Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
View on GitHubK-Dense-AI/claude-scientific-writer
claude-scientific-writer
skills/clinical-decision-support/SKILL.md
January 20, 2026
Select agents to install to:
npx add-skill https://github.com/K-Dense-AI/claude-scientific-writer/blob/main/skills/clinical-decision-support/SKILL.md -a claude-code --skill clinical-decision-supportInstallation paths:
.claude/skills/clinical-decision-support/# Clinical Decision Support Documents ## Description Generate professional clinical decision support (CDS) documents for pharmaceutical companies, clinical researchers, and medical decision-makers. This skill specializes in analytical, evidence-based documents that inform treatment strategies and drug development: 1. **Patient Cohort Analysis** - Biomarker-stratified group analyses with statistical outcome comparisons 2. **Treatment Recommendation Reports** - Evidence-based clinical guidelines with GRADE grading and decision algorithms All documents are generated as publication-ready LaTeX/PDF files optimized for pharmaceutical research, regulatory submissions, and clinical guideline development. **Note:** For individual patient treatment plans at the bedside, use the `treatment-plans` skill instead. This skill focuses on group-level analyses and evidence synthesis for pharmaceutical/research settings. **Writing Style:** For publication-ready documents targeting medical journals, consult the **venue-templates** skill's `medical_journal_styles.md` for guidance on structured abstracts, evidence language, and CONSORT/STROBE compliance. ## Capabilities ### Document Types **Patient Cohort Analysis** - Biomarker-based patient stratification (molecular subtypes, gene expression, IHC) - Molecular subtype classification (e.g., GBM mesenchymal-immune-active vs proneural, breast cancer subtypes) - Outcome metrics with statistical analysis (OS, PFS, ORR, DOR, DCR) - Statistical comparisons between subgroups (hazard ratios, p-values, 95% CI) - Survival analysis with Kaplan-Meier curves and log-rank tests - Efficacy tables and waterfall plots - Comparative effectiveness analyses - Pharmaceutical cohort reporting (trial subgroups, real-world evidence) **Treatment Recommendation Reports** - Evidence-based treatment guidelines for specific disease states - Strength of recommendation grading (GRADE system: 1A, 1B, 2A, 2B, 2C) - Quality of evidence assessment (high, moderate