplan-Meier curves, Cox regression
- Evidence Grading: GRADE system (1A/1B/2A/2B/2C), quality assessment
- Visuals: Survival curves, waterfall plots, forest plots, TikZ decision algorithms
- Use Cases: Drug development, regulatory submissions, clinical guidelines, medical strategy
When to Use
- Analyze patient cohorts stratified by biomarkers or molecular subtypes
- Generate treatment recommendations with evidence grading
- Compare outcomes between patient subgroups (survival, response rates)
- Produce pharmaceutical research documents for trials or regulatory use
- Develop clinical practice guidelines with decision algorithms
- Document biomarker-guided therapy selection (population-level)
- Synthesize evidence from multiple trials
Pharmaceutical Applications
- Phase 2/3 trial subgroup analyses
- Companion diagnostic development
- Regulatory submissions (IND/NDA)
- KOL education materials
- Medical strategy documents
- Clinical guideline development
- Real-world evidence cohort studies
Source: https://github.com/K-Dense-AI/claude-scientific-writer/tree/main/skills/clinical-decision-support License: MIT
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