HighCostDrugsDemo/analysis/CLAUDE.md

Analysis Package

Four-step pathway analysis pipeline refactored from original 267-line generate_graph() function.

Module: pathway_analyzer.py

Main entry points:

• generate_icicle_chart(df, filters) — Directory charts (Trust → Directory → Drug → Pathway)
• generate_icicle_chart_indication(df, indication_df, filters) — Indication charts using Search_Term hierarchy

Pipeline steps:

1. prepare_data() — Filter by date/trusts/drugs/directories. MUST use df.copy() to prevent mutation.
2. calculate_statistics() — Compute frequency, cost, duration stats
3. build_hierarchy() — Create Trust → Directory/Indication → Drug → Pathway structure
4. prepare_chart_data() — Format data for Plotly icicle chart

Note on modified UPIDs: For drug-aware indication matching, UPIDs are formatted as {original}|{search_term}. The hierarchy-building functions treat UPID as opaque — pipe delimiters work transparently without code changes.

Module: statistics.py

Statistical calculation helper functions (frequency, cost, duration, per-patient metrics).

Called by calculate_statistics() during pipeline execution.