local coverage determination
lcd_cdDefinition
ISO-11179 Definition
A Medicare Administrative Contractor decision that defines when a specific medical item or service is considered medically necessary and therefore covered by Medicare within a defined geographic jurisdiction, providing coding and documentation requirements that claims must meet to be reimbursed. LCDs are developed by MACs based on medical evidence and clinical guidelines to address coverage questions not resolved by National Coverage Determinations, and apply only within the MAC geographic jurisdiction. LCDs specify covered diagnoses, required documentation, coding requirements, frequency limitations, and site of service restrictions for covered services.
Healthcare data teams maintain LCD reference tables by MAC jurisdiction and procedure code, apply LCD criteria in pre-billing claim edits to identify claims lacking required medical necessity documentation before submission, generate medical necessity denial reports tracking LCD-related denial rates by procedure type, and support provider education on LCD documentation requirements to prevent avoidable medical necessity denials.
Standard Abbreviation
lcd_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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