patient statement
pt_stmtDefinition
ISO-11179 Definition
A billing document sent by a healthcare provider to a patient itemizing services rendered, insurance payments received, adjustments applied, and the remaining balance owed by the patient after insurance adjudication. Patient statements are a primary patient-facing revenue cycle touchpoint and significantly influence payment behavior — clear, accurate, and timely statements improve patient payment rates while confusing or delayed statements increase bad debt. Effective patient statements communicate the service date, description of care, amount billed, insurance payment, contractual adjustments, and net patient responsibility in plain language that patients without healthcare billing expertise can understand.
Healthcare data teams track pt_stmt metrics including statement generation timing from claim adjudication, statement delivery method preferences by patient segment, response rates by statement design and timing, and payment conversion rates from statement to payment to optimize patient financial communication strategies.
Standard Abbreviation
pt_stmt
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.
Related Content
Looking for more healthcare terms?
Browse our complete library of 100,000+ standardized healthcare data terms
Browse All Terms