electronic claim
elec_clm_indDefinition
ISO-11179 Definition
A boolean indicator identifying that a healthcare claim was submitted electronically using a HIPAA-compliant standard transaction format rather than a paper claim form. The Health Insurance Portability and Accountability Act mandates electronic submission for most Medicare and Medicaid claims, and commercial payers strongly incentivize electronic submission through faster processing times and lower administrative fees. Electronic claims are transmitted in the X12 837P format for professional claims, 837I format for institutional claims, and 837D format for dental claims.
Electronic submission through clearinghouses enables claim validation before payer submission, reducing rejection rates and accelerating payment. Healthcare data teams track elec_clm_ind to measure electronic submission rates by payer and facility, calculate administrative cost savings from paper-to-electronic conversion, identify remaining paper claim volumes by payer that could be converted to electronic submission, and benchmark electronic submission rates against industry standards.
Standard Abbreviation
elec_clm_ind
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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