timely filing limit
tmly_filing_lmtDefinition
ISO-11179 Definition
The maximum number of days from the date of service or discharge within which a healthcare provider must submit a claim to a specific payer to be eligible for reimbursement under the provider contract or program rules. Timely filing limits vary widely by payer — Medicare requires claims within 12 months of the date of service, Medicaid limits vary by state from 90 days to 24 months, and commercial payers specify limits in individual provider contracts ranging from 90 days to 365 days. Healthcare organizations must maintain a payer-specific timely filing limit table and monitor claim submission timing against these limits to prevent avoidable denials.
Healthcare data teams maintain tmly_filing_lmt reference tables by payer and plan type, use these limits in claims aging analysis to flag encounters at risk of timely filing denial, and calculate the potential revenue at risk when billing workflow delays push claims toward filing deadlines.
Standard Abbreviation
tmly_filing_lmt
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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