RWD lakehouse

Last reviewed: 2026-06-28 — see the freshness policy.

Problem & context

An organization wants to run real-world-evidence studies across clinical and claims data from multiple sources, each with a different schema and vocabulary, with governed access to PHI and reproducible results acceptable to regulators.

Requirements (NFRs)

ID Requirement Source
NFR-1 Analysts query one model, not N source schemas Research
NFR-2 Column-level PHI access control + audit HIPAA/HITRUST
NFR-3 Reproducible: pinned data + vocabulary versions RWE credibility
NFR-4 Incremental ingest at TB scale (no full reloads) Cost/scale
NFR-5 Cross-org collaboration without moving PHI Partnerships

Architecture

flowchart LR S1["FHIR $export"] & S2["Claims (X12)"] & S3["Labs"] --> Bronze["Bronze (raw, immutable)"] Bronze --> Silver["Silver (conformed)"] Vocab["OMOP vocabularies"] --> Gold Silver --> Gold["Gold: OMOP CDM"] Gold --> DQ["DQ (Achilles / DQD)"] Gold --> RWE["Cohorts / RWE (ATLAS, HADES)"] Gold --> Share["Clean room / secure share"] Gov["Governance: masking, lineage, audit"] -.-> Bronze & Silver & Gold

Built from the medallion lakehouse, OMOP on cloud gold, governance & data contracts, and tokenized linkage for external sources. See Building a health data lake & lakehouse for the practical per-modality build guide this architecture assumes.

Key decisions & trade-offs

  • OMOP as gold vs source-specific marts → OMOP for cross-source comparability and the OHDSI tool ecosystem; accept upfront mapping cost.
  • Lakehouse vs warehouse → lakehouse for cheap raw retention + ML; Snowflake variant narrows the ops gap for SQL-first teams.
  • Tokenization for external linkage → link trial/claims/EHR by patient token without exposing PII; manage residual re-identification risk on the linked set.
  • Clean room / secure share for collaboration (NFR-5) → partners compute without seeing row-level PHI.

Compliance mapping

Unity Catalog / Horizon masking + row filters (NFR-2) · immutable bronze + pinned versions + lineage (NFR-3, GxP/21 CFR Part 11 integrity) · residency-pinned storage (regional) · audited access.

Cost

Storage-heavy but cheap object tiers for bronze; compute auto-suspends; biggest lever is co-locating compute with storage to avoid egress (see TCO).

Lab

hls-lakehouse-rwd — OMOP lakehouse on Databricks and Snowflake.

Check yourself

  1. Why OMOP as the gold model rather than per-source marts?
  2. How does the design let a partner analyze your data without seeing row-level PHI?
  3. Which two practices make the RWE reproducible enough to defend to a regulator?

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