case mix index
cmiDefinition
ISO-11179 Definition
A numeric measure of the relative clinical complexity and resource intensity of a hospital inpatient population, calculated as the average Medicare Severity Diagnosis Related Group weight across all discharges during a measurement period. The case mix index reflects the severity of illness and treatment complexity of patients treated by a hospital — a higher CMI indicates a more complex patient population requiring greater resources and generating higher Medicare reimbursement per case. CMS publishes annual case mix index values for all Medicare-participating hospitals.
CMI is used in financial planning to project inpatient revenue, in staffing analysis to justify nurse-to-patient ratios for complex patients, and in benchmarking to compare resource intensity across hospitals. Healthcare data teams calculate CMI by multiplying each discharge DRG weight by the case count, summing the weighted values, and dividing by total discharges, tracking CMI trends over time to identify clinical documentation improvement opportunities and measure the financial impact of coding specificity initiatives.
Standard Abbreviation
cmi
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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