- Replace QUALIFY ROW_NUMBER()=1 with GROUP BY + COUNT(*) to return all matching
Search_Terms per patient instead of just the most recent
- Add earliest_hcd_date parameter to restrict GP codes to HCD data window
- Return code_frequency column (count of matching SNOMED codes per Search_Term)
for use as tiebreaker in drug-aware indication matching
- Update empty DataFrame returns to match new column format
Merge 'allergic asthma' and 'severe persistent allergic asthma' into
canonical 'asthma' in both CLUSTER_MAPPING_SQL (Snowflake CTE) and
load_drug_indication_mapping() (DimSearchTerm.csv loader).
- CLUSTER_MAPPING_SQL: 3 Cluster_IDs (AST_COD, eFI2_Asthma, SEVAST_COD) now
all map to Search_Term = 'asthma'
- Added SEARCH_TERM_MERGE_MAP constant for reusable normalization
- load_drug_indication_mapping() applies merge at CSV load time
- urticaria (XSAL_COD) stays separate — not merged with asthma
- Combined asthma drug list: BENRALIZUMAB, DUPILUMAB, INHALED, MEPOLIZUMAB,
OMALIZUMAB, RESLIZUMAB
The UNIQUE constraint was UNIQUE(date_filter_id, ids) instead of
UNIQUE(date_filter_id, chart_type, ids), causing INSERT OR REPLACE
to overwrite directory chart root/trust nodes when indication nodes
were inserted. Dropped and recreated the table, re-ran full refresh.
Validation: both chart types have all hierarchy levels (0-5),
all 12 date filters produce valid icicle charts, KPIs correct.
prepare_data() mapped Provider Code → Name in-place. When called for directory
charts first, then indication charts, the second call re-mapped already-mapped
values to NaN, silently dropping all data. Added df.copy() to prevent mutation.
Also fixes directory charts only generating data for the first date filter.
Results: 3,633 pathway nodes now generated (1,101 directory + 2,532 indication)
across all 12 datasets (6 date filters × 2 chart types).
- Add selected_chart_type state variable and set_chart_type() handler
- Add chart_type filter to load_pathway_data() WHERE clause
- Create segmented control toggle component in filter strip
- Add dynamic hierarchy label (Directorate vs Indication)
- Update chart title to include chart type prefix
- Add CLUSTER_MAPPING_SQL constant embedding full snomed_indication_mapping_query.sql
- Add get_patient_indication_groups() function that queries Snowflake directly
- Uses QUALIFY ROW_NUMBER() to get most recent diagnosis per patient
- Returns DataFrame with PatientPseudonym, Search_Term, EventDateTime
- Handles edge cases: empty list, Snowflake unavailable
- Batch processing with configurable batch_size (default 500)
- Comprehensive logging for match statistics
Fixed two critical bugs preventing GP diagnosis matching:
1. SNOMED codes in scientific notation now converted to integers
2. Using PseudoNHSNoLinked (not PersonKey) for GP record lookup
Full refresh is running in background - next iteration should verify completion.
- Add REF_DRUG_SNOMED_MAPPING_SCHEMA with 11 columns for direct SNOMED mapping
- Add 5 indexes for lookup performance (drug, cleaned_drug, snomed, search_term, composite)
- Add create_drug_snomed_mapping_table() helper function
- Update helper functions (drop, get_counts, verify_exists) to include new table
- Table is included in REFERENCE_TABLES_SCHEMA and created by migration
Task 1.3 (Create Migration Script) is satisfied by existing code:
- python -m data_processing.migrate creates all pathway tables
- pathway_date_filters auto-populated via INSERT OR REPLACE in schema
- Verified: fresh database creates all 3 tables with 6 date filters
Create data_processing/pathway_pipeline.py with:
- DateFilterConfig dataclass for date filter configuration
- DATE_FILTER_CONFIGS with 6 pre-defined combinations
- compute_date_ranges() for computing actual dates from config
- fetch_and_transform_data() for Snowflake fetch + transformations
- process_pathway_for_date_filter() using existing generate_icicle_chart()
- extract_denormalized_fields() to parse trust/directory/drugs from ids
- convert_to_records() for SQLite insertion
- process_all_date_filters() convenience function
- Verified all design tokens match spec exactly
- Confirmed responsive behavior via flex_wrap patterns
- Audited hover states and transitions
- Validated chart colorscale uses design system palette
- Add load_data() method to AppState that connects to SQLite database
- Populate available_drugs, available_directorates, available_indications from DB
- Detect latest date in dataset and set filter defaults accordingly
- Load KPI values: total_records, unique_patients, total_drugs, total_cost
- Add on_load handler to trigger data loading on page initialization
- Handle database errors gracefully with meaningful error messages
Andrew Charlwood