global period
glbl_prd_daysDefinition
ISO-11179 Definition
The number of days following a surgical procedure during which related pre-operative and post-operative care is considered included in the surgical procedure reimbursement and may not be billed separately to payers. CMS assigns global periods to surgical procedures — zero days for minor procedures, ten days for minor surgical procedures, and ninety days for major surgical procedures — during which evaluation and management services, wound checks, and routine post-operative care are bundled into the surgical payment. Separate billing for services included in the global period is considered incorrect billing that can generate false claims liability.
Healthcare data teams analyze glbl_prd_days in claims editing systems to apply global period logic, flag potentially duplicative post-operative claims submitted within the global period window, calculate the revenue impact of global period billing corrections, and educate surgeons and billing staff on appropriate global period billing exceptions for unrelated conditions or significant complications.
Standard Abbreviation
glbl_prd_days
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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