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Initial commit before Ralph loop

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Andrew Charlwood
2026-02-04 13:04:29 +00:00
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"""
SQLite schema definitions for NHS High-Cost Drug Patient Pathway Analysis Tool.
Contains SQL strings for creating reference tables, fact tables, and indexes.
Schema design supports:
- Reference data from CSV files (drug names, organizations, directories)
- Drug-directory mappings with single-valid-directory flag
- Patient intervention facts with proper indexing
- Cached aggregations for performance
- File tracking for incremental updates
"""
from typing import Optional
import sqlite3
from core.logging_config import get_logger
logger = get_logger(__name__)
# =============================================================================
# Reference Table Schemas
# =============================================================================
REF_DRUG_NAMES_SCHEMA = """
-- Mapping from raw drug names (as they appear in source data) to standardized names
-- Source: data/drugnames.csv
CREATE TABLE IF NOT EXISTS ref_drug_names (
id INTEGER PRIMARY KEY AUTOINCREMENT,
raw_name TEXT NOT NULL UNIQUE,
standard_name TEXT NOT NULL,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
-- Index for fast lookups during data transformation
CREATE INDEX IF NOT EXISTS idx_ref_drug_names_raw ON ref_drug_names(raw_name);
CREATE INDEX IF NOT EXISTS idx_ref_drug_names_standard ON ref_drug_names(standard_name);
"""
REF_ORGANIZATIONS_SCHEMA = """
-- NHS organization codes and names
-- Source: data/org_codes.csv
CREATE TABLE IF NOT EXISTS ref_organizations (
id INTEGER PRIMARY KEY AUTOINCREMENT,
org_code TEXT NOT NULL UNIQUE,
org_name TEXT NOT NULL,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
-- Index for fast lookups by organization code
CREATE INDEX IF NOT EXISTS idx_ref_organizations_code ON ref_organizations(org_code);
"""
REF_DIRECTORIES_SCHEMA = """
-- Medical directories/specialties
-- Source: data/directory_list.csv
CREATE TABLE IF NOT EXISTS ref_directories (
id INTEGER PRIMARY KEY AUTOINCREMENT,
directory_name TEXT NOT NULL UNIQUE,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
-- Index for fast lookups by directory name
CREATE INDEX IF NOT EXISTS idx_ref_directories_name ON ref_directories(directory_name);
"""
REF_DRUG_DIRECTORY_MAP_SCHEMA = """
-- Mapping from drug names to valid directories
-- Source: data/drug_directory_list.csv
-- A drug may map to multiple directories (one row per drug-directory pair)
-- The is_single_valid flag indicates drugs with exactly ONE valid directory,
-- which enables automatic directory assignment in department_identification()
CREATE TABLE IF NOT EXISTS ref_drug_directory_map (
id INTEGER PRIMARY KEY AUTOINCREMENT,
drug_name TEXT NOT NULL,
directory_name TEXT NOT NULL,
is_single_valid BOOLEAN NOT NULL DEFAULT 0,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
UNIQUE(drug_name, directory_name)
);
-- Index for looking up directories by drug name (most common access pattern)
CREATE INDEX IF NOT EXISTS idx_ref_drug_directory_map_drug ON ref_drug_directory_map(drug_name);
-- Index for reverse lookup (find drugs by directory)
CREATE INDEX IF NOT EXISTS idx_ref_drug_directory_map_directory ON ref_drug_directory_map(directory_name);
-- Index for quick filtering of single-valid drugs
CREATE INDEX IF NOT EXISTS idx_ref_drug_directory_map_single ON ref_drug_directory_map(is_single_valid);
"""
REF_DRUG_INDICATION_CLUSTERS_SCHEMA = """
-- Mapping from drugs to SNOMED clusters for indication validation
-- Source: data/drug_indication_clusters.csv
-- Used to validate that patients have appropriate GP diagnoses for their prescribed drugs
-- A drug may map to multiple clusters (one row per drug-indication-cluster combination)
CREATE TABLE IF NOT EXISTS ref_drug_indication_clusters (
id INTEGER PRIMARY KEY AUTOINCREMENT,
drug_name TEXT NOT NULL,
indication TEXT NOT NULL,
cluster_id TEXT NOT NULL,
cluster_description TEXT,
nice_ta_reference TEXT,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
UNIQUE(drug_name, indication, cluster_id)
);
-- Index for looking up clusters by drug name (most common access pattern)
CREATE INDEX IF NOT EXISTS idx_ref_drug_indication_clusters_drug ON ref_drug_indication_clusters(drug_name);
-- Index for looking up drugs by cluster (for finding all drugs treating a condition)
CREATE INDEX IF NOT EXISTS idx_ref_drug_indication_clusters_cluster ON ref_drug_indication_clusters(cluster_id);
-- Index for looking up by indication text
CREATE INDEX IF NOT EXISTS idx_ref_drug_indication_clusters_indication ON ref_drug_indication_clusters(indication);
"""
# =============================================================================
# Fact Table Schemas
# =============================================================================
FACT_INTERVENTIONS_SCHEMA = """
-- Patient intervention records (fact table)
-- Source: HCD activity data (CSV/Parquet files or Snowflake)
-- This is the main fact table storing all patient intervention events
CREATE TABLE IF NOT EXISTS fact_interventions (
id INTEGER PRIMARY KEY AUTOINCREMENT,
-- Patient identification
upid TEXT NOT NULL, -- Unique Patient ID (Provider Code[:3] + PersonKey)
provider_code TEXT NOT NULL, -- Original provider code (3-5 chars)
person_key TEXT NOT NULL, -- Patient key from source system
-- Intervention details
drug_name_raw TEXT, -- Original drug name from source
drug_name_std TEXT NOT NULL, -- Standardized drug name (via ref_drug_names)
intervention_date DATE NOT NULL, -- Date of intervention
price_actual REAL NOT NULL DEFAULT 0, -- Cost of intervention in GBP
-- Organization and directory
org_name TEXT, -- Organization name (cleaned, no commas)
directory TEXT, -- Medical directory/specialty (may be "Undefined")
-- Source tracking
source_file TEXT, -- Original file this record came from
loaded_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
-- Additional clinical fields (optional, used in directory fallback logic)
treatment_function_code INTEGER,
additional_detail_1 TEXT,
additional_detail_2 TEXT,
additional_detail_3 TEXT,
additional_detail_4 TEXT,
additional_detail_5 TEXT
);
-- Primary indexes for common filter patterns used in generate_graph()
-- UPID: Used for patient grouping, pathway analysis
CREATE INDEX IF NOT EXISTS idx_fact_interventions_upid ON fact_interventions(upid);
-- Drug name (standardized): Used for drug filtering
CREATE INDEX IF NOT EXISTS idx_fact_interventions_drug ON fact_interventions(drug_name_std);
-- Intervention date: Used for date range filtering (start_date, end_date, last_seen)
CREATE INDEX IF NOT EXISTS idx_fact_interventions_date ON fact_interventions(intervention_date);
-- Directory: Used for directory/specialty filtering
CREATE INDEX IF NOT EXISTS idx_fact_interventions_directory ON fact_interventions(directory);
-- Organization: Used for trust filtering (Provider Code maps to org_name)
CREATE INDEX IF NOT EXISTS idx_fact_interventions_org ON fact_interventions(org_name);
-- Composite index for common filter combination (trust + drug + directory)
CREATE INDEX IF NOT EXISTS idx_fact_interventions_composite
ON fact_interventions(org_name, drug_name_std, directory);
-- Composite index for date-based patient analysis
CREATE INDEX IF NOT EXISTS idx_fact_interventions_upid_date
ON fact_interventions(upid, intervention_date);
"""
# =============================================================================
# Materialized View Schemas (Cached Aggregations)
# =============================================================================
MV_PATIENT_TREATMENT_SUMMARY_SCHEMA = """
-- Materialized view of patient treatment summaries
-- Pre-computed aggregations per patient for faster pathway analysis
-- Refreshed when fact_interventions data changes
CREATE TABLE IF NOT EXISTS mv_patient_treatment_summary (
id INTEGER PRIMARY KEY AUTOINCREMENT,
-- Patient identification
upid TEXT NOT NULL UNIQUE, -- Unique Patient ID
-- Organization and directory (for filtering)
org_name TEXT, -- Organization name (first org seen)
directory TEXT, -- Primary directory (first directory assigned)
-- Date range
first_seen_date DATE NOT NULL, -- First intervention date
last_seen_date DATE NOT NULL, -- Last intervention date
days_treated INTEGER NOT NULL DEFAULT 0, -- Duration: last_seen - first_seen
-- Cost aggregations
total_cost REAL NOT NULL DEFAULT 0, -- Sum of all intervention costs
avg_cost_per_intervention REAL, -- Average cost per intervention
-- Treatment summary
intervention_count INTEGER NOT NULL DEFAULT 0, -- Total number of interventions
unique_drug_count INTEGER NOT NULL DEFAULT 0, -- Number of distinct drugs
-- Drug sequence (pipe-separated standardized drug names in chronological order)
-- Example: "ADALIMUMAB|ETANERCEPT|INFLIXIMAB"
drug_sequence TEXT,
-- Drug frequency counts (JSON: {"ADALIMUMAB": 5, "ETANERCEPT": 3})
-- Stores count of each drug for this patient
drug_counts_json TEXT,
-- Drug cost totals (JSON: {"ADALIMUMAB": 15000.00, "ETANERCEPT": 8000.00})
-- Stores total cost per drug for this patient
drug_costs_json TEXT,
-- Per-drug date ranges (JSON: {"ADALIMUMAB": {"first": "2023-01-01", "last": "2023-06-15"}, ...})
-- Stores first/last date for each drug
drug_date_ranges_json TEXT,
-- Metadata
computed_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
source_row_count INTEGER -- Number of fact_interventions rows used
);
-- Index for fast patient lookup
CREATE INDEX IF NOT EXISTS idx_mv_patient_summary_upid ON mv_patient_treatment_summary(upid);
-- Indexes for common filter patterns
CREATE INDEX IF NOT EXISTS idx_mv_patient_summary_org ON mv_patient_treatment_summary(org_name);
CREATE INDEX IF NOT EXISTS idx_mv_patient_summary_directory ON mv_patient_treatment_summary(directory);
CREATE INDEX IF NOT EXISTS idx_mv_patient_summary_first_seen ON mv_patient_treatment_summary(first_seen_date);
CREATE INDEX IF NOT EXISTS idx_mv_patient_summary_last_seen ON mv_patient_treatment_summary(last_seen_date);
-- Composite index for date range filtering (common in generate_graph)
CREATE INDEX IF NOT EXISTS idx_mv_patient_summary_date_range
ON mv_patient_treatment_summary(first_seen_date, last_seen_date);
-- Composite index for org + directory + dates (full filter pattern)
CREATE INDEX IF NOT EXISTS idx_mv_patient_summary_filter_composite
ON mv_patient_treatment_summary(org_name, directory, first_seen_date, last_seen_date);
-- Index for drug sequence pattern matching
CREATE INDEX IF NOT EXISTS idx_mv_patient_summary_drug_seq ON mv_patient_treatment_summary(drug_sequence);
"""
MATERIALIZED_VIEWS_SCHEMA = f"""
-- Materialized Views Schema
-- Pre-computed aggregations for performance
{MV_PATIENT_TREATMENT_SUMMARY_SCHEMA}
"""
# =============================================================================
# File Tracking Schemas (Incremental Updates)
# =============================================================================
PROCESSED_FILES_SCHEMA = """
-- Tracks processed data files for incremental updates
-- Enables detecting changed files by comparing hashes
-- Stores processing status and statistics
CREATE TABLE IF NOT EXISTS processed_files (
id INTEGER PRIMARY KEY AUTOINCREMENT,
-- File identification
file_path TEXT NOT NULL, -- Full path to the file
file_name TEXT NOT NULL, -- Just the filename (for display)
file_hash TEXT NOT NULL, -- SHA256 hash of file contents
-- File metadata
file_size_bytes INTEGER, -- Size of file in bytes
file_modified_at TIMESTAMP, -- File's last modification timestamp
-- Processing results
row_count INTEGER DEFAULT 0, -- Number of rows processed from this file
status TEXT NOT NULL DEFAULT 'pending', -- pending, processing, success, error
error_message TEXT, -- Error details if status='error'
-- Timestamps
first_processed_at TIMESTAMP, -- When first processed
last_processed_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
processing_duration_seconds REAL, -- How long processing took
-- Uniqueness: only one record per file path
-- Hash changes indicate file content changed (needs reprocessing)
UNIQUE(file_path)
);
-- Index for fast lookup by file path
CREATE INDEX IF NOT EXISTS idx_processed_files_path ON processed_files(file_path);
-- Index for finding files by status (e.g., find all pending or errored files)
CREATE INDEX IF NOT EXISTS idx_processed_files_status ON processed_files(status);
-- Index for finding files by hash (detect if same file appears at different paths)
CREATE INDEX IF NOT EXISTS idx_processed_files_hash ON processed_files(file_hash);
-- Index for finding recently processed files
CREATE INDEX IF NOT EXISTS idx_processed_files_last_processed ON processed_files(last_processed_at);
"""
FILE_TRACKING_SCHEMA = f"""
-- File Tracking Schema
-- Supports incremental data loading
{PROCESSED_FILES_SCHEMA}
"""
# =============================================================================
# Combined Schemas
# =============================================================================
REFERENCE_TABLES_SCHEMA = f"""
-- Reference Tables Schema
-- Contains lookup data migrated from CSV files
{REF_DRUG_NAMES_SCHEMA}
{REF_ORGANIZATIONS_SCHEMA}
{REF_DIRECTORIES_SCHEMA}
{REF_DRUG_DIRECTORY_MAP_SCHEMA}
{REF_DRUG_INDICATION_CLUSTERS_SCHEMA}
"""
FACT_TABLES_SCHEMA = f"""
-- Fact Tables Schema
-- Contains patient intervention data
{FACT_INTERVENTIONS_SCHEMA}
"""
ALL_TABLES_SCHEMA = f"""
-- Complete Database Schema
-- Reference tables + Fact tables + Materialized views + File tracking
{REFERENCE_TABLES_SCHEMA}
{FACT_TABLES_SCHEMA}
{MATERIALIZED_VIEWS_SCHEMA}
{FILE_TRACKING_SCHEMA}
"""
# =============================================================================
# Schema Helper Functions
# =============================================================================
def create_reference_tables(conn: sqlite3.Connection) -> None:
"""
Create all reference tables in the database.
Args:
conn: SQLite database connection.
"""
logger.info("Creating reference tables...")
conn.executescript(REFERENCE_TABLES_SCHEMA)
logger.info("Reference tables created successfully")
def drop_reference_tables(conn: sqlite3.Connection) -> None:
"""
Drop all reference tables from the database.
Args:
conn: SQLite database connection.
Warning:
This will delete all reference data. Use with caution.
"""
logger.warning("Dropping reference tables...")
conn.executescript("""
DROP TABLE IF EXISTS ref_drug_names;
DROP TABLE IF EXISTS ref_organizations;
DROP TABLE IF EXISTS ref_directories;
DROP TABLE IF EXISTS ref_drug_directory_map;
DROP TABLE IF EXISTS ref_drug_indication_clusters;
""")
logger.info("Reference tables dropped")
def get_reference_table_counts(conn: sqlite3.Connection) -> dict[str, int]:
"""
Get row counts for all reference tables.
Args:
conn: SQLite database connection.
Returns:
Dictionary mapping table name to row count.
"""
tables = ["ref_drug_names", "ref_organizations", "ref_directories", "ref_drug_directory_map", "ref_drug_indication_clusters"]
counts = {}
for table in tables:
cursor = conn.execute(f"SELECT COUNT(*) FROM {table}")
result = cursor.fetchone()
counts[table] = result[0] if result else 0
return counts
def verify_reference_tables_exist(conn: sqlite3.Connection) -> list[str]:
"""
Verify that all reference tables exist.
Args:
conn: SQLite database connection.
Returns:
List of missing table names. Empty list means all tables exist.
"""
required_tables = ["ref_drug_names", "ref_organizations", "ref_directories", "ref_drug_directory_map", "ref_drug_indication_clusters"]
missing = []
for table in required_tables:
cursor = conn.execute(
"SELECT name FROM sqlite_master WHERE type='table' AND name=?",
(table,)
)
if cursor.fetchone() is None:
missing.append(table)
return missing
# =============================================================================
# Fact Table Helper Functions
# =============================================================================
def create_fact_tables(conn: sqlite3.Connection) -> None:
"""
Create all fact tables in the database (including materialized views).
Args:
conn: SQLite database connection.
"""
logger.info("Creating fact tables...")
conn.executescript(FACT_TABLES_SCHEMA)
conn.executescript(MATERIALIZED_VIEWS_SCHEMA)
logger.info("Fact tables created successfully")
def drop_fact_tables(conn: sqlite3.Connection) -> None:
"""
Drop all fact tables from the database.
Args:
conn: SQLite database connection.
Warning:
This will delete all patient intervention data. Use with caution.
"""
logger.warning("Dropping fact tables...")
conn.executescript("""
DROP TABLE IF EXISTS fact_interventions;
DROP TABLE IF EXISTS mv_patient_treatment_summary;
""")
logger.info("Fact tables dropped")
def get_fact_table_counts(conn: sqlite3.Connection) -> dict[str, int]:
"""
Get row counts for all fact tables (including materialized views).
Args:
conn: SQLite database connection.
Returns:
Dictionary mapping table name to row count.
"""
tables = ["fact_interventions", "mv_patient_treatment_summary"]
counts = {}
for table in tables:
cursor = conn.execute(f"SELECT COUNT(*) FROM {table}")
result = cursor.fetchone()
counts[table] = result[0] if result else 0
return counts
def verify_fact_tables_exist(conn: sqlite3.Connection) -> list[str]:
"""
Verify that all fact tables exist (including materialized views).
Args:
conn: SQLite database connection.
Returns:
List of missing table names. Empty list means all tables exist.
"""
required_tables = ["fact_interventions", "mv_patient_treatment_summary"]
missing = []
for table in required_tables:
cursor = conn.execute(
"SELECT name FROM sqlite_master WHERE type='table' AND name=?",
(table,)
)
if cursor.fetchone() is None:
missing.append(table)
return missing
# =============================================================================
# File Tracking Helper Functions
# =============================================================================
def create_file_tracking_tables(conn: sqlite3.Connection) -> None:
"""
Create file tracking tables in the database.
Args:
conn: SQLite database connection.
"""
logger.info("Creating file tracking tables...")
conn.executescript(FILE_TRACKING_SCHEMA)
logger.info("File tracking tables created successfully")
def drop_file_tracking_tables(conn: sqlite3.Connection) -> None:
"""
Drop file tracking tables from the database.
Args:
conn: SQLite database connection.
Warning:
This will delete all file tracking history.
"""
logger.warning("Dropping file tracking tables...")
conn.executescript("""
DROP TABLE IF EXISTS processed_files;
""")
logger.info("File tracking tables dropped")
def get_file_tracking_counts(conn: sqlite3.Connection) -> dict[str, int]:
"""
Get row counts for file tracking tables.
Args:
conn: SQLite database connection.
Returns:
Dictionary mapping table name to row count.
"""
tables = ["processed_files"]
counts = {}
for table in tables:
cursor = conn.execute(f"SELECT COUNT(*) FROM {table}")
result = cursor.fetchone()
counts[table] = result[0] if result else 0
return counts
def verify_file_tracking_tables_exist(conn: sqlite3.Connection) -> list[str]:
"""
Verify that file tracking tables exist.
Args:
conn: SQLite database connection.
Returns:
List of missing table names. Empty list means all tables exist.
"""
required_tables = ["processed_files"]
missing = []
for table in required_tables:
cursor = conn.execute(
"SELECT name FROM sqlite_master WHERE type='table' AND name=?",
(table,)
)
if cursor.fetchone() is None:
missing.append(table)
return missing
# =============================================================================
# Combined Helper Functions
# =============================================================================
def create_all_tables(conn: sqlite3.Connection) -> None:
"""
Create all tables (reference + fact) in the database.
Args:
conn: SQLite database connection.
"""
logger.info("Creating all database tables...")
conn.executescript(ALL_TABLES_SCHEMA)
logger.info("All tables created successfully")
def drop_all_tables(conn: sqlite3.Connection) -> None:
"""
Drop all tables from the database.
Args:
conn: SQLite database connection.
Warning:
This will delete all data. Use with extreme caution.
"""
logger.warning("Dropping all tables...")
drop_file_tracking_tables(conn)
drop_fact_tables(conn)
drop_reference_tables(conn)
logger.info("All tables dropped")
def get_all_table_counts(conn: sqlite3.Connection) -> dict[str, int]:
"""
Get row counts for all tables.
Args:
conn: SQLite database connection.
Returns:
Dictionary mapping table name to row count.
"""
counts = {}
counts.update(get_reference_table_counts(conn))
counts.update(get_fact_table_counts(conn))
counts.update(get_file_tracking_counts(conn))
return counts
def verify_all_tables_exist(conn: sqlite3.Connection) -> list[str]:
"""
Verify that all tables exist.
Args:
conn: SQLite database connection.
Returns:
List of missing table names. Empty list means all tables exist.
"""
missing = []
missing.extend(verify_reference_tables_exist(conn))
missing.extend(verify_fact_tables_exist(conn))
missing.extend(verify_file_tracking_tables_exist(conn))
return missing