pre-authorization
pre_authDefinition
ISO-11179 Definition
The advance approval obtained from a health insurance payer before delivering specific non-emergency healthcare services, procedures, or medications to confirm the payer will provide coverage and reimbursement for the planned care. Pre-authorization is required by most health plans for elective surgeries, inpatient admissions, advanced imaging including MRI and CT scans, specialty medications, durable medical equipment, and certain outpatient procedures. The pre-authorization process requires submitting clinical documentation supporting medical necessity to the payer for clinical review within defined response timeframes.
CMS issued regulations in 2024 requiring Medicare Advantage plans to implement electronic prior authorization APIs using FHIR standards to reduce administrative burden. Healthcare data teams build pre-authorization tracking systems that monitor authorization request status, approval and denial rates by service type and payer, authorization expiration dates, and the revenue impact of services delivered without required authorization that result in claim denials.
Standard Abbreviation
pre_auth
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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