secondary claim
sec_clmDefinition
ISO-11179 Definition
A healthcare claim submitted to a secondary insurance payer after the primary payer has adjudicated the claim and made its payment determination, seeking reimbursement for remaining patient balance from the second insurance coverage. Secondary billing applies when a patient has dual insurance coverage under coordination of benefits rules, with the primary payer paying first according to COB priority rules and the secondary payer potentially covering some or all of the remaining balance including deductibles, copays, and coinsurance from the primary adjudication. Common secondary billing scenarios include Medicare as secondary to employer group insurance, Medicaid as secondary to commercial insurance for dual eligible members, and dependent children covered under both parents employer plans.
Healthcare data teams build secondary billing workflows that automatically identify claims with secondary payer information, generate secondary claims from primary remittance advice data, track secondary claim payment rates and timelines, and calculate the net revenue contribution from secondary billing programs.
Standard Abbreviation
sec_clm
Category
Production DDL — FACT_CLAIM_TRANSACTION
CREATE OR REPLACE TABLE FACT_CLAIM_TRANSACTION (
clm_txn_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,
tot_chrg_amt DECIMAL(18,2) -- total charged amount,
tot_alwd_amt DECIMAL(18,2) -- total allowed amount,
tot_pd_amt DECIMAL(18,2) -- total paid amount,
cntrct_adj_amt DECIMAL(18,2) -- contractual adjustment,
denial_ind CHAR(1) -- denial indicator,
denial_rsn_cd VARCHAR(10) -- denial reason code,
prior_auth_nbr VARCHAR(30) -- authorization number,
clm_lag_days SMALLINT -- claim lag days,
days_ar SMALLINT -- days in AR,
load_dt TIMESTAMP_NTZ NOT NULL -- load timestamp
);
Standard Snowflake DDL for the canonical finance table. Convert to BigQuery or Databricks →
Why This Term Matters
Healthcare data terminology is foundational for any data engineer working in this industry. Precise understanding of standard terms enables accurate schema design, reduces downstream data quality issues, and ensures pipelines meet the regulatory and interoperability requirements imposed by HIPAA, HL7 FHIR, and CMS reporting frameworks. Without this foundation, even technically well-built pipelines produce data that fails validation when it reaches payers or regulators.
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