modifier code
mod_cdDefinition
ISO-11179 Definition
A two-digit alphanumeric code appended to a CPT or HCPCS procedure code on a healthcare claim to provide additional information about the circumstances of the service without changing the definition of the code itself. Modifiers communicate important billing information including that a service was performed bilaterally, that multiple procedures were performed during the same session, that only part of a service was performed, that a service was performed by a different provider than the billing provider, or that a service was performed in a distinct encounter from other same-day services. Common modifiers include 25 for significant separately identifiable evaluation and management service, 51 for multiple procedures, 59 for distinct procedural service, and RT and LT for right and left side identification.
Healthcare data teams analyze modifier usage patterns in claims data to detect potentially improper modifier application that inflates payment, validate modifier combinations against CCI edits, and identify providers with outlier modifier rates requiring compliance review.
Standard Abbreviation
mod_cd
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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