AlterLab Treatment Plans
Skill ActivePart of the AlterLab Academic Skills suite. Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.
To enable users to create concise, professional, and compliant medical treatment plans across various specialties, supporting evidence-based practice and patient-centered care.
Features
- Generates 7 types of medical treatment plan templates (LaTeX/PDF)
- Includes 5 detailed reference guides on standards, goals, and compliance
- Provides Python scripts for template generation, validation, and timeline visualization
- Emphasizes concise, actionable, and patient-centered documentation
- Adheres to professional styling and regulatory requirements (HIPAA)
Use Cases
- Creating individualized treatment plans for patient care
- Ensuring regulatory compliance (HIPAA) in medical documentation
- Developing professional, evidence-based treatment protocols
- Streamlining the documentation process with pre-built templates and tools
Non-Goals
- Replacing professional medical judgment
- Providing medical advice directly
- Acting as a standalone EHR system
Workflow
- Select template type (interactive or via script argument)
- Generate template using provided Python script
- Customize template with patient-specific de-identified information
- Define SMART goals and interventions
- Compile LaTeX to PDF
- Run validation scripts for completeness and quality checks
- Review with patient for shared decision-making
- Implement plan and document progress
Practices
- Evidence-Based Practice
- Patient-Centered Care
- Regulatory Compliance
- Professional Documentation
Prerequisites
- LaTeX distribution (e.g., TeX Live) for PDF generation
- Python 3.6+ for script execution
- Python `matplotlib` library (optional, for visual timeline)
Maintenance
- warning:Dependency ManagementThe visual timeline generation relies on matplotlib, but no lockfile is present and the version is not explicitly pinned in the provided code, suggesting potential maintenance challenges.
Trust
- warning:Issues AttentionThere are 2 open issues and 0 closed issues in the last 90 days, indicating slow maintainer response to new issues.
Code Execution
- warning:ValidationThe Python validation scripts (`check_completeness.py`, `validate_treatment_plan.py`) lack explicit schema validation libraries like Zod or Pydantic for their inputs, relying on basic regex. Parameter shape is validated but value constraint is not robust.
- warning:LoggingThe scripts provide console output for status and errors but do not implement a structured local audit log for actions taken.
- warning:Tool FallbackThe visual timeline generation requires matplotlib and provides a fallback to text-based output but does not explicitly declare the required version or provide an explicit installation instruction for matplotlib within the main SKILL.md.
Compliance
- info:GDPRThe skill processes de-identified patient data as per HIPAA, but does not specifically mention GDPR compliance or operate in EU-specific contexts.
Portability
- warning:Runtime stabilityThe visual timeline generation requires matplotlib, which may not be universally available. While the script attempts a fallback, it warns about the missing dependency.
Execution
- warning:Pinned dependenciesWhile Python scripts are provided, there is no `requirements.txt` or lockfile to pin dependencies like matplotlib, which could lead to versioning issues.
Installation
npx skills add AlterLab-IEU/AlterLab-Academic-SkillsRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
Trust Signals
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