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EDI 837

edi_837
claims·Updated Jul 4, 2026

Definition

ISO-11179 Definition

The ANSI X12 electronic data interchange transaction set used to submit healthcare claims and encounter information from providers to payers, clearinghouses, and billing services. The 837P variant is used for professional claims submitted on CMS-1500 forms, while the 837I variant covers institutional claims submitted on UB-04 forms, and 837D covers dental claims. The 837 transaction set is the foundational data format for claims data pipelines — most raw claims data warehouses ingest either raw 837 files or data parsed from them, making familiarity with the 837 loop and segment structure essential for healthcare data engineers working with claims source systems.

Standard Abbreviation

edi_837

Category

claims

Production DDL — FACT_CLAIM_HEADER

FACT_CLAIM_HEADER.sql
CREATE OR REPLACE TABLE FACT_CLAIM_HEADER (
    clm_key        INTEGER        NOT NULL  -- surrogate key,
    clm_id         VARCHAR(50)    NOT NULL  -- claim identifier,
    mbr_key        INTEGER        NOT NULL  -- FK to DIM_MEMBER,
    prvdr_key      INTEGER        NOT NULL  -- FK to DIM_PROVIDER,
    clm_typ_cd     VARCHAR(10)              -- claim type code,
    clm_stat_cd    VARCHAR(10)              -- claim status code,
    svc_from_dt    DATE                     -- service from date,
    svc_to_dt      DATE                     -- service to date,
    diag_cd_1      VARCHAR(10)              -- principal diagnosis,
    proc_cd        VARCHAR(10)              -- procedure code,
    clm_bill_amt   DECIMAL(18,2)            -- billed amount,
    clm_alwd_amt   DECIMAL(18,2)            -- allowed amount,
    clm_pd_amt     DECIMAL(18,2)            -- paid amount,
    denial_rsn_cd  VARCHAR(10)              -- denial reason code,
    load_dt        TIMESTAMP_NTZ  NOT NULL  -- load timestamp
);

Standard Snowflake DDL for the canonical claims table. Convert to BigQuery or Databricks →

Why This Term Matters

Claims data is the financial backbone of the US healthcare system, and understanding claims terminology is essential for building accurate revenue cycle and reimbursement analytics. Data engineers who know this terminology can correctly parse 837 transactions, identify adjudication errors, and model denial patterns that represent real revenue recovery opportunities. A single misunderstood claims field can result in millions in underpayments identified only after external audits.

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