claim adjudication
clm_adjudDefinition
ISO-11179 Definition
The process by which a health insurance payer reviews a submitted claim, applies benefit plan rules and contract terms, and determines the amount to be paid to the provider. Claim adjudication involves multiple sequential steps including eligibility verification confirming the member was covered on the date of service, medical necessity review validating that the billed services were clinically appropriate, coordination of benefits processing when multiple payers are involved, contract rate application calculating the allowed amount based on the provider network contract, and member cost-sharing calculation determining deductible, copay, and coinsurance obligations. The adjudication result is communicated to providers through the HIPAA 835 electronic remittance advice transaction.
Healthcare data teams build adjudication analytics that track claim processing times, adjudication accuracy rates, payment variance between billed and allowed amounts, and adjudication outcome distributions across payer and service type combinations.
Standard Abbreviation
clm_adjud
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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