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Temperature Excursion

tmp_excrsn
supply·Updated Jun 23, 2026

Definition

ISO-11179 Definition

A recorded deviation outside the acceptable temperature range for storing medications, vaccines, or biological specimens in pharmacy or laboratory systems. Data engineers use excursion logs to trigger quality alerts, flag compromised inventory records, and support regulatory compliance reporting in cold chain management platforms.

Standard Abbreviation

tmp_excrsn

Category

supply

Production DDL — FACT_SUPPLY_ORDER

FACT_SUPPLY_ORDER.sql
CREATE OR REPLACE TABLE FACT_SUPPLY_ORDER (
    sply_ord_key    INTEGER        NOT NULL  -- surrogate key,
    sply_ord_id     VARCHAR(50)    NOT NULL  -- supply order ID,
    mbr_key         INTEGER        NOT NULL  -- FK to DIM_MEMBER,
    prvdr_key       INTEGER        NOT NULL  -- FK to DIM_PROVIDER,
    item_cd         VARCHAR(20)              -- item code,
    item_nm         VARCHAR(255)             -- item name,
    hcpcs_cd        VARCHAR(10)              -- HCPCS code,
    qty_ord         DECIMAL(10,2)            -- quantity ordered,
    qty_dspnd       DECIMAL(10,2)            -- quantity dispensed,
    unit_cst_amt    DECIMAL(10,2)            -- unit cost amount,
    tot_cst_amt     DECIMAL(10,2)            -- total cost amount,
    ord_dt          DATE                     -- order date,
    dspnd_dt        DATE                     -- dispensed date,
    prior_auth_nbr  VARCHAR(30)              -- prior authorization number,
    load_dt         TIMESTAMP_NTZ  NOT NULL  -- load timestamp
);

Standard Snowflake DDL for the canonical supply 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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