Interoperability

Amida Connect

Every healthcare data format, ingested, parsed, and classified.

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data standards in one engine: X12 EDI, HL7 v2, and FHIR

TA1 · 999 · 277CA

the full acknowledgement chain, returned to every sender

Hundreds

of quality checks, customizable for each state and program

The Problem

Healthcare data arrives in dozens of incompatible formats from dozens of senders, and most teams meet it with brittle, one-off parser tools, hard to configure, harder to change, and different for every project.

A single malformed record can sink an entire batch. Respondents rarely get a clear answer about what was accepted or rejected, and why, and the data that does land may not be shaped for analytics.

What Amida Connect Does

Amida Connect is an API-driven ingestion engine that pulls legacy X12 EDI and HL7 v2 alongside modern FHIR, from wherever your data originates: clearinghouses, EHRs, and source systems, over API, SFTP, or MFT. One hardened engine replaces a patchwork of custom scripts, and you call it from the pipelines and tools you already run, in your cloud or on-prem.

The rules are yours to shape. Hundreds of data quality checks run before, during, and after parsing. Because every state and program models its data differently, they are fully customizable without touching code. Parsing is lossless so nothing is dropped from repeating segments or nested loops, a bad record is quarantined at the claim level rather than failing the batch, and every sender gets the full response chain back: TA1 confirms the interchange envelope, 999 confirms the syntax, and 277CA reports claim-level acceptance or rejection.

The results are ready to use: a single 837P claim file becomes dozens of clean, related tables, keyed with stable IDs and loaded straight into your operational store for Tessarix™ and downstream analytics, with a reconciliation manifest that proves every record was accounted for. It is the same engine Amida uses to ingest Medicaid and payer data across our platform, available as a stand-alone component.

Credentials

✓	HIPAA compliant
✓	No PHI in application logs
✓	Encryption in transit and at rest
✓	Cloud-native and containerized: your cloud or on-prem
✓	HIPAA 5010 acknowledgement chain (TA1, 999, 277CA)

How It Works

One Engine, Any Format, End to End.

The whole ingestion pipeline in one picture. Follow a claim file through it.

Pull healthcare data from wherever it lives, clearinghouses, EHRs, and source systems, over API, SFTP, or MFT. One engine handles X12 EDI, HL7 v2, and FHIR.

Hundreds of quality checks run before, during, and after parsing, customizable for each state and each program. Parsing is lossless, and a bad record is quarantined at the claim level so the batch keeps moving.

Senders get the full response chain: TA1 confirms the interchange, 999 confirms the syntax, and 277CA reports claim-level acceptance or rejection, so everyone knows exactly what got through.

One claim file becomes dozens of clean, related tables, keyed with stable IDs and loaded straight into your operational store, ready for Tessarix™ and downstream analytics, with a reconciliation manifest proving every record was accounted for.

How It Works

Key Capabilities

Ingest from anywhereClearinghouses, EHRs, and source systems, over API, SFTP, or MFT: one engine, called from your existing pipelines.
Every major formatX12 EDI (837P/837I/837D, 835, 834), HL7 v2 clinical messages, and FHIR, handled natively by one parser.
Staged quality checksHundreds of validation rules fire before, during, and after parsing, each with a typed severity and failure alert.
Full acknowledgement chainTA1 for the interchange, 999 for the syntax, and 277CA for claim status: standards-compliant responses returned to every sender.
Lossless parse, isolated failuresNo data lost from repeating segments or nested loops; bad records are quarantined at the claim level so the batch keeps moving.
Analytics-ready outputOne claim file becomes dozens of normalized tables with stable IDs, plus a reconciliation manifest that accounts for every record.

How We Compare

Custom Point-to-Point Parsers vs. Amida Connect

Custom Point-to-Point Parsers	Amida Connect
A new script for every format and sender	One API-first engine for X12, HL7 v2, and FHIR
One malformed record fails the whole batch	Bad records quarantined at the claim level; batch continues
Senders left guessing what was accepted	TA1, 999, and 277CA acknowledgements returned automatically
Repeating loops flattened or dropped	Lossless parsing preserves every segment and nested loop
Output still needs reshaping for analytics	Normalized tables with stable IDs and a reconciliation manifest

Why It Wins

The Differentiator

Most healthcare integration is a thicket of point-to-point parsers, one per format, per sender, per project, that break quietly. Amida Connect replaces that with a single API-first engine: it speaks every major format, checks quality at every stage, tells each sender exactly what it accepted through the standard acknowledgement chain, and hands analytics teams reconciled, ready-to-query tables. Productized and battle-tested inside Amida, and available now to run in your own environment.

Works Well With