recovery audit contractor
rac_audit_indDefinition
ISO-11179 Definition
A boolean indicator identifying that a healthcare claim has been selected for review by a CMS Recovery Audit Contractor, a private company contracted by CMS to identify and recover Medicare and Medicaid improper payments through retrospective claims review. RAC auditors review claims for incorrect payments resulting from non-covered services, incorrect coding, duplicate billing, and medically unnecessary services, retaining a contingency fee percentage of improper payments identified and recovered. Providers have the right to appeal RAC determinations through the Medicare claims appeals process with multiple administrative and judicial levels available.
RAC audits focus on high-risk billing areas identified through data analysis and prior audit experience. Healthcare data teams maintain rac_audit_ind tracking systems that monitor audit request volumes by claim type, track appeal status and outcomes through the multi-level appeals process, calculate financial exposure from pending RAC determinations, and analyze RAC audit patterns to identify and remediate systemic billing issues before they generate additional audit activity.
Standard Abbreviation
rac_audit_ind
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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