Predictive mapping platform for clinical data harmonization & interoperability
Harmonize EHR (Epic, Cerner), HL7 v2, FHIR R4, DICOM, and LOINC/SNOMED at the mapping layer. Our Semantic Match Engine proposes candidate mappings; named SMEs approve them with electronic signature; every decision lands in a SHA‑256 hash‑chained ledger. Built for HIPAA §164.312(b), 21 CFR Part 11, ONC HTI‑1, and FDA GMLP.
Each pillar is a property of the data structure — not a process the application has to remember to follow.
SHA‑256 Hash Chain
21 CFR Part 11 §11.10(e)
Every ledger entry stores a SHA‑256 hash of the previous entry's content. Tampering with any historical row invalidates every hash from that row forward. A verifier walks the chain in O(n) — proof that the ledger has not been silently rewritten.
Every row is keyed by a ULID, not a UUID. The first 48 bits are a millisecond timestamp, so the primary key itself is the order. Range‑scanning to a moment in time becomes a primary‑key lookup — and there is no separate timestamp index to keep honest.
Each ledger entry records the actor's role at the moment of action — not just the role they hold today. If a contributor is later promoted to approver, last quarter's ledger still shows them acting as a contributor. The role split is preserved retroactively, not just enforced going forward.
Production releases require a Contributor's draft signature plus an Approver's release signature — and the two signers must be distinct identities. Quarterly attestations require a Compliance Officer signature satisfying §11.10(j). Both signatures are themselves ledger entries.
Four sample ledger entries, hashed with SHA‑256 in the Web Crypto API. Toggle a row to tamper with its content and watch every downstream hash fail.
Computing SHA‑256…
Hashes computed with crypto.subtle.digest("SHA-256") · chain link = SHA‑256(ulid|ts|actor|role|action|prevHash)
6 months2 weeks
Clinical data prep for AI models
Typical time to assemble a regulator‑defensible clinical dataset for downstream AI model training, before vs. after Magellan. EHR extraction (Epic, Cerner), HL7 v2 → FHIR R4 conversion, terminology binding (LOINC, SNOMED), DICOM pairing, and audit evidence collapse into one versioned artifact — proposed by the Semantic Match Engine, approved by named SMEs, and chain‑verified for 21 CFR Part 11 §11.10(e).
The Vocabulary Choice That Matters
Predictive mapping vs. "AI‑powered"
Why CMIOs, compliance officers, and ONC reviewers respond to one of these phrases — and recoil from the other.
Three of the questions an auditor asks first — and the queries that answer them.
01
Show me every change to mapping X this quarter.
Filter by mapping ULID and date range. Result is in chronological order because the primary key is the order — no separate timestamp column to second‑guess.
02
Prove this row hasn't been edited since it was written.
Export the ledger range with its SHA‑256 hash chain. Re‑walk the chain. A single altered character would break every downstream hash.
03
Who approved this release? Were there two people?
The release row carries both the Contributor's draft signature and the Approver's release signature, and RBAC enforces that the two identities differ.
The HIPAA controls on this page also satisfy SOX, GxP, GDPR, FedRAMP, and ISO 27001. Hand the matching one‑pager to Finance, Quality, Privacy, FedRAMP PMO, or InfoSec.