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Step 4: Run the Book Chapter Generator

Prompt

Run the book-chapter-generator skill

⎿  ⧉ Selected 1 lines from docs/prompts/04-run-book-chapter-generator.md in Visual Studio Code

⏺ I'll run the book-chapter-generator skill for you.

The "book-chapter-generator" skill is running

⏺ I'll help you generate a comprehensive chapter structure for your intelligent textbook. Let me start by analyzing the required input resources.

⏺ Read(docs/course-description.md) ⎿  Read 206 lines

⏺ Read(docs/learning-graph/learning-graph.json) ⎿  Read 2903 lines

⏺ Read(docs/learning-graph/concept-taxonomy.md) ⎿  Read 111 lines

⏺ Let me analyze the learning graph structure and design constraints to create an optimal chapter structure.

⏺ Bash(python3 -c " import json…) ⎿  Concept Distribution by Taxonomy Group:
================================================== PAT (Patient Data ): 25 concepts … +21 lines (ctrl+o to expand)

⏺ Now let me complete the analysis and design the chapter structure.

⏺ Proposed Chapter Structure

I've designed a 12-chapter structure for your textbook covering all 200 concepts.

Chapters:

  1. Graph Theory and Database Foundations (15 concepts) Introduces fundamental graph theory concepts, nodes, edges, labeled property graphs, directed acyclic graphs, graph traversal, and relational database concepts that serve as prerequisites for healthcare graph modeling.

  2. Introduction to Healthcare Systems (20 concepts) Covers healthcare system fundamentals including cost models (fee-for-service vs value-based care), healthcare stakeholders (patients, providers, payers), medical coding systems (ICD, CPT, HCPCS, Drug Codes), electronic health records, and healthcare interoperability.

  3. Graph Query Languages and Technologies (10 concepts) Explores graph database query languages (Cypher, GQL, GSQL), graph pattern matching, query optimization, indexing strategies, and performance tuning techniques specific to graph databases.

  4. Patient-Centric Data Modeling (25 concepts) Focuses on modeling patient records, demographics, medical history, diseases, conditions, symptoms, diagnoses, treatment plans, prescriptions, medications, lab tests, vital signs, care plans, patient journeys, and outcomes.

  5. Provider Operations and Networks (25 concepts) Examines healthcare providers including primary care, specialists, hospitals, clinics, emergency departments, provider networks, schedules, appointments, referrals, credentials, performance metrics, care teams, and clinical guidelines.

  6. Payer Perspective and Insurance Claims (20 concepts) Addresses insurance claims processing, adjudication, policies, coverage, benefit plans, copayments, deductibles, formularizes, pharmacy benefit managers, prior authorization, utilization review, and reimbursement.

  7. Healthcare Financial Analytics (15 concepts) Analyzes healthcare costs, revenue cycles, billing codes, charge masters, profitability, operating margins, payer mix, contract negotiation, provider compensation, capitation, risk adjustment, and value-based payment models.

  8. Fraud Detection and Compliance (15 concepts) Investigates healthcare fraud patterns including upcoding, unbundling, phantom billing, duplicate claims, kickback schemes, referral network analysis, community detection, anomaly detection, and specialized fraud in behavioral health and DME.

  9. Graph Algorithms and Analytics (15 concepts) Teaches graph algorithms including shortest path, centrality measures (PageRank, betweenness, degree), clustering coefficients, connected components, cycle detection, pattern recognition, similarity measures, link prediction, and graph embeddings.

  10. AI and Machine Learning Integration (15 concepts) Integrates artificial intelligence, machine learning, large language models, vector stores, semantic search, RAG architecture, knowledge graphs, clinical decision support, clinical discovery, recommendation systems, and population health analytics.

  11. Security, Privacy, and Data Governance (20 concepts) Ensures HIPAA compliance, protected health information handling, data privacy and security, access control, role-based access control, authentication, authorization, audit trails, de-identification, metadata management, data lineage, provenance, quality, governance, and explainability.

  12. Capstone Projects and Real-World Applications (5 concepts) Culminates in capstone project development, presentations, understanding graph career paths, building healthcare analytics platforms, and implementing real-world solutions.

Design Rationale:

Dependency Flow: - Chapters progress from foundational concepts (graphs, databases) → healthcare domain knowledge → graph technologies → three perspectives (patient, provider, payer) → financial analytics → fraud detection → advanced analytics → AI integration → governance → capstone - All dependencies are respected: concepts only appear after their prerequisites

Balanced Distribution: - Average: 16.7 concepts per chapter - Range: 5-25 concepts per chapter - Most chapters fall within the optimal 10-20 concept range - Chapters 4 and 5 are slightly larger (25 concepts) but represent cohesive, well-defined domains (Patient and Provider perspectives)

Logical Grouping: - Each chapter aligns with a taxonomy category or logical combination - Related concepts stay together for better cognitive cohesion - Natural progression from basic to advanced topics

Statistics:

  • Total chapters: 12
  • Average concepts per chapter: 16.7
  • Range: 5-25 concepts per chapter
  • All 200 concepts covered: ✓
  • All dependencies respected: ✓

Do you approve this chapter structure? (y/n)

If you'd like any changes, please specify: - Different number of chapters? - Specific concepts moved to different chapters? - Chapter titles revised? - Different grouping strategy?

y

⏺ Excellent! Let me now generate the chapter directory structure and files.

⏺ Bash(mkdir -p docs/chapters) ⎿  (No content)

⏺ Bash(cd docs/chapters && mkdir -p 01-graph-theory-database-foundations 02-intro-to-healthcare-systems 03-graph-query-languages 04-patient-centric-data-modeling 05-pr…) ⎿  (No content)

⏺ Write(index.md) ⎿  Wrote 38 lines to index.md
# Chapters This textbook is organized into 12 chapters covering 200 concepts in graph-based healthcare data modeling. ## Chapter Overview 1. Graph Theory and Database Foundations - Introduces fundamental graph theory concepts, nodes, edges, labeled property graphs, directed acyclic graphs, graph traversal, and relational database concepts that serve as prerequisites for healthcare graph modeling. 2. Introduction to Healthcare Systems - Covers healthcare system fundamentals including cost models (fee-for-service vs value-based care), healthcare stakeholders (patients, providers, payers), medical coding systems (ICD, CPT, HCPCS, Drug Codes), electronic health records, and healthcare interoperability. … +28 lines (ctrl+o to expand)

⏺ Now let me create the individual chapter files with the correct concept assignments:

⏺ Bash(python3 << 'EOF' import json…) ⎿  Error: Exit code 1 Traceback (most recent call last): File "", line 4, in FileNotFoundError: [Errno 2] No such file or directory: 'docs/learning-graph/learning-graph.json'

⏺ Bash(python3 << 'EOF' import json…) ⎿  Created: /Users/dan/Documents/ws/modeling-healthcare-data/docs/chapters/01-graph-theory-database-foundations/index.md Created: /Users/dan/Documents/ws/modeling-healthcare-data/docs/chapters/02-intro-to-healthcare-systems/index.md Created: /Users/dan/Documents/ws/modeling-healthcare-data/docs/chapters/03-graph-query-languages/index.md … +11 lines (ctrl+o to expand)

⏺ Now let me update the MkDocs navigation to include the chapters:

⏺ Read(~/Documents/ws/modeling-healthcare-data/mkdocs.yml) ⎿  Read 81 lines

⏺ Update(~/Documents/ws/modeling-healthcare-data/mkdocs.yml) ⎿  Updated ../../mkdocs.yml with 15 additions
11 - About: about.md 12 - Course Description: course-description.md 13
14 + - Chapters: 15 + - Overview: chapters/index.md 16 + - Chapter 1 - Graph Theory and Database Foundations: chapters/01-graph-theory-database-foundations/index.md 17 + - Chapter 2 - Introduction to Healthcare Systems: chapters/02-intro-to-healthcare-systems/index.md 18 + - Chapter 3 - Graph Query Languages and Technologies: chapters/03-graph-query-languages/index.md 19 + - Chapter 4 - Patient-Centric Data Modeling: chapters/04-patient-centric-data-modeling/index.md 20 + - Chapter 5 - Provider Operations and Networks: chapters/05-provider-operations-networks/index.md 21 + - Chapter 6 - Payer Perspective and Insurance Claims: chapters/06-payer-perspective-insurance/index.md 22 + - Chapter 7 - Healthcare Financial Analytics: chapters/07-healthcare-financial-analytics/index.md 23 + - Chapter 8 - Fraud Detection and Compliance: chapters/08-fraud-detection-compliance/index.md 24 + - Chapter 9 - Graph Algorithms and Analytics: chapters/09-graph-algorithms-analytics/index.md 25 + - Chapter 10 - AI and Machine Learning Integration: chapters/10-ai-machine-learning-integration/index.md 26 + - Chapter 11 - Security, Privacy, and Data Governance: chapters/11-security-privacy-governance/index.md 27 + - Chapter 12 - Capstone Projects and Real-World Applications: chapters/12-capstone-real-world-applications/index.md 28 +
29 - Learning Graph: 30 - Introduction: learning-graph/index.md 31 - Course Description Assessment: learning-graph/course-description-assessment.md

⏺ Chapter Structure Generated Successfully!

Created: - chapters/index.md (main chapter overview) - 12 chapter directories with index files - Updated mkdocs.yml navigation

Files Created:

Main Index: - /docs/chapters/index.md

Chapter Directories and Files: 1. /docs/chapters/01-graph-theory-database-foundations/index.md (15 concepts) 2. /docs/chapters/02-intro-to-healthcare-systems/index.md (20 concepts) 3. /docs/chapters/03-graph-query-languages/index.md (10 concepts) 4. /docs/chapters/04-patient-centric-data-modeling/index.md (25 concepts) 5. /docs/chapters/05-provider-operations-networks/index.md (25 concepts) 6. /docs/chapters/06-payer-perspective-insurance/index.md (20 concepts) 7. /docs/chapters/07-healthcare-financial-analytics/index.md (15 concepts) 8. /docs/chapters/08-fraud-detection-compliance/index.md (15 concepts) 9. /docs/chapters/09-graph-algorithms-analytics/index.md (15 concepts) 10. /docs/chapters/10-ai-machine-learning-integration/index.md (15 concepts) 11. /docs/chapters/11-security-privacy-governance/index.md (20 concepts) 12. /docs/chapters/12-capstone-real-world-applications/index.md (5 concepts)

Next Steps:

  1. Review the chapter structure: Run mkdocs serve and navigate to the Chapters section
  2. Generate chapter content: Use the chapter-content-generator skill to populate each chapter with detailed educational content
  3. Each chapter includes:
  4. Title and comprehensive summary
  5. Complete list of concepts covered (all 200 concepts assigned)
  6. Prerequisites with links to prior chapters
  7. "TODO: Generate Chapter Content" placeholder

Statistics:

  • Total chapters: 12
  • Total concepts assigned: 200
  • All dependencies respected: ✓
  • MkDocs navigation updated: ✓
  • Average concepts per chapter: 16.7
  • Concept distribution: 5-25 concepts per chapter

You can now view your chapter structure by running mkdocs serve and visiting the Chapters section in your browser!