Epic SQL Query Optimization & Clinical Data Analysis
Optimize Epic SQL queries and unlock clinical data insights instantly
What You Can Do
Write, optimize, and debug SQL queries against Epic's complex clinical databases in seconds. You can analyze query performance, identify bottlenecks, and generate production-ready queries that respect Epic's data model and security practices. This skill helps you extract meaningful clinical insights while maintaining data integrity and compliance standards.
Features
Analyze slow queries and suggest index strategies, rewrites, and execution plans tailored to Epic's schema
Generate queries for common healthcare analytics: patient cohorts, medication patterns, lab trends, and outcomes
Review execution plans and recommend materialized views, stored procedures, or query refactoring
Access detailed reference information on Epic tables (PATIENT, ORDERS, RESULTS, MEDICATION, etc.) and relationships
Enforce PHI masking, audit logging, and role-based access patterns in your queries
Translate complex SQL into plain English, document business logic, and create data dictionaries
Create multi-query workflows for common analytics pipelines (e.g., daily patient census, readmission risk)
Example Output
Example 1: Patient Medication Cohort Query
SELECT DISTINCT p.PAT_ID, p.PAT_NAME, m.MED_DESCRIPTION,
m.START_DATE, DATEDIFF(DAY, m.START_DATE, m.END_DATE) AS DURATION
FROM PATIENT p
INNER JOIN MEDICATION m ON p.PAT_ID = m.PAT_ID
WHERE m.MED_DESCRIPTION LIKE '%Metformin%'
AND m.START_DATE >= DATEADD(YEAR, -1, GETDATE())
ORDER BY p.PAT_ID, m.START_DATE DESC;
Why it works: Uses INNER JOIN to avoid null medications, DATEDIFF for readability, indexes on PAT_ID and MED_DESCRIPTION.
Example 2: Performance Analysis Report
- ✅ Query execution time: 2.3s (was 45s)
- ✅ Rows scanned: 50K (was 2.1M)
- ✅ Recommended index: CREATE INDEX idx_medication_drug ON MEDICATION(MED_DESCRIPTION, START_DATE)
- ✅ Estimated improvement: 95% faster after indexing
What's Included
- SKILL.md: Complete Claude skill with Epic SQL workflows, decision trees, and verification checklists
- Query templates: Pre-built starter queries for common clinical analyses (census, readmissions, lab trends)
- Epic schema reference: Quick-lookup guide to major tables and relationships
- Performance checklist: Step-by-step optimization workflow with profiling commands
- Compliance worksheet: Template for documenting data access justification and PHI handling
Who It's For
- Clinical data analysts — Extract cohorts, outcomes, and operational metrics from Epic
- Healthcare IT specialists — Optimize infrastructure and support data requests from clinicians
- Research coordinators — Query patient data for clinical trials and outcomes research
- Quality/compliance officers — Monitor clinical workflows and audit data access patterns
- Population health managers — Analyze patient populations for risk stratification and interventions
Best For
- Building patient cohort queries for research or quality initiatives
- Diagnosing slow reports and optimizing existing queries
- Extracting clinical metrics (readmission rates, medication adherence, lab abnormalities)
- Creating recurring data exports for dashboards and analytics platforms
- Documenting data definitions and audit trails for compliance reviews
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