specimen detail
spec_dtlDefinition
ISO-11179 Definition
Granular attribute data describing the characteristics of a biological specimen, such as volume, color, or collection method, stored in LIS and EHR systems. Data engineers use this field for specimen quality validation, rejection workflows, and building enriched lab datasets for clinical analytics.
Standard Abbreviation
spec_dtl
Category
Production DDL — FACT_LAB_RESULT
CREATE OR REPLACE TABLE FACT_LAB_RESULT (
lab_rslt_key INTEGER NOT NULL -- surrogate key,
mbr_key INTEGER NOT NULL -- FK to DIM_MEMBER,
prvdr_key INTEGER NOT NULL -- FK to DIM_PROVIDER,
loinc_cd VARCHAR(10) -- LOINC code,
lab_test_nm VARCHAR(255) -- lab test name,
lab_rslt_val DECIMAL(18,4) -- result value,
lab_rslt_unit VARCHAR(20) -- result unit,
ref_range_low DECIMAL(18,4) -- reference range low,
ref_range_high DECIMAL(18,4) -- reference range high,
abnorm_ind CHAR(1) -- abnormal indicator,
crit_val_ind CHAR(1) -- critical value flag,
coll_dt DATE -- collection date,
rslt_dt DATE -- result date,
ord_prvdr_npi VARCHAR(10) -- ordering provider NPI,
load_dt TIMESTAMP_NTZ NOT NULL -- load timestamp
);
Standard Snowflake DDL for the canonical laboratory 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.
Related Content
Looking for more healthcare terms?
Browse our complete library of 100,000+ standardized healthcare data terms
Browse All Terms