bad debt
bad_debt_amtDefinition
ISO-11179 Definition
Patient account balances that a healthcare organization has determined are uncollectible after reasonable collection efforts, written off from accounts receivable as a financial loss. Bad debt arises when patients with insurance coverage fail to pay their out-of-pocket obligations including deductibles, copays, and coinsurance, as well as from self-pay patients who do not qualify for financial assistance but do not pay their bills. Rising patient cost-sharing under high-deductible health plans has significantly increased healthcare bad debt in recent years as more financial responsibility shifts to patients.
Healthcare organizations report bad debt separately from charity care in their financial statements. Healthcare data teams analyze bad_debt_amt by service type, payer category, patient demographics, and collection touchpoint to evaluate collection strategy effectiveness, model bad debt reserve requirements for financial planning, and identify patient populations where proactive financial counseling and payment plan arrangements could reduce bad debt conversion rates.
Standard Abbreviation
bad_debt_amt
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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