length of stay
los_daysDefinition
ISO-11179 Definition
The number of days a patient remains hospitalized from admission to discharge, representing one of the most important drivers of inpatient resource consumption and Medicare DRG payment adequacy. Under the Medicare inpatient prospective payment system, hospitals receive a fixed DRG payment regardless of actual length of stay, creating a financial incentive to discharge patients efficiently when medically appropriate. Geometric mean length of stay published by CMS for each DRG represents the expected efficient stay duration.
Actual length of stay significantly above the geometric mean may indicate care coordination inefficiencies, discharge planning delays, or social barriers to discharge while lengths of stay below the mean may reflect appropriate care management or patient selection effects. Healthcare data teams analyze los_days by DRG, attending physician, service line, and payer to identify outlier cases requiring care management intervention, measure the financial impact of length of stay reduction initiatives, and benchmark hospital performance against national geometric mean length of stay standards.
Standard Abbreviation
los_days
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