05 / SQL Transformations
Connect with us →Everything is queryable.
All logic lives in SQL. Every metric, cohort, and opportunity signal is defined as a view — not hidden in compiled code.
For:BD leadersProductData teams
Canonical views
mat_condition_national_summary
High-level market magnitude and financial intensity across all conditions.
mat_condition_state_breakdown
Regional drill-downs by state, locality, and GPCI cost tier.
mat_condition_hcpcs_detail
Granular procedure-level utilization and spend analytics by HCPCS code.
mat_opportunity_score
Prioritized market targets based on normalized reach and spend composite.
mat_executive_kpis
Top-line portfolio performance metrics for executive dashboards.
data_provenance
Traceability audit table for all 7 integrated federal CMS data streams.
Querying Clinical Intensity
▸ cold_market_analysis.sql
-- Find high-spend states for Heart Failure -- where clinical intensity is below the national average SELECT state_abbr, total_beneficiaries, total_allowed_amt AS Market_Magnitude, allowed_per_patient AS Economic_Density, services_per_patient AS Utilization_Velocity FROM mat_condition_state_breakdown WHERE condition_name = 'Heart Failure' AND services_per_patient < ( SELECT AVG(services_per_patient) FROM mat_condition_national_summary WHERE condition_name = 'Heart Failure' ) ORDER BY total_allowed_amt DESC LIMIT 10;
Why SQL-native matters
- Zero Latency: Insight is generated the moment
surveilrfinishes the ingestion. - Auditability: Every metric in
mat_opportunity_scorecan be traced back viadata_provenance. - Extensibility: New clinical logic can be added by simply creating a new SQL view, with no changes required to the ingestion engine.
What this means for you
Your analysts can fork a view, adjust the definition for your business, and ship a new opportunity signal in an afternoon — not a quarter.
See this in your data
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