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disorder payment status

dsrd_pmt_sts
claims·Updated Mar 30, 2026

Definition

ISO-11179 Definition

The payment processing state for a abnormal health state. Used to capture financial data associated with disorder transactions. This field is commonly used in electronic health records (EHR), healthcare information systems (HIS), and clinical data warehouses for disorder management and reporting.

Standard Abbreviation

dsrd_pmt_sts

Category

claims

Production DDL — FACT_CLAIM_HEADER

FACT_CLAIM_HEADER.sql
CREATE OR REPLACE TABLE FACT_CLAIM_HEADER (
    clm_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,
    clm_stat_cd    VARCHAR(10)              -- claim status code,
    svc_from_dt    DATE                     -- service from date,
    svc_to_dt      DATE                     -- service to date,
    diag_cd_1      VARCHAR(10)              -- principal diagnosis,
    proc_cd        VARCHAR(10)              -- procedure code,
    clm_bill_amt   DECIMAL(18,2)            -- billed amount,
    clm_alwd_amt   DECIMAL(18,2)            -- allowed amount,
    clm_pd_amt     DECIMAL(18,2)            -- paid amount,
    denial_rsn_cd  VARCHAR(10)              -- denial reason code,
    load_dt        TIMESTAMP_NTZ  NOT NULL  -- load timestamp
);

Standard Snowflake DDL for the canonical claims table. Convert to BigQuery or Databricks →

Why This Term Matters

Claims data is the financial backbone of the US healthcare system, and understanding claims terminology is essential for building accurate revenue cycle and reimbursement analytics. Data engineers who know this terminology can correctly parse 837 transactions, identify adjudication errors, and model denial patterns that represent real revenue recovery opportunities. A single misunderstood claims field can result in millions in underpayments identified only after external audits.

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