clearinghouse
clrhs_nmDefinition
ISO-11179 Definition
A health information technology company that serves as an intermediary between healthcare providers and insurance payers, receiving electronic claims from providers, translating them into payer-specific formats, performing technical validation edits, and routing them to the appropriate payer for adjudication. Clearinghouses also receive electronic remittance advice from payers and deliver them to providers, centralizing multiple payer connections through a single vendor relationship. Major healthcare clearinghouses include Change Healthcare, Availity, and Waystar.
Using a clearinghouse reduces the technical complexity of maintaining direct payer connections and provides pre-submission claim editing to catch errors before they reach payers. Healthcare data teams track clrhs_nm performance metrics including acceptance rates by payer, edit failure rates by edit type, transaction processing times, and rejection reason distributions to evaluate clearinghouse performance and identify systematic claim preparation issues identified during clearinghouse validation.
Standard Abbreviation
clrhs_nm
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.
Related Content
Related Definitions
Looking for more healthcare terms?
Browse our complete library of 100,000+ standardized healthcare data terms
Browse All Terms