Health Systems & AMCs
Your Epic data, fully unleashed.
Epic holds your most valuable clinical, financial, and operational data — buried in Clarity, Caboodle, Chronicles, and CSV exports. Databasin was co-created at Washington University School of Medicine to change that, at AMC scale, in production.
Where Databasin Was Born
"No commercial solution existed at AMC scale. Epic data pipelines were failing and research operations were at risk. So we built one."
Co-created at Washington University School of Medicine's Institute for Informatics, Data Science & Biostatistics (I2DB)
HIMSS '23·'24·'25
Featured by Microsoft and Databricks
200+
Connectors including all Epic layers
80%
Average cost reduction vs. comparable platforms
The Problems We Solve
Epic is powerful. Getting data out of it shouldn't require a specialist queue.
01
Fragmented data across three distinct environments
Chronicles, Clarity, and Caboodle each have different access patterns, refresh schedules, and schema complexity. Most organizations treat them as one problem — and build three different fragile pipelines as a result.
02
Every analytics request requires an Epic specialist
Clarity schema knowledge is rare and concentrated. Researchers wait months for IT capacity. Operational leaders can't act on data they can't access. The bottleneck isn't interest — it's expertise gatekeeping.
03
Pipelines that break when Epic updates
Schema changes, nightly refresh failures, Clarity version upgrades — each one an incident. Research coordinators get called at 6am. Data gaps bake into reports before anyone notices.
04
PHI governance ruling out standard cloud platforms
HIPAA requirements and institutional governance policies eliminate most commercial data platforms before evaluation begins. The answer is always "we'd need to deploy in our own environment" — which means it never happens.
05
Metric definitions that differ between departments
Length of stay. Readmission. RVUs. Every AMC has multiple definitions floating across individual reports. When the CFO's number doesn't match the CMO's number, someone built the calculation twice in different places.
06
AI initiatives stalled at the data layer
Clinical AI projects require clean, governed, labeled data. Organizations that can describe the AI use case in detail still can't get it into production because the foundation — ingestion, governance, semantic layer — isn't ready.
How We Solve Each One
The problem. The Databasin fix.
Area
The Reality at Most AMCs
The Databasin Fix
Data AccessEpic data locked in specialist queues
Clarity queries require deep schema knowledge that takes years to develop. Researchers and operational leaders submit tickets and wait months. The bottleneck is structural, not a staffing problem.
Natural language queries against governed gold data mean a researcher can ask "show me sepsis encounters in the last 12 months by unit" and get a governed answer — without a Clarity expert, without a ticket.
Pipeline StabilityPipelines that break on Epic updates
Schema changes, tenant upgrades, Clarity version bumps — each one a potential incident. Research coordinators get called at 6am. Data gaps bake into dashboards silently.
Schema versioning at the bronze layer — the raw ingestion layer of Databasin's medallion architecture (bronze for raw data, silver for transformed, gold for governed analytics) — means upstream changes are detected and logged before they propagate. Pipelines adapt instead of breaking.
GovernanceConflicting metric definitions
One readmission definition in the CFO's dashboard, another in the CMO's report, a third in the research database. Leadership stops trusting data and defaults to gut instinct.
Silver-layer business rules encode institutional definitions centrally. One readmission calculation, one LOS formula — applied at transformation time, enforced by the platform, not by individual analysts.
CompliancePHI governance blocking deployment
Standard cloud data platforms require PHI to leave your environment. HIPAA posture and institutional governance policies eliminate most options before evaluation. The result is years of "we're evaluating options."
Private install in your own Azure tenant — PHI never leaves your governance perimeter. Your LLM, your endpoints, your security posture. HIPAA-ready by architecture, not by compliance policy alone.
Two Buyers. One Platform.
What matters most depends on who you are.
The CRIO and the CFO have different problems. Databasin solves both.
For the CRIO / Research Informatics
Research operations that don't depend on Epic experts
You know the data is in Epic. Getting it into a research-ready format requires a Clarity specialist, an IT queue, and three weeks. Databasin was built at WashU Medicine's I2DB precisely because this bottleneck was killing research operations.
- Epic connector handles Chronicles, Clarity, and Caboodle through one pipeline — not three
- Schema changes absorbed at bronze — research pipelines don't break on tenant updates
- REDCap, FHIR, and research databases in the same governed environment as Epic data
- Natural language queries for research teams who don't know Clarity table names
For the VP Finance / CFO
Financial and operational reporting that everyone agrees on
Your finance team builds models from Epic exports, Workday data, and manually reconciled spreadsheets. The CFO's revenue number doesn't match the CMO's. Month-end close requires a team of analysts just to reconcile the discrepancy.
- Workday and Epic financial data in one governed lake house — intercompany reconciliation automated
- One definition of charges, payments, and adjustments — enforced by the platform, not by individuals
- Board and investor reporting from a single trusted gold mart — assembled by the platform, not assembled the night before
- Operational dashboards that operational leaders actually trust and use
Proven in Production
Live in production. Not a proof of concept.
Databasin runs at WashU Medicine and BJC Health today — as the production data infrastructure for clinical research and operations, not as a pilot.
200+
Connectors including all major Epic layers, Azure, Databricks, and AI APIs
80%
Average cost reduction vs. comparable lake house platforms
3×
Featured at HIMSS by Microsoft and Databricks — 2023, 2024, 2025
"
The institutional origin of Databasin isn't a marketing story — it's the reason the product actually works. We built it because we needed it, in an environment where failure had real consequences.
Jake Gower — Co-Founder & CEO, Databasin
Ready to Move
Your Epic data.
Working for you
in days.
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