benchmark expenditure
bnchmark_exp_amtDefinition
ISO-11179 Definition
The expected total cost of care for an attributed patient population established at the beginning of a value based contract period, representing the spending target against which actual expenditures are compared to determine shared savings or shared losses at contract settlement. Benchmark expenditure is calculated from historical claims data for the attributed population adjusted for risk score changes, regional trend factors, and quality performance. CMS calculates Medicare Shared Savings Program benchmarks using three years of historical Medicare expenditure data for each ACO participant population, updated annually with national trend adjustments.
Performing below the benchmark generates shared savings distributed to ACO participants while performing above the benchmark in two-sided risk models triggers shared losses. Healthcare data teams model benchmark expenditure calculations to project in-year performance, identify utilization patterns driving variance from benchmark, and estimate final settlement amounts to support provider financial planning and care management investment decisions.
Standard Abbreviation
bnchmark_exp_amt
Category
Production DDL — FACT_QUALITY_MEASURE
CREATE OR REPLACE TABLE FACT_QUALITY_MEASURE (
qlty_key INTEGER NOT NULL -- surrogate key,
mbr_key INTEGER NOT NULL -- FK to DIM_MEMBER,
plan_key INTEGER NOT NULL -- FK to DIM_PLAN,
meas_yr SMALLINT -- measurement year,
hedis_meas_cd VARCHAR(20) -- HEDIS measure code,
denom_ind CHAR(1) -- denominator eligible,
numer_ind CHAR(1) -- numerator met,
excl_ind CHAR(1) -- exclusion indicator,
gap_open_ind CHAR(1) -- care gap open,
star_rtg_nbr DECIMAL(3,1) -- star rating,
qlty_scr DECIMAL(5,2) -- quality score,
perf_thrsh_pct DECIMAL(5,2) -- performance threshold,
raf_scr DECIMAL(10,3) -- risk adjustment factor,
outreach_cnt SMALLINT -- outreach attempts,
load_dt TIMESTAMP_NTZ NOT NULL -- load timestamp
);
Standard Snowflake DDL for the canonical quality table. Convert to BigQuery or Databricks →
Why This Term Matters
Quality measure data determines how payers and providers are rated and reimbursed under CMS Stars, HEDIS, and value-based care contracts. Data engineers who understand quality terminology build measure calculation pipelines that correctly attribute patients, apply denominator exclusions, and flag documentation gaps before submission deadlines. Incorrect quality data directly affects star ratings, pay-for-performance bonuses, and Medicare Advantage plan bids.
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