EPIC SYSTEMS DATA EXTRACTION TOOL

    Epic Systems Data Extraction Tool — Clarity-Certified, Audit-Signed

    Purpose-built Epic Systems data extraction tool for downstream finance, HCM and SCM. APIs, schedulers, parallel partitioned jobs, audit-signed manifests. Reads Clarity, cross-checks Cogito, never touches Chronicles. HIPAA chain of custody preserved at every extract.

    Clarity
    Native SQL Server interface
    Parallel
    Service-area + period partitioned
    HIPAA
    Audit-signed manifests
    0 risk
    To Chronicles operational DB

    What the epic systems data extraction tool does — and why bespoke Clarity SQL doesn't scale

    Custom SQL works for one report. The epic systems data extraction tool works for a full Epic → Fusion conversion with multi-hospital scale, full reconciliation and HIPAA audit evidence.

    Every healthcare organization running Epic has a small army of Clarity analysts writing ad-hoc SQL against Clarity tables for operational reporting. That's the bedrock of how Epic-based reporting works. But a one-time Epic to Fusion migration is fundamentally different from ad-hoc reporting: it needs multi-year volume, full reconciliation against Cogito, audit-signed evidence, parallel partitioned execution that doesn't disrupt operational reporting users, and Fusion-grade output formats (FBDI ZIPs, HDL .dat files) — none of which custom Clarity SQL gives you out of the box.

    The epic systems data extraction tool is the productised version of what consultant-led Epic to Fusion programmes build by hand. Pre-built extractors for the downstream finance, HCM and SCM domains (ARPB_TRANSACTIONS for Resolute AR, CLARITY_EMP for HR, RX_MED for Willow, OR_LOG for OpTime, etc.), with parallel partitioning by service area + fiscal period, throttled concurrency that respects Clarity SQL Server CPU/IO limits, automatic Cogito reconciliation per extract, and audit-signed manifests that satisfy HIPAA §164.312(b), SOX and Joint Commission requirements.

    Output is staged Parquet on object storage (cloud or on-prem), partitioned for downstream Fusion FBDI/HDL transformation, with hash-signed file inventories. The tool integrates with your existing scheduler (Airflow, OCI Scheduler, AutoSys, cron) or runs standalone. It works across Epic 2018 through current GA, tested against Epic's quarterly release cadence.

    Key features of the Epic data extraction tool

    1
    Clarity-native extractors
    Pre-built read patterns for every downstream finance, HCM and SCM table in Clarity. No bespoke SQL development per project.
    2
    Cogito cross-reconciliation
    Every extract is automatically reconciled against Cogito row-counts and sum-checks. Clarity ETL lag detected before load.
    3
    Parallel partitioning
    Jobs partition by service area + fiscal period and run concurrently. Multi-TB extracts complete in 12–48 hours not weeks.
    4
    Audit-signed manifests
    Every job emits a HIPAA-grade manifest: source snapshot ID, row-counts, hashes, actor log, Cogito reference. Satisfies SOX and Joint Commission.

    What the epic systems data extraction tool pulls — every Clarity domain that matters

    Pre-built extractors covering every downstream finance, HCM and SCM source domain. Configure, run, reconcile.

    💰

    Resolute HB/PB AR

    ARPB_TRANSACTIONS, HSP_TRANSACTIONS, HSP_ACCOUNT, HSP_ACCT_TX_LIST, HSP_ATB_HX — full hospital and professional billing AR sub-ledger extracted with period summarisation for Fusion GL posting.

    📒

    GL trial balance

    Legacy GL trial balance pulled from Clarity-published reporting marts (or from legacy ERP if Lawson/PeopleSoft is still in scope), reconciled against Cogito period-end snapshot.

    👥

    Workers + providers

    CLARITY_EMP (employee), CLARITY_SER (provider), CLARITY_DEP (department), with merged worker classification where employee = provider. Outputs HDL Worker.dat for Fusion HCM.

    🏪

    Willow pharmacy

    RX_MED, RX_FILL, RX_PAT_MED, CLARITY_MEDICATION — pharmacy formulary master, dispensing transactions, inventory consumption. Routed to Fusion Inventory + Cost Accounting.

    🔪

    OpTime surgical

    OR_LOG, OR_CASE, OR_LOG_CASE_TIMES, OR_LOG_ALL_PROC — surgical case-cart material consumption, preference cards, implant tracking. Routed to Fusion Materials Management.

    🧪

    Beaker laboratory

    ORDER_PROC, LAB_RSLT, CLARITY_ORDERSET — laboratory orders, reagent consumption, supplier-linked materials. Routed to Fusion Inventory + Procurement.

    Epic systems data extraction tool — typical job sequence

    A standard partitioned extraction cycle for a regional health system. Multi-TB extract completes in 12–48 hours.

    1

    Configuration — Day 0

    Service account provisioned in Clarity with scope-limited read access to downstream finance/HCM/SCM tables. Cogito reference views authorized. Output storage (cloud or on-prem object store) configured. Audit log destination set.

    2

    Freshness Check — Hour 0

    Tool queries Clarity refresh log to confirm freshness within tolerance. Aborts if lag exceeds configured threshold. Cogito reference snapshot captured for reconciliation.

    3

    Partitioned Extract — Hours 0–24

    Parallel jobs (typically 4–8 concurrent) pull data by service area + fiscal period. Each job streams to Parquet output with progressive hash signing. Throttling respects Clarity SQL Server resource limits.

    4

    Cogito Reconciliation — Hours 24–28

    Each partition's row-count and sum-check compared to Cogito reference. Variance beyond tolerance flagged for analyst review. Reconciliation pack assembled per partition.

    5

    Manifest Signing — Hours 28–30

    Final manifest emitted: source snapshot ID, partition list with row-counts/sums/hashes, Cogito reference, actor log, signature. Manifest stored alongside Parquet output.

    6

    Handoff — Hours 30–32

    Output handed off to downstream Fusion FBDI/HDL transformation step or to long-term archive (depending on use case). Audit pack retained for HIPAA + SOX + Joint Commission retrieval.

    Why customers choose the epic systems data extraction tool over custom SQL

    Six concrete differences that show up in week one of an Epic → Fusion migration project.

    ⏱️

    3 weeks vs 3 months

    Configuration in days, not bespoke Clarity SQL development in months. Pre-built extractors are tested across Epic versions.

    📊

    Cogito reconciliation included

    Custom SQL doesn't reconcile by default. The Epic systems data extraction tool reconciles against Cogito automatically — catching Clarity ETL lag before load.

    🔐

    HIPAA evidence by default

    Custom SQL doesn't emit audit-signed manifests. The tool does, satisfying HIPAA §164.312(b), SOX and Joint Commission with zero extra work.

    Parallel partitioning built in

    Custom SQL is single-threaded by default. The tool partitions by service area + fiscal period and runs concurrent, completing multi-TB extracts in 12–48 hours.

    🎯

    Fusion-ready output

    Custom SQL produces row sets. The tool produces Parquet-staged datasets partitioned for downstream Fusion FBDI/HDL transformation — saves a full round trip.

    📚

    Version-tested

    Custom SQL breaks on the next Epic upgrade. The Epic systems data extraction tool is tested against Epic's quarterly cadence — your extractors keep working.

    Frequently asked questions

    What is the Epic Systems data extraction tool?+

    The Syntra ETL Epic Systems data extraction tool is a Clarity-certified extractor product that pulls Epic's downstream finance, HCM and SCM data from Clarity (SQL Server relational mirror), reconciles against Cogito (analytics layer), and emits Parquet-staged datasets ready for Fusion FBDI/HDL transformation. It never queries Chronicles directly. The tool ships with pre-built extractors for Resolute HB/PB AR posting, GL trial balance, worker + provider master, Willow pharmacy inventory, OpTime case-cart materials, Beaker lab reagent transactions, supplier master, fixed assets and downstream interface data. APIs, schedulers, parallel jobs and audit-signed manifests are built in. HIPAA chain of custody is preserved at every read.

    Why use a purpose-built Epic Systems data extraction tool instead of custom Clarity SQL?+

    Custom Clarity SQL works at small scale but breaks at multi-hospital scale. The Epic Systems data extraction tool brings four things custom SQL doesn't: (1) parallel partitioned extraction that respects SQL Server CPU/IO limits so reporting users aren't impacted; (2) automatic Cogito reconciliation per extract per period; (3) audit-signed manifests for HIPAA chain of custody; (4) FBDI/HDL-ready output that skips a transformation round trip. On a typical 8-hospital regional system migration the tool reduces extraction development from 3–4 months of bespoke SQL to 2–3 weeks of configuration — and it's tested against Epic's version cadence so it doesn't break on the next Clarity update.

    Which Epic versions does the data extraction tool support?+

    All Epic versions on supported Clarity releases — typically Epic 2018 through Epic May 2024 (latest GA at time of writing). Clarity is reasonably stable across Epic versions because it's the analytical mirror, not the operational schema, but Epic releases do occasionally add tables or modify column behavior. The Epic Systems data extraction tool is tested against Epic's quarterly release cadence by Clarity-certified analysts. Customers running older Epic versions (2014–2017) typically have customised Clarity ETL, in which case we coordinate with the local Clarity analyst team to confirm schema compatibility during the discovery phase.

    Does the Epic Systems data extraction tool work with Cogito directly?+

    Yes. While the primary extraction surface is Clarity (the relational SQL Server mirror), the tool also reads from Cogito (the analytics layer) for two purposes: reconciliation (Cogito serves as the cross-check reference against Clarity row-counts and sum-totals per period), and direct extraction of Cogito-only marts where Clarity doesn't carry the data shape we need (typically summarised analytical models that don't have a clean Clarity equivalent). Cogito reads go through the standard Epic Cogito security model — your Cogito admins authorize the service account and the tool respects scope-limited access. Output is identical: Parquet-staged, hash-signed, ready for downstream transformation.

    How does the Epic data extraction tool handle Clarity ETL lag?+

    Clarity is a SQL Server mirror that lags Chronicles by a configurable interval — usually 2 hours operational, 24 hours analytical. The Epic Systems data extraction tool manages this with a freshness watermark check before each extract: the tool queries Clarity's CLARITY_REFRESH_LOG (or equivalent depending on local Clarity build) for the most recent successful refresh, refuses to extract if freshness is below the configured tolerance, and on critical-path datasets cross-references against Cogito to confirm consistency. Where sub-hour freshness is mandatory we use HL7 v2 message consumption from the Interconnect layer, but in practice this is rare — finance data is typically daily batch anyway.

    What does the audit-signed manifest contain?+

    Every extraction job produced by the Epic Systems data extraction tool emits a manifest with: extraction timestamp (UTC and Epic-local), Clarity database snapshot identifier, source table list with row-counts and sum-checks per table, partition key list (typically service area + fiscal period), output Parquet file paths with byte-counts and SHA-256 hashes, Cogito reconciliation reference (row-count + sum-check from Cogito for the same period), HIPAA actor log (which service account ran the extract, with scope), and a manifest-level signature. The manifest satisfies HIPAA Privacy Rule §164.312(b) audit control requirements, SOX evidence requirements, and Joint Commission survey requirements with one-click retrieval.

    Can the Epic Systems data extraction tool schedule parallel jobs?+

    Yes. The scheduler runs partitioned extraction jobs in parallel — typically by service area + fiscal period — with concurrency throttled to respect Clarity SQL Server resource limits set by your Epic technical team. A typical 8-hospital extraction parallelises across 4–8 concurrent jobs, each pulling 1 service area for 1 fiscal quarter, completing the full multi-year backfill in 12–48 hours. For ongoing delta extraction (post go-live or during parallel run) jobs typically run nightly with sub-hour completion. The Epic Systems data extraction tool integrates with your existing scheduler (Airflow, OCI Scheduler, AutoSys) or runs standalone with a built-in cron-style scheduler. All job runs feed the audit log.

    Does the Epic data extraction tool integrate with Oracle Integration Cloud?+

    Yes. The Epic Systems data extraction tool produces three output forms depending on consumption: Parquet-staged datasets for FBDI/HDL transformation (one-time and bulk migration); REST API push to Oracle Integration Cloud (OIC) endpoints for steady-state low-volume integration; HL7 v2 / FHIR R4 message bridging where Epic Interconnect is the steady-state source and OIC is the steady-state target. Most healthcare customers run a hybrid: bulk migration through the Parquet → FBDI path during the initial Epic to Fusion project, then steady-state Willow/OpTime/Beaker feeds through OIC + Interconnect after cutover. The tool supports all three deployments.

    See the epic systems data extraction tool in action

    Book a 30-minute demo. We'll connect to a Clarity sandbox, run a partitioned extraction of Resolute AR + worker master + Willow inventory, and show the audit-signed manifest with Cogito reconciliation. Concrete output before the call ends.