discharge disposition
dsch_disp_cdDefinition
ISO-11179 Definition
A standardized code recorded on inpatient claims identifying the destination or status of a patient at the time of hospital discharge, indicating where the patient goes after leaving the acute care hospital. CMS maintains the discharge disposition code set used on UB-04 institutional claims, with common values including 01 for discharge to home, 02 for discharge to short-term general hospital, 03 for discharge to skilled nursing facility, 04 for discharge to intermediate care facility, 06 for discharge to home health care, 07 for discharge against medical advice, 20 for expired, and 21 for discharge to court or law enforcement. Discharge disposition directly affects Medicare payment calculations — transfers to post-acute care settings trigger Medicare transfer payment policies that reduce the DRG payment proportionally to the length of stay.
Healthcare data teams use dsch_disp_cd in post-acute utilization analytics, readmission risk stratification, care transition quality measurement, and transfer payment policy compliance monitoring.
Standard Abbreviation
dsch_disp_cd
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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