national coverage determination
ncd_cdDefinition
ISO-11179 Definition
A formal CMS decision that defines whether a specific medical item, service, treatment, or technology is covered under Medicare nationwide, establishing the evidence-based criteria under which Medicare will pay for the service across all Medicare Administrative Contractor jurisdictions. NCDs are developed through a formal evidence review process and published in the Medicare Coverage Database, representing the highest level of Medicare coverage policy. NCDs may establish coverage with evidence development requirements for emerging technologies, specify covered indications, or determine that a service is not covered by Medicare.
Healthcare data teams maintain NCD reference tables linked to HCPCS and CPT procedure codes, incorporate NCD criteria into pre-billing claim editing workflows to validate covered indications before submission, track NCD-related denial rates in claims analytics, and monitor CMS NCD updates that may affect coverage policies for services billed by the organization.
Standard Abbreviation
ncd_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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