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payment integrity

pmt_integrity
finance·Updated Jul 21, 2026

Definition

ISO-11179 Definition

The systematic processes and technologies used by health plans to identify and prevent improper payments including fraud, waste, and abuse detection, clinical editing for medically unlikely or inappropriate billing, duplicate claim detection, coordination of benefits verification, and post-payment audit and recovery programs. Payment integrity programs generate significant return on investment through prevented and recovered overpayments, and payment integrity metrics including detection rates and recovery amounts are tracked as key financial performance indicators.

Standard Abbreviation

pmt_integrity

Category

finance

Production DDL — FACT_CLAIM_TRANSACTION

FACT_CLAIM_TRANSACTION.sql
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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